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If your business is like most online retailers, you’ve lost money because customers reused coupons when they weren’t supposed to.

The problem goes further than generating less revenue by selling more products at a discount. On one extreme, you may find yourself paying to send duplicate mailings to the same households as you scale, driving up your shipping costs without realizing any ROI. On the other hand, frustrated customers may start complaining about spam to your service department.

How does this happen?

It all comes down to a poorly designed and executed data strategy. If you aren’t careful about how you collect and use data from the outset, you may find yourself on the wrong end of this equation.

We’re going to set you straight.

How coupons go from driving sales to creating losses

You’ve certainly experienced it as a consumer. Businesses try to entice you with coupons in exchange for your information so that they can keep marketing to you.

It’s hard to go a day without being asked if you’d like to sign up for a credit card or subscribe to a newsletter in exchange for a discount on your first purchase. All you need to do is provide your email and some other information.

Savvy couponers say yes to this proposition over and over again by creating several email addresses. Sometimes they even use the same physical address. The result is that they get to double dip on the savings at the business’s expense.

Now, there’s no denying that coupons can be effective at driving sales and generating ROI. Over 90% of consumers use coupons, with 45% of consumers report using them often, if not always. And, despite the prevalence of digital technology, 93% of consumers still prefer paper coupons, though 75% use their paperless counterparts as well.

Why not use these golden tickets? After all, a dollar saved is a dollar earned. Especially when we consider the massive inflation that we’ve all been feeling recently, coupons can help us offset the cost of goods that we enjoy on a regular basis.

If you’re like most e-commerce retailers, you’ve followed this logic and offered coupon codes online and/or mailed postcard coupons directly to potential customers. Coupons are a great tool for boosting sales and increasing your brand awareness.

However, this strategy can backfire if we aren’t careful.

Identifying and stopping e-commerce coupon abusers

One of our e-commerce clients had this exact problem. Their Shopify was set up to create a new unique customer each time someone placed an order with a new email address. With that new customer status came an up to “40% off your first purchase” coupon.

The problem, though, was that most of those customers weren’t new. From the customer’s perspective, why would they pass up on an opportunity to save money if all they had to do was click a few buttons and create a new email address?

We had two options to solve their problem. First, we could have told them to live with it and use expensive database queries in an attempt to identify duplicated users on the fly. This would be a cumbersome manual solution that would regularly require writing complex code. These queries would also require a lot of computing power, and, since cloud platforms charge based on usage, this would become quite costly over time.

The other option required a bit more work up front, but it solved the problem with automation, and it keeps costs low in the long run. It involved creating a matching algorithm that groups Shopify users together to create a new unique identifier that can spot the same person trying to sign up for a new account with a different email address.

Here’s how it worked.

Savvy technology comes out ahead

We started by evaluating each order and using score-based matching logic to either create a new user or assign orders and attributes to an existing user. On the back end, this meant implementing new schema and tables to adapt the existing data structure to the new user’s data model.

Our client provided a list of their most important identifiers, and we assigned a score value to each of the data fields provided by Shopify’s order information. Our code enables our client to recognize when a customer uses the same email address, phone number, address, name, etc.

The algorithm will automatically continue to check for new upcoming orders on a predefined schedule. From there, we also use that data to create reports and other visualizations.

The end result is that our client can now identify customers based on households, allowing them to correctly attribute the cost of coupon campaigns and reduce the amount of money that they lose to coupon reuse. This technology also improved their user behavior analysis, so they can better identify blacklisted users who try to game the system by buying products with a new account.

Implementing this data-driven system also created a ripple effect. For instance, our client can make smarter decisions by using it to analyze the variables that impact their distribution processes. They’ve also gained valuable insights into their customer purchasing patterns.

An e-commerce company gets results by stopping repeat coupons cutters

The results speak for themselves. Our client found that many of their customers have extra Shopify accounts that allow them to repeatedly use the same coupons to make purchases. Our matching algorithm reduced their customer count from around 140,000 to 90,000 users.

Put another way, we detected and eliminated 50,000 fake accounts that were costing our client over $100,000 on physical retargeting campaigns. They instantly saved on mailing costs, and, over the long term, they will increase their revenue by selling fewer products at a discounted rate.

Cracking down on the problem of e-commerce coupon reuse creates tangible outcomes. But it’s only one of the ways that a comprehensive data strategy helps e-commerce retailers grow and scale.

Get in touch with us today to learn more about how we use technology to tackle the problems that you face every day.