Say goodbye to unreliable demographics and hello to ROI-proven data.

For decades, retailers and restaurants have relied on demographic data to build targeted advertising efforts. Demographics, however, are an imperfect marketing tool, as they often lack context and fall short of helping restaurants reach specific customers in a way that feels relevant. 

For instance: A 33-year-old male lives in Tennessee. Demographic-centric data might indicate that he enjoys light beer—but what if he prefers a nice glass of rosé? This person would be more likely to respond to and spend money on a rosé offering, which marketers would never know by examining demographic data alone.

“This is a pivotal thing for restaurants to understand,” says Austin Fabel, senior director of business development of restaurants at Fetch Rewards. “You may think I’d be a loyal Big Mac customer when in fact, I’m eating salads and smoothies.”

Cutting-edge digital marketing platforms don’t use demographics. Instead, they analyze data and consumer preferences, interests, and most importantly, individual purchasing behavior. The only way to know and target consumers effectively is to understand them via first-party, item-level data. Knowing who the customer is—using transactional data given to you by the customer themselves, not demographics—will always be the best way to truly understand consumers’ complete behavior.

Fetch Rewards works by using AI and machine learning to match characters on receipts to individual purchases. Users can scan receipts from anywhere—from restaurants to hardware stores—into the app, for which they receive points redeemable for gift cards or other rewards. They can also join “clubs” to earn additional points and access to exclusive offers.

“We can understand, in real time and with a degree of certainty, what offers will be exciting for which customers,” Fabel says. “We look at purchase history to determine which offers users are eligible for. When they scan receipts, we then match those products with the hyper-personalized offers. 

Fetch Rewards has more than 17 million monthly active users who, on average, submit 30 receipts per month. The company uses this data to build marketing segments for quick-serve restaurant partners. For example, data allows Fetch Rewards to see who its partners’ most loyal, somewhat loyal, lapsed, and non-customers are. Because users are incentivized to scan all of their receipts, Fetch Rewards can also see their behavior outside of partner walls and identify their competitors’ most loyal customers, and those most likely to switch. Using this rich data, Fetch Rewards creates offers unique to each segment and rewards them with in-app currency called Fetch Points—which users have shown that they are willing to shift behaviors for.

For instance if Tom has not been to his favorite quick-serve restaurant in six months, he can be targeted with an in-app offer aimed at getting him back in, while also requiring him to spend a certain amount to be rewarded. Once Tom’s visit is confirmed, he is sent a new offer that requires two trips back within 45 days in order to earn even more Fetch points.

“This gamified experience is not only fun for the user, but it also continues to reward them for taking that extra step, ordering that extra item, or visiting one more time,” Fabel says. “This ultimately drives loyalty and preference for the partner brand.”

Fetch is a performance-based platform. Restaurant customers are only charged for transactions driven by the platform, and which both Fetch and the partner brand deem “premium.”

“Fetch points keep our users happy about dining out without relying on discounting—while also ensuring that each dollar spent goes toward a confirmed purchase, not a click or an impression,” Fabel says. “This is the future of digital marketing, and it will be owned by companies who have this level of sophisticated targeted marketing.”

For more on targeting your customers more effectively, visit the Fetch Rewards website. 

-Davina van Buren

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