Rethinking Loyalty Programs through Big Data
Retailers, it’s time to rethink loyalty programs; big data brings new ideas to light
I have worked for years on retail Point-of-Sale (POS) projects since the mid-’90s. 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. These programs are still valid today, especially in brick-and-mortar establishments. With a very straightforward approach of accumulating points, membership status and enticing customers to spend more via discounts, there continues to be a measure of success around getting customers to visit physical and/or digital stores and consistently make purchases over time. Still, these loyalty tactics have me thinking that retailers are leaving money on the table–not that I'm complaining as a shopper. But, the world has changed dramatically. The ability to get new insight from all possible sources of data is forcing retailers to rethink their loyalty programs.
In the simplest terms, with big data analytics a retailer now has the ability to interpret the relationships between data points, such as items sold within a market basket that drives higher purchase amounts, item(s) that drive higher likelihood of other purchases, trends of purchases made in-store or online over a period of time, patterns of repeat purchases, and other new insights from the deep analysis using the raw data available.
Today, retailers can associate who we are in the social media world; what we tweeted, what we like and dislike based on our Facebook and other online forum conversations. It’s kind of creepy but very real, as we as a society openly communicate about just about everything. Besides, many of us are making our purchasing behavior visible by “opting in” to retailer’s marketing programs. With the latest geo-fencing location technologies, retailers can track a shopper’s movements and shopping behavior in the store or near the store, pretty much the same way they can track browsing and shopping behavior online.
In big data terms, new data types such as, social media, video and sensor data provide more insight about the customer and their shopping behavior. 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.
Big data changes how we run our loyalty programs. Maybe that 5% discount off all purchases, the one that gets you to come in and use your card so they can track your purchases, is leaving money on the table. I say this because when a retailer knows that a customer will buy at a premium on certain items, for example, a favorite designer’s line of clothing at the start of the season or the latest hot gadget right at launch, it opens up new possibilities of how to entice customers and drive to improved sales and margins. Big data delivers more precision to loyalty marketing programs than traditional programs, while keeping margins favorable to the retailer. 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. Loyalty is about a positive two-way relationship after all.
As a shopper yourself or if you work in the retail industry, I invite you to consider and comment. What does customer loyalty mean to you in this time when everything’s gone digital? Is it time to rethink your loyalty program?
Swanie Tolentino, Big Data Retail Industry Solutions Executive at IBM, will be speaking at the Omni Channel Retailing Conference, June 4-5, 2013, in Hong Kong. Her topic is The smarter retailer: What can business intelligence and analytics reveal about tactics to maximize customer spend in-store and online?
See these other resources about big data for retailers
- Pushing the Envelope for Retailers: PureData System for Analytics
- Capitalizing on the power of big data for retail
- Big Data in the Retail Industry