We were approached by a major retailer of household goods and apparel to help increase the value to the business of their store card loyalty program, which at the time had in excess of 3 million members.
Our client was seeking to transform the database into a true asset, by using it to inform targeted rewards strategies and communications activities that would ultimately increase share of wallet and improve loyalty.
Our first objective was to develop a segmentation of database members that captured the great diversity in consumer needs, attitudes and behaviours in relation to retail shopping, but that at the same time could be related to readily observable or known traits as held on the database – to enable tagging. Nature inherited a pre-existing primary research data set and using this identified a small number of key segments, each of which were unique in their needs and drivers in relation to shopping. As such, the segments provided a lens through which different membership rewards strategies could be developed and communicated.
Whilst useful in itself as a strategy development tool, the segmentation was not the entire solution, as it did not provide our client with a method of targeting members with these strategies. Hence, the second stage of the project was to develop a behavioural model for the segmentation, incorporating rich member demographic, geographic and transactional-level data. Using this data, we were able to allocate all 3 million+ database members into a needs-based segment.
The client is now using the segmentation to assist in a review of their membership rewards program, specifically to develop segment-based offers. At the completion of this step, members will be targeted with these offers at a segment level, using the customer database segmentation model developed as part of the project.