ActiveQuote work with machine learning team at Cardiff University to improve sales processes


ActiveQuote, one of the UK’s leading protection insurance comparison websites and brokers, has been working with Cardiff University to develop machine learning algorithms to improve sales processes. The application of this technology has had an immediate impact and has improved sales opportunities by 30%.


Cardiff University’s School of Computer Science and Informatics has an established and very successful track record in applying machine learning and data science through Knowledge Transfer Partnerships has teamed up with ActiveQuote to develop an algorithmic model called Rubee, which identifies customers who are likely to buy a product rather than those who are just browsing.


The model allocates a score to every enquiry, which informs the order and frequency of the customer contact strategy. This enables ActiveQuote to give customers with the highest intent to purchase the right information, guidance and support quicker and those who are just browsing the space to consider their options.


The system, which has been in place for Private Medical Insurance (PMI) for just over a month and has already increased conversion rates by 30%. This approach will help drive future developments, including assigning enquiries to specific advisor skill sets as well as supporting customers who are most likely to lapse mid-term or decline the policy at renewal to improve lifetime value.


Rob Saunders, CEO of ActiveQuote, says that the company saw the need for this kind of innovation as its data is so important, but it is difficult to predict behaviours. He decided to reach out to Cardiff University and its lead academic in data science and informatics Dr Yuhua Li to work together to develop this innovative machine learning functionality.


Rob explained: “Sophisticated data handling and processing capabilities are fundamental to our business strategy. We need to embed new technical knowledge and capabilities and transform our business model over the short, medium and long-term and this partnership will allow us to do that. What Cardiff University and ActiveQuote’s development team have created will drive future customer contact strategies for new customers and existing customers for improved customer experience, increasing our sales and also improving our profitability.


“This use of algorithms has driven business growth by embedding and exploiting the data we already had in a different efficient and effective way. We are extremely excited about what Rubee will create for us as a business and how it will benefit our clients and customers as we evolve its capability. Innovation is key to keeping ahead of the curve in business, and this is allowing us to do just that.”


Dr Yuhua Li, Senior Lecturer in the School of Computer Science and Informatics, has an established international reputation in specialist topics of machine learning such as feature selection, critical pattern selection, anomaly detection and neural networks.


Dr Li said: “ActiveQuote identified the need to address a highly challenging area. Modelling complex human centric data demands the marriage of a range of advanced topics. Through my work as KTP Supervisor, I was able to suggest and oversee the embedding of a range of unique data set characteristics and human factors challenges that helped ensure continuous knowledge transfer to the Company.”


Roger Whitaker, College Dean of Research and Professor of Collective Intelligence, School of Computer Science and Informatics, said: “The KTP with ActiveQuote not only demonstrates the commercial impact that individual academic excellence can bring to a company but also highlights the role Cardiff University can play in supporting a wider industrial transformation in Wales, through the application of data science and artificial intelligence.”


ActiveQuote is the UK’s leading comparison website and broker of health and protection insurance products, including private medical insuranceincome protectionlife insurance and critical illness cover.


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