Insurance comparison website Comparethemarket.com is using open source NoSQL database MongoDB to improve the customer experience of its home insurance offering.
Comparethemarket.com checks tens of millions of prices for customers on a daily basis. The system collects customer details and then securely sends them to a number of different insurers. Once the insurers' systems reply, Comparethemarket.com can aggregate and display prices for consumers.
The speed and efficiency that data is sent and retrieved is crucial to the Comparethemarket.com’s business. One hour’s downtime would have significant financial impact, according to the company.
“Ultimately we want every single customer to have an exceptional experience,” said Matthew Collinge, solutions architect at Comparethemarket.com.
“Our business model has changed significantly, but trying to make changes on the old system meant we spent our time dealing with complexity rather than adding any value.”
The company was previously using an nTier application backed by a single monolithic relational database management system that was limiting the scalability of and ability to quickly change its comparison experience. When it came to looking for a new database, the priorities were stability, speed to market and scalability.
Comparethemarket.com selected an event-driven architecture backed by MongoDB, which Collinge said delivers an enhanced customer experience, improved horizontal scalability and a vast improvement in the company's time to deliver business value and customer insight.
The new database is currently being used for home insurance, which accounts for millions of price checks a day, but will eventually be rolled out across the entire site – including motor, life, travel and pet insurance as well as utilities and money products such as credit cards and loans.
“This project shows how the speed and flexibility of a database can have a strong impact on business outcomes,” said Joe Morrissey, VP EMEA of 10gen, the MongoDB company.
“The price comparison market is fiercely competitive and solution architects have a tough job to process vast volumes of data quickly, and differentiate services. Implementing a simple-to-use, flexible and scalable data schema is greatly improving the service that’s on offer.”
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