How a machine learning recommendation engine increased a popular online wine retailer's sales by 71%.
Award-winning wine retailer United Cellars came to us to develop an eCommerce solution that would highlight its diverse wine selection and increase sales.
Their competitors were turning to technology to satisfy customers demanding a personal shopping experience. To stay relevant and profitable, they’d have to do better.
Resolve Digital met this demand by incorporating a recommendation engine – a proven machine learning technology that’s now available to small and mid-sized businesses.
United had a sales team to handle phone inquiries and provide personalized local wine knowledge to customers, but they felt that they could augment sales efforts (and reduce cost) by highlighting more wine options on the website. Could suggesting wines based on each customer’s individual preference increase profits?
Once we launched United’s Spree Commerce site, we continued our consulting engagement to enhance and optimize the customer experience.
We approached United during this post-deployment and analysis phase with a plan to increase “wine option awareness.” We defined the following goals:
Our solution? A recommendation engine that mines data to present options based on each customer’s likes and desires.
Our work involved three steps:
We ran tests to prove the efficacy of our solution for United. The tests revealed:
increase in average session length
increase in conversion rate
increase in average order size
Better yet? It doesn’t end here.
Overall, United Cellars realized a 71% boost in revenue.
The process laid out in this case study is repeatable. The capabilities of United’s recommendation engine can evolve along with the growing needs of its shoppers, both online and via their busy call center.
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