Table8, maker of an app that allows users to make last-minute reservations at sought-after restaurants for a fee, today announced a $4.6 million funding round led by angel investors and Concur, a business travel and expense management platform based in Bellevue, WA. Concur’s $150 million Perfect Trip Fund is dedicated to investing in companies in the travel logistics space.
Making restaurant reservations online is nothing new—OpenTable is practically a dinosaur of the Internet, founded in San Francisco in 1998—but Table8 co-founder and CEO Pete Goettner sees his company as a fundamentally different and much more modern model; it targets business travelers, tourists, and locals looking to snag last-minute table reservations at the most popular restaurants directly from their mobile phones. “In foodie kinds of cities, it’s almost impossible for me to book a reservation on OpenTable during the week for a reservation on Friday or Saturday night,” he says.
To Goettner, it’s simply an extension of the new convenience economy, where rides, babysitters, delivery, and other amenities are available at the tap of a smartphone for a generation that doesn’t have time to plan ahead. “People have tried this in the past, but the urgency now of having a phone in your pocket and being able to book something is why I think it’s going to happen this time around,” he says.
Table 8 is currently available in San Francisco, and has plans to expand to New York early this summer.
Here is a lightly edited version of our conversation.
Xconomy: With OpenTable already so well established, why did you feel this space was the one to disrupt?
Pete Goettner: If you look at OpenTable in San Francisco specifically, on Wednesday or Thursday about 20 percent of the restaurants are already sold out for Friday and Saturday. While OpenTable has a lot of listings for restaurants, they don’t provide that last minute meal reservation. Could they get into our business? Maybe. But I doubt it—it’s not really their business model.
And obviously, our reservations cost money. It’s fairly different than OpenTable.
X: Where does the supply of reservations come from?
PG: We approach restaurants; we talk to them about providing an additional revenue stream. They set aside tables for us. If you look at where our tables come from, which is a question for a lot of folks, they come from tables restaurants are already setting aside for the manager. Instead of having the old boy network get access to those tables, because they know the chef or they know the manager, or they slipped the concierge a $50 bill, what we want to do is open it for locals, or business travelers, or tourists coming into the city. And we split the revenue with the restaurant.
X: How much should users expect to pay to snag a table?
PG: If you wanted to eat at Boulevard, you could come in on, let’s say a Wednesday, and look for a reservation for Friday at 7:30, and depending on demand and how many tables we have, it could range anywhere from $20 for a two-person seating up to 40 or 50 bucks for a two-person seating. And that’s the revenue for that table, and we split that revenue with the restaurant, so they’re making money through this process as well.
Because we’re bringing a lot of business travelers into some of those tables, the average cover that we provide the restaurant is higher than the average. A cover is what the average person spends dining in a restaurant. Statistically we [bring in a higher cover]. We can’t guarantee that. But if you look at a business traveler with an expense budget, they tend to spend more money than someone like me.
X: Is the revenue split evenly?
PG: Today it’s evenly. It’s 50/50, which I think works pretty well. They’re pretty happy with it.
X: What’s the motivation for restaurants?
PG: Restaurant owners, chefs, managers, they also look at what’s happening with Uber and HotelTonight, and they understand the cell phone is now being used to make plans later and later in the cycle. [We’re moving] more and more towards real-time kind of planning.
X: How big is your supply?
PG: For a city like San Francisco, which is really our data city, I would guess at scale we would have
