A method for analyzing consumer behavior and evaluating marketing effectiveness of online websites based on multimodal data synchronization

Abstract: A good interface design is crucial for improving user experience, user stickiness and marketing effectiveness in the marketing process of shopping websites. This study is based on subjective and objective multi-modal data synchronization technology, bio-electrical signal technology, eye tracking technology, etc. The aim of the study is to explore the impact of website interface design on website marketing effectiveness. Through researching the emotional experience and behavioral response characteristics of 35 participants who completed browsing and purchasing tasks on three shopping websites (A website, B website and C website), we predicted the effectiveness of website marketing. It was found that during the browsing task, participants displayed significantly higher value of EEG frequency domain indicator α when using A website than those when using B and C websites, and the subjective evaluation score of further attractiveness was significantly higher for website A than those for the other two websites. 62.86% of participants chose website A when executing purchase tasks. In order to predict the marketing effectiveness of the website, 18 sets of modal features were extracted, including photoelectric capacitance pulse wave signal, eye movement state signal, skin electric response signal and EEG signal. The outliers of each feature set were corrected through three-sigma rule, and the corrected features were used as input parameters. The CART decision tree model was used for training. Features were selected and decision trees were constructed based on the Gini impure index. This established a marketing effectiveness model with likes and dislikes as classification objectives.

Keywords: Shopping Website, Multi-modal Data, Decision Tree Model, Marketing Effect Prediction

DOI: 10.54941/ahfe1005420

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