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At DEMO, Quantivo Challenges BI's Status Quo


Posted by John Foley, Sep 10, 2008 01:52 PM

At the DEMO conference, Quantivo showed a new data-mining-as-a-service for retailers. The company promises "super fast" business intelligence at a fraction of the cost of in-house data warehouses.


Quantivo unveiled Quantivo Retail, an on-demand service with some fairly sophisticated capabilities. They include Market Basket Analysis for evaluating the contents of a shopping cart, Customer Lifetime Value Analysis for assessing product purchases over time by repeat customers, Segmentation Analysis for uncovering demographic purchase patterns, and Affinity 360 Finder, which Quantivo describes as performing “an exhaustive search for all relevant affinities.”

In his DEMO presentation, which I watched via video replay, new CEO Brian Kelly says Quantivo took 2.5 years’ of transaction data from an unnamed retailer—comprising 20 million customer records and nearly 1 billion transactions—and made that data available for analysis within four days.



It’s a sign of the times that such sophisticated BI capabilities are offered as an on-demand service, including a “quick start” option and monthly subscriptions. DEMO lists SAS, SPSS, MicroStrategy, Oracle, SAP, Microsoft, and IBM as Quantivo’s competitors. In other words, it’s going up against the software industry establishment, which is tough in any niche, but even more so in BI.

Quantive was founded in 2003 as Quaris. In January of this year, it announced that founder and CEO Thomas Perry was resigning and that he was being replaced by Kelly, a former executive VP with Kana. At the same time, the company disclosed that it had secured $7.1 million in Series A funding from Foundation Capital and Partech International.

Whether Quantivo can actually put a dent in the market share of BI’s big boys remains to be seen. It certainly represents a disruptive force if it can deliver on its promise of fast, easy, and cheap data mining. Of course, given the well known complexities and nuances of data mining, that may be easier said than done.

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