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Feb 16, 2021
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Skinnydip dives into AI-powered merchandising and A/B testing to boost online sales

Published
Feb 16, 2021

It took the pandemic to shift all its sales operations online. So clothing, lifestyle and phone accessories retailer Skinnydip London introduced automated merchandising and A/B testing technology to boost its digital operations.


Skinnydip London


The result? A 16% increase in average visit value, with the click-through conversion (CTR) rate on its e-commerce store up 15%. That was “a substantial increase”, the company said Tuesday.

This saw beauty conversion rates rise 36% and a 23% increase in CTR; clothing also rose 12% and 26% respectively, while phone cases and accessories saw respective 35% and 38% increases.

To achieve this, the retailer utilised IT company Nosto’s AI-powered Commerce Experience Platform to optimise the way it displays and ranks products on category pages “based on real-time customer behaviour and onsite performance data”. 

The company, for which 90% of e-commerce traffic comes through mobile, is also using A/B testing tools through Nosto to identify the best performing merchandising strategies on dozens of category pages for its beauty, clothing, phone cases and accessories products.

With the pandemic abruptly halting brick-&-mortar shopping in 2020, Skinnydip, like many brands, shifted focus to its e-commerce store as the sole channel for traffic and sales. This was both an opportunity and a challenge: while online traffic has increased, so has online competition. 

Skinnydip needed a merchandising strategy to foster product discovery, convert new site traffic and nurture new shoppers into loyal customers. With Nosto it has been able to replace a labour and time-intensive manual strategy based on gut feeling and guesswork, with automated merchandising that uses data and machine learning algorithms to drive decisions”, it added.

Meghan Lewis, head of E-commerce at Skinnydip London, added: “Our previous merchandising was done through intuition and what ‘looked good’. For example, there are tons of products in our collections that work really well as add-ons, but someone manually merchandising might rank them much lower on the category page”.

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