Yummly, the semantic search engine for home cooks, has been chugging along for nearly three years without a revenue stream, but on Wednesday it revealed just how it plans to monetize its millions of recipe searches each month. As part of a site redesign this week, Yummly is launching its advertising platform, serving up ads and sponsored recipes from major food brands such as Hellman’s, Ragu and Breyer’s.
Putting food ads on a site devoted to recipes is a no-brainer, but Yummly is bringing some more complex data science to its platform than just keyword search ads. Yummly is applying the same algorithms it uses to parse recipes to its advertising, CEO David Feller said. So instead of popping off ads for boxed pastries whenever a user searches for “apple pie,” the engine can delve deeper.
An apple pie search might generate ads for the necessary ingredients such as for flour or apples, but it wouldn’t just select any variety of apples. Through recipe analysis, Yummly knows that apple pie is most often cooked using tart apples like Granny Smiths, so ads for red delicious apples just won’t do. Yummly can even infer what pairs well with a dish, Feller said.
“The data knows what we don’t know,” he said. “If somebody is looking for apple pie, Yummly knows that apple pie is complemented by ice cream, so we could give them ads for ice cream.”
Though those examples may seem rather simple, Yummly is launching with a limited number of advertisers and ad inventory. But the semantic search engine is growing quickly. In the last six months unique visitors on its site have nearly doubled, growing from 4 million in March to 7.5 million in September. That kind of growth won’t escape the notice of food brands. Feller thinks it won’t be long before Yummly can start delving down into very specific data to hone its ad targeting.
For instance, Yummly doesn’t just parse recipe ingredients. It extracts nutritional data and is even able to determine whether a dish or group of dishes is salty, sweet, savory or spicy from an analysis of its ingredients. Search options combined with histories generated by registered users tell Yummly about an individual cook’s preferences, whether he or she has food allergies, is on a fad diet or favors Asian over Mediterranean cuisines. Feller said all of these factors can be factored into ad targeting, and can be further refined by tracking seasonality of ingredients and even local weather conditions (stews and braises always go over well when its wet or cold).
The associations we make when craving food don’t always make logical sense. If I have a hankering chicken fried steak, it doesn’t mean I’m craving chicken or steak. Instead, I want comfort food, and Yummly would do much better to recommend me mac n’ cheese or meatloaf products and recipes. The ultimate goal, Feller said, is that Yummly will become wired the same ways are brains are to think about food