Impact of Influencer Authenticity on Brand Trust and Purchase Intent in Gen Z Consumers Or The Role of Personalization in Omni-Channel Marketing on Customer Loyalty in E-commerce Firms Or Sustainable Branding and Consumer Preference: A Study on Green Marketing Communications in the FMCG Sector Or Effectiveness of Social Media Metrics and Analytics on Campaign ROI for Small Businesses Or AI-Driven Customer Journey Mapping for Enhanced Conversion Rates in Retail Marketing Or Brand Community Engagement and Advocacy: A Case Study of User-Generated Content Campaigns Or Neuromarketing Techniques in Digital Advertising: A Feasibility Study for Marketers Or Impact of Cause-Related Marketing on Brand Equity in Emerging Markets Or Value Proposition Clarity and Its Impact on Startup Brand Differentiation in Competitive Markets

Project Abstract

This study investigates how influencer authenticity shapes brand trust and purchase intent among Gen Z consumers, with a focus on the mechanisms through which perceived genuineness, transparency, and alignment with audience values influence cognitive processing, affective response, and behavioral outcomes in digital ecosystems. Grounded in signaling theory and social identity theory, the research examines how authenticity signals from influencers—such as disclosures, consistency between stated values and brand actions, and relatable storytelling—affect perceived credibility, parasocial relationships, and trust in brand messages, ultimately moderating the path from exposure to purchase decisions. A mixed-methods design combines a large-scale survey (n ? 600 Gen Z respondents) to quantify relationships among influencer authenticity, brand trust, perceived value congruence, and purchase intention, with structural equation modeling to test direct, indirect, and moderating effects. In-depth interviews (n ? 20) with Gen Z consumers and content creators provide nuanced insights into what constitutes authenticity in different verticals (fashion, beauty, tech) and across social platforms (TikTok, Instagram, YouTube). The study introduces a multidimensional authenticity scale capturing perceived honesty, transparency, consistency, and alignment with social and ethical values, and it investigates boundary conditions such as platform algorithmic bias, audience size, and cultural context. Data triangulation enables the examination of cross-platform effects and potential halo effects when an influencer is associated with several brands. The research also analyzes influencer-brand co-creation practices, including long-term partnerships, product collaborations, and user-generated content campaigns, to determine how these affect trust transfer and perceived risk. Additionally, the study assesses the impact on brand equity dimensions—awareness, perceived quality, brand associations, and loyalty—and links these to short-term purchase intentions and long-term advocacy. Practical implications are drawn for marketing strategists guidelines for selecting authentic influencers, designing disclosure and storytelling strategies, and crafting omnichannel communication that reinforces trust without overwhelming consumers. The study contributes to theory by integrating legitimacy and authenticity constructs into influencer marketing models, clarifying the role of authenticity as a key mediator of trust transfer, and identifying contextual factors that amplify or dampen its effects. It also explores ethical considerations, including transparency requirements and the potential for perceived manipulation, proposing a framework for balancing authentic representation with strategic branding goals. The anticipated outcomes include a validated measurement instrument for influencer authenticity, empirical evidence of its impact on Gen Z purchase behavior, and actionable recommendations for brands to foster credible influencer partnerships that enhance trust and conversion while maintaining consumer welfare.

Project Overview

What This Project Is About

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The Problem It Addresses

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Objectives of the Project

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What You Will Do Step by Step

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Expected Outcome

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