FatFace achieves a further 1.71% conversion rate uplift in 10 days with the addition of machine learning and aggregated review messaging
"Our customer product reviews are great, scoring really highly and with machine learning helping us surface the best messages for our customers we can make sure more customers know about our great reviews."
Head of E-commerce
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FatFace is a British, family, lifestyle clothing brand that is Made for Life. With a unique heritage, FatFace creates product ranges across womens, mens, kids, footwear and accessories for the whole family to live life in. Products are designed with purpose and built to last. Considered Style. Trusted Quality. Sustainably sourced.
FatFace is a multichannel retailer with a thriving international digital business as well as over 180 stores in the UK, 20 stores in the US and a highly engaged social community. FatFace is a brand with sustainability at its core with a clear strategy around three key pillars – product, planet, and community. Devoted to style, dedicated to sustainability.
FatFace has been working with Taggstar to provide social proof messaging to help customers with their buying decisions since April 2021. It was initially operating with 11 message types running across its Product Details Page (PDP) and Basket Page and with this implementation had already seen a conversion rate uplift of 4.4%.
However, it was aware that for some customers’ buying journeys, conversion is improved still further by providing them with the extra information they may need around quality or suitability so wanted to test the incorporation of review messaging to complement the existing messaging to further improve confidence in their customers’ buying decisions.
Taggstar partners with Bazaarvoice to add aggregated review messages into social proof messaging strategies for its retail customers. For FatFace this widens the messaging used from 11 to 13 to also include information about how customers rated the products.
In the FatFace implementation, Taggstar added two BazaarVoice-inspired message types to FatFace’s existing social proof implementation. These included “Highly Rated! x% of people recommended” and “Top Pick! X people rated 5 stars.”
To make sure the right type of messaging was shown to the right customer at the right time FatFace also adopted Taggstar’s machine learning. By reacting in real-time, machine learning allows the most suitable social proof message to be surfaced for the customer as they are browsing the FatFace site, for instance, an aggregated review message if they are in browsing mode on the PDP or a stock availability message if they are closer to purchase such as viewing on the bag page. The addition of machine learning makes a Taggstar social proof messaging implementation even more effective since a retailer can broaden the range of customers converting at any point in the customer journey.
This optimisation test ran in December 2021 and in only 10 days delivered an additional conversion rate uplift of 1.71% over and above the conversion rate of 4.4% previously witnessed by FatFace with the original implementation of Taggstar.
Following the success, 2022 will see the testing of social proof messaging from Taggstar on additional pages across the customer buying journey for FatFace, including Product List Pages (PLP) and Wishlist. Social proof messaging will also be tested on additional channels including email.
Liam Price, Head of E-commerce at FatFace, said: “The addition of aggregated review messaging as part of our social proof strategy was the next logical step for optimising our onsite messaging. Our customer product reviews are great, scoring really highly and with machine learning helping us surface the best messages for our customers we can make sure more customers know about our great reviews. Really pleased to see such compelling results in such a short time!"
Peter Buckley, CRO at Taggstar, said: “FatFace shares our vision of getting the right message at the right time to the customer so that they can make the best buying decisions. At Taggstar we continue to innovate with new products and use machine learning to surface the most appropriate messages. By implementing both review messaging and machine learning within its business FatFace shares our hunger for pushing boundaries with social proof and has seen the positive results this delivers.”
"Really pleased to see such compelling results in such a short time!”
Head of E-Commerce