Four-year-old EAT Club harnesses Big Data and cloud technologies to provide high quality lunches on time to offices in the San Francisco Bay/Silicon Valley area and more recently to Los Angeles. A born-in-the-cloud company, it works at the individual employee level. Companies subscribe to the service, but their employees make their food orders directly either through a browser or a mobile app. They order off a menu that changes daily, and their food is prepared off-site in EAT Club’s kitchens, and delivered at a specified time with 99.4 percent on-time delivery.

Based in Palo Alto, EAT Club counts Samsung, Bit Torrent, Tesla, Pandora, Netflix and Kaiser Permanente among the hundreds of companies it serves. EAT Club has delivered more than 2 million meals and has approximately 375,000 customer reviews of specific dishes in its database. Its investors include Trinity Ventures, Tekton Ventures, August Capital, Great Oaks Venture Capital, Brian Lee and Mark Vadon.

So what does this have to do with Big Data? Behind the scenes, every decision is data driven, and nearly 50 percent of EAT Club’s employees – chefs, food buyers, delivery drivers – use its data analysis platform, from data-analysis-as-a-service provider Looker Data Sciences, Inc.  daily. This starts with knowing their customers.

“In a restaurant someone will come in, eat lunch and leave, and no one will know who he is, whether he is a first-time customer, or what he thought about his experience or his meal,” says EAT Club Co-founder Kevin Yang. “Because our customers order through an e-commerce platform, we know all that information, and we collect direct feedback both in terms of reviews and behavioral feedback.”

Knowing the customer

One major impact of this approach is to limit food waste. Restaurants throw away a lot of food because they do not know how much demand they will have, so they overbuy. EAT Club potentially has a more difficult problem anticipating demand than most restaurants because its menus change daily, so it cannot base its food buying for this Monday on its sales last Monday. Instead, its buyers depend on analysis of its customer base.

For example, vegetarians make up about 3 percent of the U.S. population, but EAT Club operates in the San Francisco Bay area, and Yang believes about 8 percent of its customers are vegetarian based on their food orders. But the data shows that 23 percent of dishes it sells are vegetarian, because many people who are not vegetarians order vegetarian meals some days. “If we did our meal planning on the basis of the percentage of the population who are vegetarian, we would be way off,” Yang says.

Some time ago EAT Club tried out a salmon meal in its menu and discovered that salmon is popular with a significant group of its customers. Over time it has tried other fish-based meals and found differences in customer preferences between salmon and other fish and between grilled, poached and baked preparation. Its data also shows that it gets more orders on rainy days, and that orders shift between hot and cold meals from summer to winter. Its data also shows preference differences in orders in general between San Francisco and Silicon Valley that factor into menu design and food purchasing.

Analyzing deliveries

Data analysis permeates all of the company’s business activities. For example, late delivery annoys customers, may disrupt their schedules, and can mean that hot meals arrive cold. All EAT Club’s drivers use a mobile app to confirm completion of each stage in the delivery from picking up the food at the kitchen to arrival at the customer and meal delivery to individual customers. This is analyzed to identify problems that may range from traffic delays to vehicle problems or driver issues. As a result, “we are intensely good at delivering food,” EAT Club CEO Frank Han says.

The employer benefits because the service increases employee productivity and morale. And it’s easy for companies to become involved. “If you talk to employers, they say providing food to our employees is important, but it’s a hassle,” says Han. “EAT Club uses software and the cloud to eliminate all the hassles, so it’s a pain-free experience.”

Each time an individual customer returns to the site he or she is asked to fill out a short survey about their last experience with EAT Club. These free-form comment forms are analyzed intensively to identify problems ranging from food preparation to temperature and presentation. The responses are analyzed for purposes like seeing which chefs prepare a particular dish best, which drivers make the best impression and other variables that can impact customer satisfaction. The result: Han says that EAT Club customers put in an average of eight orders each month.

EAT Club chose Looker as its data analysis system for several reasons. First, all EAT Club’s data resides in the cloud, so it made sense to use a cloud-based analysis service. Looker can also handle both traditional structured data and free-form text in the customer reviews. It provides near-real-time analysis, so problems can be identified and rectified immediately. Looker combines the ability to handle large volumes of data with an end-user friendly user interface that allows employees to do their own analysis on demand. Chefs, buyers, operations people all use Looker every day. “Basically if you can draw the data table that you want to answer your question, you can pull the answer out with Looker,” says Yang.

Top photo courtesy Eat Club

Second photo courtesy Looker