Application of Artificial Intelligence in Neuromarketing to Predict Consumer Behaviour Towards Brand Stimuli: Case Study - Neurotechnologies vs. AI Predictive Model

Application of Artificial Intelligence in Neuromarketing to Predict Consumer Behaviour Towards Brand Stimuli: Case Study - Neurotechnologies vs. AI Predictive Model

David Juárez-Varón, Ana Mengual-Recuerda, Juan Camilo Serna Zuluaga, Vincenzo Corvello
DOI: 10.4018/IJSSCI.347214
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Abstract

This research aims to analyse the current level of accuracy in predicting consumer behaviour in response to brand stimuli using artificial intelligence, comparing the results with an analysis conducted using neuromarketing biometrics. The study aims to determine the accuracy achieved in predicting consumer levels of attention and visual attraction towards visual stimuli, compared to the results recorded in a neuromarketing investigation with real users, through eye tracking. The implications of these comparative analyses are discussed in the final part of the article, concluding that the emotional intelligence tool provides very accurate predictions of consumer behaviour in response to visual stimuli. The results of this study revealed that the prediction of the percentage of users who would view each area of interest is very good, and regarding visual attraction (time until the first viewing of each area of interest), it is quite similar to the order observed by the consumer group; consequently, the level of approximation to reality of AI is very good.
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Literature Review

The study of consumer behaviour is focused on the actions and decisions individuals or groups take when selecting, purchasing, and using products, services, ideas, or experiences to satisfy their needs and desires (Bhavadharini et al., 2023). Understanding consumer behaviour is crucial for businesses, as it allows them to tailor their marketing strategies and meet market demands more effectively (Antonovica et al., 2023). Consumer behaviour is influenced by key elements such as cultural factors (values, beliefs, norms, customs, social class, and belonging to a specific cultural group, which greatly influence purchasing decisions; Coimbra et al., 2023; M. Pham et al., 2023), social factors (social relationships, reference groups, family, and other aspects of the social environment, such as the influence of friends and family; Qaiser et al., 2023), personal factors (age, gender, income, occupation, personality, and lifestyle; Boshoff, 2012), and psychological factors (perception, motivation, attitude, and decision making; Werth & Foerster, 2007; Yilmaz, 2023).

The consumer decision making process typically involves several stages, including problem identification, information search, alternative evaluation, decision making, and post-purchase evaluation. In the digital age, online presence, social media, and online reviews play a significant role in purchasing decisions, as consumers seek information online before making purchases and rely on feedback from other users (Hakami & Mahmoud, 2022). The quality of the customer experience, ranging from website navigation to interaction with customer service, may have a significant impact on consumers’ loyalty and their willingness to recommend a brand (Sáez-Ortuño et al., 2023). Furthermore, consumers are increasingly making purchasing decisions based on ethical and sustainability considerations (Ogiemwonyi & Jan, 2023; Pradeep & Pradeep, 2023), forcing companies to adopt responsible business practices to gain preference among consumers conscious of these issues (Romero Valenzuela & Camarena Gómez, 2023).

Understanding these aspects of consumer behaviour allows companies to anticipate the needs and expectations of their customers, adjust their marketing strategies, and offer products and services that resonate with their target audience. Market research, data analysis, and the application of AI are valuable tools for gaining deeper insights into consumer behaviour.

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