Seamless, a favorite resource for connecting restaurants and delivery-dependent diners, built its business helping companies order meals for its workers. But the company is now trying to become a much more consumer-focused business, and it’s now looking to the mounds of data it gathers to try to accelerate the transformation.
I recently sat down with Jonathan Zabusky, the CEO of New York-based Seamless, to talk about the company’s first iPad app, which debuted yesterday and shows some of where the company is going. It’s a nicely designed app that relies on gestures and swipes and simple- to-use filters to help consumers figure out what they want to eat.
But what’s more interesting is how the company is looking to leverage its growing data to become a bigger resource for consumers, not just for fulfilling quick deliveries but for broader local searches and research. You see hints of that in the iPad app, which presents past orders and lets users find restaurants reviews and ratings. That’s increasingly where Seamless wants to go. Instead of being a simple utility, it ultimately wants to be a Yelp or Citysearch-like destination where it can recommend good food spots and clue people in to the best dishes to try.
“We want to still give people the ability to get in and out, but we’re showing more pathways for engaging,” Zabusky said.
That’s where Seamless’ data comes in. It has 8,000 restaurants in its network and over the last three years helped ring up more than $1 billion in sales for its business customers. Now, with the data it’s collected, Seamless is looking to better surface what people are eating and what they might also like to try. Zabusky said Seamless has started highlighting the most-liked and most-ordered items on its website and is now in the process of building more personalized recommendations into the service, looking at a user’s past preferences to link them up to restaurants and dishes that similar users like. It will also help users create more content and sharing to provide even more data for Seamless.
Seamless, which spun out from Aramark and dropped the “Web” from its name last year, is a long ways from displacing Yelp. That site had 61 million unique monthly visitors, 22 million reviews, and 529,000 claimed business, as of September. In the first three quarters of 2011, it generated $58 million in revenue from 19,000 active business accounts. But Zabusky said there’s power in knowing where people are going and what they’re actually ordering and in some cases, who they’re eating with, a dataset that Seamless has been building since it 1999.
“Our ability to leverage data to understand where to eat and what to eat is unparalleled,” said Zabusky.
Seamless make its money taking a percentage of transactions. Zabusky said this model allows Seamless to avoid running advertisement on its site and apps, something Zabusky wants to maintain into the future. Instead, he just wants to keep driving more business for restaurants with the data Seamless is gathering.
Seamless is far from the only company to embrace data to help supercharge its business model. Foursquare started out as a location-based game, but a year ago put all of its check-in data to work in a new Explore recommendation feature that is now helping Foursquare compete with Yelp and others in local commerce. Another site, Yipit, has turned its aggregated daily deals data into analytics and research information for business clients. It’s taken its data gathered for consumers and built a B2B business opportunity on top of it. Pandora, Amazon and Netflix have also taken their user data to improve recommendations and help people discover content.
As more and more companies are sitting and mounds of data, and have technology that can help store and process it, the differentiator is being able to develop products and business ideas from the data. Zabusky believes that if Seamless can better tap the data it gathers from transactions and consumers, it can push the amount of sales it helps generates from $400 million last year to a $1 billion annually in the next couple of years.
We’ll be talking more about big data at GigaOM’s Structure:Data event next month in New York.