Rethinking Loyalty Programs with a Big Data Brain
When customer loyalty programs debuted in the mid 1990s, it changed how grocery stores and other retailers viewed their point of sale (POS) transactions. While traditional loyalty programs still have value, the advent big data analytics is giving retailers an incentive to overhaul those programs, and take advantage of new capabilities to boost profits and strengthen relationships with customers.
IBM’s Swanie Tolentino was involved with installing some of the first loyalty programs nearly 20 years ago. “I remember the early days of enabling loyalty card tracking and pushing out ‘buy-one, get-one’ (BOGO) and various other discounts via POS applications,” the manager of industry and solutions marketing manager for distribution, industrial, and life sciences writes in a recent post on The Big Data Hub blog.
Those programs are still helping retailers to some extent. But they’re not taking advantage of the big breakthroughs that have been made in the area of big data analytics. The loyalty tactics have her thinking that “retailers are leaving money on the table,” Tolentino writes.
A wide new world of opportunity is possible if retailers put the proper analytics to work against the raw data they already possess. Tolentino says big data analytics have the potential to give retailers a real edge to accomplish goals, such as driving higher purchase amounts, tracking items that drive higher likelihood of other purchases, identifying trends of repeat purchases.
There’s also the possibility to utilize data from the social media world, where Americans love to Tweet or post on Facebook about what they like and don’t like. What’s more, mining social media for personal tastes doesn’t even require consumers to purposefully share their purchasing behavior by opting into retailer’s marketing programs, which many do anyway.
Retailers could also use the latest geo-location capabilities to track consumers’ movements in their stores in “pretty much the same way they can track browsing and shopping behavior online,” she writes.
When retailers have a more complete of the consumer–including not only what they tend to buy but where they are right now–it gives retailers the power to make more profitable decisions, and to do so quickly.
“Analyzing data in real-time gives retailers the ability to send personalized communications with competitive offers to the shopper, instantly increasing the likelihood of a purchase conversion,” Tolentino writes.
Big data in loyalty programs is all about increasing precision. A retailer that has a good sense of what products will draw customers in and when may decide not to extend the 5 percent discount to particular customers. This can boost profits for the retailers without antagonizing the consumer.
“By using big data, retailers can gain insight that helps them show the customer that they understand and know them as individuals and can even anticipate what they want,” she concludes. “Loyalty is about a positive two-way relationship after all.”