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MarketingBig Data Analytics in Marketing Decision-Making
Elijah T
About This Research Topic The volume, velocity and variety of data from digital marketing, transactions, CRM and social media have exploded, making big data analytics central to modern marketing. Businesses that systematically examine large datasets to uncover patterns should make faster, more accurate and more defensible decisions than those relying on intuition alone. At SCHOLARNESTHUB, we transform survey-based projects into publication-ready SEO articles. This study on big data analytics in marketing decision-making is tailored for students searching for marketing project topics and business administration project topics in Nigerian secondary cities. While global surveys by McKinsey report growing analytics investment, adoption is uneven — large firms with data science teams progress faster than resource-constrained SMEs. Whether Enugu metropolis businesses have meaningfully integrated analytics or still rely on managerial intuition remains empirically underexplored. This article presents a fully verified guide with descriptive and inferential evidence from 240 marketing managers in Enugu East, North and South. Main Abstract This study examined the role of big data analytics in marketing decision-making among businesses in Enugu metropolis. Guided by four objectives, it examined extent of utilisation, effect on quality/accuracy, effect on speed, and relationship with overall effectiveness, plus comparison between firms with and without dedicated analytics tools/teams. A descriptive survey design was adopted. Data were collected from 240 marketing managers and business decision-makers in Enugu metropolis, determined using Taro Yamane formula from estimated population of 600 businesses with formal marketing decision-making function, selected through multi-stage sampling, using structured 24-item 5-point Likert-scale questionnaire. Analysis used descriptive statistics (frequencies, percentages, mean scores) and inferential statistics (simple linear regression, Pearson Product Moment Correlation, independent samples t-test) with SPSS version 26. Findings revealed: (1) big data analytics utilisation significantly and positively predicts quality and accuracy of marketing decisions (β = 0.556, p < 0.05); (2) utilisation significantly and positively predicts speed of decision-making (β = 0.487, p < 0.05); (3) strong positive relationship between utilisation and overall marketing decision-making effectiveness (r = 0.634, p < 0.05); and (4) businesses with dedicated analytics tools or teams reported significantly higher effectiveness than those without, t = 6.93, p < 0.05. The study concluded big data analytics is statistically significant and substantial driver of both quality and speed, and that formal dedicated investment, rather than ad hoc data use, most strongly distinguishes higher-performing decision-makers. It recommends formalising analytics capability through tools, personnel or training, equipping managers with data literacy, and exploring affordable outsourced/platform-based options for smaller businesses to close the effectiveness gap.
MarketingPredictive Marketing Analytics and Customer Purchase Behaviour
Elijah T
About This Research Topic Marketing has traditionally been reactive, adjusting campaigns after sales happen. Predictive marketing analytics changes this logic: using historical transaction, browsing and CRM data to build models that forecast future behaviour, allowing brands to anticipate needs before they occur. At SCHOLARNESTHUB, we rewrite complex analytics projects into clear, SEO-optimized academic articles. This study on predictive marketing analytics and customer purchase behaviour is crafted for students searching for marketing project topics and digital marketing project topics . Three consumer-facing applications define the field: propensity-based offers that estimate likelihood of response, replenishment and next-purchase reminders timed to anticipated need, and retention and win-back campaigns triggered by churn prediction before lapse. While promising, effectiveness depends on consumer perception — a well-timed reminder feels attentive, a mistimed one feels intrusive. This article examines 400 consumers (392 retrieved, 383 usable, 95.8% response) to test individual effects and the moderating role of perceived predictive accuracy. Main Abstract This study examined the effect of predictive marketing analytics on customer purchase behaviour when businesses deploy predictive models to anticipate rather than merely respond to needs, through propensity-based offers, replenishment reminders, and retention campaigns. Four objectives: effect of propensity-based offers, effect of replenishment/next-purchase reminders, effect of retention/win-back campaigns, and moderating role of perceived predictive accuracy. Survey research design was adopted, structured questionnaire administered to 400 consumers who reported experiencing at least one predictive-analytics-driven communication, using multi-stage sampling, of which 392 retrieved and 383 usable (95.8% response). Analysis used descriptive statistics (frequencies, percentages, means, SD) and inferential statistics (Pearson correlation, hierarchical multiple regression, chi-square) with SPSS 26. Findings revealed predictive propensity-based offers (β=0.27, p<0.05), replenishment and next-purchase reminders (β=0.23, p<0.05), and retention and win-back campaigns (β=0.30, p<0.05) each had positive significant effect on purchase behaviour, jointly accounting for approximately 56.5% variance (Adjusted R²=0.565, F=164.8, p<0.05). Perceived predictive accuracy significantly moderated relationship (ΔR²=0.033, p<0.05), strengthening effect among consumers perceiving predictions as accurate and relevant, weakening it among those perceiving poor timing or mismatch. Study concluded predictive marketing analytics is significant multidimensional driver of purchase behaviour, with retention and win-back campaigns exerting strongest individual influence, but influence is conditioned by perceived accuracy. Recommended investing in retention-focused modelling, continuously validating model accuracy against real feedback, and avoiding poorly calibrated triggers that risk irrelevance, given demonstrated importance of perceived accuracy.
MarketingONLINE SHOPPING EXPERIENCE AND CONSUMER PURCHASE INTENTION
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About This Research Topic Electronic commerce in Nigeria expanded rapidly over past decade driven by rising smartphone penetration growing internet access proliferation both established online marketplaces such as Jumia Konga and informal social commerce channels operating through Instagram WhatsApp Facebook per Statista 2023. As shift accelerates overall online shopping experience — encompassing website or platform usability perceived transactional security trust reliability delivery order fulfilment — emerged as central determinant whether consumers form favourable purchase intentions toward given online retail channel. Unlike physical retail online shopping removes tangible cues physical inspection face-to-face interaction immediate possession that traditionally reassure consumers during purchase decision replacing them with set digital logistical cues how easy website app navigate whether payment personal data feel secure whether order will arrive as promised. Marketing and information-systems scholars long argued through frameworks such as Stimulus-Organism-Response model that environmental cues shape internal consumer states trust comfort satisfaction that in turn drive behavioural outcomes such as purchase intention per Mehrabian & Russell 1974 Eroglu et al. 2001. Within Nigeria specifically among consumers in urban centres Enugu metropolis online shopping grown substantially yet persistent challenges inconsistent delivery timelines concerns payment fraud counterfeit goods variable platform usability particularly on informal social commerce channels that proliferated alongside formal marketplaces continue documented in industry commentary as constraints on consumer confidence. Whether to what extent dimensions actually shape purchase intentions and whether purchase intention differs systematically between shoppers using established marketplace platforms and those using less formally structured social commerce channels remains important empirical question. Studies on antecedents of trust perceived ease of use security on-time delivery in online shopping and effects of perceived service quality website quality reputation trust perceived risk purchase intention online shopping confirm perceived ease of use security on-time delivery are antecedents of trust loyalty and that trust mediates website quality and purchase intention. For related project materials see ScholarNestHub e-commerce collection . Main Abstract Growth of e-commerce in Nigeria made online shopping experience — encompassing website usability perceived security and trust and delivery/fulfilment performance — increasingly critical determinant of whether consumers form favourable purchase intentions toward online retail platforms. Despite rising internet and smartphone penetration Nigerian e-commerce continues to face documented challenges around trust delivery reliability and platform usability that may constrain conversion of online browsing into actual purchase intention. This study examined online shopping experience and consumer purchase intention among online shoppers in Enugu metropolis. Guided by four objectives: examine effect of website usability on consumer purchase intention; assess effect of perceived security and trust on consumer purchase intention; evaluate effect of delivery and fulfilment experience on consumer purchase intention; and compare purchase intention between consumers who primarily shop on marketplace platforms and those who primarily shop through social commerce platforms. Descriptive survey research design adopted and data collected from 277 online shoppers in Enugu metropolis determined using Taro Yamane formula from estimated population of 900 active online shoppers and selected through multi-stage sampling technique using structured 24-item 5-point Likert-scale questionnaire. Data analysed using descriptive statistics frequencies percentages mean scores and inferential statistics simple linear regression multiple linear regression and independent samples t-test with aid of SPSS version 26. Findings revealed website usability significantly and positively predicts purchase intention β=0.478 p<0.05; perceived security and trust significantly and positively predicts purchase intention with largest individual effect of three dimensions β=0.541 p<0.05; delivery and fulfilment experience significantly and positively predicts purchase intention β=0.463 p<0.05; and consumers who primarily shop on established marketplace platforms reported significantly higher purchase intention than those who primarily shop through social commerce platforms t=5.86 p<0.05. Combined multiple regression model showed three online shopping experience dimensions jointly explaining approximately 49.6% variance in purchase intention with perceived security and trust emerging as strongest individual predictor. Study concluded online shopping experience and perceived security/trust in particular significant driver of consumer purchase intention in Enugu metropolis e-commerce market and platform type marketplace versus social commerce meaningfully shapes strength of that intention. Recommended online retailers and social commerce vendors prioritise investment in transparent security assurances and reliable delivery communication alongside continued usability improvements to strengthen consumer purchase intention. Keywords: Online shopping experience, purchase intention, website usability, perceived security, delivery experience, e-commerce, social commerce, Enugu metropolis
MarketingTHE ROLE OF ONLINE REVIEWS IN CONSUMER PURCHASE DECISION-MAKING
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About This Research Topic Online reviews have become one of the most consequential forms of marketing communication in contemporary retail. Before completing a purchase, especially online, the vast majority of shoppers routinely consult star ratings and buyer commentary, treating this user-generated content as a critical input often weighted as heavily as brand advertising. This shift reflects a broader transformation in consumer trust away from brand-controlled narratives toward collective, largely uncensored testimony of prior buyers. As a form of electronic word-of-mouth, online reviews are analyzed along three distinct dimensions: review valence, the overall positive or negative sentiment summarized in aggregate star ratings; review volume, the total number of reviews serving as a social proof signal; and review quality, the comprehensiveness, detail, and argument strength that provides substantive decision-relevant information. Understanding how these dimensions individually and jointly shape purchase decisions is critical, because businesses often chase volume or valence without clear evidence of relative impact. This article for SCHOLARNESTHUB presents a rewritten, SEO-optimized analysis of a survey of 400 online shoppers, of whom 382 responses were usable, examining how valence, volume, and quality affect consumer purchase decision-making and how product involvement moderates that relationship. For complementary research models, see online reviews project topics on SCHOLARNESTHUB for related eWOM frameworks. Main Abstract This study examined the role of online reviews in consumer purchase decision-making at a time when most online shoppers consult reviews before buying, making review content a consequential yet imperfectly understood marketing communication. Guided by four objectives, the study determined effect of review valence, volume, and quality on purchase decision-making and evaluated moderating role of consumer product involvement. Survey research design was adopted, structured questionnaire administered to 400 online shoppers who reported reading reviews before at least one purchase, using multi-stage sampling, of which 390 retrieved and 382 usable representing 95.5 percent response rate. Data analysed using descriptive statistics and inferential statistics including Pearson correlation, hierarchical multiple regression, and chi-square tests with SPSS version 26. Findings revealed review valence β = 0.24 p < 0.05, review volume β = 0.21 p < 0.05, and review quality β = 0.34 p < 0.05 each had positive statistically significant effect on purchase decision-making, jointly accounting for approximately 55.3 percent variance Adjusted R² = 0.553 F = 155.9 p < 0.05. Consumer product involvement significantly moderated relationship ΔR² = 0.032 p < 0.05, strengthening positive effect among higher involvement consumers and weakening among lower involvement. Study concluded online reviews are significant multidimensional influence, with quality exerting strongest individual influence consistent with central-route persuasion processing, but overall persuasive weight conditioned by personal involvement. Recommendations include soliciting detailed high-quality reviews rather than volume alone, designing interfaces that surface argument-rich reviews for high-involvement categories, and calibrating review-based communication across involvement levels.
MarketingTHE EFFECT OF OMNICHANNEL MARKETING ON CUSTOMER EXPERIENCE AND LOYALTY
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About This Research Topic Modern consumers no longer shop in a straight line. They discover a product on Instagram, compare prices on a website, check availability on a mobile app, purchase in-store, and request support via WhatsApp — often within a single journey. This fluid behaviour has elevated channel integration from a back-office IT concern to a core marketing strategy. At the heart of this shift is omnichannel marketing and its impact on customer experience , which focuses not just on being present on many channels, but on making those channels work together seamlessly. Unlike multichannel retailing where channels operate as separate silos, omnichannel marketing emphasizes synergistic management of touchpoints — synchronizing pricing, inventory, customer data, and service standards. When done well, it allows customers to move frictionlessly between online and offline, creating a superior, consistent customer experience that drives loyalty. In Nigeria's rapidly evolving retail sector — from banking to fashion to FMCG — firms are investing heavily in e-commerce platforms, mobile apps, and physical outlets, but many still struggle with true back-end integration. This article examines the effect of omnichannel marketing on customer experience and loyalty among retail consumers. Drawing on Service-Dominant Logic and channel integration theory, it assesses the extent of integration experienced, how omnichannel drives experience, how experience drives loyalty, and why perceived channel consistency is the critical moderator that determines whether channel proliferation builds or breaks loyalty. Main Abstract The proliferation of digital and physical touchpoints – websites, mobile apps, physical stores, social media, and call centres – has elevated channel integration from an operational concern to a central strategic marketing priority. Omnichannel marketing, defined as the synergistic management of multiple channels and touchpoints to optimise experience and performance across channels, has emerged as a dominant retail paradigm. However, mechanisms through which integration quality translates into customer experience and loyalty remain underexplored in emerging market contexts. This study examined the effect of omnichannel marketing on customer experience and loyalty among selected retail consumers. Specific objectives were to assess the extent of channel integration experienced across brand touchpoints; determine the effect of omnichannel marketing on customer experience; examine the influence of customer experience on customer loyalty; and evaluate the moderating role of perceived channel consistency on the omnichannel-loyalty relationship. A descriptive survey design was adopted. Data were obtained from 384 retail consumers determined via Cochran formula for infinite populations, selected through purposive and convenience sampling. A structured five-point Likert questionnaire was validated and pilot-tested, yielding Cronbach's Alpha above 0.70 for all constructs. Data were analysed using descriptive and inferential statistics (Chi-square and multiple regression) with SPSS version 26. Findings revealed that channel integration experienced is moderate among sampled brands; that omnichannel marketing has a significant positive effect on customer experience; that customer experience significantly and positively influences customer loyalty; and that perceived channel consistency significantly moderates the relationship between omnichannel marketing and loyalty, such that the positive effect strengthens substantially among consumers perceiving high consistency. The study concluded that omnichannel marketing is a significant driver of experience and loyalty, but its effectiveness depends on perceived consistency rather than mere multiplicity of channels. Recommendations include prioritizing back-end systems integration for consistent pricing, inventory and customer data, unified customer service training, and treating consistency as a core loyalty capability. Keywords: Omnichannel Marketing, Customer Experience, Customer Loyalty, Channel Integration, Channel Consistency, Customer Journey, Multichannel Retailing
MarketingTHE ROLE OF SOCIAL MEDIA INFLUENCERS IN SHAPING CONSUMER PURCHASE DECISIONS
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About This Research Topic Proliferation of social media platforms given rise to distinct category of marketing communicator: social media influencer, individual who cultivated dedicated engaged online following and leverages that following and perceived authenticity of voice to shape audience attitudes preferences behaviour per Freberg et al. 2011. Unlike traditional celebrity endorsers whose fame typically originates outside digital sphere influencers build following credibility directly through sustained often highly personal content creation distinction widely believed to confer greater relatability perceived authenticity per De Veirman et al. 2017. Brands across virtually every product category from fast-moving consumer goods to financial services responded by channelling substantial growing proportions marketing budgets toward influencer partnerships. Growth premised on belief influencers through parasocial relationships they cultivate with audiences command level audience trust engagement traditional advertising formats increasingly struggle to replicate particularly among younger digitally native segments per Lou & Yuan 2019. Consumer purchase decision process encompassing need recognition information search evaluation alternatives purchase decision post-purchase evaluation per Kotler & Keller 2016 fundamentally reshaped by influencer phenomenon. Influencers now frequently intervene at multiple stages simultaneously introducing consumers to products they were previously unaware of providing seemingly authentic experience-based information during evaluation stage and directly facilitating purchase completion through affiliate links discount codes. This multi-stage intervention distinguishes influencer marketing from more narrowly targeted traditional advertising formats which typically operate primarily at awareness or persuasion stage alone. Within Nigeria and other emerging markets influencers become prominent commercially significant feature digital marketing landscape with both globally recognised and locally rooted influencers actively shaping perceptions fashion beauty technology lifestyle products. Regulatory bodies including Advertising Regulatory Council begun developing guidelines specifically addressing sponsorship disclosure reflecting growing recognition format's commercial significance. Research on parasocial relationships mediated source trustworthiness brand credibility purchase intention and parasocial relationships with influencers sponsorship disclosure and purchase intention shows parasocial relationships mediate interactions and source trustworthiness which in turn affects brand credibility and purchase intention and that disclosure can enhance intentions via parasocial relationship. For related project materials see ScholarNestHub marketing collection . Main Abstract Rise of social media given birth to distinct category marketing communicator social media influencer individual who cultivated dedicated online following and who leverages following to shape audience attitudes and behaviour including purchase decisions. Brands increasingly channel substantial proportions of marketing budgets toward influencer partnerships premised on belief influencers command level of audience trust and relatability that traditional celebrity endorsement and conventional advertising formats struggle to replicate. However specific mechanisms through which influencer characteristics including perceived credibility parasocial connection and sponsorship transparency translate into actual consumer purchase decisions remain incompletely understood particularly within emerging market contexts. Study examined role of social media influencers in shaping consumer purchase decisions among selected online consumers. Specifically sought to assess extent of consumer engagement with social media influencer content; determine effect of influencer credibility on consumer purchase decisions; examine influence of parasocial relationships with influencers on brand trust; and evaluate moderating role of sponsored content disclosure on relationship between influencer credibility and consumer purchase decisions. Descriptive survey research design adopted and data obtained from sample of 384 online consumers determined using Cochran formula for infinite populations and selected through purposive and convenience sampling. Structured questionnaire anchored on five-point Likert scale validated and pilot-tested yielding Cronbach Alpha coefficients above 0.70 for all constructs. Data analysed using descriptive statistics frequency percentage mean standard deviation and inferential statistics Chi-square test and simple/multiple linear regression using SPSS version 26. Findings revealed consumer engagement with social media influencer content is high among sampled online consumers; influencer credibility has statistically significant positive effect on consumer purchase decisions; parasocial relationships with influencers significantly and positively influence brand trust; and sponsored content disclosure significantly moderates relationship between influencer credibility and consumer purchase decisions with disclosure found not to substantially weaken and in some cases strengthening effect of credibility on purchase decisions. Study concluded social media influencers occupy genuinely influential position within consumer purchase decision process whose effectiveness rests substantially on perceived credibility and parasocial connection rather than follower count alone and that transparent sponsorship disclosure need not undermine and may enhance influencer marketing effectiveness. Recommended among others brands prioritise influencer-product fit and authenticity over reach embrace transparent sponsorship disclosure practices and invest in longer-term influencer relationships capable of sustaining parasocial trust. Keywords: Social Media Influencers, Influencer Marketing, Source Credibility, Parasocial Relationships, Consumer Purchase Decisions, Sponsored Content Disclosure, Electronic Word of Mouth
MarketingTHE EFFECT OF USER-GENERATED CONTENT ON BRAND TRUST AND PURCHASE INTENTION
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About This Research Topic In today's online marketplace, brand-controlled advertisements compete for attention with reviews, ratings, unboxing videos, testimonials, and casual social media posts created by ordinary consumers. Collectively termed user-generated content (UGC), this peer-created material now surrounds almost every purchase decision on platforms such as Instagram, TikTok, Facebook, Jumia, and Konga. For many shoppers in Nigeria, a 30-second unboxing clip from a peer carries more weight than a polished brand commercial. The persuasive advantage of UGC is often explained by Source Credibility Theory, which holds that trustworthiness and expertise of the source determine message impact. Because UGC creators are perceived as independent and not commercially motivated, their content is judged more credible, fostering brand trust and ultimately purchase intention. Yet response to UGC is not uniform. Consumers high in advertising skepticism, a general tendency to distrust advertising claims, may rely more heavily on UGC than those who still trust brand messaging. This conditional relationship has important implications for firms allocating budgets between review programmes and traditional advertising. This article, prepared for SCHOLARNESTHUB, presents a fully rewritten SEO-optimized analysis of a survey of 300 online shoppers in Enugu State, Nigeria, examining the sequential pathway from UGC exposure to credibility to brand trust to purchase intention, moderated by advertising skepticism. For related research designs, see user-generated content project topics on SCHOLARNESTHUB and consumer behaviour studies. Main Abstract User-generated content including reviews, ratings, unboxing videos, testimonials, and social media posts created by ordinary consumers has become central to online shopping, often positioned as more credible than brand-created advertising. However, the mechanism by which UGC exposure translates into brand trust and purchase intention, and the extent to which this depends on underlying skepticism toward traditional advertising, remains underexamined in Nigeria. This study examined the effect of user-generated content on brand trust and purchase intention, focusing on mediating role of perceived UGC credibility and moderating role of advertising skepticism among online shoppers in Enugu State. Anchored on Source Credibility Theory, Elaboration Likelihood Model, and Social Proof Theory, the study adopted descriptive survey design. Structured questionnaire was administered to 300 online shoppers selected through convenience and simple random sampling. Data were analysed using descriptive statistics and inferential statistics including Chi-square, Pearson correlation, and multiple regression with SPSS version 26. Findings revealed UGC exposure has statistically significant positive effect on perceived UGC credibility, credibility has significant positive effect on brand trust, brand trust has significant positive effect on purchase intention, and advertising skepticism significantly and positively moderates the relationship between perceived UGC credibility and brand trust, such that credibility-trust relationship is considerably stronger among consumers with high skepticism toward traditional advertising than among those with low skepticism. The study concluded UGC builds purchase intention primarily through sequential process: exposure fosters credibility, credibility fosters brand trust, trust fosters purchase intention, especially powerful among consumers who distrust conventional advertising. The study recommended firms actively facilitate, curate, and showcase authentic UGC, particularly among audiences with high advertising skepticism, rather than relying solely on brand-controlled messaging.
MarketingMICRO-INFLUENCER MARKETING AND CONSUMER TRUST IN DIGITAL MARKETPLACES
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About This Research Topic Social media fundamentally reshaped architecture of marketing communication displacing or substantially supplementing traditional celebrity endorsement with new class of digital opinion leaders known as influencers. Within this landscape micro-influencers generally defined as individuals with followings ranging approximately 1,000 to 100,000 followers emerged as particularly potent marketing force distinguished from macro-influencers and celebrities not by reach but by depth engagement perceived authenticity they command within niche communities per Campbell & Farrell 2020. Unlike celebrity endorsers whose relationship with audiences typically distant aspirational micro-influencers often perceived by followers as relatable peers ordinary individuals with specialised knowledge taste whose recommendations carry credibility of trusted friend rather than paid spokesperson per De Veirman et al. 2021. Commercial significance grown rapidly alongside expansion social commerce digital marketplaces. Brands and digital retailers increasingly favour micro-influencer partnerships over celebrity endorsement citing higher engagement rates more precisely defined niches comparatively lower costs per Kay et al. 2020. In Nigeria trend especially pronounced within fashion beauty lifestyle consumer electronics where micro-influencers on Instagram TikTok routinely feature products sourced from marketplaces Jumia Konga as well as independent social commerce vendors operating primarily through Instagram WhatsApp storefronts. However growth occurred against backdrop persistent scepticism toward digital commerce broadly rooted in concerns about online fraud counterfeit products misrepresented goods. Within environment question whether how micro-influencer endorsement translates into genuine consumer trust in digital marketplaces as opposed to mere engagement remains empirically underexplored. Existing global literature established source credibility comprising expertise trustworthiness attractiveness and parasocial relationships one-sided emotional bonds audiences form with personalities are key psychological mechanisms per Lou & Yuan 2022 Sokolova & Kefi 2020. Yet extent mechanisms function similarly within Nigerian socio-cultural context where trust deficits more acute not sufficiently investigated. Complexity introduced by regulatory ethical considerations surrounding sponsored content disclosure. As consumers become aware content often commercially sponsored question arises whether disclosure erodes trust-building effect or transparency itself becomes trust-enhancing signal tension documented in international literature per Boerman et al. 2021 but rarely examined within Nigerian market. Research on micro vs macro influencer impact on brand trust and loyalty source credibility and parasocial interaction and parasocial relationships with micro-influencers sponsorship disclosure shows micro-influencers have higher source credibility and parasocial interaction and that sponsorship disclosure moderates bond. For related project materials see ScholarNestHub marketing collection . Main Abstract This study examined relationship between micro-influencer marketing and consumer trust in digital marketplaces among online shoppers in Enugu metropolis. Proliferation of social media platforms Instagram TikTok YouTube given rise to micro-influencers individuals with modest but highly engaged followings typically between 1,000 and 100,000 followers increasingly deployed by brands and digital marketplaces as more relatable and cost-effective alternative to celebrity endorsement. Despite rapid growth within Nigerian digital economy limited empirical work examined how perceived credibility and relatability translate into consumer trust and purchase behaviour particularly within emerging market context characterised by both high social media engagement and persistent scepticism toward online commerce. Study adopted descriptive survey research design drawing sample of 384 respondents from estimated population social-media-active online shoppers in Enugu metropolis using Taro Yamane formula complemented by purposive and convenience sampling. Structured thirty-item five-point Likert-scale questionnaire administered to respondents who follow at least one micro-influencer and have purchased or considered purchasing product based on micro-influencer recommendation. Data analysed using descriptive statistics and inferential statistics namely Pearson Product Moment Correlation and hierarchical moderated regression using SPSS version 26. Findings revealed micro-influencer marketing has statistically significant positive relationship with consumer trust in digital marketplaces; perceived source credibility comprising expertise trustworthiness attractiveness significantly predicts consumer trust; parasocial relationships formed with micro-influencers significantly influence purchase intention; and sponsored content disclosure significantly though only partially moderates relationship between micro-influencer marketing and consumer trust. Study concludes micro-influencers function as credible relationally embedded intermediaries capable of meaningfully shaping consumer trust and purchasing behaviour within Nigerian digital marketplaces and recommends brands prioritise authenticity and transparent sponsorship disclosure in influencer partnerships, micro-influencers be selected based on demonstrated credibility and audience relationship quality rather than follower count alone and regulatory attention be paid to advertising disclosure standards in influencer-mediated digital commerce. Extends Source Credibility Theory and Parasocial Interaction Theory to under-researched context of micro-influencer marketing in Sub-Saharan African digital marketplaces. Keywords: Micro-Influencer, Influencer Marketing, Consumer Trust, Source Credibility, Parasocial Relationship, Digital Marketplace, Enugu
MarketingTHE EFFECT OF SOCIAL COMMERCE ON ONLINE PURCHASE INTENTION
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About This Research Topic Social media has evolved from a communication channel into a fully functional marketplace. The convergence known as social commerce now allows product discovery, peer consultation, and purchase completion to happen directly inside platforms such as Instagram, Facebook, TikTok, and WhatsApp, without redirecting to a standalone e-commerce site. Features like shoppable posts, in-app checkout, live shopping streams, and embedded reviews have collapsed the funnel from inspiration to transaction into a single scroll. Unlike traditional e-commerce where a consumer interacts with a relatively impersonal storefront, social commerce is socially architected. Shoppers see likes, comments, mutual friends who bought, influencer endorsements, and real-time questions during live commerce. This social embedding is theorized to provide informational support, emotional support, and social presence that reduce uncertainty and build trust. Globally, TikTok Shop, Instagram Shopping, and Facebook Marketplace have scaled rapidly, with live commerce driving explosive growth in Asia and accelerating adoption in Nigeria where small and informal sellers bypass websites entirely to sell via social platforms. For Nigerian consumers, however, concerns about fraud, payment security, and legitimacy remain salient. This article for SCHOLARNESTHUB rewrites and deepens an undergraduate study that examined how social commerce drives online purchase intention among 384 online consumers, clarifying the roles of social support, trust, and perceived risk. Readers exploring similar topics can start with social commerce project topics on SCHOLARNESTHUB for complementary frameworks and recent Nigerian case studies. Main Abstract The convergence of social media and electronic commerce has produced social commerce, where shopping activities including product discovery, peer consultation, and purchase completion occur directly within social media environments rather than on dedicated e-commerce websites. Features such as shoppable posts, in-app checkout, live shopping streams, and socially embedded reviews have transformed platforms into commercial marketplaces. However, the mechanisms through which social commerce features translate into online purchase intention, distinct from social media marketing or e-commerce generally, remain incompletely understood, particularly in emerging markets. This study examined the effect of social commerce on online purchase intention among selected online consumers. Objectives were to assess extent of engagement with social commerce features, determine effect of social commerce on purchase intention, examine influence of social support on consumer trust, and evaluate moderating role of perceived risk. Descriptive survey design was adopted. Data were obtained from 384 online consumers determined using Cochran formula for infinite populations via purposive and convenience sampling. A structured five-point Likert scale questionnaire was validated and pilot-tested, yielding Cronbach's Alpha above 0.70 for all constructs. Analysis used descriptive statistics and inferential statistics including Chi-square and simple/multiple linear regression with SPSS version 26. Findings revealed moderate-to-high engagement with social commerce features, a statistically significant positive effect of social commerce on online purchase intention, significant positive influence of social support on consumer trust in social commerce platforms, and significant moderation by perceived risk such that positive effect of engagement on purchase intention weakened substantially among consumers reporting higher transactional risk. The study concluded that social commerce is a significant and increasingly central driver of purchase intention, whose effectiveness rests on social support and trust but remains constrained by residual risk perception. Recommendations include strengthening visible trust signals such as verified seller badges and buyer protection guarantees, cultivating community-based informational and emotional support, and investing in secure transparent payment infrastructure.
MarketingSOCIAL MEDIA ENGAGEMENT AND CUSTOMER LOYALTY IN THE DIGITAL ECONOMY
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A bout This Research Topic The digital economy has redefined brand-customer relationships from periodic transactions to continuous, real-time interaction. Where brands once relied on in-store experiences and broadcast advertising, social platforms now enable daily two-way dialogue. This evolution has placed social media engagement as a core driver of customer loyalty at the center of modern marketing strategy. Engagement is no longer just about likes; it reflects how deeply consumers think, feel, and act around a brand online. Research shows that true engagement is multidimensional: cognitive engagement captures attention and mental focus on brand content, affective engagement reflects emotional connection and enjoyment, and behavioural engagement represents observable actions like liking, commenting, sharing, and co-creating. Together, these dimensions build psychological bonds that transactional interactions alone cannot achieve. Yet many brands with high engagement metrics struggle with retention. This disconnect suggests that engagement quantity alone does not guarantee loyalty, especially when trust is low. In emerging digital markets like Nigeria, where social media adoption outpaces trust in digital commerce, understanding which engagement dimension drives loyalty most, and how trust conditions this link, is strategically vital. This article examines social media engagement and customer loyalty in the digital economy, disaggregating engagement into its three dimensions and testing customer trust as a moderator. Main Abstract This study examined the effect of social media engagement on customer loyalty within the digital economy, with particular attention to the roles of cognitive, affective, and behavioural engagement, and the moderating influence of customer trust on the engagement-loyalty relationship. The study was guided by four objectives: to determine the effect of cognitive engagement on customer loyalty; to examine the effect of affective engagement on customer loyalty; to assess the effect of behavioural engagement on customer loyalty; and to evaluate the moderating role of customer trust. A survey research design was adopted. A structured questionnaire was administered to 395 social media users who engage with at least one brand on social media using multi-stage sampling; 385 were retrieved and 376 found usable, representing a 95.2% response rate. Data were analysed using descriptive statistics and inferential statistics including Pearson correlation, hierarchical multiple regression, and chi-square tests via SPSS version 26. Findings revealed that cognitive engagement (β = 0.23, p < 0.05), affective engagement (β = 0.33, p < 0.05), and behavioural engagement (β = 0.27, p < 0.05) each had a positive and significant effect on customer loyalty, jointly explaining 56.2% of variance in customer loyalty (Adjusted R² = 0.562, F = 159.7, p < 0.05). Customer trust significantly moderated the relationship (ΔR² = 0.034, p < 0.05), strengthening the effect of engagement on loyalty among high-trust consumers and weakening it among low-trust consumers. The study concluded that social media engagement is a significant multidimensional driver of loyalty, with affective engagement exerting the strongest individual influence, but its loyalty-building potential is substantially conditioned by customer trust. Brands should prioritize emotional connection alongside cognitive and behavioural tactics and invest in transparency and responsive service to build trust, as engagement without trust is unlikely to yield durable loyalty. Keywords: Social Media Engagement, Customer Loyalty, Cognitive Engagement, Affective Engagement, Behavioural Engagement, Customer Trust, Digital Economy
MarketingTHE EFFECT OF ELECTRONIC WORD-OF-MOUTH ON CONSUMER PURCHASE INTENTION
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About This Research Topic The shift from private product conversations to public, searchable online opinions has fundamentally reshaped modern shopping. Today, consumers instinctively check ratings, detailed reviews, and social media commentary before committing to a purchase. This powerful phenomenon, known as electronic word-of-mouth and its influence on buying decisions , has become more trusted than traditional advertising because it is perceived as independent and experience-based. Unlike brand-generated content, eWOM offers authentic insights from real users, directly shaping how consumers judge products. In Nigeria and other emerging economies, this reliance is even more intense. With explosive growth of e-commerce platforms like Jumia, Konga, and Instagram vendors, coupled with near-universal social media adoption, shoppers face a constant stream of opinions. Yet, not all reviews carry equal weight. Academic evidence shows that argument quality, source credibility, and review valence determine whether eWOM is perceived as useful and adopted. Understanding these drivers is critical for brands seeking to turn online conversations into conversions. This article provides a fully rewritten, SEO-optimized analysis of the effect of electronic word-of-mouth on consumer purchase intention. Grounded in the Information Adoption Model and Source Credibility Theory, it examines how credibility drives usefulness and why negative reviews exert disproportionate influence, offering practical strategies for marketers in competitive digital marketplaces. Main Abstract This study investigates the effect of electronic word-of-mouth (eWOM) on consumer purchase intention among online shoppers in an emerging market context. The proliferation of online reviews, ratings, and social media commentary has transformed word-of-mouth from a private interpersonal exchange into a public, permanent, and globally accessible information source that heavily influences pre-purchase evaluation. Anchored on the Information Adoption Model, the study specifically assesses consumer exposure to and reliance on eWOM, determines the effect of eWOM on purchase intention, examines how eWOM source credibility influences perceived information usefulness, and evaluates the moderating role of review valence on the eWOM-purchase intention link. A descriptive survey design was adopted. A sample of 384 active online consumers was selected using the Cochran formula for infinite populations through purposive and convenience sampling techniques. Data were collected using a structured questionnaire on a five-point Likert scale, validated through expert review and pilot testing with Cronbach's Alpha exceeding 0.70 for all constructs. Analysis was conducted using descriptive statistics and inferential techniques including Chi-square and multiple linear regression via SPSS version 26. Findings indicate a high level of exposure to and reliance on eWOM among respondents. Results show that eWOM exerts a significant positive effect on consumer purchase intention, that source credibility significantly enhances perceived information usefulness, and that review valence significantly moderates the relationship between eWOM and purchase intention. Notably, negative reviews demonstrated a stronger, asymmetric influence on purchase intention compared to positive reviews of similar volume. The study concludes that eWOM is a powerful determinant of purchase intention whose effectiveness depends more on credibility and argument quality than on sheer volume. It recommends proactive monitoring of online conversations, transparent response to negative feedback, and strategies that encourage authentic, detailed customer reviews. Keywords: Electronic Word-of-Mouth, eWOM, Consumer Purchase Intention, Source Credibility, Review Valence, Information Usefulness, Online Reviews
MarketingTHE EFFECT OF INFLUENCER AUTHENTICITY ON BRAND CREDIBILITY AND CONSUMER BEHAVIOUR
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About This Research Topic Influencer marketing grown from niche promotional tactic into mainstream pillar digital marketing strategy with brands across virtually every category — fashion, beauty, food, finance, technology — partnering with social media personalities to reach audiences through content perceived as more personal and relatable than traditional advertising per De Veirman et al. 2017. Appeal rests substantially on premise influencers unlike traditional celebrity endorsers perceived as ordinary relatable individuals whose product endorsements carry credibility of trusted peer rather than paid spokesperson. This premise however come under increasing strain as influencer marketing scaled and commercialised. As sponsored content proliferated consumers grown more attuned and sceptical of commercial motives behind endorsements giving rise to what scholars term authenticity work — deliberate strategies influencers use to signal genuine personally held opinions amid pervasive sponsorship per Audrezet et al. 2020. Influencer authenticity — extent perceived to express honest unbiased personally consistent views rather than purely transactional promotion — consequently emerged as critical construct understanding whether how endorsements translate into brand credibility and favourable behaviour. Within Nigeria specifically urban centres Enugu metropolis influencer marketing highly visible feature spanning spectrum from large-following macro-influencers celebrities to smaller niche micro-influencers with tightly engaged communities. Anecdotal commentary and emerging global research suggest smaller-following influencers may paradoxically be perceived as more authentic and trustworthy than larger counterparts precisely because more personal less overtly commercial tone per Kay et al. 2020. Recent studies on impact of influencer authenticity on purchase intentions Source Credibility Theory and persuasive power of social media influencers in brand credibility and purchase intention show authenticity and credibility synergistically foster consumer trust and that informative value authenticity homophily positively affect parasocial relationships which affect brand credibility and purchase intention. For related project materials see ScholarNestHub marketing collection . Main Abstract Influencer marketing become dominant strategy through which brands seek to reach and persuade consumers on social media yet growing consumer scepticism toward sponsored content placed increasing scrutiny on authenticity of influencer endorsements. Whether influencer perceived as genuinely authentic — expressing honest personally held opinions rather than purely paid promotion — increasingly theorised as critical determinant of whether endorsements translate into brand credibility and favourable consumer behaviour yet empirical evidence on relationship within Nigerian social media contexts remains limited. This study examined effect of influencer authenticity on brand credibility and consumer behaviour among social media users in Enugu metropolis. Guided by four objectives: examine consumers' perception of influencer authenticity on social media; assess effect of influencer authenticity on brand credibility; evaluate effect of brand credibility on consumer purchase intention; and determine whether brand credibility mediates relationship between influencer authenticity and consumer purchase intention. Descriptive survey research design adopted and data collected from 318 social media users in Enugu metropolis determined using Cochran formula for unknown population and selected through multi-stage sampling technique using structured 24-item 5-point Likert-scale questionnaire. Data analysed using descriptive statistics frequencies percentages mean scores and inferential statistics simple linear regression, mediation analysis using Baron and Kenny causal-steps approach with Sobel test confirmation and independent samples t-test with aid of SPSS version 26. Findings revealed influencer authenticity significantly and positively predicts brand credibility β=0.612 p<0.05; brand credibility significantly and positively predicts consumer purchase intention β=0.489 p<0.05; brand credibility significantly and partially mediates relationship between influencer authenticity and purchase intention reducing direct effect from β=0.518 to β=0.241 upon inclusion of mediator Sobel z=6.87 p<0.05; and followers of micro-influencers reported significantly higher perceived influencer authenticity than followers of macro-influencers t=8.02 p<0.05. Study concluded influencer authenticity significant driver of both brand credibility and consumer purchase behaviour operating substantially though not entirely through its effect on brand credibility and that smaller-following micro-influencers currently enjoy distinct authenticity advantage over larger macro-influencers among Enugu metropolis social media users. Recommended brands prioritise authenticity and genuine fit over follower count when selecting influencer partners invest in longer-term rather than one-off influencer relationships to build credibility and that micro-influencer partnerships be given greater strategic weight in Nigerian influencer marketing budgets. Keywords: Influencer authenticity, brand credibility, consumer behaviour, purchase intention, micro-influencers, macro-influencers, social media marketing, Enugu metropolis
MarketingPERSONALIZED ONLINE MARKETING AND CUSTOMER PURCHASE BEHAVIOUR
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About This Research Topic Evolution of digital marketing marked by decisive shift away from mass undifferentiated advertising toward personalized marketing communication tailored to individual characteristics preferences behaviour. Personalized online marketing encompasses practices including personalised advertisements retargeted based on browsing history, individualised email campaigns triggered by past purchase, dynamically customised website content and targeted promotional offers generated from consumer data profiles all unified by underlying logic of using consumer data to deliver communication perceived as more relevant than generic alternatives per Aguirre et al. 2022. Commercial rationale rests on well-established research suggesting messages perceived as personally relevant receive greater cognitive attention processed more favourably more likely to influence subsequent behaviour than generic communication competing for attention within cluttered digital environment per Tucker 2022. Platforms invested heavily in data collection infrastructure capable of supporting real-time individualised personalisation at scale. Within Nigerian digital retail context personalized marketing increasingly visible manifesting in retargeted product ads following browsing sessions across platforms, personalised email offers referencing viewed or abandoned-cart items and dynamically tailored homepage content on Jumia and Konga. However psychological and behavioural mechanisms through which personalisation actually translates into purchase behaviour among Nigerian consumers as distinct from mere attention remain comparatively underexamined. Central theoretical tension concerns trade-off between convenience relevance benefits and privacy costs associated with data collection formalised in Privacy Calculus Theory as rational weighing of perceived benefits against privacy risks per Dinev & Hart 2021. This tension may be particularly salient within Nigerian context where concerns about online fraud and data misuse coexist with strong price-sensitivity and appetite for relevant promotional offers creating distinctive calculus differing from digitally mature markets. Complementing perspective Elaboration Likelihood Model offers insight into how perceived relevance shapes depth of cognitive processing with highly relevant content more likely processed via effortful attitude-changing central route rather than superficial peripheral route per Petty & Cacioppo 1986 and recent integration. Studies on personalization-privacy paradox in AI-driven advertising and effects of web personalization integrating Elaboration Likelihood Model confirm relevance and privacy trade-off. For related project materials see ScholarNestHub marketing collection . Main Abstract This study examined relationship between personalized online marketing and customer purchase behaviour among online shoppers in Enugu metropolis. Personalized online marketing encompassing tailored advertisements, personalised email campaigns, individualised website content and targeted promotional offers generated from consumer browsing and purchase data has become central feature of digital retail strategy as e-commerce platforms and digital marketers seek to cut through information overload and deliver more relevant marketing communication. Despite widespread deployment limited empirical work examined how personalized online marketing actually shapes purchase behaviour among Nigerian online shoppers particularly given psychological trade-off consumers must navigate between convenience of relevant marketing and growing concern over personal data such personalisation requires. Study adopted descriptive survey research design drawing sample of 384 respondents from estimated population of online shoppers in Enugu metropolis using Taro Yamane formula complemented by purposive and convenience sampling. Structured twenty-five-item five-point Likert-scale questionnaire administered to respondents who had encountered personalized online marketing content while shopping online. Data analysed using descriptive statistics and inferential statistics namely Pearson Product Moment Correlation and hierarchical moderated regression using SPSS version 26. Findings revealed personalized online marketing has statistically significant positive relationship with customer purchase behaviour; perceived relevance of personalized marketing content significantly predicts purchase behaviour; personalized promotional targeting significantly influences impulse buying behaviour; and privacy concern significantly though only partially moderates relationship between personalized online marketing and purchase behaviour. Study concludes personalized online marketing functions as genuinely effective driver of Nigerian online shoppers' purchase behaviour operating principally through perceived relevance it generates while privacy concern tempers without eliminating this effect. Recommends digital marketers prioritise accuracy and contextual relevance of personalisation over sheer frequency, data collection practices underlying personalisation be made transparent to reduce consumer privacy apprehension and marketers exercise restraint in personalised promotional targeting to avoid encouraging excessive impulse purchasing. Extends Elaboration Likelihood Model and Privacy Calculus Theory to under-researched context of personalized online marketing in Sub-Saharan African digital retail markets. Keywords: Personalized Marketing, Online Marketing, Purchase Behaviour, Perceived Relevance, Privacy Concern, E-commerce, Enugu
MarketingSOCIAL MEDIA ALGORITHMS AND THEIR EFFECT ON CONSUMER BRAND DISCOVERY
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About This Research Topic Way consumers encounter new brands fundamentally reshaped by algorithmic systems governing content distribution. Where discovery once depended primarily on active search, word-of-mouth or paid advertising placements, platforms Instagram, TikTok and X now employ sophisticated recommendation algorithms determining largely without explicit user request which content and which brands user encounters within feed, Explore page or For You page. This algorithmic mediation made algorithms themselves rather than brands' own marketing effort alone decisive gatekeeper of brand discovery. Algorithms operate through several interconnected mechanisms relevant to discovery. Algorithmic personalization uses prior behaviour likes follows watch time interaction patterns to tailor content surfacing brands aligned with inferred interests even without follow relationship. Algorithmic trend and virality surfacing prioritises content demonstrating high engagement velocity across broader platform exposing users to brands riding wave of collective attention regardless of individual history. Algorithmic hashtag and explore discovery features dedicated interfaces TikTok For You page Instagram Explore tab hashtag aggregation deliberately designed to surface content and brands beyond established following functioning as structured discovery mechanism distinct from personalization or organic virality. This mediation carries notable tension. On one hand algorithmic systems particularly explore and trend mechanisms hold genuine potential to expose consumers to novel brands unlikely encountered through existing connections or search alone phenomenon aligned with serendipitous discovery in information behaviour research per research on how algorithms shape user experience and content discovery . On other hand substantial commentary raises concern heavily personalized curation may narrow rather than broaden range of brands encountered phenomenon widely termed filter bubble effect potentially reinforcing existing preferences rather than facilitating genuine discovery per systematic review on filter bubbles and echo chambers and Pariser filter bubble analysis . For related project materials see ScholarNestHub marketing collection . Main Abstract This study examined effect of social media algorithms on consumer brand discovery with particular attention to roles of algorithmic personalization, trend and virality surfacing and hashtag/explore discovery features and moderating influence of perceived filter bubble concern on algorithm-discovery relationship. Guided by four objectives: determine effect of algorithmic personalization on brand discovery; examine effect of algorithmic trend and virality surfacing on brand discovery; assess effect of algorithmic hashtag and explore discovery features on brand discovery; and evaluate moderating role of perceived filter bubble concern on relationship between social media algorithms and consumer brand discovery. Survey research design adopted and structured questionnaire administered to 390 social media users who reported discovering at least one new brand through social media using multi-stage sampling technique of which 380 retrieved and 372 found usable representing response rate 95.4%. Data analysed using descriptive statistics frequencies percentages means standard deviation and inferential statistics Pearson correlation, hierarchical multiple regression and chi-square tests with aid of SPSS version 26. Findings revealed algorithmic personalization β=0.26 p<0.05 algorithmic trend and virality surfacing β=0.24 p<0.05 and algorithmic hashtag/explore discovery features β=0.32 p<0.05 each had positive and statistically significant effect on consumer brand discovery jointly accounting for approximately 55.9% variance in brand discovery Adjusted R²=0.559 F=155.8 p<0.05. Further found perceived filter bubble concern significantly moderated relationship ΔR²=0.036 p<0.05 weakening positive effect among consumers who perceived feed as narrow or repetitive and strengthening it among those who perceived feed as diverse. Concluded social media algorithms are significant multidimensional driver of consumer brand discovery with explore and hashtag-based discovery features mechanisms deliberately designed to surface novel content beyond user's established interests exerting strongest individual influence but discovery potential meaningfully constrained by consumers' perceived filter bubble concern. Recommended among other things brands invest in hashtag and explore-page-optimised content strategies as strongest driver identified, platforms continue improving algorithmic diversity safeguards to counter filter bubble effects and brands pursuing discovery-stage objectives prioritise content formats and signals most likely to be surfaced through trend and virality mechanisms rather than relying solely on personalization to reach entirely new audiences. Keywords: social media algorithms, algorithmic personalization, brand discovery, filter bubble, explore features, hashtag discovery, consumer behaviour
MarketingSOCIAL MEDIA MARKETING ANALYTICS AND MARKETING PERFORMANCE
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About This Research Topic Rise of social media as dominant marketing channel has fundamentally altered how SMEs with limited traditional advertising budgets engage customers and build brand presence. Platforms Facebook, Instagram, TikTok, X have become primary marketing infrastructure for large proportion of Nigerian SMEs offering low-cost access to audiences otherwise requiring substantial traditional media expenditure to reach per Appiah-Otoo & Song 2021. Alongside adoption has come proliferation of social media marketing analytics tools and dashboards both native (Meta Business Suite, Instagram Insights) and third-party (Hootsuite, Sprout Social) that provide granular data on reach, impressions, engagement rate, audience demographics and conversion behaviour. Analytics represents in principle significant opportunity for SMEs to make more informed evidence-based decisions optimising content strategy, posting schedules, targeting and budget allocation based on empirical data rather than intuition alone per Wedel & Kannan 2022. This aligns with broader shift toward data-driven decision-making where marketing performance encompassing brand awareness, customer engagement, lead generation and sales conversion increasingly expected to be measurable trackable optimisable in near real time. However extent Nigerian SMEs actually harness analytics to drive measurable performance remains empirically underexplored. Evidence suggests many adopt platforms for reach and low cost without developing analytical capability skills tools organisational routines needed to convert data into actionable decisions per Eze et al. 2021. This gap raises theoretical question: does mere availability translate into improved performance or does relationship depend critically on analytical skill and data-driven orientation? Resource-Based View suggests valuable rare difficult-to-imitate resources including capacity to collect and interpret social media data can serve as source of sustained advantage per Barney 1991. Complementing Dynamic Capabilities Theory emphasises firms must develop capacity to sense seize reconfigure resources in response to changing conditions per Teece 2021. Recent frameworks on determinants of SME performance from RBV perspective and social media and analytics for competitive performance framework integrate RBV and dynamic capabilities view. For related project materials see ScholarNestHub marketing collection . Main Abstract This study examined relationship between social media marketing analytics and marketing performance among small and medium enterprises SMEs in Enugu metropolis. Widespread adoption of platforms Facebook, Instagram, TikTok as marketing channels accompanied by growing availability of analytics tools ranging from native platform insights to third-party dashboards allowing businesses to track reach, engagement, conversion and audience behaviour in real time. Despite growing availability many Nigerian SMEs continue to rely on intuition-based marketing decisions rather than systematically leveraging data generated by social media activity raising questions about whether and how analytics actually translates into improved marketing performance within resource-constrained SME context. Study adopted descriptive survey research design drawing sample of 384 respondents comprising SME owners, marketing managers and social media managers from estimated population of social-media-active SMEs in Enugu metropolis using Taro Yamane formula complemented by purposive and convenience sampling. Structured twenty-five-item five-point Likert-scale questionnaire administered to respondents whose businesses actively use social media platforms for marketing and have access to at least basic analytics data. Data analysed using descriptive statistics and inferential statistics namely Pearson Product Moment Correlation and hierarchical moderated regression using SPSS version 26. Findings revealed social media marketing analytics usage has statistically significant positive relationship with marketing performance; data-driven marketing decision-making significantly predicts marketing performance; analytics usage has statistically significant positive influence on customer engagement; and managerial analytics skill significantly moderates relationship between analytics usage and marketing performance such that performance benefits substantially greater among SMEs whose decision-makers possess higher levels of analytics competence. Study concludes analytics constitutes genuine strategic capability rather than merely cosmetic reporting function for Nigerian SMEs and recommends SME owners invest in analytics skill development, platform providers and business support agencies simplify analytics tools for low-resource users and SME support policy prioritise digital marketing capability-building alongside access to platforms themselves. Study extends Resource-Based View and Dynamic Capabilities Theory to under-researched context of social media marketing analytics among Sub-Saharan African SMEs. Keywords: Social Media Marketing, Marketing Analytics, Marketing Performance, Data-Driven Decision-Making, Customer Engagement, SME, Enugu
MarketingTHE EFFECT OF E-COMMERCE CUSTOMER EXPERIENCE ON CUSTOMER LOYALTY
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About This Research Topic As e-commerce markets mature and product assortments across competing platforms converge, price and selection alone increasingly fail to differentiate one online retailer from another. In this environment, customer experience — cumulative impression shopper forms across every touchpoint including website/app usability, delivery and fulfilment, customer service responsiveness, and personalization — has emerged as primary battleground for competitive differentiation per Lemon & Verhoef (2016) customer journey framework . Firms delivering superior experience widely believed to build stronger more durable loyalty than firms competing on price alone. Theoretical logic connecting experience to loyalty typically runs through satisfaction: Expectancy-Disconfirmation Theory (Oliver, 1980) holds satisfaction arises when experience meets or exceeds prior expectations and drives repurchase intention and loyalty. Applied to e-commerce positive experience theorized to generate satisfaction which translates into repeat purchases, positive word-of-mouth and resistance to competitor offers constituting loyalty. However important complication exists: not all loyalty reflects genuine satisfaction. Switching Barriers Theory (Jones et al., 2000) documents customers may remain loyal not because satisfied but because switching perceived as costly inconvenient risky — lost loyalty points, unfamiliarity with new interface, saved payment details, habit. This creates distinction between true loyalty rooted in satisfaction and spurious or lock-in loyalty rooted in switching costs — distinction with strategic implications since cost-driven retention generally more fragile and vulnerable to competitive disruption than satisfaction-driven loyalty, as also shown in recent e-commerce loyalty research where satisfaction explained 36% variance . For related project materials, see ScholarNestHub e-commerce collection . Main Abstract As e-commerce competition intensifies firms increasingly compete not merely on price but on quality of overall customer experience — website/app usability, delivery and fulfilment, customer service responsiveness and personalization — as means of building lasting customer loyalty. However loyalty in e-commerce is not always pure reflection of satisfaction with experience: consumers may also remain loyal or appear loyal because switching to competing platform is inconvenient or costly phenomenon that complicates straightforward experience-to-loyalty relationship assumed in much practitioner discourse. This study examined effect of e-commerce customer experience on customer loyalty focusing on mediating role of customer satisfaction and moderating role of perceived switching cost among online shoppers in Enugu State Nigeria. Study anchored on Expectancy-Disconfirmation Theory, Experience Economy framework, Switching Barriers Theory and Relationship Marketing Theory and adopted descriptive survey research design. Structured questionnaire administered to sample of 300 online shoppers selected through convenience and simple random sampling techniques. Data analysed using descriptive statistics and inferential statistics Chi-square test, Pearson correlation and multiple regression with aid of SPSS version 26. Findings revealed e-commerce customer experience has statistically significant positive effect on customer satisfaction; customer satisfaction has statistically significant positive effect on customer loyalty; perceived switching cost significantly moderates satisfaction-loyalty relationship but in dampening rather than amplifying direction such that satisfaction predicts loyalty considerably more strongly among consumers facing low switching costs than among those facing high switching costs; and perceived switching cost also has statistically significant positive direct effect on customer loyalty independent of satisfaction. Study concluded e-commerce customer loyalty comprises two empirically distinguishable components — genuine satisfaction-driven loyalty and cost-driven potentially spurious loyalty — and that firms relying on switching costs to retain dissatisfied customers risk mistaking retention for true loyalty. Recommended firms prioritize genuine experience quality improvement over erection of switching barriers given satisfaction-driven loyalty more robust and less vulnerable to competitive disruption than cost-driven retention. Keywords: E-commerce customer experience, customer satisfaction, switching cost, customer loyalty, expectancy-disconfirmation theory
MarketingTHE EFFECT OF SOCIAL MEDIA MARKETING ON BRAND AWARENESS AND CUSTOMER PURCHASE INTENTION
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About This Research Topic Social media platforms have evolved from simple tools for personal connection into central pillars of contemporary brand-building. Platforms such as Instagram, Facebook, TikTok and X host substantial share of brands' marketing activity ranging from organic content posting to influencer partnerships. Social media marketing defined as use of social platforms to promote brand and build customer relationships has become indispensable valued for reach, low cost entry and capacity for direct two-way interaction. Activity spans three interconnected dimensions. Content marketing involves creation of informative entertaining valuable content to attract attention. Interactivity and engagement involve two-way features comments, DMs, polls, live sessions. Influencer marketing and electronic word-of-mouth involve amplification through trusted third parties. Brand awareness extent consumers can recognise or recall brand within category has long been recognised as foundational building block of brand equity and necessary precondition for purchase consideration per classical hierarchy-of-effects models. Social media is theorised to be potent driver given capacity for rapid wide-reaching distribution and shareable nature allowing organic spread. Customer purchase intention willingness and plans to purchase represents immediate commercial outcome brands seek. Growing literature suggests relationship may not be entirely direct: social media may operate through capacity to first build awareness which then shapes intention positioning awareness as critical mediator. Recent studies on mediation analysis of brand awareness in social media marketing and mediating role of brand awareness influence of social media marketing confirm this pathway. For related marketing project materials, see ScholarNestHub marketing collection . Main Abstract This study examined effect of social media marketing on brand awareness and customer purchase intention with particular attention to mediating role brand awareness plays in translating social media marketing activity into purchase-related consumer outcomes. Guided by four objectives: determine effect of social media content marketing on brand awareness; examine effect of social media interactivity and engagement on brand awareness; assess effect of social media influencer marketing and electronic word-of-mouth eWOM on brand awareness; and evaluate mediating role of brand awareness on relationship between social media marketing and customer purchase intention. Survey research design adopted and structured questionnaire administered to 400 social media users who reported following or engaging with at least one brand on social media using multi-stage sampling technique of which 380 retrieved and found usable representing response rate 95%. Data analysed using descriptive statistics frequencies percentages means standard deviation and inferential statistics Pearson correlation, multiple regression and Baron and Kenny causal-steps mediation approach complemented by Sobel test with aid of SPSS version 26. Findings revealed social media content marketing (β=0.28 p<0.05), interactivity and engagement (β=0.24 p<0.05) and influencer marketing/eWOM (β=0.31 p<0.05) each had positive and statistically significant effect on brand awareness jointly accounting for approximately 54.7% variance in brand awareness Adjusted R²=0.547 F=150.6 p<0.05. Brand awareness in turn had statistically significant positive effect on customer purchase intention β=0.42 p<0.05. Mediation analysis revealed brand awareness significantly and partially mediated relationship between social media marketing and purchase intention Sobel z=6.38 p<0.05 with effect reducing from β=0.56 total effect without mediator to β=0.31 direct effect controlling for brand awareness upon inclusion indicating substantial though not exclusive portion operates through capacity to build brand awareness. Concluded social media marketing significant driver of both brand awareness and customer purchase intention and that brand awareness functions as genuine partial transmission mechanism linking activity to purchase outcomes rather than purchase intention driven by social media exposure alone. Recommended among other things brands prioritise influencer marketing and eWOM as strongest individual driver identified, maintain consistent high-quality content marketing and genuine audience interactivity to sustain awareness-building momentum and explicitly track brand awareness metrics alongside direct conversion metrics when evaluating social media marketing ROI. Keywords: social media marketing, brand awareness, customer purchase intention, content marketing, influencer marketing, electronic word-of-mouth, mediation analysis.
MarketingSHORT-FORM VIDEO MARKETING AND CONSUMER PURCHASE BEHAVIOUR: A STUDY OF SELECTED ONLINE CONSUMERS
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About This Research Topic The past several years have witnessed decisive shift toward short-form video, brief typically 15- to 90-second vertically oriented videos distributed through TikTok, Instagram Reels and YouTube Shorts. Since TikTok's global expansion, format evolved from entertainment into central pillar of digital marketing, with brands and creators using it to showcase products, deliver tutorials and build relationships at scale unmatched by longer-form content. Central to marketing appeal is distinctive discovery mode: rather than relying on deliberate search or existing social connections, platforms surface content predominantly through algorithm-driven recommendation feeds, the 'For You' page, which continuously learns individual interest based on engagement signals per Omar & Dequan 2020. This allows even small brands significant organic reach without large budgets. Content commonly blends entertainment, information and persuasion featuring demonstrations, unboxings, tutorials and creator testimonials in conversational seemingly unscripted style. This authenticity is believed to enhance trust and engagement relative to polished traditional advertising per Sokolova & Kefi 2020. Recent studies on impact of short-form video ads content characteristics on purchase behaviour and influence of short-form video advertising on purchase intention show short-form significantly shapes purchase. For related digital marketing materials, see ScholarNestHub marketing collection . Main Abstract Rapid rise of short-form video platforms including TikTok, Instagram Reels and YouTube Shorts has fundamentally reshaped how brands communicate with consumers and how consumers discover and evaluate products. Characterised by brevity, high shareability, algorithm-driven discovery and strong emphasis on creator authenticity short-form video emerged as one of most influential digital marketing formats of current decade. However extent to which engagement with short-form video marketing content translates into actual consumer purchase behaviour as opposed to mere passive viewing or entertainment consumption remains empirically underexplored particularly within emerging market contexts. This study examined short-form video marketing and consumer purchase behaviour among selected online consumers. Specifically sought to assess extent of consumer engagement with short-form video marketing content; determine effect of short-form video marketing on consumer purchase behaviour; examine influence of content creator credibility on consumer purchase decisions; and evaluate moderating role of platform algorithm-driven content discovery on relationship between short-form video engagement and purchase behaviour. Descriptive survey research design adopted and data obtained from sample of 384 online consumers determined using Cochran formula for infinite populations and selected through purposive and convenience sampling. Structured questionnaire anchored on five-point Likert scale validated and pilot-tested yielding Cronbach Alpha coefficients above 0.70 for all constructs. Data analysed using descriptive statistics (frequency, percentage, mean, standard deviation) and inferential statistics (Chi-square test and simple/multiple linear regression) using SPSS version 26. Findings revealed consumer engagement with short-form video marketing content is high among sampled online consumers; that short-form video marketing has statistically significant positive effect on consumer purchase behaviour including notable prevalence of impulse purchasing; that content creator credibility significantly and positively influences consumer purchase decisions; and that platform algorithm-driven content discovery significantly moderates relationship between short-form video engagement and purchase behaviour such that consumers who perceive algorithmic recommendations as highly relevant exhibit substantially stronger purchase responses to short-form video content. Study concluded short-form video marketing is potent and increasingly central driver of consumer purchase behaviour whose effectiveness amplified by creator credibility and algorithmic content relevance. Recommended among others that brands prioritise authentic creator-led short-form video content, invest in seamless in-app purchase pathways and align content strategy with platform algorithmic dynamics to maximise purchase conversion. Keywords: Short-Form Video, Social Media Marketing, Consumer Purchase Behaviour, Impulse Buying, Influencer Marketing, Content Engagement, Platform Algorithm
MarketingAI-POWERED RECOMMENDATION SYSTEMS AND ONLINE CONSUMER BUYING BEHAVIOUR
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About This Research Topic E-commerce has fundamentally transformed how consumers discover, evaluate and purchase products. Within this ecosystem, artificial intelligence has emerged as defining force through recommendation systems that analyse vast consumer data to generate personalised suggestions. These systems powering 'customers who bought this also bought', 'recommended for you', and 'trending near you' features on Jumia, Konga, Amazon and AliExpress have moved from peripheral conveniences to central pillars of retail strategy. AI recommendation systems operate through collaborative filtering, content-based filtering and hybrid models drawing on browsing history, purchases, search queries, demographics and real-time behavioural signals to predict purchase likelihood, as detailed by Ricci et al. on recommender systems and research on technology acceptance model for AI in e-commerce . Global evidence shows Amazon attributes substantial sales to recommendations, while Netflix credits engine for engagement. In Nigeria, e-commerce growth driven by internet penetration and mobile payments has made Enugu metropolis major commercial hub with rising online shopping among youthful tech-literate population. However, consumer response varies: some find personalisation helpful reducing search costs, others perceive intrusive manipulative threat to privacy per Aguirre et al. Theoretical lens combining SOR model for AI technology and purchase intention and Technology Acceptance Model provides framework for this study. For related marketing project materials, see ScholarNestHub marketing collection . Main Abstract This study examined influence of artificial intelligence-powered recommendation systems on online buying behaviour of consumers in Enugu metropolis. Rapid adoption of e-commerce platforms such as Jumia, Konga and AliExpress accompanied by increasing reliance on algorithmic recommendation engines personalising suggestions based on browsing history, purchase patterns and demographic data. Despite ubiquity limited empirical attention paid to how Nigerian shoppers perceive and respond to AI-driven personalisation particularly regarding purchase intention, trust, perceived usefulness and impulse buying tendencies. Study adopted descriptive survey research design drawing sample of 384 respondents from estimated population of online shoppers in Enugu metropolis using Taro Yamane formula and combination of purposive and convenience sampling techniques. Structured questionnaire anchored on five-point Likert scale administered to registered users of major e-commerce platforms and data analysed using descriptive statistics (frequencies, percentages, means, standard deviations) alongside inferential statistics (Pearson Product Moment Correlation, Chi-square tests and multiple regression) using SPSS version 26. Findings revealed AI-powered recommendation systems have statistically significant positive relationship with online purchase intention, that perceived personalisation accuracy significantly predicts consumer trust in e-commerce platforms, and that recommendation-induced product exposure significantly influences impulse buying behaviour among respondents. Study also found privacy concerns moderate but do not eliminate positive effect of recommendation systems on purchase behaviour. Based on findings study concludes AI-powered recommendation systems constitute significant driver of consumer decision-making in Nigerian online retail space and recommends e-commerce operators invest in transparent explainable recommendation algorithms, strengthen data privacy assurances and calibrate personalisation intensity to avoid consumer fatigue. Study contributes to marketing theory by extending Technology Acceptance Model and Stimulus-Organism-Response framework to context of algorithmic personalisation in emerging e-commerce market and offers practical guidance to online retailers, digital marketers and policymakers. Keywords: Artificial Intelligence, Recommendation Systems, Online Consumer Behaviour, Purchase Intention, E-commerce, Enugu
MarketingThe Effect of AI-Generated Advertising on Consumer Purchase Decisions
Elijah T
About This Research Topic Advertising has always required someone to write the words, shoot the images, and cut the footage together, a process that traditionally took weeks of coordinated creative work. Generative AI has started to strip much of that time out. Language models can draft ad copy in seconds, image and video generation tools can produce polished creative from a short text prompt, and AI-powered ad platforms can assemble and personalize thousands of ad variants automatically, at a scale no human creative team could realistically match. This shift raises a question that brands are still working out in practice: does AI-generated advertising actually persuade consumers to buy, and does it do so as effectively as advertising produced the traditional way? This article draws on a study that disaggregated AI-generated advertising into three components, ad copy, visual and creative content, and personalization, and tested how each affects consumer purchase decisions, along with the extent to which perceived authenticity shapes how AI-generated content is received . The sections below set out the study's background, problem, objectives, and scope, along with definitions of its key terms, to give a grounded picture of what generative AI can and cannot be expected to deliver in advertising. Main Abstract This study examined the effect of artificial intelligence (AI)-generated advertising on consumer purchase decisions, at a time when brands increasingly use generative AI tools to produce advertising copy, visual and video creative, and personalized ad content at a speed and scale unattainable through traditional, fully human-led ad production. The study was guided by four objectives: to determine the effect of AI-generated ad copy on consumer purchase decisions; to examine the influence of AI-generated visual and creative content on consumer purchase decisions; to assess the effect of AI-generated ad personalization on consumer purchase decisions; and to evaluate the moderating role of perceived authenticity on the relationship between AI-generated advertising and consumer purchase decisions. A survey research design was adopted, and a structured questionnaire was administered to 405 social media and digital platform users who had encountered AI-generated advertising, using a multi-stage sampling technique; 385 responses were retrieved and found usable, a response rate of 95.1%. Data were analysed using descriptive statistics (frequencies, percentages, means, standard deviation) and inferential statistics (Pearson correlation, hierarchical multiple regression, and chi-square tests) with SPSS version 26. Findings revealed that AI-generated ad copy (β = 0.25, p < 0.05), AI-generated visual and creative content (β = 0.29, p < 0.05), and AI-generated ad personalization (β = 0.28, p < 0.05) each had a positive and statistically significant effect on consumer purchase decisions, jointly accounting for approximately 57.1% of the variance in purchase decisions (Adjusted R² = 0.571, F = 169.4, p < 0.05). Perceived authenticity significantly moderated the relationship (ΔR² = 0.037, p < 0.05), strengthening the positive effect of AI-generated advertising on purchase decisions among consumers who perceived the content as authentic and credible, and weakening it among those who perceived it as artificial, manipulative, or untrustworthy. The study concluded that AI-generated advertising is a significant, multidimensional driver of consumer purchase decisions, but that its persuasive effectiveness is substantially conditioned by perceived authenticity, such that technically impressive AI-generated content that fails to feel genuine or credible risks underperforming relative to its creative and personalization potential. Recommendations included investing in AI-generated visual and creative content given its identified strength as a driver of purchase decisions, pairing AI-generated advertising with authenticity-reinforcing cues such as transparent disclosure and human oversight, avoiding AI-generated content that trends toward the uncanny or overtly synthetic, and continuously testing AI-generated ad variants against consumer authenticity perception rather than production efficiency alone. Keywords: AI-generated advertising, generative AI, ad copy, ad creative, ad personalization, perceived authenticity, consumer purchase decision
MarketingThe Role of Machine Learning in Predicting Customer Purchase Intention
Elijah T
About This Research Topic Customer purchase intention has become one of the most closely studied outcomes in modern marketing, because knowing in advance which customers are likely to buy allows a business to spend its limited marketing budget where it will do the most good. Over the past decade, the tools used to estimate this intention have shifted away from simple surveys and scoring sheets toward machine learning systems that learn directly from browsing history, transaction records, and engagement data. This shift promises sharper targeting and better returns on marketing spend, and it sits at the centre of a wider and growing body of research on AI-driven customer analytics that many businesses now draw on to justify investment in predictive tools. Yet a model that predicts accurately is not automatically a model that changes decisions for the better. A growing body of behavioural research shows that managers do not always trust, or act on, the recommendations an algorithm produces, even when those recommendations are demonstrably more accurate than human judgement. This article examines that gap directly, drawing on a study of digitally-enabled businesses in Enugu State, Nigeria, that investigated how machine learning capability and data quality shape the predictive accuracy of purchase intention models, how that accuracy translates into marketing decision effectiveness, and, critically, how much of that translation depends on whether managers actually trust the algorithm's output. See our broader coverage of AI-driven customer analytics in marketing decision-making for related findings on this theme. Main Abstract Businesses increasingly rely on machine learning (ML) to forecast whether a given customer will make a purchase, using behavioural, transactional, and demographic data to sharpen targeting and stretch marketing budgets further. Yet how far this predictive capability actually improves marketing decisions remains under-studied in emerging markets, and prior work on algorithmic decision-making warns that accuracy alone does not guarantee better decisions, since managers do not automatically trust or act on what an algorithm tells them. This study investigated the part machine learning plays in predicting customer purchase intention among digitally-enabled businesses in Enugu State, Nigeria, focusing on how ML capability and data quality shape predictive accuracy, how predictive accuracy in turn affects marketing decision effectiveness, and how managerial trust in algorithms moderates that relationship. Grounded in the Technology Acceptance Model, Diffusion of Innovation Theory, and Algorithm Aversion/Appreciation Theory, the study used a descriptive survey design. A structured questionnaire was administered to marketing managers, data analysts, and business owners drawn from a population of 1,200 registered businesses; applying the Taro Yamane formula produced a sample of 300 respondents, selected through stratified random sampling. Data were analysed using descriptive statistics alongside Chi-square tests, Pearson correlation, and multiple regression, run in SPSS version 26. The results showed that both ML capability and data quality significantly and positively affect predictive accuracy; that predictive accuracy significantly and positively affects marketing decision effectiveness; and that managerial algorithm trust significantly strengthens this last relationship, so that accurate predictions produce far greater improvements in marketing decisions where managers trust algorithmic output than where they do not. The study concludes that the business value of ML-based purchase intention prediction depends jointly on technical capability, data quality, and an organisation's willingness to act on what its models tell it; accuracy by itself is not enough. It recommends that businesses invest simultaneously in ML infrastructure and in building managerial trust, through explainable model design and a gradual, evidence-based approach to folding ML recommendations into everyday marketing decisions. Keywords: machine learning, purchase intention prediction, predictive accuracy, algorithm trust, marketing decision effectiveness
MarketingThe Role of AI-Driven Customer Analytics in Marketing Decision-Making
Elijah T
About this Research Topic AI-driven customer analytics doesn't improve marketing decisions by magic — it improves them by producing better insight, and that insight only helps if the people reading it actually understand what it's telling them. This study traces that exact chain among registered businesses in Enugu State, testing whether AI analytics genuinely improves decision quality, and how much of that improvement depends on the marketing team's own AI literacy rather than the tool itself. Readers interested in a related mechanism may also want to look at our project on AI-driven personalization and customer purchase intention , which examines a different downstream effect of the same underlying analytics capability. What follows carries the full research structure — background, problem statement, aim and objectives, research questions, significance, scope, and definitions — rebuilt for a wider readership while preserving the original study's focus and findings. Main Abstract Artificial intelligence-driven customer analytics — encompassing AI-powered segmentation, sentiment analysis, and predictive/churn analytics — is increasingly positioned as a means of processing customer data beyond human cognitive capacity, thereby improving the quality of marketing decisions. However, the mechanism by which such analytics actually improves decision-making, and the organizational conditions under which this improvement is realized, has remained underexamined in emerging market contexts. This study examined the role of AI-driven customer analytics in marketing decision-making, focusing on the mediating role of customer insight quality and the moderating role of marketing team AI literacy, among registered businesses in Enugu State, Nigeria. The study was anchored on Information Processing Theory, Bounded Rationality Theory, and the Technology-Organization-Environment framework, and adopted a descriptive survey research design. A structured questionnaire was administered to marketing managers and business owners drawn from a population of 1,200 registered businesses using the Taro Yamane formula to determine a sample size of 300, selected through stratified random sampling. Data were analysed using descriptive statistics and inferential statistics (Chi-square test, Pearson correlation, and multiple regression) using SPSS version 26. Findings revealed that AI-driven customer analytics adoption has a statistically significant positive effect on customer insight quality; that customer insight quality has a statistically significant positive effect on marketing decision-making quality; that AI-driven customer analytics adoption also has a smaller but statistically significant direct effect on marketing decision-making quality, consistent with partial mediation through insight quality; and that marketing team AI literacy significantly and positively moderates the relationship between customer insight quality and marketing decision-making quality. The study concluded that AI-driven customer analytics improves marketing decision-making primarily by improving the quality of customer insight available to decision-makers, and that this improvement is substantially amplified when marketing teams possess sufficient AI literacy to interpret and act on analytics outputs, and it recommended that businesses invest jointly in AI-driven analytics tools and in building marketing staff's AI literacy, rather than treating tool adoption alone as sufficient to improve decision-making.
MarketingThe Role of Real-Time Data Analytics in Digital Marketing Campaign Performance
Elijah T
About This Research Topic Two campaign managers can stare at the exact same live dashboard and walk away with completely different results — one adjusts bids and creative on the fly, the other just watches the numbers scroll by. This study breaks real-time data analytics into its three actual components — monitoring, optimisation, and personalisation — and finds that they don't contribute equally, and that a marketer's own analytics capability determines how much value any of them actually deliver. Readers interested in a related digital marketing performance question may also want to look at our project on AI-powered chatbots and customer satisfaction in digital marketing , which examines a different real-time customer-facing technology from a similar performance angle. What follows carries the full research structure — background, problem statement, aim and objectives, research questions, significance, scope, and definitions — rebuilt for a wider readership while preserving the original study's focus and findings. Main Abstract This study examined the role of real-time data analytics in digital marketing campaign performance, in a marketing environment where digital platforms now generate continuous streams of behavioural, engagement, and transactional data that can be captured and acted upon within minutes, or even seconds, of occurrence. The study was guided by four specific objectives: to determine the effect of real-time data monitoring on digital marketing campaign performance; to examine the influence of real-time campaign optimisation on digital marketing campaign performance; to assess the effect of real-time personalisation on digital marketing campaign performance; and to evaluate the moderating role of marketers' data analytics capability on the relationship between real-time data analytics and campaign performance. A survey research design was adopted, and a structured questionnaire was administered to 400 digital marketing practitioners, including in-house marketers, digital agency staff, and freelance digital marketers, using a multi-stage sampling technique, of which 380 were retrieved and found usable, representing a response rate of 95%. Data were analysed using descriptive statistics and inferential statistics (Pearson correlation, hierarchical multiple regression, and chi-square tests) with the aid of SPSS version 26. Findings revealed that real-time data monitoring (β = 0.26, p < 0.05), real-time campaign optimisation (β = 0.34, p < 0.05), and real-time personalisation (β = 0.25, p < 0.05) each had a positive and statistically significant effect on digital marketing campaign performance, jointly accounting for approximately 62% of the variance in campaign performance (Adjusted R² = 0.617, F = 202.8, p < 0.05). The study further found that marketers' data analytics capability significantly moderated the relationship (ΔR² = 0.038, p < 0.05), strengthening the positive effect of real-time data analytics on campaign performance among practitioners with higher self-rated analytics proficiency, and weakening it among those with lower proficiency. The study concluded that real-time data analytics is a critical, capability-dependent driver of digital marketing campaign performance, and that the ability to translate real-time data into timely optimisation decisions, rather than data availability alone, is what ultimately determines performance outcomes. It was recommended that organisations invest in real-time analytics dashboards and automation tools, build in-house data analytics capability through structured training, prioritise real-time campaign optimisation actions such as dynamic bid and budget adjustment over passive monitoring alone, and adopt real-time personalisation cautiously with due regard for consumer privacy expectations.
MarketingPredictive Customer Analytics and Customer Lifetime Value
Elijah T
About This Research Topic Two firms can buy the exact same predictive analytics platform and get wildly different returns on it — and this study's findings suggest the difference usually isn't the software. It's the data feeding it. This piece looks at how predictive customer analytics actually translates into customer lifetime value across banking, telecoms, e-commerce, and FMCG firms, and why data quality turned out to matter more than tool sophistication alone. Readers interested in a closely related question may also want to look at our project on customer data analytics and customer retention in Nigeria , which examines a closely related piece of the same customer-value puzzle. What follows carries the full research structure — background, problem statement, aim and objectives, research questions, significance, scope, and definitions — rebuilt for a wider readership while preserving the original study's focus and findings. Main Abstract The proliferation of customer data across digital and offline touchpoints has positioned predictive customer analytics as a strategic capability through which firms seek to understand, forecast, and maximise the long-run value of their customer relationships. Customer Lifetime Value (CLV), a forward-looking estimate of the net profit a firm expects to derive from a customer over the duration of the relationship, has emerged as a central metric guiding acquisition, retention, and resource-allocation decisions. Yet the extent to which predictive analytics adoption translates into measurable CLV and broader marketing performance outcomes, particularly among firms operating in emerging markets, has remained empirically underexplored. This study examined predictive customer analytics and customer lifetime value among selected firms and marketing professionals, assessing the extent of predictive customer analytics adoption; determining its effect on customer lifetime value; examining the influence of customer segmentation practices on customer retention; and evaluating the moderating role of data quality on the relationship between predictive analytics capability and customer lifetime value. A descriptive survey research design was adopted, and data were obtained from a sample of 272 marketing, sales, and CRM professionals drawn from banking, telecommunications, e-commerce/retail, and FMCG firms, determined using the Taro Yamane formula and selected through stratified random sampling. A structured questionnaire anchored on a five-point Likert scale was validated and pilot-tested, yielding Cronbach's Alpha coefficients above 0.70 for all constructs. Data were analysed using descriptive statistics and inferential statistics (Chi-square test and simple/multiple linear regression) using SPSS version 26. Findings revealed that predictive customer analytics adoption is moderate-to-high among sampled firms; that predictive customer analytics has a statistically significant positive effect on customer lifetime value; that customer segmentation practices significantly and positively influence customer retention; and that data quality significantly moderates the relationship between predictive analytics capability and customer lifetime value, such that firms with higher data quality derive substantially greater CLV benefits from their analytics investments. The study concluded that predictive customer analytics is a strategic driver of customer lifetime value, but that its commercial payoff is highly contingent on the underlying quality and integration of customer data, and it recommended that firms invest in robust data governance and integration infrastructure, build in-house analytical capability, and embed predictive insights directly into frontline marketing and retention decision-making.
MarketingMarketing Attribution Models and Digital Marketing Effectiveness
Elijah T
About This Research Topic A customer rarely buys after seeing one ad. They see a social post, click a search result days later, open a retargeting email, and finally convert after typing the brand name directly into Google. Figuring out which of those touchpoints actually deserves credit is the entire point of marketing attribution, and this study asks how well Nigerian SMEs and digital marketers in Enugu are actually doing it. This article works through a survey of 272 digital marketing practitioners and SME owners, testing how attribution model usage and sophistication relate to measurement accuracy and budget allocation efficiency. Readers researching related marketing topics can browse the Business Administration project collection on ScholarNestHub for comparable studies in marketing and analytics. What follows covers the background to marketing attribution and digital marketing measurement in Nigeria, the specific problem this study addresses, its objectives, questions, and hypotheses, the key terms used throughout, and closes with frequently asked questions for students and researchers working on marketing analytics and SME digital capacity. Main Abstract As digital marketing spend continues to grow, marketers face increasing pressure to demonstrate which channels and touchpoints actually drive conversions, and to allocate budgets accordingly. Marketing attribution models, ranging from simple single-touch models, first-touch and last-touch, to more sophisticated multi-touch and data-driven models, have emerged as the primary analytical tools for assigning credit for conversions across the customer journey, yet their adoption and effective use, particularly among small and medium enterprises in emerging markets, remains inconsistent. This study examined marketing attribution models and the measurement of digital marketing effectiveness among digital marketing practitioners and SMEs in Enugu metropolis. The study was guided by four objectives: to examine the extent of attribution model usage among digital marketing practitioners in Enugu metropolis; to assess the effect of attribution model usage on the accuracy of digital marketing performance measurement; to evaluate the relationship between attribution model sophistication and marketing budget allocation efficiency; and to identify the challenges militating against the adoption of advanced attribution models among SMEs in the study area. A descriptive survey research design was adopted, and data were collected from 272 digital marketing practitioners and SME owners/managers in Enugu metropolis, determined using the Taro Yamane formula from a target population of registered digitally active SMEs and marketing professionals, and selected through a multi-stage sampling technique. Data were analysed using descriptive statistics, frequencies, percentages, mean scores, and inferential statistics, Pearson Product Moment Correlation, simple linear regression, independent samples t-test, and Chi-square test of independence, with the aid of SPSS version 26. Findings revealed a statistically significant positive relationship between attribution model usage and accuracy of digital marketing performance measurement (r = 0.588, p < 0.05); that attribution model sophistication significantly predicts marketing budget allocation efficiency (β = 0.471, p < 0.05); that businesses using multi-touch attribution models reported significantly higher perceived measurement accuracy than those using single-touch models (t = 6.204, p < 0.05); and a statistically significant association between business size and the sophistication of attribution models adopted (χ² = 29.84, p < 0.05). The study concluded that while marketing attribution models substantially improve the accuracy and defensibility of digital marketing performance measurement, adoption of more sophisticated multi-touch approaches remains constrained among smaller enterprises by limited analytical capacity, tool cost and data-integration challenges. It was recommended that SMEs progressively adopt accessible multi-touch attribution tools, invest in basic marketing analytics capability, and that marketing technology providers develop simplified, affordable attribution solutions suited to the Nigerian SME context. Background to the Study The modern consumer's path to purchase rarely involves a single marketing touchpoint. A typical buyer may first encounter a brand through a social media advertisement, later click a search engine result, receive a retargeting display ad, open a promotional email, and finally convert after clicking a direct link or searching the brand name, a journey spanning multiple channels, devices and sessions over days or weeks. This fragmentation of the customer journey has made a foundational marketing question, which marketing activities actually drove this sale, considerably harder to answer than in the era of traditional, single-channel advertising. Marketing attribution models have emerged as the analytical response to this challenge. Attribution models are rule-based or algorithmic frameworks that assign credit for a conversion across the various touchpoints a customer interacted with prior to purchase. Simple single-touch models, such as first-touch, crediting the first interaction, and last-touch, crediting the final interaction before conversion, remain widely used due to their simplicity, but are increasingly recognised as providing an incomplete, often misleading picture of channel contribution. More sophisticated multi-touch attribution models, linear, time-decay, position-based and algorithmic or data-driven models, distribute credit across multiple touchpoints in proportion to their estimated influence, offering a more nuanced, though more analytically demanding, measurement approach. The choice and sophistication of attribution model used has direct commercial consequences: it shapes how marketing budgets are allocated across channels, which campaigns are judged successful or discontinued, and how return on marketing investment is reported to business stakeholders. Global marketing analytics platforms, Google Analytics 4, Meta Ads Manager, HubSpot and enterprise marketing mix modelling tools, have increasingly built multi-touch and data-driven attribution capabilities directly into their reporting dashboards, reflecting broader industry recognition that attribution methodology materially affects marketing decision-making. Within Nigeria, and particularly among small and medium enterprises and digital marketing practitioners operating in urban commercial centres such as Enugu metropolis, digital marketing spend has grown substantially, driven by increased social media and e-commerce adoption. The Small and Medium Enterprises Development Agency of Nigeria has made capacity building and market access central to its mandate for exactly this reason, recognising that many SMEs need structured support to translate digital spend into measurable business outcomes. However, anecdotal evidence and industry commentary suggest that many Nigerian SMEs continue to rely on simplistic, often intuition-driven approaches to measuring digital marketing effectiveness, with limited systematic use of formal attribution modelling, a gap with direct implications for marketing budget efficiency and accountability. This study examines marketing attribution models and the measurement of digital marketing effectiveness among digital marketing practitioners and SMEs in Enugu metropolis, with a view to understanding current attribution practices and their relationship with measurement accuracy and budget allocation efficiency.
MarketingMarketing Analytics Capability and Competitive Advantage of Businesses in Enugu State
Elijah T
About This Research Topic In today's marketplace, data is abundant but advantage is scarce. Every point-of-sale swipe, website click, social media comment and CRM entry generates signals about customer preferences and market movements. Yet many firms remain data-rich and insight-poor. The differentiator is marketing analytics capability — the disciplined ability to collect, integrate, analyze and activate marketing-relevant data for better decisions. This article examines how marketing analytics capability influences competitive advantage among registered businesses in Enugu State, Nigeria. Anchored on Resource-Based View, Dynamic Capabilities and Marketing Capabilities theories, the study moves beyond tool ownership to investigate how data-driven decision-making and organizational data-driven culture condition performance outcomes. Using survey data from 300 marketing managers and business owners, it provides empirical evidence relevant to SMEs operating in resource-constrained, highly competitive emerging markets. For readers exploring related frameworks, insights on building data-driven marketing systems for Nigerian SMEs offer useful context on translating analytics into measurable business value. Main Abstract The study examined the effect of marketing analytics capability on competitive advantage, with specific focus on data-driven decision-making and organizational data-driven culture, among registered businesses in Enugu State, Nigeria. The research was grounded in Resource-Based View, Dynamic Capabilities Theory and Marketing Capabilities Theory. A descriptive survey design was employed. The population comprised 1,200 registered businesses obtained from the Enugu Chamber of Commerce, Industry, Mines and Agriculture register. Using Taro Yamane formula, a sample of 300 respondents was determined and selected through stratified random sampling across retail/trade, manufacturing, financial/fintech services and professional services sectors. Data were collected via a structured questionnaire and analyzed using descriptive statistics (frequencies, percentages, means, standard deviations) and inferential statistics (Chi-square test, Pearson correlation and multiple regression) with SPSS version 26. Findings revealed that marketing analytics capability exerts a statistically significant positive effect on competitive advantage; that marketing analytics capability significantly enhances data-driven decision-making; that data-driven decision-making significantly improves competitive advantage; and that organizational data-driven culture significantly and positively moderates the relationship between marketing analytics capability and competitive advantage, such that firms with strong data-driven cultures extract substantially greater competitive benefit from equivalent levels of analytics capability. The study concluded that marketing analytics capability satisfies Resource-Based View criteria as a strategic resource, but its conversion into competitive advantage is not automatic. It depends critically on decision processes and cultural support. The study recommended joint investment in analytics infrastructure, analytical talent and a deliberate data-driven culture rather than isolated technology adoption. Keywords: marketing analytics capability, competitive advantage, data-driven decision-making, data-driven culture, resource-based view, Enugu State
MarketingArtificial Intelligence Impact on Marketing Performance of Businesses in Enugu Metropolis
Elijah T
About This Research Project Artificial intelligence is redefining how businesses attract, convert and retain customers. From intelligent chatbots that handle inquiries at scale to predictive models that forecast demand and programmatic systems that optimize advertising spend in real time, AI has moved from experimental to essential in modern marketing. For companies competing in dynamic, resource-constrained environments, the question is no longer whether AI matters, but how deeply it translates into measurable marketing outcomes. This study examines the impact of artificial intelligence on the marketing performance of businesses in Enugu metropolis, Nigeria. Drawing on survey data from 267 marketing managers and business owners, it provides empirical evidence on adoption patterns, performance effects across sales, engagement and market share, and the practical challenges facing local enterprises. Unlike global studies focused on large corporations in advanced economies, this research offers grounded insight into how Nigerian businesses, particularly SMEs, can leverage accessible AI tools to improve competitiveness. Readers exploring similar themes may benefit from related research on digital marketing strategies for small businesses, which contextualizes how emerging technologies complement traditional marketing capabilities in Nigeria. Main Abstract This study investigated the impact of artificial intelligence (AI) on the marketing performance of businesses operating in Enugu metropolis, comprising Enugu East, North and South Local Government Areas. The research was motivated by the growing deployment of AI tools such as chatbots, predictive analytics, programmatic advertising, recommendation systems and generative content tools, alongside limited empirical evidence from emerging-market secondary cities. Guided by six objectives, the study adopted a descriptive survey design. Data were obtained from 267 marketing managers and business owners selected through multi-stage sampling using a structured 26-item five-point Likert-scale questionnaire. Analysis was conducted with SPSS version 26 using frequencies, percentages, mean scores, Pearson Product Moment Correlation, simple linear regression and one-way Analysis of Variance (ANOVA). Results showed a statistically significant positive correlation between AI adoption and sales performance (r = 0.601, p < 0.05). AI adoption significantly predicted customer engagement and retention (β = 0.489, p < 0.05) and market share growth (β = 0.433, p < 0.05). Furthermore, marketing performance differed significantly across low, medium and high AI adoption groups (F = 34.62, p < 0.05), with high adopters recording superior performance. The study concludes that AI adoption enhances marketing performance in sales, engagement and market share dimensions, but benefits depend on depth of integration, data quality and staff competence rather than mere tool acquisition. Recommendations include investing in training and data infrastructure and pursuing phased, cost-effective adoption pathways for SMEs. Keywords: artificial intelligence, marketing performance, AI adoption, sales performance, customer engagement, market share, Enugu metropolis
MarketingThe Effect of Generative AI Content on Consumer Trust and Brand Perception
Elijah T
About This Research Topic Every brand quietly using generative AI to write ad copy or generate product images is running a bet: that consumers either won't notice, or won't care if they do. This study tests that bet directly, and the answer turns out to hinge less on whether AI was used at all, and much more on whether the brand was honest about it. Readers interested in a closely related question may also want to look at our project on the ethical use of artificial intelligence in digital marketing and its effect on consumer trust and purchase behaviour , which examines a closely related dimension of how AI use shapes consumer response. What follows carries the full research structure — background, problem statement, aim and objectives, research questions, significance, scope, and definitions — rebuilt for a wider readership while preserving the original study's focus and findings. Main Abstract The rapid adoption of generative Artificial Intelligence tools capable of producing text, images, and video has enabled brands to scale content production for advertising, product descriptions, and social media engagement at unprecedented speed and volume. However, the increasing presence of AI-generated content in consumer-facing marketing communication raises important questions about how such content shapes consumer trust and brand perception, particularly given growing public awareness of, and concern about, synthetic media and the potential for AI-generated content to mislead. This study examined the effect of generative AI content on consumer trust and brand perception among selected online consumers. Specifically, the study sought to assess the extent of consumer awareness and recognition of generative AI content in brand marketing; determine the effect of generative AI content use on consumer trust; examine the influence of AI-content disclosure on brand perception; and evaluate the moderating role of perceived content authenticity on the relationship between generative AI content use and brand perception. A descriptive survey research design was adopted, and data were obtained from a sample of 384 online consumers determined using the Cochran formula for infinite populations and selected through purposive and convenience sampling. A structured questionnaire anchored on a five-point Likert scale was validated and pilot-tested, yielding Cronbach's Alpha coefficients above 0.70 for all constructs. Data were analysed using descriptive statistics and inferential statistics (Chi-square test and simple/multiple linear regression) using SPSS version 26. Findings revealed that consumer awareness and recognition of generative AI content is moderate, with many consumers reporting difficulty reliably distinguishing AI-generated from human-created content; that generative AI content use has a statistically significant negative effect on consumer trust when undisclosed; that AI-content disclosure has a statistically significant positive influence on brand perception; and that perceived content authenticity significantly moderates the relationship between generative AI content use and brand perception, such that brands perceived as using generative AI authentically and transparently suffer substantially less erosion of brand perception than brands perceived as using it deceptively. The study concluded that generative AI content is a double-edged strategic tool, capable of either strengthening or undermining consumer trust and brand perception depending critically on transparency and perceived authenticity, and it recommended that brands adopt clear AI-content disclosure practices, maintain rigorous human oversight of AI-generated brand content, and avoid using generative AI in ways that could be perceived as deceptive or inauthentic.
MarketingThe Effect of Data-Driven Marketing on Business Performance
Elijah T
About This Research Topic Buying analytics software and actually becoming a data-driven organisation are two very different things — and the gap between them explains why some firms get real business performance gains from their marketing data while others end up with dashboards nobody consults before making decisions. This study puts that gap under the microscope, testing not just whether data-driven marketing improves business performance, but which organisational conditions determine how much of that potential value a firm actually captures. Readers interested in a closely related question may also want to look at our project on marketing analytics capability and competitive advantage of businesses , which examines a similar capability-performance relationship from a slightly different angle. What follows carries the full research structure — background, problem statement, aim and objectives, research questions, significance, scope, and definitions — rebuilt for a wider readership while preserving the original study's focus and findings. Main Abstract The growing availability of customer, transactional, and behavioural data has positioned data-driven marketing — the systematic use of data analytics to inform and optimise marketing decisions — as a central lever through which firms seek to improve business performance. Yet, despite substantial and growing organisational investment in marketing data infrastructure and analytics capability, the extent to which data-driven marketing practice translates into measurable gains in business performance, particularly among firms operating in emerging markets, has remained empirically underexplored. This study examined the effect of data-driven marketing on business performance among selected firms. Specifically, the study sought to assess the extent of data-driven marketing practice adoption among sampled firms; determine the effect of data-driven marketing on business performance; examine the influence of organisational data-driven culture on marketing decision-making; and evaluate the moderating role of analytical capability on the relationship between data-driven marketing and business performance. A descriptive survey research design was adopted, and data were obtained from a sample of 384 marketing and business managers drawn from firms across multiple sectors, determined using the Cochran formula for infinite populations and selected through purposive and convenience sampling. A structured questionnaire anchored on a five-point Likert scale was validated and pilot-tested, yielding Cronbach's Alpha coefficients above 0.70 for all constructs. Data were analysed using descriptive statistics and inferential statistics (Chi-square test and simple/multiple linear regression) using SPSS version 26. Findings revealed that data-driven marketing practice adoption is moderate-to-high among sampled firms; that data-driven marketing has a statistically significant positive effect on business performance; that organisational data-driven culture significantly and positively influences marketing decision-making quality; and that analytical capability significantly moderates the relationship between data-driven marketing and business performance, such that firms with stronger analytical capability derive substantially greater performance benefits from their data-driven marketing investments. The study concluded that data-driven marketing is a significant driver of business performance, but that its commercial payoff is highly contingent on the organisation's underlying analytical capability and data-driven culture, and it recommended that firms invest in building in-house analytical skill, cultivate a top-management-endorsed data-driven culture, and embed data-derived insights directly into frontline marketing decision-making.
MarketingThe Use of Customer Segmentation Analytics in Improving Marketing Performance
Elijah T
About This Research Topic Two banks can own the exact same customer data and get completely different results from it — one keeps running the same blanket campaign to everyone, the other uses that data to send the right offer to the right customer at the right time. This study looks at what actually separates those two outcomes among Deposit Money Banks in Enugu, testing whether behavioural, demographic, and predictive segmentation analytics genuinely move the needle on marketing performance, and whether a bank's data-driven culture changes how much of that potential actually gets captured. Readers interested in a related angle on this question may also want to look at our project on customer data analytics and customer retention in Nigeria , which examines how similar analytics capabilities affect how long banks keep the customers they already have. What follows carries the full research structure — background, problem statement, aim and objectives, research questions, significance, scope, and definitions — rebuilt for a wider readership while preserving the original study's focus and findings. Main Abstract This study examined the use of customer segmentation analytics in improving marketing performance, with specific focus on selected Deposit Money Banks operating in Enugu metropolis, Enugu State, Nigeria. The increasing availability of customer transaction, demographic, and behavioural data has enabled banks to move away from mass, undifferentiated marketing toward analytically driven customer segmentation, in which distinct customer groups are identified and targeted with tailored marketing strategies. Despite the growing adoption of segmentation analytics tools within the Nigerian banking sector, empirical evidence on the extent to which specific forms of segmentation analytics translate into measurable improvements in marketing performance has remained limited. Guided by four specific objectives, the study examined the effect of behavioural segmentation analytics, demographic and geographic segmentation analytics, and predictive (Recency-Frequency-Monetary, RFM) segmentation analytics on marketing performance, and evaluated the moderating role of data-driven marketing culture on that relationship. Using a descriptive survey research design, the population comprised marketing, sales, and customer relationship staff of Deposit Money Banks operating within Enugu metropolis, with a sample size of 171 respondents determined using the Taro Yamane formula; 160 correctly completed questionnaires were used for analysis, a 93.6 percent response rate. Data were collected using a structured 27-item, five-point Likert-scale questionnaire and analysed using descriptive statistics, Pearson correlation, and multiple regression analysis, with hypotheses tested at the 0.05 level of significance using SPSS. Findings revealed that behavioural segmentation analytics, demographic and geographic segmentation analytics, and predictive segmentation analytics each had a positive and statistically significant effect on marketing performance, and that data-driven marketing culture significantly moderated the relationship between customer segmentation analytics and marketing performance. The study concluded that customer segmentation analytics is a decisive driver of marketing performance among Deposit Money Banks in the study area, and that this effect is strengthened within organisations that cultivate a data-driven marketing culture. It was recommended that banks deepen investment in predictive analytics capabilities, integrate segmentation insights more systematically into campaign design, and build a stronger data-driven culture through training and management commitment.
MarketingCustomer Data Analytics and Customer Retention Nigeria
Elijah T
About This Research Topic Nigerian telecom subscribers switch networks the way people change their minds, quickly, cheaply, and often without much warning. With mobile number portability removing the last real friction from leaving, and network offerings looking increasingly alike, keeping a customer has become just as strategic as winning one in the first place. The tools telecom operators have to fight that churn, churn prediction models, customer lifetime value analysis, personalised retention campaigns, have gotten genuinely sophisticated. Whether that sophistication is actually working is a different question. This article draws on a study that surveyed 154 marketing, customer care, and CRM staff across telecom firms operating in Enugu metropolis, examining whether specific analytics techniques translate into measurable retention gains, and whether how well those tools are wired into day-to-day CRM systems changes the outcome. For readers interested in how a study like this is designed and tested statistically, our sample research projects library includes comparable marketing and business analytics studies worth reviewing as models. The findings speak to a genuinely practical question facing telecom marketing and CRM teams across Nigeria: which analytics investment actually moves the needle on retention, and does the tooling matter as much as the technique. The sections below cover the background to the problem, what the study found, and what it means for retention strategy. Main Abstract This study examined the relationship between customer data analytics and customer retention strategies, focusing on telecommunications firms operating in Enugu metropolis, Enugu State, Nigeria. Nigeria's telecom industry runs on intense competition, low switching costs, and persistently high customer churn, conditions that make the effective use of customer data analytics to anticipate and head off attrition a genuine determinant of commercial survival. Despite heavy investment by operators in customer relationship management infrastructure and analytics capability, solid empirical evidence on whether specific analytics techniques actually translate into measurable retention improvements within the Nigerian market has remained thin. Guided by four objectives, the study examined the effect of churn prediction analytics, customer lifetime value analytics, and personalised behavioural retention campaign analytics on customer retention effectiveness, and evaluated whether CRM system integration strengthens or weakens that relationship. A descriptive survey design was used, drawing on marketing, customer care, and retention or CRM staff across telecom firms in Enugu metropolis. A sample size of 165 was calculated using the Taro Yamane formula, and 154 completed questionnaires were usable for analysis, a 93.3 percent response rate. Data were gathered through a structured 27-item, five-point Likert-scale questionnaire and analysed using descriptive statistics, Pearson correlation, and multiple regression, with hypotheses tested at the 0.05 significance level using SPSS. The findings showed that churn prediction analytics, customer lifetime value analytics, and personalised behavioural retention campaign analytics each had a significant positive effect on customer retention effectiveness. CRM system integration also significantly moderated the relationship between customer data analytics and retention effectiveness, meaning the benefit of good analytics depends meaningfully on how well it's actually wired into frontline systems. The study concluded that customer data analytics is a genuinely decisive driver of retention performance among telecom firms in the study area, and that this effect strengthens considerably where analytics insight is technically integrated into frontline CRM systems rather than sitting in a separate reporting layer. It recommends that telecom firms deepen investment in churn prediction capability, embed customer lifetime value segmentation directly into retention budgeting, and prioritise full integration of analytics insight into CRM and customer care workflows.
MarketingAI-Powered Chatbots and Customer Satisfaction in Digital Marketing
Elijah T
About This Research Topic A chatbot that answers instantly but gives you the wrong information is arguably worse than no chatbot at all. Nigerian e-commerce platforms have leaned hard into AI-powered customer service over the past few years, betting on round-the-clock availability and lower costs, but this study asks the harder question: does any of that actually make shoppers more satisfied, or does it depend entirely on whether they trust the AI in the first place? This article works through a survey of 372 online shoppers in Enugu metropolis who had interacted with AI-powered chatbots on e-commerce platforms, testing responsiveness, personalisation, and ease of use separately, and measuring how much consumer trust in AI changes the equation. Readers researching related digital marketing topics can browse the Business Administration project collection on ScholarNestHub for comparable studies in marketing and consumer behaviour. What follows covers the background to AI chatbot adoption in Nigerian e-commerce, the specific problem this study addresses, its objectives, questions, and hypotheses, the key terms used throughout, and closes with frequently asked questions for students and researchers working on AI-driven customer service and digital marketing. Main Abstract This study examined the relationship between AI-powered chatbots and customer satisfaction in digital marketing, with specific focus on online shoppers who have interacted with AI-powered chatbots on e-commerce platforms in Enugu metropolis, Enugu State, Nigeria. The growing adoption of artificial intelligence in customer service has led many e-commerce and digital marketing platforms to deploy chatbots as a primary channel for handling customer enquiries, product recommendations, and order support, promising round-the-clock availability and reduced service costs. However, the extent to which specific dimensions of chatbot service quality actually translate into customer satisfaction, and the role that consumer trust in artificial intelligence plays in this relationship, remains empirically underexplored within the Nigerian e-commerce context. Guided by four specific objectives, the study examined the effect of chatbot responsiveness, chatbot personalisation, and perceived ease of use of chatbot interactions on customer satisfaction, and evaluated the moderating role of perceived trust in AI chatbots on the relationship between AI-powered chatbot service quality and customer satisfaction. The study adopted a descriptive survey research design. The population comprised online shoppers within Enugu metropolis who had interacted with AI-powered chatbots on e-commerce platforms, and a sample size of 391 respondents was determined using the Taro Yamane formula, out of which 372 copies of the questionnaire were correctly completed and used for analysis, representing a 95.1 percent response rate. Data were collected using a structured 27-item questionnaire anchored on a five-point Likert scale and analysed using descriptive statistics, Pearson correlation, and multiple regression analysis, with hypotheses tested at the 0.05 level of significance using SPSS. Findings revealed that chatbot responsiveness, chatbot personalisation, and perceived ease of use each had a significant positive effect on customer satisfaction, and that perceived trust in AI chatbots significantly moderated the relationship between AI-powered chatbot service quality and customer satisfaction. The study concluded that AI-powered chatbots are a meaningful driver of customer satisfaction within Nigerian e-commerce, and that this effect is strengthened where consumers hold higher trust in the chatbot technology itself. It was recommended, among other things, that e-commerce platforms should continue to invest in chatbot responsiveness and personalisation capability, improve the naturalness of chatbot conversation, and adopt transparency measures that build consumer trust in AI-driven customer service.
MarketingAI-Driven Personalization and Customer Purchase Intention
Elijah T
About This Research Topic Every online shopper has felt both sides of AI personalization: the product recommendation that reads your mind in a good way, and the ad that follows you around the internet in a way that feels a little too close. This study set out to measure which side wins, testing whether AI-driven personalization actually increases the likelihood someone buys, and how much privacy discomfort cancels that effect out. This article works through a survey of 390 online shoppers who had experienced AI-personalized features, testing product recommendations, personalized marketing messages, and AI chatbot interactions separately rather than treating personalization as one blanket capability. Readers researching related digital marketing topics can browse the Business Administration project collection on ScholarNestHub for comparable studies in marketing and consumer behaviour. What follows covers the background to AI-driven personalization in e-commerce, the specific problem this study addresses, its objectives, questions, and hypotheses, the key terms used throughout, and closes with frequently asked questions for students and researchers working on AI marketing and consumer privacy. Main Abstract This study examined the effect of artificial intelligence-driven personalization on customer purchase intention, at a time when online retailers and service platforms increasingly deploy AI to tailor product recommendations, marketing messages, and customer interactions to individual users in real time. The study was guided by four specific objectives: to determine the effect of AI-powered product recommendation personalization on customer purchase intention; to examine the influence of AI-powered personalized marketing communication on customer purchase intention; to assess the effect of AI-powered personalized customer interaction on customer purchase intention; and to evaluate the moderating role of perceived privacy concern on the relationship between AI-driven personalization and customer purchase intention. A survey research design was adopted, and a structured questionnaire was administered to 410 online shoppers who had experienced at least one AI-personalized feature on an e-commerce or digital service platform, using a multi-stage sampling technique, of which 390 were retrieved and found usable, representing a response rate of 95.1%. Data were analysed using descriptive statistics, frequencies, percentages, means, standard deviation, and inferential statistics, Pearson correlation, hierarchical multiple regression, and chi-square tests, with the aid of SPSS version 26. Findings revealed that AI-powered product recommendation personalization (β = 0.27, p < 0.05), AI-powered personalized marketing communication (β = 0.31, p < 0.05), and AI-powered personalized customer interaction (β = 0.24, p < 0.05) each had a positive and statistically significant effect on customer purchase intention, jointly accounting for approximately 58.8% of the variance in purchase intention (Adjusted R² = 0.588, F = 185.3, p < 0.05). The study further found that perceived privacy concern significantly moderated the relationship (ΔR² = 0.035, p < 0.05), weakening the positive effect of AI-driven personalization on purchase intention as privacy concern increased, with the dampening effect most pronounced among respondents who reported prior negative experiences with data misuse or overly intrusive targeted advertising. The study concluded that AI-driven personalization is a significant and multidimensional driver of customer purchase intention, but that its persuasive power is bounded by consumers' privacy sensitivities, such that personalization strategies pursued without regard for perceived intrusiveness risk undermining the very purchase intention they are designed to build. It was recommended, among other things, that businesses calibrate the frequency and specificity of AI-personalized messaging to avoid perceived intrusiveness, give customers transparent control over the data underlying personalization, invest in personalized marketing communication as the strongest individual driver of purchase intention identified in this study, and pair personalization strategy with clear privacy assurances to sustain consumer trust.
MarketingThe Effect of Sustainable Marketing on Consumer Purchase Intention
Elijah T
About This Research Topic Walk down any supermarket aisle today and sustainability is everywhere on the packaging, recyclable materials, eco-labels, claims about reduced carbon footprint. What's far less visible is whether any of it actually gets a product into someone's cart over the cheaper, less green alternative sitting right beside it. That gap between environmental values and actual purchase decisions, often called the attitude-behaviour gap, is one of the more stubborn puzzles in marketing research, and it's exactly what this study set out to examine. This article rewrites and expands a research study looking at how sustainable marketing, broken down into green product strategy, green promotion, and green pricing, affects consumer purchase intention among FMCG buyers in Enugu metropolis, and how environmental consciousness changes that relationship. It sits alongside other work in ScholarNestHub's marketing project library , including a related study on green branding and consumer loyalty in the digital economy . The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about sustainable marketing and purchase intention. Main Abstract This study examined the effect of sustainable marketing on consumer purchase intention, with particular focus on consumers of fast-moving consumer goods (FMCG) brands in Enugu metropolis, Enugu State, Nigeria. The growing awareness of environmental degradation and climate change has compelled firms to integrate sustainability into their marketing strategies, yet the extent to which such practices translate into actual consumer purchase intention in emerging markets like Nigeria remains under-investigated. The study was guided by four specific objectives: examining the effect of green product strategy, green promotion (eco-labelling and green advertising), and green pricing on consumer purchase intention, and evaluating the moderating role of environmental consciousness on the relationship between sustainable marketing and consumer purchase intention. The study adopted a descriptive survey research design. The population comprised consumers of FMCG brands within Enugu metropolis, and a sample size of 387 respondents was determined using the Taro Yamane formula, of which 360 copies of the questionnaire were correctly completed and used for analysis, representing a 93 percent response rate. Data were collected using a structured 27-item questionnaire anchored on a five-point Likert scale and analysed using descriptive statistics (frequency, percentage, mean, and standard deviation) and multiple regression analysis, with hypotheses tested at the 0.05 level of significance using SPSS. Findings revealed that green product strategy, green promotion, and green pricing each had a positive and statistically significant effect on consumer purchase intention, and that environmental consciousness significantly moderated the relationship between sustainable marketing and consumer purchase intention. The study concludes that sustainable marketing practices meaningfully shape the purchase decisions of consumers in the study area. It recommends that FMCG firms operating in Nigeria invest more deliberately in credible eco-labelling, transparent green pricing, and sustainability education to strengthen consumer trust and purchase intention.
MarketingAbout This Research Topic Scroll through almost any brand's
Elijah T
About This Research Topic Scroll through almost any brand's social feed today and you'll find some version of the same message: recyclable packaging, carbon offsets, ethical sourcing, a pledge toward a greener future. Sustainability has become part of the standard brand vocabulary. What's less settled is whether any of it actually keeps consumers coming back. Green messaging is easy to produce and, increasingly, easy for consumers to see through when it doesn't hold up. The question that matters for brand managers isn't whether to talk about sustainability, but whether that talk translates into something as durable as loyalty. This article rewrites and expands a research study examining exactly that question, looking at how green branding communicated through digital platforms shapes consumer loyalty, and how perceived authenticity determines whether that effect holds or collapses. It sits alongside other work in ScholarNestHub's marketing project library , including a related study on ESG communication and brand trust . The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about green branding and consumer loyalty. Main Abstract This study examined the relationship between green branding and consumer loyalty in the digital economy, with particular attention to how digital platforms shape consumer perception, trust, and repurchase behaviour toward environmentally responsible brands. The study was guided by four specific objectives: assessing consumer awareness of green branding practices communicated through digital channels; determining the effect of green branding on consumer loyalty; examining the role of digital marketing tools in reinforcing green brand messages; and identifying the challenges brands face in communicating authentic sustainability claims online. A descriptive survey research design was adopted, and data were collected from a sample of 384 consumers drawn from a population of urban digital consumers using a structured questionnaire anchored on a five-point Likert scale. Data were analysed using descriptive statistics (frequencies, percentages, mean, and standard deviation) and inferential statistics (Chi-square and simple linear regression) with the aid of SPSS. Findings revealed that green branding has a statistically significant positive effect on consumer loyalty, that digital platforms substantially enhance consumer awareness of and engagement with green branding initiatives, and that perceived authenticity of sustainability claims moderates the strength of consumer loyalty. The study concludes that green branding, when communicated consistently and transparently through digital channels, is a strategic tool for building long-term consumer loyalty. It recommends that firms integrate verifiable sustainability data into their digital content, engage consumers interactively on social media around green initiatives, and avoid greenwashing practices that could erode consumer trust.
MarketingEthical Use of Artificial Intelligence in Digital Marketing and Its Effect on Consumer Trust and Purchase Behaviour
Elijah T
About This Research Topic An algorithm decides which ad you see, a chatbot decides how it talks to you, a pricing engine decides what you pay, and most of the time, nobody asks whether any of it feels fair. AI has quietly taken over a great deal of the decision-making in digital marketing, and consumers are left to judge its fairness from the outside, based on how the experience feels rather than how the system actually works. That judgment, whether AI-driven marketing feels ethical or exploitative, turns out to carry real weight in whether people trust a brand and whether they buy. This article rewrites and expands a research study examining exactly that relationship among consumers in Enugu metropolis, looking at how perceived ethical use of AI in digital marketing shapes consumer trust, how AI-driven personalisation affects purchase behaviour, and how privacy and transparency concerns complicate the picture. It builds on other work in ScholarNestHub's marketing project library , including a related study on AI transparency and consumer trust in brands . The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about AI ethics and consumer trust. Main Abstract Artificial intelligence has become deeply embedded in digital marketing practice, powering personalised recommendations, programmatic advertising, chatbots, predictive analytics and dynamic pricing. While AI offers marketers considerable efficiency and precision gains, its growing use has simultaneously raised pressing ethical concerns around data privacy, algorithmic transparency, manipulation, consent and consumer autonomy. This study examined the ethical use of artificial intelligence in digital marketing and its effect on consumer trust and purchase behaviour, using consumers in Enugu metropolis as a case study. The study was guided by four objectives: examining the relationship between perceived ethical use of AI in digital marketing and consumer trust; assessing the effect of AI-driven personalisation on consumer purchase behaviour; evaluating the influence of data privacy and transparency concerns on consumer attitudes toward AI-powered marketing; and identifying the ethical challenges associated with the deployment of AI in digital marketing from the consumer's perspective. A descriptive survey research design was adopted, and data were collected from 384 consumers in Enugu metropolis, selected through a multi-stage sampling technique, using a structured 30-item, five-point Likert-scale questionnaire. Data were analysed using descriptive statistics (frequencies, percentages, mean scores) and inferential statistics (Pearson Product Moment Correlation, simple and multiple linear regression, and Chi-square test of independence) with the aid of SPSS version 26. Findings revealed a strong, statistically significant positive relationship between perceived ethical use of AI in digital marketing and consumer trust (r = 0.647, p < 0.05); that AI-driven personalisation significantly predicts purchase behaviour (β = 0.512, p < 0.05), though this effect is moderated by perceived intrusiveness; that data privacy and transparency concerns significantly and negatively predict favourable attitudes toward AI-powered marketing (β = -0.398, p < 0.05); and that a statistically significant association exists between awareness of AI ethical issues and scepticism toward AI-driven marketing content (χ² = 38.76, p < 0.05). The study concludes that while artificial intelligence enhances the efficiency and relevance of digital marketing, its capacity to build rather than erode consumer trust depends fundamentally on transparency, informed consent and the perceived fairness of algorithmic decision-making. It recommends that marketing organisations adopt explainable AI practices, transparent data-use disclosures, opt-in personalisation controls and regular algorithmic bias audits to ensure that AI-driven marketing strategies remain both effective and ethically sound.
MarketingESG Communication and Brand Trust: Why Sustainability Messaging Can Build or Break Consumer Confidence
Elijah T
About This Research Topic Sustainability claims are everywhere now. Carbon-neutral packaging, community investment reports, diversity pledges, ethics charters, brands have never talked more about doing the right thing. Yet the more they talk, the more sceptical consumers seem to get. A claim that once impressed can now trigger an eye-roll, or worse, active distrust, if it feels exaggerated or unearned. That gap between saying and being believed sits at the centre of one of marketing's more delicate challenges: communicating Environmental, Social and Governance practices in a way that actually builds trust rather than inviting suspicion. This article rewrites and expands a research study examining exactly that question, how environmental communication, social responsibility communication, and governance disclosure each affect brand trust, and how perceived greenwashing can undercut all three. It sits alongside other work in ScholarNestHub's marketing project library , which documents how corporate communication practices shape consumer perception and behaviour. The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about ESG communication and brand trust. Main Abstract This study examined the effect of Environmental, Social and Governance (ESG) communication on brand trust, with particular attention to how consumers interpret and respond to corporate sustainability messaging in an increasingly transparency-conscious marketplace. The study was guided by four specific objectives: determining the effect of environmental communication on brand trust; examining the influence of social responsibility communication on brand trust; assessing the effect of governance-related disclosure on brand trust; and evaluating the moderating role of perceived greenwashing on the relationship between ESG communication and brand trust. A survey research design was adopted, and a structured questionnaire was administered to 400 consumers using a multi-stage sampling technique, of which 384 were retrieved and found usable, a response rate of 96%. Data were analysed using descriptive statistics (frequencies, percentages, means) and inferential statistics (Pearson correlation, multiple regression and chi-square tests) with the aid of SPSS version 26. Findings revealed that environmental communication (β = 0.31, p < 0.05), social responsibility communication (β = 0.27, p < 0.05), and governance disclosure (β = 0.24, p < 0.05) each had a positive and statistically significant effect on brand trust, jointly accounting for approximately 58% of the variance in brand trust (Adjusted R² = 0.578, F = 176.4, p < 0.05). Perceived greenwashing significantly moderated this relationship, weakening the positive effect of ESG communication on brand trust when consumers perceived such communication as exaggerated or insincere. The study concludes that ESG communication is a critical, though delicate, driver of brand trust, and that authenticity, consistency, and third-party verification are essential for ESG messaging to translate into genuine consumer trust. It recommends that brands adopt verifiable, specific, and consistent ESG disclosures, integrate ESG communication into broader Integrated Marketing Communication strategies, and avoid vague or symbolic sustainability claims that could be perceived as greenwashing.
MarketingDigital Surveillance and Personalized Advertising: The Double-Edged Effect on Consumer Behaviour
Elijah T
About This Research Topic It's a familiar moment: you mention something in passing, browse it once, and suddenly it's everywhere online. The ad feels almost too well-timed to be coincidence, because it isn't. Behind that single well-placed ad sits a quiet, continuous system of tracking, profiling, and prediction that most consumers never see directly but increasingly sense. That sense of being watched, even loosely, changes how people respond to brands, and not always in the direction marketers hope for. This article rewrites and expands a research study examining exactly that dynamic among online shoppers in Enugu State, Nigeria, looking at how digital surveillance awareness and personalized advertising jointly shape purchase intention, privacy concern, and brand trust. It sits alongside related work in ScholarNestHub's marketing project library , including a companion study on data privacy and personalized digital marketing . The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about surveillance-based advertising and consumer trust. Main Abstract The proliferation of digital technologies has enabled firms to track, profile, and target consumers with unprecedented precision, giving rise to widespread digital surveillance practices embedded within personalized advertising systems. This study examined the effect of digital surveillance and personalized advertising on consumer behaviour, with specific attention to purchase intention, brand trust, and privacy concern among online shoppers. The study was anchored on Consumer Behaviour Theory, the AIDA Model, and Privacy Calculus Theory, and adopted a descriptive survey research design. A structured questionnaire was administered to a sample of 300 online shoppers drawn from Enugu State, Nigeria, selected through convenience and simple random sampling techniques. Data collected were analysed using descriptive statistics (frequencies, percentages, means) and inferential statistics (Chi-square and Pearson Product Moment Correlation) with the aid of SPSS. Findings revealed that personalized advertising, though often perceived by consumers as intrusive, significantly and positively influences purchase intention; that awareness of digital surveillance significantly heightens consumer privacy concern; and that privacy concern significantly moderates the relationship between personalized advertising and brand trust. The study concludes that while data-driven personalization enhances marketing relevance and short-term purchase response, unchecked surveillance-based targeting erodes consumer trust over time. It recommends that firms adopt transparent data practices, obtain explicit consumer consent, and balance personalization with privacy protection in order to sustain long-term consumer relationships. The study contributes to marketing literature by providing empirical evidence on the dual-edged effect of surveillance-based personalization within an emerging market context.
MarketingThe Effect of Data Privacy on Personalized Digital Marketing
Elijah T
About This Research Topic Personalized ads have a strange way of feeling both helpful and unsettling at once. The product you were just thinking about shows up in your feed within hours, and it's convenient, right up until you start wondering exactly how the platform knew. That flicker of unease sits at the heart of what researchers call the personalization-privacy paradox: consumers want marketing that feels relevant to them, yet they remain wary of the data collection that makes such relevance possible. This article rewrites and expands a research study examining that paradox among internet and social media users in Enugu metropolis, Enugu State, looking specifically at how data privacy concern, perceived data control, and data transparency shape consumer engagement with personalized digital marketing, and how privacy literacy changes the picture. It complements other work in ScholarNestHub's marketing project library , including a related study on data privacy concerns and willingness to share personal information . The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about data privacy and personalized marketing. Main Abstract This study investigated the effect of data privacy on personalized digital marketing, with specific focus on internet and social media users in Enugu metropolis, Enugu State, Nigeria. The proliferation of digital platforms and the growing sophistication of data-driven marketing techniques have enabled firms to deliver highly personalized advertising and content based on consumers' online behaviour, browsing history, and personal data. However, this practice has simultaneously heightened consumer anxiety about how personal data is collected, stored, and used, giving rise to what scholars describe as the personalization-privacy paradox, in which consumers desire the convenience of personalized marketing while remaining deeply concerned about the privacy implications of the data collection that makes such personalization possible. Guided by four specific objectives, the study examined the effect of data privacy concern, perceived data control, and data transparency on consumer engagement intention toward personalized digital marketing, and evaluated the moderating role of privacy literacy on the relationship between data privacy concern and consumer engagement intention. The study adopted a descriptive survey research design. The population comprised active internet and social media users within Enugu metropolis, and a sample size of 392 respondents was determined using the Taro Yamane formula, of which 365 copies of the questionnaire were correctly completed and used for analysis, representing a 93.1 percent response rate. Data were collected using a structured 27-item questionnaire anchored on a five-point Likert scale and analysed using descriptive statistics, Pearson correlation, and multiple regression analysis, with hypotheses tested at the 0.05 level of significance using SPSS. Findings revealed that data privacy concern had a significant negative effect on consumer engagement intention toward personalized digital marketing, while perceived data control and data transparency each had a significant positive effect on consumer engagement intention. Privacy literacy was also found to significantly moderate the relationship between data privacy concern and consumer engagement intention, such that the negative effect of privacy concern was attenuated among respondents with higher privacy literacy. The study concludes that data privacy is a decisive factor shaping consumer response to personalized digital marketing in the study area, and that firms which prioritise transparent data practices and meaningful user control are better positioned to sustain consumer engagement. It was recommended, among other things, that digital marketers operating in Nigeria embed privacy-by-design principles into personalization strategies, comply proactively with the Nigeria Data Protection Act 2023, and invest in consumer data-literacy initiatives to build lasting trust.
MarketingMarketing Analytics Capability and Competitive Advantage of Businesses
Admin
About This Research Topic Every business collects data today — sales figures, website clicks, customer feedback, social media engagement — yet very few translate that flood of information into a real competitive edge. This gap between having data and using it well sits at the heart of a growing conversation in strategic marketing: what exactly is marketing analytics capability, and does it actually make a business more competitive? This article presents a research-based examination of that question, drawing on an original study conducted among registered businesses in Enugu State, Nigeria. Rather than treating marketing analytics capability as just another buzzword bolted onto a strategy deck, the study digs into the organisational machinery — tools, skills, and decision routines — that separates firms who profit from their data from firms who merely store it. Along the way, it tests whether data-driven decision-making genuinely improves competitive outcomes, and whether an organisation's underlying data culture changes how much benefit a firm gets from its analytics investment. Students, business owners, and marketing researchers working on related themes may also find it useful to browse Scholarnesthub wider collection of business administration project topics , which covers adjacent questions in strategic marketing, digital transformation, and SME performance. The sections below walk through the study's background, problem statement, objectives, research questions, significance, scope, and key definitions — reorganised and expanded for clarity and readability, while preserving the original research intent, findings, and conclusions exactly as reported. Main Abstract How much of a business's competitive edge actually comes from its ability to analyse marketing data — and how much depends on what the organisation does with that analysis? This study set out to answer that question by examining the effect of marketing analytics capability on the competitive advantage of businesses, paying particular attention to the roles played by data-driven decision-making and organisational data-driven culture. The research focused on registered businesses in Enugu State, Nigeria, and was grounded in three complementary theoretical lenses: the Resource-Based View, Dynamic Capabilities Theory, and Marketing Capabilities Theory. A descriptive survey design guided the study. Working from a population of 1,200 registered businesses drawn from the Enugu Chamber of Commerce, Industry, Mines and Agriculture (ECCIMA) register, the researcher applied the Taro Yamane formula to arrive at a sample of 300 marketing managers and business owners, selected through stratified random sampling across industry sectors. Structured questionnaires supplied the primary data, which were analysed using descriptive statistics (frequencies, percentages, means, and standard deviations) alongside inferential techniques — Chi-square tests, Pearson correlation, and multiple regression — computed in SPSS version 26. The results were consistent and, in places, striking. Marketing analytics capability showed a statistically significant, positive effect on competitive advantage. It also significantly and positively predicted data-driven decision-making, which in turn had its own significant, positive effect on competitive advantage. Most notably, organisational data-driven culture significantly and positively moderated the relationship between marketing analytics capability and competitive advantage — meaning firms with a strong data-driven culture extracted substantially more competitive benefit from a given level of analytics capability than firms lacking that culture. Taken together, the findings support marketing analytics capability as a genuine strategic resource in the Resource-Based View sense, but one whose payoff is far from automatic. Its translation into competitive advantage depends heavily on how decisions get made and on the cultural norms surrounding data inside the organisation. The study's central recommendation follows directly: businesses should invest jointly in analytics infrastructure, analytical talent, and a genuinely supportive data-driven culture, rather than assuming that technology adoption alone will deliver a competitive payoff. Keywords: marketing analytics capability, competitive advantage, data-driven decision-making, data-driven culture, Resource-Based View.
MarketingData Privacy Concerns and Consumer Willingness to Share Personal Information
Admin
About This Research Topic Every online signup asks for something: a phone number, a location, a payment card, sometimes a fingerprint or a face. Consumers hand this information over constantly, often without much thought, yet beneath that routine sits a quiet, ongoing calculation. Is what I'm getting worth what I'm giving up? Does this company deserve my data? What happens if it leaks? These questions shape one of the most consequential behaviours in the digital economy: a consumer's willingness, or reluctance, to share personal information. This article rewrites and expands a research study examining exactly that calculation among online shoppers in Enugu State, Nigeria, focusing on how privacy concern, perceived benefit, trust, and prior data breach experience combine to shape disclosure behaviour. It builds on themes explored elsewhere in ScholarNest's marketing project library , including a related study on digital marketing and consumer behaviour in Enugu Metropolis . The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about data privacy and consumer disclosure behaviour. Main Abstract The growth of e-commerce and data-driven marketing has made the exchange of personal information a routine precondition for consumers seeking to access digital products, services, and personalised offers. This exchange, however, is increasingly shadowed by rising consumer awareness of data privacy risks. This study examined data privacy concerns and consumer willingness to share personal information, focusing on the roles of perceived benefit, trust, and prior data breach experience among online shoppers in Enugu State, Nigeria. The study was anchored on Privacy Calculus Theory, Communication Privacy Management Theory, and the Theory of Planned Behaviour, and adopted a descriptive survey research design. A structured questionnaire was administered to a sample of 320 online shoppers selected through convenience and simple random sampling techniques, of which 300 valid responses were retained for analysis. Data were analysed using descriptive statistics (frequencies, percentages, means, standard deviations) and inferential statistics (Chi-square test, Pearson correlation, and multiple regression) with the aid of SPSS version 26. Findings revealed that privacy concern has a significant negative effect on consumer willingness to share personal information; that perceived benefit has a significant positive effect on willingness to share; that trust significantly strengthens the relationship between privacy concern and willingness to share; and that consumers with prior data breach experience report significantly lower willingness to share information than those without such experience. The study concludes that consumer disclosure behaviour is governed by an active cost-benefit calculus in which trust and perceived benefit can offset, but not eliminate, the depressing effect of privacy concern on information disclosure. It recommends that firms invest in verifiable trust signals, offer proportionate and transparent value in exchange for data, adopt robust data breach prevention and response protocols, and comply strictly with Nigeria's data protection framework in order to sustain consumer willingness to share the information necessary for effective, data-driven marketing.
MarketingAI Transparency and Consumer Trust in Brands: Why Disclosure Alone Isn't Enough
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About This Research Topic A chatbot answers a customer's question in seconds. A recommendation engine curates an entire product feed. An algorithm quietly decides who qualifies for a loan. None of this is new anymore, but what remains strikingly inconsistent is whether brands tell consumers any of it is happening. As artificial intelligence moves from a backend efficiency tool to the primary interface between brands and the people they serve, a widening gap has opened between what these systems actually do and what consumers understand about them. Closing that gap, or failing to, has direct consequences for something brands cannot manufacture on demand: trust. This article rewrites and expands a research study examining exactly that relationship, how AI transparency communication, broken down into explainability, data usage transparency, and algorithmic disclosure, affects consumer trust in brands, and how a consumer's own perceived risk around AI changes the equation. It sits alongside other studies in ScholarNest's marketing project library , which documents how digital and algorithmic tools are reshaping consumer-brand relationships. The sections below walk through the study's background, problem, objectives, and scope, before closing with answers to the questions most commonly asked about AI transparency and brand trust. Main Abstract This study examined the effect of Artificial Intelligence (AI) transparency communication on consumer trust in brands, at a time when organisations are rapidly deploying AI-powered systems, ranging from recommendation engines and chatbots to algorithmic credit scoring and personalised advertising, often with limited disclosure to the consumers whose data and decisions these systems affect. The study pursued four objectives: determining the effect of AI explainability communication on consumer trust; examining the influence of data usage transparency on consumer trust; assessing the effect of algorithmic disclosure on consumer trust; and evaluating the moderating role of perceived AI risk on the relationship between AI transparency communication and consumer trust. A survey research design was adopted, with a structured questionnaire administered to 430 consumers of AI-enabled digital brands across e-commerce, fintech, and social media/streaming platforms, using a multi-stage sampling technique. Of these, 412 responses were retrieved and found usable, a response rate of 95.8%. Data were analysed using descriptive statistics (frequencies, percentages, means, standard deviation) and inferential statistics (Pearson correlation, hierarchical multiple regression, and chi-square tests) via SPSS version 26. Findings showed that AI explainability communication (β = 0.29, p < 0.05), data usage transparency (β = 0.33, p < 0.05), and algorithmic disclosure (β = 0.22, p < 0.05) each had a positive and statistically significant effect on consumer trust in brands, jointly accounting for approximately 61% of the variance in trust (Adjusted R² = 0.609, F = 213.7, p < 0.05). Perceived AI risk significantly moderated this relationship (ΔR² = 0.041, p < 0.05), weakening the positive effect of transparency communication on trust as perceived risk increased, an effect particularly pronounced among respondents with low prior familiarity with AI systems. The study concludes that AI transparency communication is a significant and increasingly indispensable driver of consumer trust, but that its effectiveness depends on pairing disclosure with risk mitigation, comprehensibility, and demonstrable safeguards rather than technical disclosure alone.
MarketingConsumer Trust in AI-Powered Marketing and Purchase Intention: What Online Shoppers Really Think
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About This Research Topic Marketing has always depended on a relationship between brand and audience, but artificial intelligence has quietly rewired the mechanics behind that relationship. Product recommendations now arrive already knowing a shopper's size and style, chatbots resolve complaints before a human agent gets involved, and prices shift in response to demand signals invisible to the person browsing on the other end of the screen. For businesses, this shift promises efficiency and relevance at a scale traditional marketing could never match. For consumers, it raises a quieter but more consequential question: do they actually trust the system making these decisions on their behalf? That question sits at the centre of a growing stream of research on how digital and AI-driven tools shape consumer behaviour, a theme also explored in ScholarNest's marketing project library , which houses several undergraduate studies on how emerging digital tools influence purchasing decisions. This article rewrites and expands a research study examining precisely this relationship: how consumer trust in AI-powered marketing affects purchase intention among online shoppers, and what role data privacy, algorithmic transparency, and personalisation quality play in building, or eroding, that trust. The discussion below walks through the study's background, problem, objectives, and scope, then closes with answers to the questions students and researchers most often ask about this topic. Main Abstract Artificial intelligence has become deeply woven into modern marketing, powering recommendation engines, conversational chatbots, dynamic pricing, and highly personalised advertising across digital platforms. Yet the same qualities that make AI-powered marketing effective, its dependence on large volumes of personal data, its often opaque decision logic, and its capacity to act autonomously, also introduce new sources of consumer unease. This study investigated the relationship between consumer trust in AI-powered marketing and purchase intention among online consumers, with specific attention to the roles of data privacy, algorithmic transparency, and personalisation quality. A descriptive survey design was used, drawing on a sample of 384 online consumers determined through the Cochran formula for infinite populations and recruited via purposive and convenience sampling. A structured five-point Likert questionnaire was validated and pilot-tested, producing Cronbach's Alpha coefficients above 0.70 across all constructs. Data were analysed using descriptive statistics (frequency, percentage, mean, standard deviation) and inferential statistics (Chi-square and simple/multiple linear regression) via SPSS version 26. The findings showed that consumer trust in AI-powered marketing tools was moderate to high among respondents; that this trust had a statistically significant positive effect on purchase intention; that perceived data privacy protection and algorithmic transparency were significant predictors of trust; and that perceived personalisation quality significantly strengthened the trust–purchase intention relationship. The study concludes that trust functions as a critical precursor to the commercial success of AI-powered marketing, and recommends that firms prioritise transparent data practices, explainable recommendations, and human-in-the-loop customer support to sustain consumer confidence and drive purchase behaviour.
MarketingSustainable Consumption and the Role of Digital Marketing in Shaping Consumer Behaviour: A Study of Consumers in Enugu Metropolis
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This study examined sustainable consumption and the role of digital marketing in shaping consumer behaviour, using consumers in Enugu metropolis as a case study. The rising global concern for environmental sustainability has pushed brands to increasingly deploy digital marketing tools — social media campaigns, influencer partnerships, content marketing and e-commerce platforms — to promote eco-friendly products and cultivate sustainable consumption habits among consumers. However, it remains unclear how effectively these digital marketing efforts translate into actual sustainable purchase behaviour among Nigerian consumers, particularly within emerging urban markets such as Enugu. The study was guided by three objectives: to examine the relationship between exposure to digital marketing content and sustainable consumption behaviour; to assess the influence of social media influencer marketing on consumers' intention to purchase eco-friendly products; and to evaluate the role of digital marketing in creating awareness of sustainable consumption practices. A descriptive survey research design was adopted, and data were collected from 384 consumers in Enugu metropolis using a structured 5-point Likert-scale questionnaire, selected through a multi-stage sampling technique. Data were analysed using descriptive statistics (frequencies, percentages, mean scores) and inferential statistics (Pearson Product Moment Correlation, Chi-square test and simple linear regression) with the aid of SPSS version 26. Findings revealed a significant positive relationship between exposure to digital marketing content and sustainable consumption behaviour (r = 0.612, p < 0.05); that social media influencer marketing significantly and positively predicts consumers' intention to purchase eco-friendly products (β = 0.548, p < 0.05); and that digital marketing platforms play a statistically significant role in raising consumer awareness of sustainable consumption practices (χ² = 42.31, p < 0.05). The study concluded that digital marketing is a potent tool for shaping sustainable consumption behaviour among Nigerian consumers, though its effectiveness is moderated by trust, message credibility and accessibility of sustainable product alternatives. It was recommended that marketers intensify authentic, value-driven digital content, collaborate with credible micro-influencers, and pair digital campaigns with tangible product accessibility to convert environmental awareness into sustained purchase behaviour. Keywords: Sustainable consumption, digital marketing, consumer behaviour, green marketing, social media influencer marketing, eco-friendly products, Enugu metropolis.
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