While Facebook forbids third-party app developers from collecting user data without consent, the social platform’s users may find profile information in the hands of marketers nevertheless.
A new tool measuring social influence, Swaylo, requires users to opt in to share information about themselves and their friends and is pitching its services to brands to provide anonymized reporting about their fans.
Swaylo, which has existed as a stand-alone site since January, already has 6.2 million users, giving it access to information about hundreds of millions of their Facebook friends. It has 12 employees and $6 million in funding and was spun off from Threadsy, a 2009 startup that let users see their email, Facebook, Twitter and other social streams in one place.
Swaylo users must opt in to share their Facebook profile information, including their activities, interests, likes, locations, and religious and political views. They also give the app permission to read the same data about their friends. The purpose is to measure their influence inside relatively small social circles, differentiating Swaylo from Klout, which pulls in data from various social feeds.
Swaylo began as an engineering side project within Threadsy about 18 months ago and attracted a million users in its first 10 days, according to founder and CEO Rob Goldman, who folded Threadsy in November because it had failed to grow a user base.
“The way people behave inside Facebook is much more intimate, [since] you’re interacting with close friends and family, as opposed to Twitter which is much more of a public square,” said Goldman. (He noted that a future product update will add Twitter data to Swaylo’s algorithm.)
Swaylo rates users’ influence within their networks on a scale of 0 to 10 and determines whether they’re “connectors” linking disparate groups of people or whether their friends tend to know each other. It also maps out “speed to trends” to gauge whether users are typically informing their networks about musicians, TV shows and public figures, or whether they’re the ones being informed.
Swaylo’s algorithm also infers the probability that a user’s clicking the “like” button prompts friends to do so, according to Goldman. For example, if a friend liked “The Hunger Games” a day after you did, the correlation between the two actions would be higher than if they happened a month apart. But the algorithm accounts for broader activity and wouldn’t attribute a like to friend activity if it had been clicked in a week when the studio heavily promoted the film.
Goldman said he began talking to marketers early this year and is pitching two products. The first is an offering similar to Klout “Perks,” where Swaylo will identify users who are influential about a certain product and enable marketers to send them freebies and promotions. And the second is anonymized reporting on segments of Facebook users marketers are interested in – whether it’s their fan base or people who are signed up to play a social game it’s running, for example.
If the marketer wants to know its own fans better, Swaylo could report on the top likes and interests of a random sampling of 10,000 of them (and on more granular areas like top clothing and household-supply likes) and then compare them to 100,000 randomly chosen Facebook users.
There’s more! To read the full article in Advertising Age, click here.
