Leveraging Interesting Facts to Enhance User Engagement with Conversational Interfaces (2024)

Abstract: Conversational Task Assistants (CTAs) guide users in performing a multitude of activities, such as making recipes. However, ensuring that interactions remain engaging, interesting, and enjoyable for CTA users is not trivial, especially for time-consuming or challenging tasks. Grounded in psychological theories of human interest, we propose to engage users with contextual and interesting statements or facts during interactions with a multi-modal CTA, to reduce fatigue and task abandonment before a task is complete. To operationalize this idea, we train a high-performing classifier (82% F1-score) to automatically identify relevant and interesting facts for users. We use it to create an annotated dataset of task-specific interesting facts for the domain of cooking. Finally, we design and validate a dialogue policy to incorporate the identified relevant and interesting facts into a conversation, to improve user engagement and task completion. Live testing on a leading multi-modal voice assistant shows that 66% of the presented facts were received positively, leading to a 40% gain in the user satisfaction rating, and a 37% increase in conversation length. These findings emphasize that strategically incorporating interesting facts into the CTA experience can promote real-world user participation for guided task interactions.

## introduction conversational task assistants (ctas) are a class of conversational agents that guide human users step-by-step in performing a multitude of activities, like cooking or home improvement tasks @xcite @xcite @xcite . ctas help users search and find the right task for their needs, inform about the task execution (e.g., tools to use), and answer questions about the task (e.g., substituting an ingredient). besides ensuring that ctas provide useful, accurate content, it is crucial to encourage users to consistently use ctas to accomplish long and complex tasks. in this setting, users can easily get bored and abandon tasks, so maintaining interesting and entertaining conversations is key @xcite . understanding and predicting human interest is crucial to engage and retain users @xcite . we hypothesize that incorporating relevant, entertaining pieces of information into conversations is a powerful tool to maintain and sustain user attention, satisfaction, and participation. for example, while cooking with a cta, users are likely to interact with it longer, frequently and repeatedly, if their experience is enriched with intriguing facts about the recipe's history, nutritional benefits of its ingre-dients, or useful tips about its cooking techniques (see figure 1 for an example). such information can increase user knowledge, satisfaction and trust in the cta by establishing it as a knowledgeable domain expert. it transforms users' dialogue with the cta into more than just task-oriented, resulting in an improved user experience, particularly during long, tedious, or monotonous activities. we propose a practical approach to enhance user engagement with ctas. grounded in sociopsychological theories on human interest @xcite @xcite , we design a novel schema to comprehensively and objectively examine the interestingness of pieces of information (henceforth called 'facts') in a cta setting. we study if such facts can spark and foster user interest, and thus boost user satisfaction and engagement during a conversation with a cta. we also explore multiple techniques to share interesting facts with users. we perform live testing of our framework in a leading multi-modal voice assistant. 66% of our facts were received positively by real-world users, resulting in a 40% gain in average user satisfaction ratings, and a 37% increase in average conversation length. these results demonstrate the practical benefits of enriching the cta experience with interesting facts, and showcase our approach's potential to enhance the adoption of ctas for complex realworld tasks requiring sustained user engagement. we also create for public release a dataset of 1, 379 interesting facts associated with cooking, extracted from online sources and cleaned for grammar, style, relevance, interestingness, and appropriateness. we believe that this can be a valuable resource to drive future research in ctas, and user engagement in task-assistance conversations. ## related work interest and interestingness: our work on enhancing user engagement with ctas by increasing their level of interest in the conversation is inspired by multiple psychological theories conceptualizing the human behavioral dimensions of interest and interestingness. one of the earliest theories is that of berlyne @xcite , who viewed interest as a defining factor of motivation, influenced by several factors including uncertainty, complexity and novelty of the subject at hand. @xcite ; silvia (2005) defined interest as an appealing effect of an activity on a human caused by novelty, exploration, learning, creativity and affect, leading to increased interaction with the subject matter. @xcite surveyed multiple features relevant to interestingness such as conciseness, coverage, reliability, novelty, surprise and utility in the context of pattern mining and association rules. @xcite studied their correlation with real human interest. @xcite ; @xcite observed a negative correlation between interest and low-arousal emotions like memorability, familiarity, and boredom. clark et al. (2019); ceha et al. (2021) employed humor, jokes and fun facts within their conversation agents to demonstrate that providing such entertaining information to users can increase user interest, engagement and retention, and reduce monotony. in our work, we model several aspects contributing to human interest in section 3, to identify facts that can interest and engage users interacting with a cta, and reduce monotony. we show in section 4 that a cta without interest enhancing signals can cause boredom and reduce engagement by users. conversational task assistants: ctas are a special type of conversational assistants @xcite , different from general purpose intelligent assistants (e.g., amazon's alexa, apple's siri). ctas guide users to perform tasks in a stepwise manner, also answering user questions along the way. ctas differ from conversational search agents @xcite and task-oriented conversational agents @xcite , where the agent and not the user performs a task based on user input (e.g., booking a ticket). user satisfaction and engagement has been widely studied in the areas of search, task-oriented dialog systems and virtual assistants @xcite @xcite @xcite . however, these approaches lack a theoretical backing and have not been studied for ctas. the work that bears the most similarity with ours is wizard of curiosities (woc) @xcite , which also adds facts within dialogues between users and ctas. however, both works differ in the following ways: (i) woc targets informationseeking traits of humans based on curiosity theory @xcite . our work is more principled and draws upon the broader theories of interest which encompass informativeness and curiosity, and are better suited for studying and improving user engagement @xcite ; ## boosting cta engagement with facts we now describe our framework to offer interesting facts to users conversing with a multi-modal cta, having both display and voice components, to entertain users and increase their engagement. we focus on cooking-specific conversations, but as explained in section 5, we believe that our framework can generalize to any cta-feasible domain. ## conclusions drawing on psychological theories on human interest, this work defines what users might find interesting during guided task-based conversations with ctas, and empirically demonstrates the value of engaging and satisfying users with appealing external knowledge. engaged users are, in fact, more likely to complete tasks and leverage the power of ctas for complex task assistance. to achieve this goal, we defined a semi-automatic framework to build a dataset of 1, 379 contextual and interesting facts for the cooking domain, and investigated different options to effectively inject the facts into user-cta conversations. offline human evaluations and live testing on a multi-modal voice assistant showed significant gains in user satisfaction and engagement in a cta enriched with our interesting facts experience.