Last week, Snapchat became the latest company to add an AI-powered food scanning and recognition feature to their product. Called Food Scan, the new feature enables Snapchat users to scan food items and get recipe suggestions and other information about the food.
Here’s how it works:
Snapchat users can scan food by opening up the AR bar within Snapchat from the main camera menu option. From there, they choose to scan and click a picture of the food item. Snapchat’s AI will process the image and suggest a recipe from partner Allrecipes, as well as serve up other information, such as a Wikipedia page, about with the item.
According to Snapchat, the feature has access to over 4 thousand recipes and can process up to 1500 ingredients. However, based on my own attempts, the product may need to add a few more items to the list to be helpful.
When I scanned Campbell’s Cream of Celery Soup, it offered up recipes for Campbell’s bacon soup. A scan of Adam’s peanut butter resulted in recipes for tahini. The closest match came from a scan of a navel orange, which resulted in a Wikipedia page for a mandarin orange and recipe recommendations for mandarin orange cake and mandarin orange salad.
Here at The Spoon, we’ve written a lot over the years about attempts by companies to create a ‘Shazam for food.’ Big tech companies such as Microsoft, Pinterest, and Google have been at work at this for some time, as have appliance brands like Samsung and Whirlpool. Part of the reason so many have dedicated resources to building augmented reality and AI products for food recognition is, quite simply, because food is one of the easiest product categories to recognize and create databases around. But it’s also because food recognition unlocks numerous commerce, health and nutrition tracking, and kitchen management scenarios if done right.
Snapchat’s new Food Scan feature, while pretty rudimentary at this point, clearly has designs on building potential revenue through shoppable recipes and product recommendations. However, I can also see it becoming a broader food-related augmented reality recommendation tool that suggests, similar to Alexa’s new What to Eat skill, restaurants, meal kits, and other potential monetizable recommendations.
