From Metrics to Meaning: Insights from a Mixed-Methods Field Experiment on Retail Robot Deployment

We report a mixed-methods field experiment of a conversational service robot deployed under everyday staffing discretion in a live bedding store. Over 12 days we alternated three conditions--Baseline (no robot), Robot-only, and Robot+Fixture--and video-annotated the service funnel from passersby to purchase. An explanatory sequential design then used six post-experiment staff interviews to interpret the quantitative patterns. Quantitatively, the robot increased stopping per passerby (highest with the fixture), yet clerk-led downstream steps per stopper--clerk approach, store entry, assisted experience, and purchase--decreased. Interviews explained this divergence: clerks avoided interrupting ongoing robot-customer talk, struggled with ambiguous timing amid conversational latency, and noted child-centered attraction that often satisfied curiosity at the doorway. The fixture amplified visibility but also anchored encounters at the threshold, creating a well-defined micro-space where needs could ``close'' without moving inside. We synthesize these strands into an integrative account from the initial show of interest on the part of a customer to their entering the store and derive actionable guidance. The results advance the understanding of interactions between customers, staff members, and the robot and offer practical recommendations for deploying service robots in high-touch retail.

What you reward is what you learn: Comparing rewards for online speech policy optimization in public HRI

Designing policies that are both efficient and acceptable for conversational service robots in open and diverse environments is non-trivial. Unlike fixed, hand-tuned parameters, online learning can adapt to non-stationary conditions. In this paper, we study how to adapt a social robot's speech policy in the wild. During a 12-day in-situ deployment with over 1,400 public encounters, we cast online policy optimization as a multi-armed bandit problem and use Thompson sampling to select among six actions defined by speech rate (slow/normal/fast) and verbosity (concise/detailed). We compare three complementary binary rewards--Ru (user rating), Rc (conversation closure), and Rt (>=2 turns)--and show that each induces distinct arm distributions and interaction behaviors. We complement the online results with offline evaluations that analyze contextual factors (e.g., crowd level, group size) using video-annotated data. Taken together, we distill ready-to-use design lessons for deploying online optimization of speech policies in real public HRI settings.

Influence of collaborative customer service by service robots and clerks in bakery stores

In recent years, various service robots have been introduced in stores as recommendation systems. Previous studies attempted to increase the influence of these robots by improving their social acceptance and trust. However, when such service robots recommend a product to customers in real environments, the effect on the customers is influenced not only by the robot itself, but also by the social influence of the surrounding people such as store clerks. Therefore, leveraging the social influence of the clerks may increase the influence of the robots on the customers. Hence, we compared the influence of robots with and without collaborative customer service between the robots and clerks in two bakery stores. The experimental results showed that collaborative customer service increased the purchase rate of the recommended bread and improved the impression regarding the robot and store experience of the customers. Because the results also showed that the workload required for the clerks to collaborate with the robot was not high, this study suggests that all stores with service robots may show high effectiveness in introducing collaborative customer service.

Service Robots in a Bakery Shop: A Field Study

In this paper, we report on a field study in which we employed two service robots in a bakery store as a sales promotion. Previous studies have explored public applications of service robots public such as shopping malls. However, more evidence is needed that service robots can contribute to sales in real stores. Moreover, the behaviors of customers and service robots in the context of sales promotions have not been examined well. Hence, the types of robot behavior that can be considered effective and the customers' responses to these robots remain unclear. To address these issues, we installed two tele-operated service robots in a bakery store for nearly 2 weeks, one at the entrance as a greeter and the other one inside the store to recommend products. The results show a dramatic increase in sales during the days when the robots were applied. Furthermore, we annotated the video recordings of both the robots' and customers' behavior. We found that although the robot placed at the entrance successfully attracted the interest of the passersby, no apparent increase in the number of customers visiting the store was observed. However, we confirmed that the recommendations of the robot operating inside the store did have a positive impact. We discuss our findings in detail and provide both theoretical and practical recommendations for future research and applications.