Tamecco uses artificial intelligence to generate coupons and discounts you’ll actually use

Almost everyone has a favorite restaurant or local business that they frequent, where the waitress knows your order before you even sit down and the clerk tips you off about a new shipment or upcoming sale. Many shoppers carry physical loyalty cards or coupons when they head to the mall, and an increasing number of people are utilizing brand-specific apps or online mailing lists to catch wind of special offers.

What if you could receive all of the benefits that come with being a “regular” with a single mobile app? Tokyo-based startup Tamecco is trying to achieve just that, while also promoting discovery and providing deep analytics and artificial intelligence-powered targeting for the businesses themselves.

“Amazon provides personalized content and recommendations in the online shopping space,” Jonah Oh, the startup’s CEO, tells Tech in Asia. “Tamecco focuses on bringing that same kind of personalization for shoppers to the physical world, in brick and mortar shops.”

“Amazon gets information from a user’s browsing or shopping history, and it’s easy to get that from cookies and shopping cart data,” Oh adds. “But it’s much more difficult to find out these things in the physical world, like where you went window shopping versus where you actually went in and bought something.”

Tamecco leverages AI and machine learning to provide targeted coupons, discounts, and other perks for its users’ favorite or most-frequented brick-and-mortar stores. As long as the app is installed, launched at least once, and a user has given permission for location services, alerts are sent automatically from the startup’s proprietary hardware – similar to iBeacon, but compatible with both iOS and Android-powered mobile devices. Tamecco will continue to work until the user uninstalls it.

“As the user experience is our utmost important design factor, Tamecco really focuses on keeping the application’s impact to the user and their phone to a minimum – including battery impact, data usage, and other phone services,” Oh explains.

For the retailer, Tamecco can analyze a variety of things based on a user’s location, such as high and low-traffic areas or how close a customer got to the cash register without making a purchase. It can also tell when a user is a first-time visitor to a specific shop, and perhaps offer them a one-time discount or a free cup of coffee for new customers. If you used to eat or shop somewhere but haven’t made a purchase in a while, Tamecco might send you a special coupon to entice you to return as you walk by.

Anonymity and discovery

Services that track your movements and gather data about your personal habits often throw up red flags for the privacy conscious. Tamecco couldn’t exist without gleaning such information, and Oh stresses that data collection is always anonymized.

“It’s never you,” he says. “It only knows that there’s this person in their 20s or 30s who tends to hang out in this area. Individual behavior also feeds into the group consensus, so we can follow trends within groups. Our AI engine learns by understanding your behavior patterns, and your individual movements help shape ideas about the larger public.”

As users make transactions, Tamecco aggregates the data in real-time to pick up on trends. It combines merchant POS data, geospatial data, organic engagement with the app itself (i.e. redeeming a coupon), and AI-driven engagement (personalized and/or time-sensitive offers sent via push notifications).

“On top of all this, the AI engine can also determine strong indicators of an individual’s highly-probable behavior to enrich gaps in explicit data,” Oh says. “Even if you use cash for your transaction, there are many ways that Tamecco would be able to link you to that transaction.”

All the while, Tamecco’s machine learning algorithms consider how relevant an offer is on a per-person basis. If sushi is trending, and you don’t eat sushi, it doesn’t make sense to send you a coupon for a sushi restaurant. Similarly, if you’re a man, you probably wouldn’t care about a nail salon discount. Tamecco hopes that its AI will keep customers engaged, as no one likes getting spammed with offers they have zero interest in.

Oh gives a simple example: Imagine that you pass by stores A, B, and C on your way to work. You occasionally shop at store A, eat at store B, but never go to store C. Another user also visits A and B from time to time, and similarly avoids C – but they often visit store E around the corner. Tamecco would likely send offers for stores A and B, and might also generate a coupon for store E – but only if its AI determines a match between whatever that shop offers and the user’s individual profile.

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