• Increase in NPS

    18%

  • Decrease in average
    handle time in chat

    28%

Challenge

Overstock is a leading US online retailer that sells a broad range of products including furniture, rugs, bedding, electronics, clothing, and jewelry. [24]7.ai provides sales and services support on live chat to Overstock’s customers. Overstock wanted to find avenues to improve the quality and effectiveness of its chat customer experience.

Solution

Overstock wanted to find opportunities to improve its NPS score in chat and worked with [24]7.ai to achieve this goal. First, [24]7.ai applied advanced text mining and analytics to 100% of chat transcripts to find factors impacting NPS. The insights gleaned from this analysis provided a foundation from which [24]7.ai was able to create a curriculum that would optimize agent performance and help boost NPS.

[24]7.ai created a two-pronged approach that included implementing personalized training programs for chat agents who fall into the bottom quartile in performance. In addition, changes were made in processes based on the customer's initial intent to ensure the customer's needs were addressed quickly.

Result

The two-pronged approach resulted in a significant improvement in the performance of the chat program. Closed-loop bottom quartile management coupled with daily reviews by operations managers and team leads helped vastly improve the performance of underperforming agents. And changes in business processes configured to the customer's intent and needs helped boost NPS.

Within three months of implementation, the new approach improved NPS by 18%. The changes also helped agents service customers faster, as shown by 28% reduction in average handle time (AHT).

"No improvement needed. He was pleasant, went out of his way to resolve the issue, very patient. He made the chat experience awesome!"

"Anytime I have had a problem with an order here, your representatives have been very helpful and have solved my problems to my satisfaction."

Overstock customer feedback after chat