WeottaGo reinvents local with smart data intelligence

San Francisco-based startup Weotta is looking to solve all-too-common problem of “what should we do tonight?” with its new iOS app, WeottaGo.

The app functions like a local recommendation engine, using sophisticated data processing technology to provide suggestions for what to do, based on location, time, and a user’s established preferences. Partnerships with StubHub, Ticketmaster, Fandango and OpenTable allow WeottaGo to provide up-to-date inventory information, such as if tickets are still available for the nearby concert that starts in 30 minutes. The app’s recommendations are displayed as photos that can be saved, emailed or dismissed with a swipe.

It’s simple, but it’s also proving to be sticky. In the first two weeks after launch WeottaGo is boasting some impressive retention and engagement figures. According to Weotta co-founder Grant Wernick, 75 percent of WeottaGo’s usersbase have used it twice, and 50 percent have used it at least three times since installing it.

“People really don’t know what they want to do,” says Wernick. “So we decided to build an app to solve the problem. This is the app for everyone who wants to explore the world around them here and now.”

According to Wernick, WeottaGo’s stickiness comes from the technology behind it. Wernic and his co-founder Jacob Perkins spent two years working on WeottaGo’s data processing capabilities in order to create something that doesn’t just catalogue local information, but understands it. This allows the service to give users better recommendation than competing services because it can understand that a user is looking for things to do that fall into fuzzy categories like “going out with friends.”

The app starts with suggestions that are already popular, and over time WeottaGo learns what a user likes and starts to add more customized recommendations. While it may seem counterintuitive to have the service improve gradually, rather than have the user input information to ensure its recommendations hit the mark immediately, Wernick tells us this approach actually improves WeottaGo’s engagement.

“People often are looking for something new and interesting now,” he explains. “They don’t want to train a system. They want an app that magically already knows them. As you say no to some things, and maybe to other things, the app starts giving you feedback. In the mood for drinks? Are you entertaining clients? Going out with the girls?”

Although Wernick tells us Weotta doesn’t have plans to monetize the app immediately, he sees the service generating income in a non-intrusive way down the line.

“Being able actually know the kind of stuff people like because it’s been trained over time, means we can actually give you the right kind of stuff,” he says. “We’ll know you want to go to a U2 concert this weekend, so here you go. We can be very pro-active about stuff, but it should actually be a very nice relationship because we’ll actually be giving people the things they want. It won’t feel like the whole pushy ad world.”

WeottaGo is currently available in 20 metropolitan areas in the U.S., and the Weotta team is working on expanding the app’s coverage, with more U.S. cities and major Canadian ones like Vancouver and Montreal slated next for development. The team is also working on adding a future tab to the app that will let users see events seven days in the future in order to make advance plans.

The company is backed by what it calls a lean amount of Angel funding from investors like Matt Ocko, Eric Chin and Omar El-Ayat.