Mastercard tosses a lifeline to data-challenged merchants

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Merchants that can't put their customer data to use risk irrelevance in a digital age, giving Mastercard an opportunity to put an acquired analytics unit to work as an acquisition lure.

Around the same time Target, Walmart and Best Buy were trying to turn data into revenue via the Merchant Customer Exchange, Mastercard acquired Applied Predictive Technologies. It was a move with an eye on the future, a chance for Mastercard to integrate APT's Test & Learn cloud-based data analytics platform to inform any type of decision a business client might make.

Since the acquisition, Mastercard has built out a service that helps merchants establish data mining and testing for data-driven decisions such as product price changes, new promotions, technology or capital investments, or changing interactions with consumers.
"We just say they should try that idea first, which is an easy thing to say but a hard thing to do, and learn as much as possible from that test," said Anthony Bruce, president of applied analytics at Mastercard.

At first glance, the concept of trying something before fully committing to it seems like something right out of Business 101 classes. But in the digital age, where data comes from any number of channels and delivers potentially different messages to the merchant, it becomes imperative to take a deep dive into that data and connect every dot.

What may have been considered a "no-brainer" idea years ago to reduce the cost of a product to generate sales and lure in new customers, needs far more detailed attention in the digital age, Bruce said.

As an example, a nationwide sandwich shop chain might consider reducing the price of its most popular sandwich by $2 to see if it could increase foot traffic and thus sales of other items in the restaurant, Bruce said.

With applied analytics and a test run in only a few locations, the data could tell that merchant the promotion might work only in certain geographic areas at certain times of the year. It would halt the loss of money if the company were to just launch the promotion across all properties.

"You could compare the sites you are testing with the promotion to the sites you did not try it at yet, and compare all of the data," Bruce said. "It might turn out that sales were no different, and that could result from weather conditions, what was going on in the city at that time, where the sites were located, and many other things."

That type of insight is powerful for a company and allows it to compare transaction numbers and sales percentages against those of competitors, he added. "Your sales may be down, but maybe theirs were too for some unforeseen reason."

Ultimately, Mastercard operates its data analytics on the premise that it can help its merchant clients turn data into action — and better decisions. In doing so, the business would grow and potentially increase transactions on the Mastercard network.

"There are multiple elements about how we can leverage this discipline for deeper relationships with our merchant partners, as we help organizations with their loyalty programs in obvious ways and in optimizing customer relationships," Bruce said.

Merchants are increasingly realizing that data is a "renewable source that allows them to stand on their own," said Richard Crone, chief executive of San Carlos, Calif.-based payments consulting firm Crone Consulting LLC.

"Retailers stand to gain by turbocharging their data, as they and their payment processors are starting to glean wisdom from the data," Crone added. "That is what the applied data analysis is doing for Mastercard, as well as taking it to the next level by developing machine learning so that it can do this type of analysis on the fly."

Data will play an even larger role in the advancement of omnichannel experiences at retailers or Internet of Things advancements.

"You have to leverage all of the data you have for the consumer's benefit," Mastercard's Bruce said. "That is the core of the mission."

That translates to merchants using what they learn about their customers through all channels and then communicating to the customer at all touchpoints, mobile, online and in physical retail settings.

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