IBM - FEATURED ARTICLES
May 02, 2012
IBM Picks Up Tealeaf Technology, Looks to Predict Behavior
By Steve Anderson, Contributing TMCnet Writer
IBM (News - Alert) has made an agreement with Tealeaf Technology to buy their entire company for an undisclosed sum. While details on the terms of the agreement haven't been announced, the sale is expected to complete sometime in the second quarter of this year. Just how much IBM will be paid in cash, stock or any combination is unknown – the mere substance of the deal is impressive by any measure.
Tealeaf Technology, as the name implies, has a line of software which allows companies to analyze customer behavior and react accordingly. Tealeaf's software can perform a variety of functions to that end, including analyzing reactions to mobile marketing in which customer sessions ended prematurely.
From there, a business can make relevant changes with an eye toward improving customer sessions in the future, as well as possibly recapturing lost revenue when customers ended their sessions early.
IBM has lately made several purchases geared toward an area they refer to as "smarter commerce" having made three such acquisitions in the last year, and six since 2010 as part of a total investment of $3 billion in the field. IBM looks to use the "smarter commerce" tools to improve its online analytics offerings, and its automation offerings, to provide businesses with better tools toward improving their bottom line, an all too necessary part of any business climate, especially a poorer one like we're in now.
Of course, predictive software like Tealeaf Technology's model in the hands of, say, IBM's sublimely potent Watson supercomputer, might yield some equally impressive results on a scale previously unimagined, though whether or not IBM has an eye to reverse engineering Tealeaf Technology stock for use with the Watson is unknown and may not even be feasible.
Still, it's a very interesting notion, and will bear watching to see just what IBM does with its combination of "big iron" hardware and predictive software. They may eventually have a better idea of what users will do in the future than even the users themselves do at the present.
Edited by Braden Becker
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