Year: 2025
Type: article
Study design: Observational Study
Abstract: This study aims to investigate the impact of artificial intelligence (AI) on consumer responses in the realm of crosschannel marketing. As companies adopt AI technologies to provide tailored experiences on digital platforms such as email, websites, and social media, it is crucial to understand consumer perceptions and behavioural responses. This study employs a quantitative approach, using a structured questionnaire to assess seven independent variables: personalisation, transparency, cross-channel consistency, trust in AI, ease of use, AI-generated suggestions, and privacy concerns, alongside one dependent variable, consumer response. Each item was assessed utilising a five-point Likert scale. The data collection involved an online survey disseminated through social media channels, which facilitated a broad representation of demographics without geographic limitations. A total of 184 valid responses were collected from mid-January to the end of February 2025. The data analysis took place in March, utilising JMP statistical software and applying multiple linear regression to assess the impact of AI-related constructs on consumer responses. The results indicated that comprehending the functionality of AI, the simplicity of engaging with AI-driven platforms, and the perception of personalisation play crucial roles in influencing consumers' readiness to respond to AI-generated suggestions. Nevertheless, conventional marketing elements, such as message consistency and the acceptance of AI tools, demonstrated limited predictive capability. Interestingly, personalisation showed a negative correlation, indicating a potential consumer backlash against overly aggressive targeting. The findings underscore the increasing demand for transparency, usability, and the ethical application of AI in marketing. This investigation offers actionable insights for marketers and contributes to the growing conversation about consumer-AI engagement in online settings.
Authors: Dr. Narsis I, Sumathi K
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412655811