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National Restaurant Association - 3 steps to implement predictive ordering technology

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3 steps to implement predictive ordering technology

Netflix suggests content based on subscribers’ viewing preferences. Google Now notifies travelers, based on traffic, of the ideal time to head to the airport. To satisfy customers’ desires for streamlined experiences, some restaurants, such as Panera, are utilizing predictive ordering technology.

Imagine the following scenario: It's 11:45 a.m. and Sara, one of your restaurant customers, hasn't even thought about lunch yet. You know she loves your salads, hasn't visited this week and tends to come in around noon when your line is long.  At 11:46 a.m. through your app, you send Sara this push notification that displays on her phone: “Hi Sara. Coming for lunch today? Want us to have your Greek salad ready when you get here at noon?” With a screen swipe, she places her order, heads over to your restaurant, and picks up her salad. Sara may not have planned on buying your Greek salad for lunch that morning, but by tracking her preferences, you gained an extra sale.

Here are the three steps you can take to prepare your business for predictive ordering:

1. Set up online ordering.

To predict and remotely receive customer orders, you'll need to have a reliable online ordering platform in place. Select a provider that directly integrates with your point-of-sale.

2. Develop a mobile solution.

Offer a mobile app or website that places the power of online ordering in customers’ hands. Your online ordering provider can build a stand-alone solution or a centralized digital hub with ordering, loyalty program and mobile payments capabilities. Determine what mobile capabilities best fit your business.

3. Analyze data and suggest orders.

With these two pieces in place, plus some order history, you can predict customers’ orders and tailor your marketing accordingly. Some providers offer predictive suggestions as add-ons to customers’ orders; for example, when a customer orders a cheeseburger, the app may suggest also ordering a milkshake. Others providers are building mobile payment solutions that suggest items based on preexisting purchasing patterns.

To streamline the predictive process, assign each menu item with a unique SKU number. When a customer places an order, information about that individual (his or her name, age and address), the item (SKU number) and situation (time of day and location) is recorded. This data is processed by the predictive ordering system, and, over time, behavioral patterns are recognized. This information can then be used to more accurately target your customers.

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