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Case Study
Fashion

Fashion-Specific AI Business Increases Revenue per Visitor by 5% and Reduces Returns by 2% for House of Bruar

House of Bruar partnered with Mapp Fashion to implement fashion-specific AI personalization, resulting in a 5% increase in revenue per visitor and a 2% reduction in return rates.

Fashion-Specific AI Business Increases Revenue per Visitor by 5% and Reduces Returns by 2% for House of Bruar
Table of contents
Challenge
Results
Challenge

With a vast product catalogue across a broad customer base, House of Bruar were keen to see whether personalisation could increase revenues by putting better products in front of each customer. With a large cohort of female shoppers, House of Bruar were also interested in a solution that could reduce return rates.

“The team at Mapp Fashion really understands the nuances around the fashion domain, we have been so impressed with their knowledge and experience. The results of their personalisation are impressive and we are very happy with the strong results achieved so far.”
John Hodge
Head of eCommerce @House of Bruar

Objectives

The partnership started by AB testing Mapp Fashion’s fashion-specific prediction models in two areas: Similar Items on the PDP, and Personalised Outfits on the PDP. This was tested vs a more generic algorithm (not trained on the fashion domain) and outfits that were manually created by the team internally.

Results
+5%

Revenue per Visitor

-2%

Return Rate

Additional Benefits

  • Every product is given the love it deserves
  • Every customer sees products they love and won’t return
  • No manual work for in-house teams
  • Access to the Mapp Fashion Return Dashboard to highlight quick wins in order to optimise return rates
We have loved working with House of Bruar. They are a great team with a very open approach to collaboration. We have enjoyed ensuring that their very distinctive brand DNA is maintained across the personalised outfits and that we can cater effectively for country sporting pursuits.”
Sarah McVittie
VP Marketing, Mapp