Towards Using Voice for Hedonic Shopping Motivations
Morteza Behrooz, Preetham Kolari, Fred Zaw, Lindsay Kenzig, Arnav Jhala
TL;DR
The paper investigates whether voice interfaces are particularly suited to supporting hedonic online shopping motivations, especially learning trends (idea shopping). It presents a lightweight prototype that generates voice-friendly summaries of sales trends and background product information from real-category data, using NLG templates and a product database, and deploys via DialogFlow on Google Home. Through a qualitative study with nine non-technical participants from eBay, the authors observe distinct needs and preferences: recreational shoppers favor trend-oriented voice content and interactivity, while need-based shoppers seek research support and decision aids. The findings yield actionable design recommendations, such as supporting bookmarking, adding broader hedonic topics (discounts, gifts, social aspects), and enabling context-aware, interactive experiences. Overall, the work provides guidance for designing voice-based hedonic shopping experiences and assessing their potential to influence shopping behavior and information consumption patterns.
Abstract
Besides the utilitarian aspects of online shopping, hedonic motivations play a significant role in shaping the shopping behavior of online users. With the increased popularity of voice-enabled devices, online shopping platforms have attempted to drive online shopping on voice. However, we explain why voice might be more suitable for the hedonic aspects of shopping. We introduce a prototype that enables such focus in a voice experience and share our findings from a qualitative study.