Decoding Health-Oriented Consumer Behavior Using Machine Learning and Behavioral Analytics

Abstract

This research investigates the impact of health and fitness consciousness (HFC) on consumer behavior (CB) among Indian millennials. It combines psychometric measurement with advanced statistical and machine learning techniques. Survey data from 550 respondents were analyzed through a wide, ranging framework including correlation analysis, mediation moderation testing, predictive modeling, and consumer segmentation. The results reveal that HFC and CB are strongly positively related (r = 0.789, p < 0.001). Health consciousness accounts for 62.2% of the behavioral variance, thus there is only a slight intention behavior gap for this group. Among predictive models, Random Forest regression significantly surpassed linear models (R = 0.924, RMSE = 3.35), which suggests that taking into account nonlinear relationships is quite important when predicting behavior. Traditional health and fitness advertising only accounts for a tiny portion (4.2%) of the relationship between HFC and CB, according to mediation analysis. On the other hand, social media influence positively moderates the behavioral translation ( = 0.007, p < 0.001), as revealed by the moderation analysis. Four millennial consumer segments were identified through cluster analysis, each segment having different levels of health consciousness, digital engagement, and purchasing behavior. Income was found to be the main demographic factor limiting health, related consumption (F=20.41, p < 0.001). At the same time, education and gender had almost no effects. Psychological factors, especially HFC and cognitive affective behavioral states, have been shown to be more influential than demographics in a feature importance model that predicts consumer behavior. In general, the study results are in accord with the previous literature on the consciousness, to, consumption pathway that is highly supported by data, and they also provide practical guidance for data, driven health marketing as well as policy interventions that target millennial populations.