Demographic and location data increases new house prices up to 10% for housebuilder

The Challenge

This FTSE100 residential developer relied on its local sales teams to set the pricing of newly built homes – almost always based upon a ‘cost plus’ method. There was a view this was designed to ensure sales were made as quickly as possible, rather than at an optimum price. They knew they could be using data in a more clever way, but weren’t sure how. 

The Solution

Barcanet initially created a database of relevant external information – previous house price sales, and current for-sale prices were obvious targets. However we realised really valuable information wasn’t being considered… Supermarket and school locations, transport links, and other social and proximity data, enabled the commercial team to identify trends and traits that had been previously invisible. 

The Results

The initial findings supported the view that new home prices were under-valued – by between 2-10% across the locations reviewed. The initial insights were extremely useful for the company to ensure current and future housing stock prices were optimised.

But these insights gave even more back to our customer. Knowing eventual house prices meant they were able to predict the value of new land, before they had even built any houses on it. This meant they could buy new land at the right price, for optimum sales prices later down the line.