Transforming First Impressions in Digital Marketing: Leveraging Artificial Intelligence to Transform Early-Stage Consumer Engagement

Silvia Iommi

No pswec_v1, Thesis Commons from Center for Open Science

Abstract: This dissertation presents a retrospective, current, and prospective analysis of the Artificial Intelligence impact on marketing, with an emphasis on early-stage consumer engagement. In an era marked by media saturation and diminishing consumer attention spans, brands face increasing pressure to establish meaningful engagement from the very first interaction. Artificial Intelligence has emerged as a transformative force in marketing, revolutionising data collection, segmentation, targeting, personalisation, and content creation. Despite exponential growth in AI research and adoption, academic literature has yet to fully address the strategic, operational, and ethical implications of AI in upper funnel marketing, especially regarding brand awareness, brand equity, and the privacy-personalisation paradox. The study specifically focuses on three core areas: (1) the effectiveness of AI in optimising brand awareness and consideration, (2) the development of methodologies for monitoring AI’s impact on brand equity, and (3) the ethical balance between AI-driven personalisation and consumer privacy. The research aims to bridge the gap between academic theory and industry practice, offering actionable insights for both researchers and marketing professionals. Employing a thematic analysis of secondary data, this study synthesises findings from 37 academic and 11 industry publications, filtered through systematic review protocols. Data sources include Google Scholar, Perplexity, Forbes, and McKinsey, ensuring a robust multi-perspective approach. Key findings reveal that AI adoption in upper-funnel marketing significantly enhances brand awareness and consideration, outperforming traditional methods when paired with human oversight. AI-driven personalisation increases conversion rates. However, the privacy-personalisation paradox remains a critical challenge. The study recommends phased AI implementation, putting a human-centric strategy first, and the technology second. This study also recommends including new KPIs, such as Answer Share Rate and impressions from LLMs, to measure the impact of Artificial Intelligence on brand equity. Limitations include reliance on short-term data collected through platforms owned by companies with a commercial interest in AI, as well as the underrepresentation of non-Western perspectives. Future research should address longitudinal impacts, cross-cultural consumers’ sensitivities, the evolving role of agentic AI in marketing, and the future of marketing organizations. ________________________________________ Key Words: Artificial Intelligence, Upper Funnel Marketing, Brand Equity, Personalisation, Privacy

Date: 2026-02-20
New Economics Papers: this item is included in nep-mkt
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/6999da0d4fae794bc8c50a7f/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:thesis:pswec_v1

DOI: 10.31219/osf.io/pswec_v1

Access Statistics for this paper

More papers in Thesis Commons from Center for Open Science
Bibliographic data for series maintained by OSF ().