With Uber deciding to sell Uber Eats India to Swiggy for a stake in the latter, the food delivery space in India is consolidating with Swiggy, Zomato (owned by the publicly listed company, Info Edge) and Food Panda (owned by Ola). But this piece in the WIRED is about the fascinating data science behind the food delivery business and the disruptions it is likely to cause to the much larger restaurants business.
“The more detail with which we can model the physical world, the more accurate we can be,” says Eric Gu, an engineering manager with Uber Eats’ data team. The company employs meteorologists to help predict the effect of rain or snow on orders and delivery times. To refine its predictions, it also tracks when drivers are sitting or standing still, driving, or walking—joining the growing ranks of employers monitoring their workers’ every move. Improved accuracy can convert directly into dollars, for example by helping Uber combine orders so that drivers carry multiple meals without any getting cold. Drivers get a small bonus for ferrying multiple orders on one trip. “We can save on delivery costs and pass back some savings to the eater,” Gu says. Four blocks away, Uber rival DoorDash has its own team of data mavens working on an AI-powered crystal ball for food deliveries. One of their findings is that sunset matters. People tend to order dinner when it’s dusk, meaning they eat later in summer and shift their habits when the clocks change in spring and fall. Like Uber, the company keeps a close eye on sports schedules and weather patterns, while also tracking prep times for the dishes offered at different restaurants. Company data indicates that pad thai takes 2 minutes longer to prepare Friday through Sunday than during the rest of the week, because kitchens are busier.
Rajat Shroff, vice president of product, says DoorDash data also clearly shows the connection between accurate delivery predictions and customer loyalty. “That’s driving a big chunk of our growth,” he says. The company was valued at $7 billion this month by investors who plowed in $400 million of fresh funding. DoorDash has also been working to better understand what happens in restaurants, for example by connecting its systems with Chipotle’s in-house software so orders can be sent in more smoothly, and DoorDash can track how they’re progressing. The company has built a food-delivery simulator in which past data is replayed to test different scheduling and prediction algorithms. Both DoorDash and Uber use their data to offer drivers more money to head to areas where demand is expected to be strong…. “I’ve spent my whole career trying to figure out how to put the best product in front of people,” Hargrave says. “Now I’ve been thrown this curveball where I have to put it in a box.” Tacolicious switched its register system to better handle delivery orders without compromising in-store service. There’s now often a person in each restaurant working exclusively on packaging and checking delivery orders.
Muller and Hargrave say the app-and-algorithm approach to dining can squeeze conventional restaurants and could even put some out of business. Uber’s standard cut of each order is 30 percent, a significant bite in a traditionally low-margin industry. Even restaurants like Tacolicious that accommodate delivery services must also serve people who walk in the door. That’s one reason Uber is encouraging the development of “virtual restaurants,” which operate out of an existing restaurant’s kitchen but sell only via its app. Uber said last year that it was working with more than 800 virtual restaurants in the US; many operate during hours when a restaurant’s main business is slack or closed, allowing more efficient operation and use of the property. Uber and DoorDash also work with so-called dark kitchens, operations that serve only via delivery apps and can be more efficient and predictable than conventional restaurants. DoorDash operates a 2,000-square-foot kitchen space in the Bay Area that it rents to such operators.
Muller likens the arrival of Uber Eats and others to how online travel sites shook up the hotel industry, forcing hoteliers to adapt their business models to a market where consumers are more engaged, driving more visits, but at lower prices. How lucrative this new form of restaurant business will be is unclear.
Uber and DoorDash both declined to provide more detail about their businesses but are rapidly expanding their reach. DoorDash says it covers 80 percent of the US population, and Uber Eats claims to have reached more than 70 percent, in addition to serving more than 100 cities in Africa, Asia, and Europe. Sallenave, the Uber Eats head for the US and Canada, predicts eating via app will become the norm everywhere, not just in urban areas. “We fundamentally believe we can make this business economically viable, not only in large cities but also in small towns and in the suburbs,” she says.”
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If you want to read our other published material, please visit https://marcellus.in/blog/
Note: The above material is neither investment research, nor financial advice. Marcellus does not seek payment for or business from this publication in any shape or form. The information provided is intended for educational purposes only. Marcellus Investment Managers is regulated by the Securities and Exchange Board of India (SEBI) and is also an FME (Non-Retail) with the International Financial Services Centres Authority (IFSCA) as a provider of Portfolio Management Services. Additionally, Marcellus is also registered with US Securities and Exchange Commission (“US SEC”) as an Investment Advisor.
