The age-old pursuit of dinner used to be a game of chance — maybe you found a special spot down the street, or maybe you didn’t.
James Roedding, head of product and data science at Rewards Network, told PYMNTS that the age of digital engagement is changing the restaurant experience — and can transform the ways in which the restaurants operate while improving their margins and customer loyalty.
“More and more, you are seeing more digital adoption across all customer groups,” he told PYMNTS as part of the “What’s Next in Payments” series on how various companies have shaped and refined their online efforts.
Young consumers and boomers have used their mobile devices as a way to conduct daily life — and it’s incumbent upon firms to ensure they build their products and services in ways that are so intuitive that anyone can use those offerings regardless of their digital literacy.
As his job title would imply, Roedding has a vantage point that’s unique — combining data with the evergreen endeavor of enriching and expanding his firm’s reach and innovation in the digital age. As he said: “Data science is interacting with every part of the world.”
At a high level, Roedding said, “as consumers, not only are we expecting to be able to interact with a brand or a service through digital means, but the expectation is also that the interaction is going to be highly personalized.”
To get to that level of personalization, data science and Big Data are essential to crafting digital services that truly help individuals and consumers — and businesses looking for those customers — find one another seamlessly.
Roedding noted that Rewards Network, operating as a platform that connects restaurants and consumers, can and does use data to keep track of how frequently both sides of the equation are interacting with one another.
On the restaurant side, Rewards Network has a vast expanse of data across their customers’ businesses. To understand how this is used by their customers, Rewards Network keeps tabs on how often restaurants are visiting the company’s portal and what they’re doing once they’re there. The real-time insight, as Roedding put it, informs the platform: “Are they viewing our analytics? Are they making updates to the marketing program that we run for them? Are they replying to member reviews?”
The company also gives its restaurant customers flexible funding options to help smaller independent eateries tap into the capital they need to grow. “We’ll predict how much consumer volume we think we can drive into a restaurant, and we’ll pay the restaurant a portion of that volume upfront,” Roedding said, that predictive effort is aided by real-time modeling.
Roedding noted that another unique feature of the Rewards Network platform that measures the interaction between restaurant and member is the verified review capability. Only members that have actually dined at participating restaurant can leave a review, which gives the establishment real insight into what they are doing well and what can be improved.
The reviews are verified, he said, and Rewards Network has the ability to “seamlessly trigger” that review the moment a card is swiped, in real time, as the establishment prompts them to leave feedback at the time of payment. The review response rate is three times higher than the industry average, he said, and the restaurants also respond to those reviews at a high rate.
That level of data-driven granularity extends to the member side of the platform, where the network gauges how often members are searching for restaurants, which eateries they are interested in, and what type of marketing is indeed resonating with them — along with what diners are saying in their reviews. Members earn rewards at airline, hotel and other loyalty programs with each dollar they spend at the participating restaurants.
Looking ahead, Roedding said, Rewards Network will be ramping up its efforts to enable user-generated content, as customers promote restaurants and restaurant owners can update their online content with the help of artificial intelligence (AI).
AI is also useful in analyzing large swaths of data, he added, which in turn can synthesize thousands of reviews, for example, and improve analytics functions.
Rewards Network is expanding an offering that looks at consumers’ dining behavior and models it out to other consumers that it believes are similar to one another and then finds dining suggestions that have yet to be sampled by that diner, and which would be a good match.
“The thing I’m most excited about is increasing the level of personalization that we can provide,” he told PYMNTS.
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