DataSift nabs $7.2M, moves into its own SF offices

Twitter filtering tool continues to show its growth, seven months after launch, with new funding

Technology trends and news by Krystal Peak
May 2, 2012
Short URL: http://vator.tv/n/264c

DataSift, a tool helping enterprises aggregate and find insight from Twitter, has just secured $7.2 million for its Series A round of funding.

This funding comes from its existing investors GRP Partners and IA Ventures and will be used to accelerate company growth as more businesses sign on to use its filtering services. With this funding announcement, DataSift is also announcing its move into a new office in San Francisco’s SOMA district. Previously, DataSift was housed in the communal tech headquarters of the Founders Den.

“DataSift has been flooded with interest from both customers and investors since our launch in November. We are seeing incredible demand from a wide variety of sectors of customers, including Social Media Monitoring, Business Intelligence, News and Finance,” said Rob Bailey, CEO. “While we were not actively looking for financing, we were lucky to receive a fantastic offer from our existing investors that will enable us to continue building our business without the distraction of raising a funding round. GRP and IA Ventures have been amazing to work with. They’ve been instrumental in helping us achieve the success we’ve had so far and we are excited to continue working with them.”

DataSift, has spent roughly the last four years creating a software that would allow simple coding commands to filter through the billions of tweets and organize them for easier analysis and action.

The San Francisco and UK-based company is one of only a handful of companies that has access to the entire Twitter fire hose (not just the tweets but the information on each user's profile and Twitter history.)

Since its inception, DataSift has gathered together more than $15 million in funding from various investors and financial groups and is gearing up to staff aggressively within the U.S.

The co-founder and CTO Nick Halstead has been a passionate coder since he was a child and wanted to harness the immense information available on social platforms, such as Twitter, but it took a while to get the system to the point were it could launch.

What it does

A client or company that wants to track a particular trend or discussion topic through Twitter would create an account with DataSift under one of two payment structures:

1. On demand -- where the user will pay for the data that returns from each search and meets the criteria set forth. This pay system would often look like $0.10 per thousand tweets returned.
2. Prepaid package -- where you choose the budget you wish to spend and limit the number of searches you aggregate from.

Depending on the level of difficultly and the magnitude of the searches a company is interested in, either someone within the user's company can manage the searches or a DataSift employee would spearhead the project.

If a company, say Starbucks, is interested in getting feedback about a new special they are running in particular regions, a DataSift search can be created that target geographical areas, key search terms and then analyzes whether the responses are positive or negative. The data can also understand and sort through 31 languages.

Overall reports on the general public sentiment or the amount of feedback for a given search can be found in mere moments and then, if the client is so inclined, they can dig deeper and look at each individual response or organize them based on gender or location or the level of influence they have on Twitter.

How DataSift has grown over the last few months

Just a few weeks ago, DataSift announced that it was able to search back two years in the Twitter firehose, allowing for more research on a topic over an extended period of time. Prior to this DataSift could only capture results since its inception for filtered responses.

Earlier this month, DataSift announced a partnership with NewsCred in April that brings together the troves of data from Twitter as well as 750 news sources so people can track the public conversation on a variety of topics, nearly in real time.

This new service comes just a month after DataSift launched Historics, a product that gives its users the ability to search through the Twitter firehouse back to January 2010. 

The young San Francisco-based company focused on social data tracking and analysis created this partnership with NewsCred to help its users access even more information about any topic or keyword that they may wish to search.

NewsCred is a platform that connects publishers and brands and includes content from The EconomistThe GuardianForbes and Bloomberg

For instance, if anyone wanted to track the conversation about the Facebook IPO from the time of the announcement onward they would be able to look at each news article in the NewsCred data base and see, overtime how often it was shared on Twitter and if the sentiment of the tweets were positive or negative. The researcher could also see which articles were most shared, the times they gained virility and if there were any other trends such as age demographics of those sharing or geographical location of the people sharing.

Here is the evolution of the Facebook IPO discussion across NewsCred articles, as they are shared via Twitter. As you can see, one of the first articles that broke the story got the most shares (denoted by the fact that the graph circle is the largest). And you can also see that the general sentiment about the IPO is positive since it is dark blue. 

Tim Barker, DataSift’s CMO, explained to me in an interview that this new tool can really help identify factors in what connects with a given audience and how to engage a response from different demographics.

“Companies that want to watch breaking news can see the conversation and sharing of a single article or topic will be able to better understand news diffusion with these graphs,” Barker said. “ And publishers no longer have to passively monitor clippings about their companies – they can see as different conversations are started and how they morph and evolve.”

The possibilities are wide open, and since more than half of the people that have already started working with DataSift were really interested in historical data, the company got to work archiving that information for better search options and results (which usually could only go back in time a month or to the start of the company.)

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