Bodybuilding Warehouse smashes email engagement
Get the case study
Bodybuilding Warehouse (BBW) is the UK’s fastest-growing supplement company that prides itself on exemplary customer service.
BBW sell everything from the best-value high-quality whey protein concentrate, to tasty high protein flapjacks, which are produced in their state of the art factory in-house. Customers will find an extensive range of bodybuilding products and brands all under one roof, at extremely competitive prices, shipped with fast, convenient delivery.
Customized content is improving the customer experience
Bodybuilding Warehouse wanted to enforce a high level of customer service online, by making the entire shopping experience as unique and enjoyable as possible.
Having used Engagement Cloud for email marketing automation and Nosto for on-site recommendations, BBW decided to combine the power of the two. By adding Nosto recommendations to dotdigital's emails, BBW could further personalize its emails, improve the user experience, click-through rates and sales.
Kim McIntyre, Marketing Manager at Bodybuilding Warehouse, explains how Nosto and dotdigital have helped the brand to deliver a better customer experience: “We wanted to utilize our emails as a channel through which to give our customers product recommendations suited to their unique browsing and purchase history, and that is exactly what Nosto has allowed us to do. By tailoring our email marketing to include recommendations for individuals, we have been able to capture the attention of our audience with more tailored, valuable communications which, in turn, has improved our core email KPIs.”
Product recommendations produced a 20% increase in conversion
With Nosto’s Email Personalization Widgets, Bodybuilding Warehouse is able to promote the right products, to the right audience, at the right time. This technique allows BBW to attract new shoppers, as well as re-engage with loyal customers to increase sales and AOV. BBW has seen a 20% increase in email conversion after switching from displaying static product recommendations to offers based on individual user behavior.