Dynamic Yield Uses Mastercard Data to Power Personalized Experiences for Merchants and Issuers  

Digital commerce has long relied on personalization, so everyone from Amazon to Zillow knows what to show you from a universe of possible choices. That’s all moving up a notch with the Weds. (March 15) launch of the Element solution from Dynamic Yield.

Marrying Dynamic Yield’s form of personalization — what it calls “hyper-personalization” — to Mastercard’s vast aggregated and anonymized data sets, Element is meeting ever-higher demands for personalization, not just in eCommerce but in banking and other verticals.

“[The vast majority] of consumers say that they expect to see personalization in the day-to-day apps that they use,” Dynamic Yield CEO Ori Bauer told PYMNTS’ Karen Webster. “At this point, 98% of the companies that we talk to say that they view personalization as an important capability that they need to have.”

Described as “an exclusive suite of Mastercard applications and extensions integrated into Dynamic Yield’s Experience OS” in the announcement, Element unites Mastercard data services with Experience OS so users can create custom experiences based on user demand.

Purchased by McDonald’s in 2019 as the heart of the fast-food chain’s McD Labs personalization division, Mastercard then acquired Dynamic Yield in early 2022 to operationalize more of its invaluable consumer spending data for a host of use cases. Dynamic Yield is an agnostic solution and available to integrate with any third party, says Bauer.

Importantly, while Bauer said most personalization today is based on first-party data and consumer behavior within the four virtual walls of an app’s ecosystem, Element lets users import their own CRM data and offline sales data, delivering a more comprehensive view when crafting and delivering offers.

This quest for deep personalization is table stakes in the digitally connected economy, and the introduction of Element is expected to help more companies benefit from smart customization.

Prediction and Propensity

Relevance plays a central role in the Element offering, serving the right products and offers at the ideal moment to increase sales and customer satisfaction in one go.

“Our models are predictive in nature. We can notice the changes that happen in behavior, and update our models to reflect those changes,” Bauer said.

Propensity modeling has applications from travel to mobile banking, allowing account holders to accurately predict the likelihood of consumer purchase and then serve timely and relevant offers that can dramatically impact the outcome of that opportunity. That means the right offer gets served to the right customer at the right time when it’s most relevant.

Bauer said the solution is as useful to an issuer as it is to an eCommerce site or service provider. In the retail space, Element uses MasterCard’s aggregated and anonymized information on emerging trends in consumer behavior so retailers can quickly adapt their offers to unexpected surges in demand.

But Element isn’t just built to serve up relevant offers. The solution also packs Dynamic Yield’s established capabilities in customizing and personalizing web experience for its own sake.

“If we’re talking about a website, for example, in the e-commerce or the retail space, using Dynamic Yield you can change the digital experience to fit best to the specific consumer that is engaging with it,” he said. “This could be all the way from how the homepage looks, what banner you show, what menu items you show, what is the order of menu items, because people tend to look at the first menu items, and then lose their patience.”

The Store of One

Personalization is the antidote to users feeling a site doesn’t cater to their specific tastes and preferences. However, that can’t come at the price of consumers feeling a company knows them so well that it’s questionable. Bauer said Mastercard places a premium on privacy, adhering to a policy of “responsible personalization” and opt-ins so as not to cross the “creepy” line.

With that in mind, he likened it to entering a store designed just for the individual — but at scale — with Dynamic Yield providing services like social proof that shows shoppers how many people are browsing an item and how many have purchased it, creating a sense of urgency that leads to conversion.

The solution also integrates business intelligence from Mastercard SpendingPulse, enabling subscribers to launch SpendingPulse through Experience OS and use those insights to modify offers, switch up packaging, and operate other data levers to create more relevance for users.

Bauer said, “What Dynamic Yield excels at, and Element, of course, strengthens that, is the ability to very quickly understand, based on their behavior, what are they interested in? What is their affinity, as we call it? So very quickly, for example, we could understand that this particular person is a student potentially shopping for a student card.”

That engages the solution, at which point Element activates predictive models that zero in on what a user is likely to be interested in based on anonymized data of millions of transactions.

Bauer said, “another example could be if an issuer is trying to promote a certain ride-share service, but that consumer is using a different service. This could be an opportunity to pop up an offer to say, hey, you could get some savings if you use this service versus the other service.”

Then there’s the notion of serendipity — encountering offers that may be outside a consumer’s predicted choices — and the significance of retaining that sense even as data winnows down the offers someone is bound to respond to.

Bauer said, “some of our advanced models take this into account” and allow for a blend of offers, keeping it predictive without being too predictable for the consumer.