Deep Learning for Deep Discounts AI Creates Personal Deals for Gas, Food, and Retail

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2 min read
Upside app screen video capture

With prices on the rise, an app analyzes user data to deliver cash back on retail purchases.

What’s new: Upside, a startup based in Washington, D.C., works with gas stations, grocery stores, and restaurants to offer personalized discounts to consumers, The Markup reported.

How it works: The app displays a map studded with offers, customized for each user, from 30,000 partners, most of them U.S. retail chains. A user who patronizes a partner pays full price, then uploads an image of the receipt. The app applies a discount to the user’s in-app balance, which can be transferred to a bank account — for a fee — or traded for digital gift cards.

  • A machine learning system calculates discounts based on anonymized data including the user’s location, credit card number, and past purchases. External factors such as prices offered by competing establishments nearby also affect the discount.
  • To pre-empt price wars among, say, gas stations clustered around a single intersection, Upside partners with only a single station in the cluster.

Behind the news: Founded in 2015, Upside says its services reach 30 million U.S. users. Lyft and Uber integrate it with their driving app to offset inflation-driven spikes in gas prices. Fuel-saving apps GasBuddy and Checkout51 offer Upside-powered promotions, and DoorDash and Instacart have offered Upside to their drivers.

Yes, but: Upside’s algorithmic approach to calculating discounts may leave some customers feeling left out.

  • It’s more profitable for partners to offer bigger discounts to newer or less-frequent customers, Upside’s CEO wrote in a white paper. He advocated cutting discounts for users who are part of a partner’s loyalty program.
  • A driver for a ride-sharing service told The Markup that an offer he had received from his employer through Upside — up to 25 cents cash back per gallon of gasoline — was misleading, and that he often received far less in cash back.

Why it matters: Many families, individuals, and employees are on the lookout for ways to cut their expenses, and they may consider surrendering personal information a fair trade. However, the terms of the deal should be transparent and easy to understand. It’s deceptive to offer discounts that don’t pan out or diminish without warning as a casual shopper becomes a steady customer.  

We’re thinking: Offering discounts to attract users is an old tactic; think of Groupon and its countless competitors. But AI can tailor a deal to each individual user — a new approach that could make this strategy more effective, scalable, and sticky.


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