Key KPIs delivered by Taggstar

  • 1.71%

    additional conversion rate uplift in 10 days

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The Challenge

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.

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The Solution

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.”

“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.”

Liam Price, Head of E-commerce

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The Results

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.

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The Results

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!”

The Results

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.”

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