ShopLC is a leading television and e-commerce retailer specializing in jewelry, gemstones, beauty, fashion, and home products. Through its live shopping network and online store, ShopLC serves customers across the United States with a 24/7 shopping experience.
A meaningful portion of ShopLC's sales comes through television shopping, where customers call in while products are being featured live on air. With a high volume of customer phone calls every day, each conversation is an important opportunity to support shoppers, answer questions, and drive additional sales.
Earlier this year, ShopLC partnered with Ambi Labs to make every customer conversation more valuable for personal shoppers, while helping managers make QA audits more effective and efficient through automation.
Today, ShopLC has rolled out Wink to 50 personal shoppers. With Wink, ShopLC has:
- Boosted sales through live upsell opportunities
- Made QA audits more effective and efficient
- Enabled live transcription across customer calls
Every Call Carries Context
At ShopLC's scale, customer conversations are one of the most important parts of the business. Every day, customers call in to purchase products, ask questions about items being shown live, resolve issues with existing orders, or get help deciding what to buy.
Each conversation gives the team a clearer picture of what the customer needs and how the shopper can help.
As call volume grew, it became difficult for ShopLC to understand what was happening across every interaction. Managers could only review a limited number of calls manually, which made it hard to consistently measure conversation quality, identify coaching opportunities, and understand why some personal shoppers were more successful at converting calls into additional sales.
ShopLC needed a way to evaluate customer conversations at scale while also helping its team turn more interactions into high-quality shopping experiences.
Helping Shoppers Recommend the Next Product
Before Wink, many personal shopping calls followed a familiar pattern: the customer called in, the shopper helped fulfill the order, and the call ended.
Wink gives personal shoppers more context while the conversation is still happening. As the customer talks, Wink uses the current conversation, customer details, and previous purchases to surface other products the customer may be interested in.
This helps shoppers move beyond simply completing the original request. When there is a natural fit, they can suggest relevant products, complementary items, or similar pieces without manually searching through the catalog or guessing what the customer might like.
Making QA Audits More Effective
For managers and quality assurance teams, Wink provides visibility into customer interactions at scale. After each call, conversations are automatically evaluated against the performance criteria defined by ShopLC, including customer service standards, sales behaviors, and compliance requirements.
Instead of relying only on a small sample of manual call reviews, managers can understand performance across many more interactions. This makes it easier to identify coaching opportunities, spot patterns across the team, and improve the customer experience without adding more administrative review time.