INTEGRATION OF NEUROMARKETING AND DATA-DRIVEN APPROACH IN THE MANAGEMENT OF MARKETING CAMPAIGNS IN SOCIAL NETWORKS

Abstract

The rapid development of digital communications and the intensifying competition in the social media market necessitate the continuous improvement of marketing management. Traditional analytical methods based solely on quantitative indicators do not allow for a full understanding of the deep-seated motives behind consumer choice. While the Data-Driven approach enables the processing of behavioural data and neuromarketing provides access to the study of emotional responses, these two approaches continue to develop in parallel without proper integration. The absence of established models for combining neurophysiological data with marketing metrics creates a gap between the potential of modern technologies and the actual practice of managerial decision-making. The aim of the article is to develop the theoretical and methodological foundations and practical recommendations for the integration of neuromarketing and the Data-Driven approach in the management of marketing campaigns in social networks in order to enhance their effectiveness and the accuracy of consumer behaviour forecasting. To achieve this aim, theoretical approaches were generalised, neuromarketing tools were systematised, a conceptual integration model was developed, a methodological approach to performance evaluation was proposed, and practical recommendations were formulated. The study was based on data from 12 advertising campaigns conducted for four enterprises during the first half of 2025. The total sample size comprised 48,600 unique users of Facebook and Instagram. The research employed theoretical methods (analysis, synthesis, systematisation), empirical methods (eyetracking, facial coding, behavioural data analysis), and mathematical and statistical methods (correlation analysis, regression modelling, Student’s t-test). The comparative analysis demonstrated the advantages of the integrated approach: CTR increased by 34.2%, conversion rate by 27.6%, and ROI by 41.3% (p < 0.01). Neuromarketing screening revealed a significant gap between declared preferences and actual responses: a creative asset rated 4.7 out of 5 exhibited low emotional valence (0.23), whereas an asset rated 3.2 out of 5 demonstrated high emotional valence (0.78). The integrated forecasting model reduces the prediction error for virality by 49.6% and for conversion by 47.4%. A differentiated impact of stimuli across age groups was identified: for the 18–29 age group, dynamic creatives with gamification elements proved most effective (engagement index 0.82); for the 30–45 group, status-related stimuli (0.76); and for the 45+ group, structured content with moderate colour schemes (0.71). The implementation of neuromarketing screening reduces Customer Acquisition Cost (CAC) by 23.7%, while budget redistribution based on integrated forecasting lowers CPC by 16.2% and CPM by 12.8%. The net economic effect per medium-scale campaign (budget: UAH 500,000) amounts to UAH 150,000. Future research envisages the implementation of artificial intelligence for the automated processing of neurodata, the expansion of the instrumental toolkit (EEG, galvanic skin response), the adaptation of the proposed model for e-commerce applications, and the investigation of ethical aspects. The developed models can serve as a foundation for software solutions aimed at automating marketing campaign management.