How to Monetize Your Loyalty Program


Share on LinkedIn

It’s hard to believe that loyalty programs once weren’t an industry standard. Loyalty programs, in their current form, didn’t truly emerge until the 1980s. Even still, it took another decade for the card-based loyalty programs that most consumers currently utilize to gain popularity. Today, the trend is in full force: from retailers to restaurants to hotels, there isn’t a customer-centric industry that hasn’t embraced the concept. But these programs aren’t cheap and the question of whether they pay back is a widely debated topic. What can’t be debated is that loyalty programs provide the ability to track your customers over time, understand their behavior, and establish a one-to-one communication channel with each individual customer. This targeted communication channel is where the secret to monetizing your loyalty program lies.

The purpose of a loyalty program can be condensed into a simple sentence: Loyalty programs help you figure out who your best customers are and provide them with right incentives to spend more money with you. It sounds straightforward, but in practice, most companies struggle to achieve this goal.

The challenges associated with this goal are clear when we focus on three key phrases in the sentence: “best customers,” “right incentives,” and “spend more money.”

Let’s dive into each of these aspects:

Best customer: Many companies currently have a standard definition for their “best” customers. It might be those who have historically spent the most money with the brand. A simple table with customer IDs and their past spend should clearly identify who the best customers are. Unfortunately, that’s not the whole story. Your best customers are those who will spend the most money with the brand going forward. Their spending patterns may also be facilitated by certain incentives and rewards (another important element which we’ll discuss later). While historical data is a good starting point, it won’t provide an accurate view into a company’s “best” customers. It’s future behavior, not past, that matters.

Right incentives: As we just mentioned, incentives are a key piece of the puzzle, and an extremely complex piece at that. Does a company need to offer a substantial discount to bring shoppers into the store, or will an email announcing the new spring line entice shoppers? The right tactic varies, by industry and by customer, over time. Understanding the interplay of these elements and having the capabilities to target your customers with the right offer at the optimal time is fundamental to efficiently monetizing your loyalty program.

Spend more money: This is the most important, and yet most nuanced, element of a loyalty program’s overarching goal. Theoretically, any new transaction improves the topline, correct? As long as you customers are redeeming your promotions, company sales are growing. Unfortunately, that’s not entirely true. “More money” really means incremental money, or dollars that would otherwise have not been spent. If the promotion or coupon is applied by the customer on a transaction that would have happened anyways, they are spending less money, not more. Therefore, a customer is spending more money only if the promotion drives incremental visits or increases his/her basket size.

Combining these three points, we can conclude that a company which wants to efficiently monetize its loyalty program must figure out what promotions drive the highest incremental spend for each customer, and then target each customer with specific promotions.

Again, this can’t be done by running regression models or learning algorithms on historical data and spend behavior. The only way this can be done with confidence is to employ the scientific method to test and analyze promotions and then build targeting models on incremental test vs. control behavior.

Execute this methodology correctly and your loyalty program will be worth the cost and a whole lot more.

Varun Kishore
Applied Predictive Technolgoies
Varun Kishore is a Principal Consultant at Applied Predictive Technologies (APT). Varun has led engagements with clients across financial services, casino, retail and restaurant verticals. He has advised clients on diverse strategic initiatives such as promotional targeting, digital marketing, capex investments and pricing.Varun holds an M.Sc in Management Science & Engineering from Stanford University and a B.Tech from Indian Institute of Technology, Madras.


Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here