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Zopa is the worlds first and UK's leading peer-to-peer lending service. With over 45,000 active savers and 71,000 borrowers their mission is to enable people to bypass banks and their high charges - and reward savers and borrowers who are good with their money - by providing lower rate loans and higher interest on savings. 

Having experienced rapid growth recently, Zopa have been looking at putting a focus on being a more data-driven organisation - they wanted to better understand the behaviour of their customers. Their vision was to become more responsive to their clients' requirements and preferences when looking to lend or borrow.

Zopa was already using Google Analytics and other insights tools extensively. They called in ºÚÁÏÃÅ to see if there was even more business insight they could glean through connecting online and offline data sets together - they wanted to deeply understand the true nature of their end to end customer journey. 

Using Clojure, R and Python the team could get to the core of the data fast - allowing them to validate or reject hunches and suspicions Zopa had previously expressed. 

The outcome of the data research allowed Zopa to answer some key questions around how their customers were interacting with competitors, what the prominent lending windows throughout the week were and how they could offer their customers the best rates. 

The results? The new data sets revealed the answers to these to all of these questions and more - prompting changes to their business which will now drive product and service development for their customers. Helping even more Brits secure lower rates on loans, and higher rates on their savings.