Don’t Launch that Loyalty Program Until You Have the Right Customer Intelligence

When every retailer basically uses the same loyalty program structure, it’s not a value-add for your customers—it’s business as usual. This is how you overcome business as usual.

Let’s talk about loyalty programs. It’s been said that the first loyalty-ish program started with “premium marketing” in the 18th century. Basically, you’d make a purchase and the retailer would give you a copper token that could be redeemed on future purchases. A very basic version of a coupon.

In 1891, stamps replaced coins. Get enough Green Shield stamps—which are little rewards for purchases—and you can redeem them all for a catalog purchase. Not totally unlike your basic coffee shop punch card.

Then in 1981, American Airlines changed everything with Frequent Flyer Miles, a bigger, fancier, more sophisticated version of all those earlier loyalty programs. Deregulation in the airline industry had made for a pricing race to the bottom, and rather than give in to the downward spiral, American introduced a program that incentivized flying with them despite the times when a competitor might have the lowest price or most convenient route.

The real loyalty program innovation came about in 1994 when Tesco, then second in the UK retail market, teamed up with Dunnhumby consultants to create a new loyalty card, one that gathered data on the individual-user level. This user-purchase data was the mythical Holy Grail of retail. The Tesco Clubcard enabled Tesco to track customer purchases over time, see who was buying what and when, and gain visibility into buying patterns that no one had before.

According to The Independent:

A trial scheme at three Tesco stores...ended so successfully that the then chairman, Lord MacLaurin of Knebworth, told the men in charge of the trial: "What scares me about this, is that you know more about my customers in three months than I know in 30 years."

The next big step in the evolution of loyalty programs wasn’t in retail but in gambling, at Harrah’s Casino in 1997 with their Total Rewards program. Harrah’s not only gathered customer intelligence to learn how to better run their business, but how to market to, serve, and delight their most loyal and valuable customers. This could take the form of a dinner voucher, free hotel stay, or plane tickets to and full accommodations at one of their casinos.  

As AdAge wrote of the program:

[Total Rewards] is heralded by many as the gold standard of customer-relationship programs. And with the program generating $6.4 billion yearly, or 80% of its gaming revenue, Harrah's is confident where it ranks among competitors as well.

Sounds pretty sweet, right? So why does the title of this post start with “Don’t Launch Your Loyalty Program…?” Lots of good reasons!

Don’t Launch that Loyalty Program…

It's helpful when evaluating your options with regard to creating or revamping your loyalty program to think about them through the lens of two quite different objectives.

The first objective is the obvious one: increase loyalty through a rewards system to create switching costs (i.e., how painful/costly is it to switch to a competitor?), providing a financial or experiential incentive for them to be loyal to your product.

The other objective is to track longitudinal behavior on the individual-user level by incentivizing customers to volunteer their personal information to help you make better business decisions and deliver more personalized experiences throughout all of your marketing.

Rewards programs can accomplish both of these things, but the objectives should not be conflated. Let’s take a step back and think about what your primary objective would be.

Is your primary goal to lock in customers through a traditional “stamp collecting” model that builds in switching costs to incentivize loyalty (or at least behavior resembling loyalty)? Or is your primary goal to better understand your customers and how they interact with your brand over time?

The average consumer is registered for 14 loyalty programs but only has the capacity to be active in seven. Which kind of makes it sound like the “lock-in” model doesn’t work that well, right? We think so too, or at least we don’t think it’s the optimal model for retail.

The problem with the old model—as far as it applies to retail, specifically—is that it merely discourages “bad behavior” (switching, churn) but it doesn’t have the capacity to encourage high-value behaviors (frequent full-price shopping, voluntary brand ambassadorship, etc.).

When you consider that the vast majority of loyalty programs are little more than sophisticated coffee shop punch cards—a transactional, accrual model that offers discounts or store credits—you might notice how little differentiation exists in the loyalty space.

In the e-com-saturated, Amazon-dominated retail ocean that is drowning brands left and right, differentiation is oxygen. Differentiation of product offerings, of branding, of marketing, and of customer experience are the primary reason customers come to you. So why not take the time to understand your customers and then approach your retention efforts (loyalty program or loyalty-program alternative) with differentiation in mind?    

Well, of course, you want to. Who wouldn’t? The question is how to get there.

...Until You Have the Right Customer Intelligence

The loyalty-driving heuristic we use with our customers is first KNOW, then GROW.

Know means that you gather and analyze individual-user level data. Grow is when you use that knowledge to inform targeted marketing actions to drive loyalty.

Let’s put this out there up front: Loyalty programs are the most widely used mechanism for capturing what would otherwise be anonymous in-store data for retailers and service providers.

Loyalty programs aren't the only way that retailers identify users. For example, some retailers try to do email collection at the point of checkout, which doesn’t always have the best hit rate. Others use more sophisticated, data-driven match-backs, so they can take, for instance, the last four digits of a credit card number and match them across a master database so they can see that Jayne Dough who bought in store and volunteered no personal info is the same person who filled out all the form-fills when purchasing online a month ago.  

Regardless of how you do it, data-gathering is an important step, but only just the first step in the big project of personalizing and differentiating your loyalty-driving triggers.

As mentioned earlier, the problem with the standard-issue loyalty program is that it doesn’t address the unique value that your brand has for your unique mix of customers. The Know step is about learning what incentives, messaging, and affinities drive loyalty and high-value behaviors in your audience. It’s at this stage that you test and learn the best strategies for preventing churn, reducing one-time-buyer-itis, and increasing customer lifetime value.

Without this foundational knowledge, you have a non-zero chance of pouring a lot of resources into a suboptimal program. With the right intelligence up front, you can spend less and get more.

The Grow stage overlaps with The Know stage, and it can be quite straightforward if you’ve got the right data-analysis models and learning structures in place.

From this point, you can choose to launch a formal loyalty program or not. In our next post on this topic, we’ll talk to two Custora customers, one who’s opted to use a formal loyalty program and another who has decided their business doesn’t require it.

In the meantime, if you’d like to learn more about using data to deliver a better customer experience and ultimately drive greater loyalty, check out our book, It’s Not You, It’s My Data.

Like this? You might also enjoy these.

How Supergoop Topped Custora’s Retail Benchmarks, part 1

This past May, Custora announced a new benchmarking feature within our...
Read

Your Revenue Forecasting Ignores the Source of Your Revenue

If you’re like most organizations, your finance department focuses on overall...
Read

4 Steps to Solving the One-Time Buyer Problem, Part III

In parts one and two of this series, we laid the groundwork on a methodology to...
Read