Can every single household receive promotional coupons that closely match their preferences? That was the question that Belgian retailer Colruyt asked itself when developing its new marketing strategy.

SAS, the leader in business analytics software and services, helped turn this vision into reality, thanks to predictive analytics in SAS Enterprise Miner and SAS Marketing Optimisation that forecast which promotional items are most likely to result in purchases by each individual household.
Initial results show an increase in the use of coupons, as well as higher average spending by each household. Households get a vast amount of information in their mailbox from a variety of retailers.
This makes it difficult to reach customers with the right message. Colruyt searched for a way to ensure that customers would look at their flyer every two weeks. They concluded that the best way to achieve this would be for each household to only receive promotional coupons for products they are interested in.
"If a customer goes through a flyer only to find that there are no products of interest, they will feel that we have wasted their time," says Bart Van Roost, head of Colruyt's analytics department.
"And as a result, they may not bother opening our promotional envelopes in the future."
But how can the company make sure that each household gets the most appropriate coupons? Colruyt worked on an idea that goes beyond segmentation, as Van Roost explains.
"What we had in mind was nothing less than selective marketing. In other words, marketing on an individual basis."
With 1.6-million "extra-card" holders and 11,000 products on offer, this involves managing and exploiting a huge amount of data.
"We required a powerful application with advanced analytical capabilities. After conducting two proof-of-concept trials, we were convinced that SAS has the robustness to handle this vast amount of information."
SAS can calculate purchasing probabilities based on past customer behaviour, as well as on household and demographic information stored in the Colruyt database. Based on this intelligence, it selects 30 promotional coupons that each household is likely to use. These coupons are chosen from among the 400 products that are on offer during each promotional period.
"SAS not only knows how to cope with extremely large amounts of data, it can also make an enormous number of calculations in a relatively short run time," says Karel De Wilde, team leader for analytics at Colruyt. "SAS exploits data intelligently."
"Another strength of SAS is that it takes marketing restrictions and rules into account," adds Van Roost.
For example, each household will only receive up to eight promotions within the same product category. This is to avoid any household receiving only promotional coupons for drinks, cosmetics or any other particular product category.