The Effect of Proactive Cues on the Use of Decision Aids in Conversational Recommender Systems
Yuan Ma, Jürgen Ziegler · 2024
Conversational recommender systems (CRS) are increasingly able to conduct complex conversations with the user due to the advances in natural language processing techniques. As a consequence, dialogs in CRS can go beyond the mere recognition of product-related intents, offering decision aids that let users, for example, compare or critique recommendations. Users may, however, not be aware of such functionality and fail to actively query the system for such functions. It may thus be helpful, if the system proactively provides cues for using the advanced functions. Whether and how such proactive cues are perceived and used by the user has not been investigated yet. We report an online study investigating user interaction behavior under two interaction schemes: a proactive scheme prompting the user to use the functions and a passive scheme without prompts where users can freely enter their requests. To compare the two schemes, we implemented a chatbot in the domain of smartphones. Two groups of participants on Prolific (total n=270) used the system, which operates either with a proactive or passive scheme. In addition to interaction data, we measured several psychological factors and users’ subjective assessment of the system through questionnaires. We mainly found: 1. There is no significant difference in user experience under the two schemes. 2. Users tend to accept prompts when the system provides them. 3. Overall, more intuitive users (as measured by an established decision-making style instrument) tend to accept the system’s prompts more than more rational persons. 4. A tendency that acceptance of interaction prompts aligns with self-reported dialog-related preferences. The results provide heuristic suggestions for dialog strategy design and the potential personalization of CRS.