NatureBox, a Calif.-based Start Up is using Big Data to Build a Snack-Recommendation Engine

SUMMARY: Over the last few months, a San Carlos, California-based start up, NatureBox has developed an algorithm to convert one time consumers into brand ambassadors.

. It is safe to assume that the use of big data is a success, based on 10,000 to 20,000 new ratings that the company receives every day.

It is safe to assume that the use of big data is a success, based on 10,000 to 20,000 new ratings that the company receives every day.

Companies like Fresco Data Inc and Kaggle make us realize how Big Data-related business solutions can help us provide top-notch service to our consumers and add a certain competitive advantage. One such start up, NatureBox has done the exact thing to be more than just an online snack retailer to its customer base.

On Wednesday, NatureBox debuted a new feature that will help several subscribed customers to compile their choice of healthy snack boxes and at the same time feed into its recommendation engine. Customers will be able to prioritize up to 20 items in the online snack pantry, which NatureBox’s service will automatically dispatch top five items each month. In order to appeal to its customers, who keep away from subscription, the company also plans to launch NatureBox Market, an a la carte option, which is being tested currently.

Currently, NatureBox offers up to 120 to 130 snack options.

Currently, NatureBox offers up to 120 to 130 snack options.

Since past several months, the company’s analysts, developers and data scientists developed an algorithm to recommend healthy snacks which are analogous to customer’s individual tastes.

“I think we’re just starting to scratch the surface of what’s possible,” says CEO and cofounder Gautam Gupta. “The snack pantry is giving us an indication of who the customer is and what products they like. From there, we’re able to improve our snack recommendation engine.”

Currently, the innovative retailer offers up to 120 to 130 snack options. It is safe to assume that the use of big data is a success, based on 10,000 to 20,000 new ratings that the company receives every day. To top it all, the company also has data on customer’s dietary restrictions, allergies and preferences for varied flavors which was recorded from a quiz taken by users.

The algorithm can perform a function to filter snacks with allergens for those who have allergies or filter out non-vegan ingredients for those who follow a vegan diet. The company has also added a certain degree of surprise element more of a ‘surprise snack’, which users can opt for, if they wish to try out something new.

“We have so much data, and we’re constantly improving the performance of the algorithm,” Gupta said. The healthy snack company, plans to open up a 40,00 sq ft facility in Indiana and might even incorporate other types of customer data to improve its services in the future, such as – location of a user,  log in time of day, various combination of snacks and much more.

“We’re starting to use other signals that might be seemingly unrelated to snack ratings or how you might enjoy a particular snack, but as the data set gets larger, we can start to correlate those things,” he said. “All of this is driven through our direct relationship with the customer. We really have a data set that traditional brands that distribute to retail don’t because we know who our customer is.”

 

Christy Gren
Christy Gren is an Industry Specialist Reporter at Industry Leaders Magazine she enjoys writing about Unicorns, Silicon Valley, Startups, Business Leaders and Innovators. Her articles provide an insight about the Power Players in the field of Technology, Auto, Manufacturing, and F&B.

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