Pricing, Popularity, and Customer Satisfaction in Online Pain-Relief Products: An AI-Powered Analysis

Objective: To examine how product popularity and pricing are associated with customer satisfaction across pain-relief device types on online e-commerce platforms. Methods: A cross-sectional study was conducted to analyze pain-relief products from Amazon and Best Buy. Data were collected via automated web scraping, verified, and categorized into 10 device types. Key variables including product names, prices, customer ratings, and review volumes were assessed in multivariable regression models. Results: A total of 378 distinct pain-relief products were analyzed. The median customer ratings for pain-relief devices varied significantly by type, ranging from 3.2 to 4.5 (p < 0.001). TENS units and cold/heat therapy packs achieved the highest median ratings of 4.5 (4.3-4.6). In contrast, hand/arm massagers received the lowest median rating of 3.2 (2.2-4.2). Pricing differences across device types were significant (p < 0.001), with neck stretchers being the least expensive (median: $29.99) and hand/arm massagers being the most expensive (median: $249.50). Discussion: Although price and the number of reviews were not significant predictors of customer ratings in multivariable regression models, significant interactions were observed between price and device type for hand/arm massagers (p < 0.001) and massage guns (p = 0.006). Additionally, significant interactions between the number of reviews and device type were observed for hand/arm massagers (p = 0.004). Conclusion: Although pricing and review quantity were not significant predictors of satisfaction for most devices, they did interact with specific categories such as hand/arm massagers and massage guns. These findings indicate that customer satisfaction is driven more by device-specific characteristics than by price or review volume.