Brandwatch now offers three-year searches of Unlimited Historical Data

Social intelligence provider Brandwatch launched this week its Unlimited Historical Data for searching online conversations and news over the recent past.

The UK-based company says this new offering is the fastest tool for custom historical analysis of online news and conversations.

Marketers can search by topic without a limit on the number of queries over three years of historical data, with results returned in seconds or minutes. The capability is built around Brandwatch’s new use of the Twitter Decahose of data, which makes available 10 percent of tweets on any topic over the past three years.

Brandwatch then extrapolates from that sample to estimate the total number of posts on a topic, just as a pollster might make conclusions about the relative standing of political candidates from a representative sample.

The Twitter Decahose is also available to other social intelligence platforms, but Brandwatch stores the three-year sample internally and then combines it with its massive database of 80 million other online sources, including other social networks (such as Facebook, Instagram, Tumblr and YouTube), as well as news sites, review sites, forums, company sites and others.

Here’s a screen shot for a search over historical data looking for positive, negative and neutral mentions of “I want a car”:

Before implementing Unlimited Historical Data, Product Marketing Manager Phillip Agnew told me, customers interested in a topic could search social and news sources in real time over a specific period of time — say, from now ’til June. Or they could search within other customers’ past searches, which were also real-time searches from now to a future point in time.

The non-Twitter data is available for real-time searches (now ’til whenever) or for new searches of data that other customers have pulled in their past real-time searches.

It was possible previously to search historical Twitter data through other feeds from that social network, Agnew said, but it was slow and very expensive.

He recalled that Unilever, which now owns Ben & Jerry’s ice cream, wanted to see how seasonality affected sales.

It was able to conduct very fast repeated searches over three years of Unlimited Historical Data, he said, resulting in about one million mentions. Sales rose and fell, but they weren’t always in sync with warmer seasons.

By overlaying weather data and quickly running repeated searches, he said, the company found that rain was generating sales, regardless of season.

“When it was raining,” he said, “people would tweet about purchasing a tub of Ben & Jerry’s.”

[Article on MarTech Today.]

About The Author

Barry Levine

Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.