MyBuys Acquires Veruta, Offers Predictive Remarketing

MyBuys recently introduced Predictive Remarketing, a consumer profile-driven remarketing suite designed to drive higher response rates from consumers across all channels including display advertising, email and direct mail.

The company also recently announced the acquisition of online remarketing provider Veruta, a move designed to power the display advertising component of the new suite with its advertising platform.

"Veruta has two key elements," notes Bob Cell, CEO or MyBuys. "A dynamic ad delivery capability, and a real-time spend optimization solution. By combining these two elements with MyBuys personalized recommendations, retailers get the one-two punch: more targeted ads getting to consumers through the most cost effective ad network. No other remarketing or brand advertising solution on the market has the combination."

MyBuys said the Predictive Remarketing solution is helping its clients drive more than 500% improvement in click-through rates (CTRs) and over 50% improvements over all other remarketing offerings. MyBuys solutions are designed to predict what shoppers want to buy and present multiple options to each consumer through display ads.

In an interview I did with Bob Cell at the Internet Retailer Conference in Chicago in June, he explained "We show targeted offers to customers in ways that others can’t. We are the only ones who proactively send an automated, personalized, customized remarketing e-mail to consumers, which looks like it is coming from the merchant. Everyone else is in the correlation business, finding connections between consumers and products by what other consumers have tended to do in the way of cross-correlated purchases: someone bought this, then they bought that. It’s product associations, and you don’t have to know anything about the products. We do something entirely different. We break down the attributes of relevance of every product: size, material, fabric, brand, price point, etc. You can do a statistical analysis of these attributes, which we do within an array of category structures based on the range of merchandise the merchant offers.

"By working at the attribute level, we are much better able to analyze what trade-offs and decisions consumers made that led to the actual purchase decision. It also means that we can apply attribute analysis to virtually any other product. Products come and go, but they all share certain attributes. So while others build models from the outside in, at the consumer level, we build models form the inside out, at the attribute level.

"It also means that our models are not just retrospective, but truly predictive. We gather the data by analyzing every click on every purchase on every consumer, and we can add in off-line purchases as well. That allows us to send an e-mails with offers based on predictive modeling of all the attributes of a consumer’s past purchases, not based on correlations of the purchases of other consumers. And we also factor in demographic attributes of the consumer – age, gender, and so – to add a further dimension to the analysis. It truly is how the ideal retail sales person intuitively approaches each of their best customers, based on a grasp of the attributes of what that person has bought before."