

Connotate is a provider of social media and web data monitoring software that lets companies observe trends that are relevant to their business, and gain insight on consumer behavior. This translates into the ability to measure the reaction of customers to merchandising and marketing related changes, among other things.
And this week, the firm decided to extend its portfolio with the acquisition of competitor Fetch for an undisclosed amount. The startup is also a data aggregation service that correlates with Connotate, and evidently in a way that justified an investment on behalf of its new partner company.
“Fetch is very excited to combine our information extraction, integration, and data analytics solution with Connotate’s monitoring, collection and analysis solution,” said Ryan Mullholland, Fetch’s former CEO and now President of Connotate. “Our similar product and business development histories, but differing go-to-market strategies creates an extraordinary opportunity to fast-track the creation of world-class proprietary ‘big data’ collection and management solutions.”
Big data is becoming extremely lucrative, and not just for the pioneers in the Hadoop ecosystem. Alex Williams picked up a freshly published IDC report today that forecasts the analytics space will grow to $16.9 billion in the next three years alone – an astonishing figure considering this market was worth only $3.2 billion in 2010.
Commercial Hadoop distributions will undoubtedly account for a very big portion of that, alongside platforms such as the one offered by Connotate and ClickFox. The latter company has developed itself a specific niche within the big data picture, and focuses more on customer satisfaction and technical support efficiency. One of ClickFox’s biggest customers is carrier Sprint, according to a case study I covered earlier this week, and it’s interesting to see how an enterprise of this scale is leveraging an analytics solution.
Sprint has its own resident data scientists, who process the raw data and move it to the business users who need to impalement the insight gained to achieve the impressive figures the company provided with the use case.
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