Hey Robot, Tell It to Me Straight: How Different Service Strategies Affect Human and Robot Service Outcomes.

Area of Science:

• Human-Robot Interaction
• Service Robotics
• Customer Experience Research

Background:

• Robots are increasingly performing service tasks, necessitating an understanding of effective customer interaction strategies.
• Current customer service models may not be optimal for robotic agents.

Purpose of the Study:

• To compare the effectiveness of different customer service styles (straight, data-driven, traditional) when performed by robots versus humans.
• To determine which service styles enhance customer satisfaction and perceived information levels when executed by robots.

Main Methods:

• Three online studies involving over 1300 participants were conducted.
• Customer service interactions were simulated with robots and humans employing distinct service styles.
• Customer satisfaction, perceived informativeness, and naturalness were measured.

Main Results:

• Traditional customer service styles were most effective when performed by human shopkeepers.
• Robots utilizing straight or data-driven communication significantly increased customer satisfaction.
• Robot-delivered service styles were perceived as more informative and natural compared to human delivery of the same styles.

Conclusions:

• Robot-specific best practices for customer service are essential for maximizing customer satisfaction.
• Simply replicating human-human interaction models may not yield optimal results for robots in social contexts.
• Further research into robot-specific social interaction is warranted.