B&Q is to introduce more personalised marketing to customers in the second half of this year to better target specific segments such as older shoppers and trade customers.
The DIY retailer has been analysing customer data using things like its Trade Discount Card, to work out how different customer segments behave, and to identify the type of DIY projects they are likely to embark on.
It has been able to analyse this data and create predictive models of customer behaviour since investing in a data mining tool from SPSS last year.
B&Q business project manager David Collar explained that the system is being used to analyse data on both store and web sales, and it hopes to begin analysing customers’ web behaviour too.
At present most of its marketing activity is mass market, such as TV and newspaper advertising, but B&Q will use the insight gathered to develop one-to-one marketing programmes and potentially to create dynamically generated web content.
The insight gathered could also be used to assist decisions on range reviews.
In addition, the system has been used by B&Q’s profit protection team, mainly to reduce internal fraud. Collar said that the system had paid for itself within 8 months through this alone.