Decoding the Digital Mind: How AI-Driven Consumer Insights Transform Marketing Effectiveness in India

Abstract

The rapid integration of artificial intelligence (AI) into digital ecosystems has significantly reshaped how firms understand and engage consumers. This study investigates the impact of AI-driven consumer insights on digital marketing effectiveness in the Indian context, with a particular focus on the mediating roles of consumer engagement and personalization. Using a quantitative research design, primary data were collected from 420 digital consumers across major urban centers in India. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed conceptual framework. The findings reveal that AI-driven consumer insights have a strong and significant influence on both consumer engagement and personalization. In turn, these factors positively affect digital marketing effectiveness, highlighting their mediating roles. Additionally, AI-driven insights demonstrate a direct positive impact on marketing effectiveness, emphasizing their strategic importance. The model exhibits strong explanatory and predictive power, confirming its robustness in capturing the dynamics of AI-enabled marketing. This study contributes to the literature by providing empirical evidence from an emerging market and by integrating multiple constructs into a comprehensive analytical framework. The findings offer valuable insights for marketers and policymakers, emphasizing the need for strategic investment in AI technologies and the development of ethical data governance frameworks to ensure sustainable digital marketing practices.

Received: 2026-03-26 | Revised: 2026-05-12 | Accepted: 2026-05-17 | Published: 2026-05-18

Declarations

Ethics and Guidelines: The study was conducted in accordance with the Declaration of Helsinki, and ethically approved by the Institutional Review Board of Metropolia University of Applied Sciences (Approval Number: 2387-2025-387) on [Date: 20-02-2025]. The ethical approval specifically covers the research procedures and data collection activities conducted for this study.

Consent to participate: Written informed consent was obtained from all participants prior to data collection. Consent was obtained using a standardized written form, signed by each participant before participation in the survey.

Consent to publish: The authors have provided consent to publish.

Competing interests: The authors declare no competing interests.

Data availability statement: Data will be made available on reasonable request from the corresponding author.

Funding: This research received no external funding.

Clinical Trial Number: Not Applicable.

Declaration of using generative AI: During the preparation of this work the author(s) used ChatGPT in order to correct the grammatical errors. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the published article.

Author Contributions: Conceptualization, M.F.U., S.K.S., and M.C.; methodology, M.F.U., S.K.S., and M.C.; writing—original draft preparation, M.F.U., S.K.S., and M.C.; writing—review and editing, M.F.U., S.K.S., and M.C. All authors have read and agreed to the published version of the manuscript.