At British Gas, the chatbot plays a crucial role in handling customer inquiries, but when users needed to escalate to a live agent, they often encountered frustration.

Many customers found themselves waiting in long, opaque queues with little visibility into their position or estimated wait time. This lack of transparency led to high queue dropout rates, increased customer dissatisfaction, and unnecessary repeat contacts, as users abandoned the chatbot and sought alternative support channels.

From a business perspective, these inefficiencies not only impacted customer experience but also placed additional strain on support teams, leading to operational inefficiencies and higher service costs.

The core issue was a lack of perceived progress and engagement during the waiting period, which made users feel uncertain and out of control.

Customers needed a clearer, more structured queue experience that provided transparency, set expectations, and reduced frustration while they waited.

Our goal was to design a smarter queue system that not only communicated wait times but also leveraged behavioral psychology to improve perceived waiting experiences, reducing dropouts and increasing overall satisfaction. This meant balancing user needs with operational constraints to create a scalable, data-driven solution that delivered both customer and business value.