Software // Information Management
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12/17/2013
09:06 AM
Doug Henschen
Doug Henschen
Commentary
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Real-Time Prediction, Big Data Scale: Impossible Dream?

WibiData challenges IBM, Oracle, and SAS by combining vast customer history as well as real-time behavioral data to generate personalized recommendations.

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D. Henschen
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D. Henschen,
User Rank: Author
12/17/2013 | 11:05:22 AM
There are plenty of other options...
Beyond all the well-known vendors mentioned above, plenty of integrators and other startups are working on combining big-data analytsis and real-time prediction. WibiData is working toward productizing this capability and making it less of a one-off, reainvent the wheel proposition. It still requires plenty of development work on the app side and data science on the analytics side, but at least you're not starting entirely from scratch. 
Tullio Siragusa
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Tullio Siragusa,
User Rank: Apprentice
12/17/2013 | 4:11:34 PM
Re: There are plenty of other options...
A framework to develop apps (wibidata) may help financial services firms do it themselves. An enterprise big-data vertical software application providing a micro-contextual segmentation consumer dossier at the touch point within the existing CRM workflow, tying in both structured/unstructured enterprise and perpetually connected consumer data semantically is underway by SegONE Inc.
D. Henschen
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D. Henschen,
User Rank: Author
12/17/2013 | 4:29:01 PM
Re: There are plenty of other options...
Tullio,

Thanks for the comment. "Micro-contextual segmentation consumer dossier at the touch point within the existing CRM workflow..." is quite a mouthful, but what is it? Is that synonymous with one-to-one-predictive offers? Wibi's claim is that's it's getting away from segments and predicting the right offer for individual customers. The latest interaction info is even more relevant, because if the offer is for a TV, but they just bought one, what good it the prediction?
Tullio Siragusa
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Tullio Siragusa,
User Rank: Apprentice
12/17/2013 | 4:38:00 PM
Re: There are plenty of other options...
It is virtually impossible today to segment all the customer data into a one:one relationship "real time". It is also unmanageable especially in banking with so many data silos.  The idea behind SegONE is to do it near real time at "the touch point" with the customer - be it a visit to a branch, a call to a customer service center, and online transaction, or invoking a programmatic buy via an agency trading desk to present an ad to a consumer that is shopping for a car without it being creepy, that reminds them they are a customer and an offer that is relevant to them is available.

The question to answer about your scenario is why did they just buy a TV?  The transaction data only shows behavior after the fact.  The perpetually connected consumer data can tie in the why. Did the person just get a promotion a month before?  When was the last purchase they made for a TV?  When you triangulate both the context for what may trigger the purchase (got a promotion), with the history of transactions (is the customer due to upgrade now that they are making more money?) - you have context you did not have before.  This is obviously a very elementary view into the semantics of both sets of data that can help a bank gain knowledge on how to engage in relevant ways with each individual customer such as offering a bigger credit line, or loan, etc. 
Laurianne
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Laurianne,
User Rank: Author
12/17/2013 | 12:50:40 PM
Real-time shopping intent
I always smile when i log into Amazon and it suggests "a little something for you," except it is based on gift purchases I have made for boys under the age of 10. So WibiData promises to figure out I am shopping for a gift, not for myself? What are the clues?
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