PG: Discuss the role a personalized loyalty program plays in the overall omnichannel journey — before, during, and after purchase.
MS: Grocery customers make way more purchases in comparison to customers in other industries. This means that grocers have access to a massive amount of data that can be used to understand purchasing behaviors and map out the entire customer lifecycle. Through this information, retailers can send more personalized messaging, ads, and even discounts to their customers, which can help inform their purchasing behavior before the buying process even begins.
Retailers can even use non-member data to see which product groups are best to discount in their loyalty program, which can encourage customers to enroll in and use the program.
While they’re in the store, customers can use their app/ portal to apply coupons and discounts, keep track of their shopping list, and more. After the purchase is completed, customers receive bonus incentives based on their purchase behavior along with personalized messaging and gamification elements like tiers, contests, and referrals to keep them invested in the program.
PG: Creating an ecommerce program that includes a robust loyalty program is one thing; measuring its performance is another. Are there ways retailers can see their return on investment? If so, how can they calculate and interpret the loyalty program ROI?
MS: Increasing the amount of data collection is the best way to measure and improve a program’s performance. As I said earlier, grocery customers are interacting so frequently that retailers have a handful of ways to gauge their investment. Comparing coupon usage by non-members to that of loyalty members is one way. Looking at the recency, frequency, and monetary spend of members versus non-members is another. And of course, retailers can always analyze customer churn scores throughout the lifecycle of their program interactions to calculate and interpret ROI.
Interpreting this data should come from campaign and promotions reporting. This can be used to adjust and improve future iterations — whether that’s adjusting cross and upselling products or introducing new elements like gamification/challenges into the mix.