Card Linking

The next generation of card-linked merchant offers is here

May 26, 2023

Better Data Will Invigorate Card-Linked Offer Programs

The problem with traditional CLO

You’ve probably received an offer for a product or service through your digital banking experience that may have felt random and irrelevant to you, like “get 5% back at The Car Wash.”

Such offers are initiated by a card-linked offer (CLO) program, which provides discounts and rebates to cardholders based on their transactions.

For over a decade these programs have relied on basket-level data—the transaction location and the total purchase amount—to apply that discount or rebate. 

Without data on the specific products purchased in that basket, retailers and financial institutions have had a limited understanding of a consumer’s purchasing preferences.

The result? Poorly targeted offers that don’t resonate with customers or broad discounts (10% off everything!) that don’t allow merchants to promote individual products and drive department or brand specific consumer purchase behavior.

CLO programs have been challenged to achieve the results required by sophisticated marketers in today’s hyper-personalized, data-driven world. Until now.

Product-level data ushers in a new era

As a result of growing infrastructure and industry partnerships between data networks, merchants, and financial institutions, CLO program providers now have the opportunity to see exactly what’s inside that basket.

The availability of product-level (or SKU-level) data enables merchants and financial institutions to craft offers that gauge the constantly shifting interests of consumers and subsequently present them with offers that will resonate.

Because traditional merchant-funded offers had to be applied to every item in a transaction, entire merchant categories—like the supermarkets and convenience stores where consumers shop most frequently—were reluctant to participate or opted to offer very low-percentage discounts.

Now, with a more robust dataset and measurement tools, SKU-enhanced CLOs are able to drive traffic to entire store categories or specific products that a customer frequently uses. 

For example:

• Grocery stores can offer exclusive discounts on private label products.

• Convenience stores can exclude fuel purchases from discounts.

• DIY stores can exclude lumber from offers. 

• Pharmacies can offer discounts on health and beauty items.

• Hotels can apply discounts to hotel purchases excluding the stay itself.

A new ecosystem unlocked

This ability to have increased insight into the specific items purchased by consumers will, over the next few years, revolutionize the card-linked offer landscape for all participants.

For merchants, this more targeted approach  delivers dramatically more targeted return on their ad spend, leading to bigger discount offers and access to more ad budgets.  This new level of sophistication will also put the CLO channel on the radar for merchants who previously were reluctant to participate.

For consumers, new, more relevant, and better discount offers will become available when they shop using their enrolled payment card.

For CLO program providers, the availability of more detailed purchase data will allow for the provision of new discounts and hyper-relevant experiences for consumers with a growing appetite for savings on necessities.

For financial institutions, this enhanced offering tied to more of their cardholders’ everyday spend will lead to increased card usage and cardholder satisfaction.

The endeavor to gain access to item-level data and enhance the benefits of all participants is not necessarily new. But, as with most major changes, the required advancements in technology and infrastructure, as well as business relationships that allowed access to this data in ways that protect privacy and confidentiality, are now in place and starting to scale. 

Momentum is building. So, whether you are a merchant or a financial institution, it is important to understand and take advantage of this exciting opportunity now.