It can be creepy to realize how well machines can know us and predicts our wants and needs. But at the same time, it’s part of the magical future that we were all promised. As we share more and more data about ourselves and machine learning and predictive analytics continue to improve this omnipotent guardian angel effect will only increase.
Today, Weotta is launching what it calls the first take-me-out app to include intention-mapping. In other words, the app knows you and your friends, knows where you are, and knows what food and entertainment options are available nearby. From this data, the Weotta aims to deliver the social options most likely to appeal to you and your crew, be they friends or family, and also make sure you don’t find out about a big event the day after it happens.
“The joke around the office is this is the ‘boyfriend’s ultimate cheat sheet’ or the ‘mother knows everything cheat sheet,’” says co-founder and CEO Grant Wernick.
There have been countless attempts to solve the vent recommendation problem with limited success. Most have taken the form of simple aggregator, occasionally with “personalization” through user surveys. But the real magic occurs in delivering the perfect recommendation that the user doesn’t even know they want, but ultimately end up loving. No one has really nailed this to date.
To deliver this type of recommendation magic, Weotta relies on massive amounts of big data. Not only does the company aggregate and parse publicly available places and events data – such as that from Eventbrite, Facebook, Fandango, OpenTable, StubHub, TicketFly, YouTube, and other sources – but it also incorporates the activity and preferences of you and your social circle. The goal is to amplify existing social signals, with the result being a comprehensive and customized view of the social landscape in a given city.
“At times we think we’re offering more than people are really ready for,” Wernick says. “People have super fast-paced, on-the-go lifestyles and demand products that deliver 100 percent of the time, simply, quickly, and with focus. But at the same time, they’re not ready to trust machines to say, ‘This is the ultimate plan for you. Go do it.’ So we try to find a balance between machines augmented by friends.”
The app offers a gesture-based interface that allows the user to view each suggestion and swipe to indicate yes, no, or maybe later. Subsequent suggestions change and adapt based on each response, aiming to match the user’s intent in the moment, whether its a parent looking to entertain a child, couple on a date, or a businessperson heading to a meeting. When planning an event, Weotta can also notify the user if any friends might also be interested or are nearby.
Weotta currently cover 400 US cities and has plans to expand internationally in 2014. Due to its machine learning underpinnings, the experience delivered by the app improves over time both as the individual user interacts with it and as the total usage across all users grows.
The company does not currently monetize and has no plans to do so in the near future. Longer term, it’s likely that any monetization strategy will involve event sponsorships and promotions, as well as possibly branded experiences.
The Weotta team is just five people, a number that will grow to eight in the coming months, but due to its limited staff, the company has been forced to automate as much of process as possible. Adding a new city is 85 percent automated, according to Wernick, who says that queries to event, places, and census databases is straightforward but cleaning up inconsistencies created by local conventions and slang requires limited human input. The CEO believes Weotta can execute its planned international expansion with a team of just 12.
The San Francisco startup has raised a Seed round of undisclosed size from Google Ventures, Data Collective Venture Capital, Crosslink Captial, Gil Elbaz and David Waxman’s TenOneTen Capital, Path founder Dave Morin’s Slow Ventures, and former Expedia CEO Eric Blachford.
We are in the very early stages of personalized big data tools. The popularity of Google Now, Tempo, and other calendaring and intelligent digital personal assistant suggest that consumers may finally be ready for this level of personalization and machine input. But at the same time, the technology has only barely begun to deliver on the enormous promise of the category.
Weotta is taking similar science and applying it, not to managing our calendars, but to the problem of discovering the world around. It’s an area that should see massive innovation in the next few years. With a head start and the backing of several social and data experts, the company it’s exciting to imagine what could come out of this company and the field as a whole in the future.