How to Energize Shopper Loyalty Strategies

Shopper loyalty is not a traded commodity and needs to be earned through personalized experiences.

That notion was supported by new research from the Food Marketing Institute and Precima, a global
retail strategy and analytics company.

Results of their study showed that supermarkets can use shopper loyalty strategies to compete effectively and deliver differentiated growth.

“Retailers will find success in looking at loyalty in 3D by strategically allocating resources to earn customer loyalty, by enabling daily decisions to be made that consistently satisfy shopper needs, and by delivering a meaningfully differentiated value proposition to shoppers through their loyalty programs,” said Graeme McVie, Chief Business Development Officer at Precima, speaking at an FMI-hosted conference in Miami recently. “Food retailers need to take a more holistic approach to loyalty than simply viewing it as the domain of the loyalty team.”

According to survey results previewed at the conference, shoppers rated loyalty toward their primary grocery store quite high (4 out of 5). However, the reality may be different if you look at shoppers’ behavior: Three out of five shoppers would shop at one store if they could have all their needs satisfied, 19 percent typically shop at only one store each week and only seven percent allocate more than 90 percent of their weekly grocery budget to their primary store.

The survey of more than 3,000 shoppers and dozens of FMI member retailers, recommends that food retailers:

  • Think of loyalty as a comprehensive strategy based on insights gained directly from the shopper.
  • Consider loyalty as the outcome of daily decisions across pricing, promotions, assortment, space, marketing and store operations.
  • Go beyond a two-tier price discount loyalty programs and provide differentiated value to shoppers.

McVie believes that one of the key elements for personalization is to ensure that the mix of offer types is specific to each individual customer based upon their level of current engagement with the retailer. For example, a customer who gives a retailer 90 percent of their spend should naturally receive more thank-you offers, whereas someone who only gives a retailer 40 percent of their spend should receive more cross-sell, upsell and spend-stretch offers.

The incentive levels can also be tailored by individual customer, according to McVie. For example, one customer may require a discount of 35 percent, while another may only require a discount of 15 percent; if the first customer happens to be a valuable customer, the retailer should provide the deep discount. A discount for a “cherry-picker” (a customer who cherry-picks good deals with no regard for brand) is likely not justified, due to their lack of loyalty.

“This is a daunting task given the millions of customers that retailers often serve,” McVie wrote in a chapter The Little Book of Big Data, a book from the Shopper Technology Institute. “That is why it’s important to employ offer optimization technology to ensure each customer receives the right content, offers, products and prices – all delivered through their channel of preference. This approach can also be leveraged in the moment, like the way Amazon pre-calculates all the next-best offers for each customer. So, when an e-commerce customer places an item in their basket or is getting ready to check out, a series of next-best offers can be presented to encourage the customer to consolidate more of their spend with the retailer.”

In his chapter, McVie wrote that a frequent challenge in implementing personalization is cost. While some of the more fundamental approaches to addressing this question involve a re-design of the interaction between manufacturers and retailers, a simpler option is available.
“Retailers and manufacturers agree that there are large numbers of traditional trade promotions that simply don’t deliver an ROI,” he wrote.
“When viewed through the lens of incremental cases or pure volume metrics, it can appear that most trade promotions meet their goals. If retailers and manufacturers are expecting incremental volume, then it is easier to classify trade promotions as being successful. As soon as metrics like incremental gross profits, ROI of trade funds, incremental category sales/profits and percentage of sales from valuable customers versus cherry-pickers are applied, then a different outcome is revealed.”

McVie believes that it is easy to categorize trade promotions using the broader set of ROI-oriented metrics into three groups:

  • Those that are performing
  • Those that could perform better if their promotion mechanics were altered
  • Those that don’t perform.

“In practice, more than 30 percent of promotions should simply not be run as they add no incremental value and have negative ROI,” he wrote. “When metrics like the appeal of promotions to the retailer’s most loyal shoppers are added, this percentage increases dramatically. In addition, numerous studies show that 30 to 70 percent of trade promotions do not deliver a positive ROI. Clearly there is an issue with trade-promotion performance.

“If those under-performing funds were re-deployed to personalized promotions. then the retailer could find a viable funding source to enable a greater push for personalization,” he summed up.