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SOLUTION REVIEW: PREDICTIVEINTENT

November 15, 2012

Retail recommendations: red shoes

Maggie’s Red Shoes, by Charles Plaisted
Great recommendations make shopping joyful.


This post is a brief summary of my in-depth analysis of PredictiveIntent, published in a Patricia Seybold Group report in May 2012. The evaluation is based on my Recommendation Solution Evaluation Framework, which details 100+ criteria in 7 categories. It is available as a free download here.
PredictiveIntent was founded in 2009 by Neil Hamilton and Stuart Swift, who have considerable experience in the development and sale of mobile internet technology. On September 13, 2012 PredictiveIntent was acquired by Emailvision. Emailvision can now offer behavioral targeting, personalized customer experiences, and predictive analytics to its clients. The broader range of offerings will strengthen Emailvision in a competitive landscape that is shifting from silo’ed tools to comprehensive platforms for digital marketing. Once the technologies are tightly integrated, PredictiveIntent clients will have streamlined access to a broader range of marketing capabilities in a single interface and relationship.
PredictiveIntent serves 50+ small-medium retail clients operating 82 sites, many of which are multi-country.
PredictiveIntent’s IntentPredictionServer is designed to seamlessly select and deliver content to any channel, to manage customer profiles across channels and visits, and to personalize the customer experience by adapting content, navigation, and menus. PersonalMerchant and PersonalSearch are the solutions built on IntentPredictionServer.
I identified three key strengths of PredictiveIntent’s solution:
1. PredictiveIntent is able to use Facebook data to select more relevant content. PredictiveIntent has the only solution we’ve yet seen that allows customers (end-users, visitors) to opt-out of behavioral tracking and have their behavior deleted. Social data is collected and used when visitors have logged in to Facebook. These two features increase the likelihood that PredictiveIntent’s clients will be in compliance with the emerging “cookie laws,” which require user permission before placing a cookie and collecting user information. Visit PredictiveIntent’s blog for an excellent review of cookie laws and compliance.
2. PredictiveIntent is integrated with ecommerce platforms, third-party test systems, and any content repository. This will be satisfactory to clients who see recommendations as a function of ecommerce: these clients will build their recommendation short list based on the depth of a vendor’s ecommerce integrations.
3. PredictiveIntent’s direct contribution to client revenue is stronger than many of its competitors, making PersonalMerchant more attractive to retailers.

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