Anyone who has attended a retail industry conference in the past two years to three years has likely seen a shift in focus. Where once it was all about merchandising, which led to shopper marketing, it's now all about mobile and big data. Many retailers are struggling with both of these ideas; they know they should be taking action, but exactly what action is unclear.
While food stores have to worry less about the showrooming phenomenon than an office supply or consumer electronics store does, the fact remains that mobile use in-store is common and continuing to grow. Shoppers all want more information about the products they buy, from price to peer reviews to alternatives. For retail operators to be effective, regardless of what channel they operate within, they need to have that same level of insight about their shoppers.
The interesting thing about big data is that the concept has been around for a couple of decades, ever since the introduction of the first shopper loyalty programs in the late 1980s. Loyalty programs are a misnomer for what's essentially a data-gathering device, and many retailers have been building massive data warehouses for years using shopper behavior gathered through card usage. But very few have done anything meaningful with the data collected. Most shoppers have key tags for multiple stores, which is a sign of anything but loyalty.
The value proposition for a loyalty program goes like this: use some sort of data-gathering device (i.e., loyalty card) that identifies shoppers uniquely; offer incentives to use the card (i.e., price incentives); gather relevant information on what, when, where, etc.; mine the data for insights; and act on the insights to drive behavior. The industry got the first part right but never effectively got past the data-gathering stage. Few shoppers have ever received any incentive from a loyalty program. Most just belong to loyalty programs to get the "card price."