AI-Driven Customer Service Transformation at Harry Rosen
Applicable Functions
- Sales & Marketing
About The Customer
Harry Rosen is a leading Canadian menswear retailer. The company has a significant digital presence, which became even more crucial during the COVID-19 pandemic when lockdowns and changing customer behavior led to a surge in online shopping. As a result, Harry Rosen experienced a sharp increase in digital customer service tickets, putting a strain on its customer service department. The company needed a solution that could handle the increased volume of tickets, particularly during peak shopping seasons, without compromising on the quality of customer service.
The Challenge
During the COVID-19 pandemic, Canadian menswear retailer Harry Rosen experienced a significant shift in its business to the digital realm due to lockdowns and changing customer behavior. This transition led to a sharp increase in digital customer service tickets, stretching the customer service department thin. The company initially tried to manage the surge by reallocating in-store associates to digital customer care. However, this approach proved to be insufficient and unsustainable, as the volume of tickets continued to rise, especially during peak seasons like the holiday shopping period.
The Solution
Harry Rosen turned to Netomi's AI, named Hailey, to manage the influx of customer service tickets. Hailey began by assisting agents with suggested replies and actions, and eventually became an integral part of the workforce, interacting directly with customers to resolve tickets on both email and chat platforms. The AI was integrated with Harry Rosen's backend systems, enabling it to effectively handle repetitive customer queries such as order status and cancellations, exchanges, and alterations. Hailey's capabilities were particularly beneficial during busy seasons, as it automated repetitive tickets without any human effort, eliminating the need to hire additional agents to handle the increased ticket volume. This drastically reduced the resolution time on tickets to mere hours, down from several days.
Operational Impact
Quantitative Benefit
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