Twitter will tell brands more about people who see their tweets, visit their sites

Copyright Aaron Durand (@everydaydude) for Twitter, Inc.

Twitter knows a lot about a person based on their Twitter account. Like whether they’re male or female, what language they speak, what kind of music they like, which TV shows they watch, what major city they live in and who their cell service provider is. Now Twitter is making it easier for more brands to access that information.

On Tuesday Twitter-owned data platform Gnip officially opened up its Audience API so that any brand can use the analytics tool to get a cheat sheet of demographic and interest data about any group of Twitter accounts. And it’s making it easier for any brand using the tool to find out about people who may have come across the brand’s tweets or stumbled onto its website.

Before we get into the kinda creepy stuff, it’s worth noting that brands won’t be given this data specific to individual accounts. The data will be anonymized and aggregated based on a defined group of at least 500 Twitter accounts. So it’s not like a brand will be able to use the tool to find out that Tim Peterson is a male who lives in Los Angeles, likes surfing and watches “Pretty Little Liars” (not like I would ever admit that on Twitter). Instead Twitter will say that some percentage of the defined audience group is male, another percentage lives in Los Angeles, another percentage likes surfing and another percentage watches “Pretty Little Liars.”

Twitter first unveiled the tool in October 2015 but limited its availability and usage. For example, brands could only get this audience data about people if a brand had the IDs connected to those individuals’ Twitter accounts. It’s not hard to get someone’s Twitter ID — Twitter has an online tool and instructions for how to get the IDs for everyone who follows or is followed by a given Twitter account — but it was enough of a hassle to be a limiting factor.

Now Twitter is making it easier for brands to pull this information about anyone who follows a specific Twitter account, was shown a brand’s tweet, signed up for brand’s email newsletter or simply used a brand’s mobile app or visited its site.

In addition to now being able to create audience segments of people who follow any public Twitter account without having their IDs, brands can create audience segments of anyone who was shown a brand’s unpaid tweet within the past 90 days. Brands will be able to deep-dive into that audience to create smaller segments of the people who engaged with a brand’s tweet by clicking on it, liking it or retweeting it.

Brands can also pull this data about people who are in their customer databases. A brand would just need to upload a list of people’s email addresses, phone numbers or the mobile advertising IDs that brands can collect when someone uses their mobile app. And if a brand has placed Twitter’s Tailored Audience tag on its site — which Twitter uses to connect site visitors to their Twitter accounts — they will be able to create audience segments of those site visitors as well.

Twitter isn’t adding any new types of demographic or interest data that it hasn’t already exposed during the Audience API’s beta period. But here’s a quick refresher on what categories of information brands will be able to access.

Gender: Twitter will tell brands what percentage of an audience group is male and what percentage is female. Twitter guesstimates people’s gender based on their Twitter profile names and the accounts they follow and then cross-references that with data from third-party companies, who may have a better idea.

Language: Twitter will tell brands what percentage of an audience speaks certain languages. This is based on the language set in someone’s Twitter profile settings and the language(s) they use when tweeting.

Interests: If Twitter thinks you like books — because you follow @Shteyngart, live-tweeted your way through David Sedaris’s latest memoir or like everything @paulocoehlo tweets — it’ll group you in the percentage of a brand’s defined audience who are interested in books and literature and a sub-category of people who are interested in biographies and memoirs. There are other interest categories like music and radio, which has “alternative” as a sub-category.

TV: Brands can find out which TV genres or specific shows a defined audience is interested in. Again this is a guesstimate based on what people tweet, who they follow and what tweets they interact with.

Location: Brands can find out where the people who make up a defined audience are in the world, by country, state/province or designated market area (which roughly translates to major metropolitan area). Twitter figures out where people are currently and where they’ve been recently by checking their web IP address, mobile GPS signal, mobile wifi signal and the location attached to a person’s tweets (assuming a person attaches a location to their tweets).

Device and wireless network: Brands can find out what share of a defined audience is using an Android device, iOS device, desktop computer, mobile web or even a BlackBerry. They can also determine what percentage subscribe to AT&T, Verizon or some other carrier. Twitter collects this data through its mobile app.

About The Author

Tim Peterson
Tim Peterson, Third Door Media's Social Media Reporter, has been covering the digital marketing industry since 2011. He has reported for Advertising Age, Adweek and Direct Marketing News. A born-and-raised Angeleno who graduated from New York University, he currently lives in Los Angeles. He has broken stories on Snapchat's ad plans, Hulu founding CEO Jason Kilar's attempt to take on YouTube and the assemblage of Amazon's ad-tech stack; analyzed YouTube's programming strategy, Facebook's ad-tech ambitions and ad blocking's rise; and documented digital video's biggest annual event VidCon, BuzzFeed's branded video production process and Snapchat Discover's ad load six months after launch. He has also developed tools to monitor brands' early adoption of live-streaming apps, compare Yahoo's and Google's search designs and examine the NFL's YouTube and Facebook video strategies.