Sweaty Betty
, the UK activewear retailer with over 65 stores and a growing international business, has seen a 62% revenue uplift in six months after using Dynamic Yield’s data-driven, artificial intelligence (AI) approach and marketing technology to make better recommendations and online quizzes to get to know the customer better.
Working with Dynamic Yield, a Mastercard company, Sweaty Betty served its many audiences internationally more accurately by using guided selling quizzes, time-sensitive messaging and AI-powered recommendations. As a result, sales conversions, online transactions and revenue have all increased.
Fitness first
The global activewear and lifestyle brand for women wanted to provide a curated, empathetic experience for shoppers. Sweaty Betty’s brand is based on empowering women on their individual fitness journeys. The company wanted to accurately target customers from different markets with the right product based on their different needs, in order to deliver a more hyper-personalised experience that would drive loyalty, conversion and revenue.
The company said it wanted to improve the website experience and boost conversion rates by gaining valuable insights on key audience segments. Sweaty Betty needed to improve its ability to accurately target customers at the right time, at the right place, with the right product — no easy feat with such diverse needs across its customer base and the brand’s ambitious international growth.
A retailer best known for clothes that last a lifetime, Sweaty Betty’s products come with higher price points and require more product education than many other sportswear brands. This can be overwhelming for shoppers, so one of Sweaty Betty’s goals was to simplify and guide the product discovery process with quizzes, informing customers about the types of products to buy and questions they should consider when making a purchase. Using Dynamic Yield Experience OS, these approaches could be tailored, tested and adjusted with ease, increasing the viability by filtering the most popular products – like leggings and bras – based on the answer profile of each user.
Guided selling for discovering new products
In the UK, Sweaty Betty saw a dramatic uplift in revenue after using more personalised recommendations, including a +52% increase in the number of items per transaction and 57% higher order values.
In a trial aimed at measuring the effectiveness of personalised, time-sensitive messaging during peak-selling periods – notably Black Friday – Sweaty Betty found that pop-ups flagging “limited stock”, or the amount saved if checked-out at that moment, would lead to a 20.4% increase in purchases from new EU customers (compared to a control group with no personalised messaging). They also led to speedier checkouts and more conversions from site visitors.
Savings were based on each individual’s shopping cart and differed for each user. The pop-up was shown to 95% of those users who added an item to the shopping basket and proceeded to the following two more pages (showing reasonable intent to buy). The remaining 5% of visitors served as the control group, in order to measure uplift.
AI-powered recommendations
Following successful testing, Sweaty Betty determined that AI-powered recommendations drive better conversion rates than manually chosen ones. So, the retailer used the algorithms in Experience OS to add a product recommendation using contextual information from other users’ behaviour to serve similar browsed products in their results. Tests showed a 3% uplift in average order value (AOV) in the UK, and 8% rise in the US, after using recommendation widgets displayed on the product details page. Based on this success, Sweaty Betty has since deployed these widgets sitewide and significantly reduced the number of team hours spent on manually providing recommendations.
Dynamic Yield’s “affinity mapping” enables Sweaty Betty to create audience segments, hone in on potential opportunities and pursue them with precision. Sweaty Betty’s digital team isn’t huge, so it was important that the solution was scalable and economical. The project took less than six months to implement and see the rewards. The audience data in Dynamic Yield turned out to be invaluable, given it had previously made assumptions about certain audience segments that turned out to be inaccurate with testing. A number of other potential revenue avenues are also being tested and explored.
“With Dynamic Yield, we can build amazing experiences with huge agility and speed across digital channels. Since we’re no longer heavily reliant on big technical integrations and merchandising, we can now move faster and can deliver more experiences for our customers,” said Helen Martin, Lead Digital Product Manager at Sweaty Betty.
Sweaty Betty plans to ingest CRM data into Dynamic Yield to build more sophisticated audience segments. It also has plans to expand the personalisation program and use the same AI technology to help make more recommendations via email.
