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Boden gets personal

By Retail Technology | Monday March 6 2017

Fashion retailer, Boden saw an 18% increase in ‘add-to-basket’ after implementing a new personalisation platform

The company began using Monetate’s platform to make its customer experience more relevant to different segments of online shoppers.

“The way in which people shop on our sites has changed as new devices are introduced and there is a greater shift to mobile,” said Hayley Lingard, web optimisation executive at Boden. “We are focusing on optimising their experience regardless of the device they are using and personalising it based on their language as well as their browse or purchase history.”

Boden was keen to improve its mobile experience  having seen through data analysis that it wasn’t very clear that swiping showed more images and colour options.   “We tested adding a ‘Swipe for More’ prompt on top of the main image on the mobile site” said Lingard.  “Learning from initial results, we tweaked the message, this time using Dynamic Testing as we were nearing our peak trading times. With the goal metric as ‘add-to-basket’, Dynamic Testing reduced the risk during a busy trading period. It was so successful that within a week, 99% of the traffic was being sent to the experiment, as the add-to-basket rate was seeing significant uplift. Overall we saw an 18% increase in add-to-basket.”

Dynamic 

Launched last month, Monetate’s Dynamic Testing is a new machine powered testing 
capability as part of the Monetate personalisation platform, that helps retailers reduce risk and capitalise on early gains during testing.   

The technology assesses campaign performance in real-time, determining which targeted experiences are performing best. Traffic is then dynamically allocated to the winning variant, enabling retailers to maximise ROI at a much earlier stage.

Boden also added product page recommendations through Monetate, recommending relevant products after a visitor had added an item to their online bag. 

For the UK, Boden saw a 7% increase in ‘average order value’ (AOV) when recommending girls’ accessories if a visitor added a girls’ product to their basket.  “By integrating our CRM data, we have been able to track specific customer segments, which gives us a greater insight in how we need to target and personalise towards these visitors,” added Lingard.



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