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Recommender Systems

Client Benefit


Information technology and innovative thinking are transforming everyday processes. Recommender systems are now a huge component of the online shopping experience, with a “you may also like” section, recommending what other products to explore. Typically we see very similar items to what we’ve just purchased or generic items that aren’t applicable to our exact tastes and interests.

A huge proportion of waste, whether food, fashion, or even furniture, is created from making the wrong decisions whilst online shopping. There is an average return rate of 15% for online retailers and our purchasing habits are having a detrimental impact on the environment because our wrong purchasing decisions have carbon emissions and end up in landfill. A solution is needed, using innovative technology and creative thinking, to improve purchasing decisions and reduce the return rate.

What did our client do?

Our client rethought the recommender systems of e-commerce businesses through an exploration of technology and psychology studies. They used Artificial Intelligence to analyse customer data so the recommended products are specific to the personality of the shopper, creating a Recommendation-as-a-Service (RaaS) platform. This has not been done before in e-commerce. This approach helps to provide customers with bespoke recommendations, aligned with what they’re really looking for, resulting in increased dwell times and loyalty.

How did we help?

Our team helped to identify qualifying R&D activities such as overcoming challenges through the trial and error of utilising different technologies. This included scaling optimisation, deploying the technology, migrating to an alternative application better suited to their aim and product investigation, and much more. By documenting all qualifying activities in line with HMRC’s standards, and the costs of this activity, we helped our client receive every penny they were eligible for, helping them to reinvest this benefit back into the project to grow it bigger.

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