RTB House Uses 'Deep Learning' Tech To Model Conversion Probabilities

RTB House, an ad-tech company focused on retargeting, has announced a new model relying on "deep learning" technology to help marketers personalize retargeting and identify customer attitudes and  intentions for more-accurate estimations of the probability of conversion.

The model uses mathematical functions inspired by the neurons in our brains, the company says -- and can apply even to consumers who haven’t clicked ads.

“We live in a world where big data is comprised of endless streams of information about Internet users,” stated Bartlomiej Romanski, CTO of RTB House.

“We’ve used new technologies to construct an algorithm which, by using recurrent neural network (deep learning architecture), is able to accurately predict how Internet users will behave, what purchase intentions they have, and what decision they will take.”



1 comment about "RTB House Uses 'Deep Learning' Tech To Model Conversion Probabilities".
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  1. John Grono from GAP Research, October 11, 2016 at 7:36 p.m.

    Wow.   All we need now is a recurrent neural network inspired by our brains neurons that can apply to consumers who haven't got computers or smartphones.   Get to it lads!

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