If retailers really want to use their loyalty programs to drive up sales in 2017 and beyond, then they better give their customers the wheel.
Asking for directions and understanding how to use the data map were among five crucial requirements that retail and loyalty experts provided when asked to identify the least-known or -understood aspects of retail reward programs today. From early customer input to assortment optimization, these observations might sound head-scratchingly obvious.
- Sales don’t always indicate bestsellers
Advanced analytics and loyalty data can unearth hidden value in items that may be slow sellers, if retailers examine different sets of metrics, said Graeme McVie, vice president of business development at Precima, a retail analytics firm.
“Retailers often rank and yank when evaluating their assortment; that is to say they rank all items in their category by sales and de-list the bottom performers,” McVie said. He suggests retailers use the “true item value” and “customer item importance” metrics:
True item value: This is calculated by taking an item’s total sales (ABC laundry detergent), subtracting the sales that would transfer to a similar item if the original item were eliminated (XYZ laundry detergent), and then adding in the sales of complementary items that were purchased with the original item (ABC fabric softener).
Customer item importance: This gauges the value of an item, even a slow seller, to very loyal customers. If the item is removed and the retailer offers no alternative options, the customer is likely to take her entire basket to another retailer. Walmart learned this the hard way with its inventory optimization a few years ago.
- There’s still a lot of bloom on the boom
Retailers are right to target millennials and other younger generations, particularly through mobile communications. However, if they fail to extend the same opportunities to baby boomers, they risk missing significant opportunities, said Phil Seward, regional director of the Americas at ICLP, a global loyalty marketing agency for retailers and part of the Collinson Group.
More than nine in 10 boomers (93%) feel overlooked and inadequately rewarded, according to ICLP research. Consequently, they are less loyal to their favorite brands, Seward said.
Losing this loyalty, to a retailer, means losing a healthy revenue stream. Data shows that 84% of boomers use smartphones throughout the shopping journey and 79% are willing to indulge in purchases for their families. “In order to build emotional connections with this highly influential and often more affluent generation, retailers should better tailor online and mobile marketing initiatives, leveraging data-driven insights to turn them into repeat, loyal customers.”
- You should let customers drive
When it comes to developing or revamping a loyalty program, retailers might overlook their most valuable information resource — their customers.
We’re not talking about the insights gathered through loyalty program data, which would help a merchant determine ongoing assortment, promotions, communications and customer engagement. Rather, we’re talking about the elements that shape the loyalty program’s model. Retailers rarely ask their customers what motivates their loyalty because they assume they already know, said Chip Bell, author of the book “Kaleidoscope: Delivering Innovative Service That Sparkles,” and senior partner of the Chip Bell Group, a customer experience consultancy.
“Customers are constantly changing — today’s fad is tomorrow’s antique,” Bell said. “Start a loyalty program by asking customers. Look at the theme of frequent customer complaints as a path to the opposite end of the spectrum. It can reveal what matters most!”
- But let the insights intelligently map the journey
Once the foundation of a good loyalty program is poured, it’s time to use the data. This leads us to the most vexing question in loyalty marketing: figuring out how to use the data.
There’s no shortage of it — retailers have a wealth of data on their shoppers. The issue is they often don’t know how to interpret it. This makes implementing a targeted rewards program difficult, said Debjyoti Paul, assistant vice president of digital business at Mindtree, an IT services consultancy based in India and New Jersey.
“The first step is to clean up the loyalty data to uniquely identify each shopper and form a basic profile that is trustworthy,” Paul said. Next, enrich those profiles through machine-learning techniques such as artificial neural networks and support vector machines, the former of which adapts through trial and error and the latter of which can be trained to solve optimization problems. “This will ensure [retailers] are able to frame enduring loyalty programs that effectively develop customer stickiness and reward loyalty over time,” Paul said.
- Take a breath on breadth
Product assortment is often derived from loyalty insights, but striking that balance — too much? Too little? — is arduous. Total store optimization helps retailers assess the necessary breadth and depth of various categories, said McVie.
“Consider the yogurt category. How many flavors of yogurt are required versus how many sizes versus how many brands?” he said. “Now contrast this with the spices category, where breadth is required but not depth — lots of different spices but not many types of oregano.” This strategy enables retailers to align the depth and breadth of each category with the needs of shoppers to ensure the correct amount of shelf space is allocated to each category.
These five essentials may not be a total secret, but they do hold the keys to loyalty success. If a retailer wants its loyalty program to be among those 42% in which Americans maintain activity, it should consider acting on them now.