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Transforming the shopping experience in only 6 months with Sweaty Betty

See how this global activewear and lifestyle brand maximized key customer engagement strategies to generate an overall lift from personalization, including a +62% uplift in same-session revenue from recommendations-powered quizzes.
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Industry
Capability Used
+62%
uplift in same-session revenue from recommendations-powered quizzes, compared to quizzes run on a prior system without recommendations
+20.4%

increase in Black Friday purchases from new EU customers from personalized messaging, compared to the control group with no personalized messaging

+8%

uplift in AOV in the US from recommendation widgets displayed on PDPs

Introduction

Sweaty Betty, a UK-based activewear and lifestyle brand for women, has always been about more than just high-quality clothes — they have made a global business by putting the customer first, empowering women through fitness and beyond. It was the ongoing desire to provide a curated, empathetic experience for shoppers that led the company to invest in personalization.

In the course of only six months, Sweaty Betty created a personalization-focused squad within their Digital Product Management team, coordinated their departments on goals associated with personalization, implemented their new tool Dynamic Yield, and hit the ground running with strategic on-site experiences and tests. Overall in their biggest market, the UK, they saw an uplift in revenue from personalization in 6 months, including a +52% increase in items per transaction and a +57% higher average order value from personalized recommendations.

Sweet Betty logo

“Collaborating with Dynamic Yield has meant 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. 

Historically, we used to rely heavily on product recommendations; we can now leverage what we think is right for our customer in terms of their needs and try to anticipate and then meet the customer’s intent. This approach has transformed the customer experience and as a result, customer loyalty and conversion rates.”

Helen Martin, Lead Digital Product Manager, Sweaty Betty
The Challenge section thumbnail

The Challenge

Unlocking agility and targeted experiences

When Sweaty Betty and Dynamic Yield first started working together, the brand had exhausted the benefits from existing tools to drive customer engagement via personalization, but it wasn’t enough. 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.

Leveraging Experience OS, Sweaty Betty worked to drive UX growth and deliver a personalized, world-class onsite experience, measured by conversion rates and uplifts and informed by insights gained on key audience segments. By delivering a more end-to-end, hyper-personalized experience, they drove customer loyalty, conversion rates, and revenue. Below are some examples of their successful use cases and challenges solved with personalization.

Early Execution

Achieving scalability with guided selling to increase product discovery

A brand that makes clothes to last a lifetime, Sweaty Betty’s products come with higher price points and require more product education than average sportswear. This can be overwhelming for shoppers, so one of Sweaty Betty’s goals was to simplify and guide the product discovery process with personalized quizzes for leggings and bras.

While the brand had seen some success using a third-party system to implement on-site quizzes, this solution was ultimately unscalable as it became impractical to consistently test and optimize the quiz for unique visitor types. Through Experience OS, Sweaty Betty launched template-based quizzes that could be tested and adjusted with ease, increasing the viability and impact of this guided selling approach. The quizzes were powered by a custom-built Experience OS recommendation strategy that filtered the most popular leggings based on the answer profile of the user.

leggings
In this quiz, visitors were prompted to answer a series of questions about their leggings preferences, which generated a unique page of shoppable results. This helped Sweaty Betty deliver a personalized shopping experience.
bra_1
In this quiz, visitors were prompted to answer a series of questions about their bra preferences, which generated a unique page of suggested products. In addition to delivering a personalized shopping experience, the quiz helped Sweaty Betty educate customers on the types of available bras to buy and the questions they should consider when making a purchase.

With these two quiz templates, Sweaty Betty gained the ability to easily run tests and adjust the recommendations strategy powering the on-site quizzes, making this strategy scalable in the long run.

Since the new quizzes went live, Sweaty Betty has seen an overall +1.93% uplift in the average order value (AOV), a +7% increase in conversion rates, and a +62% uplift in same-session revenue compared to the previous quiz experiences.

The revenue impact of personalized, time-sensitive Black Friday messaging

On Black Friday, Sweaty Betty wanted to minimize the time between an add-to-cart action and the final transaction, ensuring more conversions from site visitors. To achieve this, they implemented a personalized pop-up to visitors containing scarcity messaging (“limited stock”), as well as the amount of money the visitor would save if the checkout occurred at that moment. This number was based on the individual’s cart and differed for each user. 

The pop-up was shown to 95% of users who added an item to the basket and proceeded to browse two more pages (indicating reasonable intent to buy). The remaining 5% of visitors in this group served as the control in order to measure uplift.

black_friday

As a result of the personalized pop-up, Sweaty Betty saw a +3% uplift in incremental revenue in the UK and a +8.3% uplift in incremental revenue in the EU.

Leading with AI-powered recommendations
Following successful testing, Sweaty Betty determined that algorithm-powered recommendations drive better conversion rates than manually chosen ones. So, they used the algorithms in Experience OS to add a product recommendation widget on all PDPs, using contextual information from other users’ behavior to serve similar browsed products in the results.
recommendation
See here two different types of product recommendation widgets displayed on a PDP. One shows a single product, and the other shows 3 products with the option to toggle over into “Recently Viewed.”
After an early test of the recommendation widgets generated a +3% uplift in average order value (AOV) in the UK and a +8% uplift in AOV in the US, Sweaty Betty deployed these widgets sitewide. In addition to the increased revenue, this strategy decreased team hours spent on recommendations, yielding a better impact for less work.

The Key Takeaway

With the capability to rebuild quizzes, power recommendations, understand key audience insights, and deploy a truly personalized site experience to each visitor, Dynamic Yield has enabled Sweaty Betty to fine-tune a number of customer engagement strategies to make them even more targeted and effective — all within six months, including implementation.  

Dynamic Yield’s affinity mapping enables Sweaty Betty to create audience segments, hone in on and size up potential opportunities, and then pursue these opportunities with precision. Sweaty Betty’s digital team isn’t huge, so it was key that the solution was scalable and economical, allowing them to make smart use of their time by focusing on the right things. The audience data in Dynamic Yield has also been invaluable; the team had previously made assumptions about certain audience segments that turned out to be inaccurate with testing. Through their work with Dynamic Yield, Sweaty Betty now has a bank of business cases which its CRO team can use to test potential revenue avenues.

What’s next for this innovative brand? Sweaty Betty plans to ingest CRM data into Dynamic Yield to build more sophisticated audience segments. They also have plans to expand their personalization program to email, maximizing the AI-powered tools in Dynamic Yield to populate recommendations directly in consumers’ inboxes. Finally, Sweaty Betty recently launched a headless website architecture and will begin powering all personalized experiences on their website via Experience APIs.

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