Increase Campaign Precision and Relevancy with Dynamic Predictive Audiences

Chicago, Illinois, USA – January 30, 2018 – simMachines, Inc., the leader in Explainable AI / Machine Learning applications, announces the launch of their latest product—Dynamic Predictive Audiences designed for data companies, publishers and media platforms. In just 5 clicks and 3 minutes, Dynamic Predictive Audiences generates audience segments across the U.S. population that are both immediately actionable and highly predictive of a customer’s behavior—all based on an advertisers first party data matched to an audience seller’s regional or national footprint.

simMachines’ proprietary and unique customer segmentation software, Dynamic Predictive Audiences specifies the contextually weighted factors associated with the predicted behavior of each of the dynamically generated segments. With Dynamic Predictive Audiences, advertising clients can benefit from more granular and precise machine generated audience insights, enabling them to achieve highly personalized, relevant messages and offers that consumers have come to expect.

With ad spend waning due to challenges with transparency in digital advertising, Dynamic Predictive Audiences from simMachines opens up new opportunities for audience sellers to provide their clients with the power of rich, transparent audience insights that inform their ad campaigns with the relevant drivers of predicted purchase behavior vs. descriptive characteristics only. Marketing campaigns and advertising programs can now benefit from the precision of audience segments that have both predictive power and contextual relevancy.

According to a new Forrester Research study, “Capture the Customer Moment with Dynamic Predictive Segmentation¹,” 50% of marketing leader respondents cited the risk for not adopting dynamic predictive segmentation to be the lack of precision in executing campaigns, 40% cited the inability to predict what a customer wants during an interaction and 34% the inability to predict with enough precision the next best offer or recommendation. The research further reveals the potential increase in value that this customer segmentation software can provide to advertisers.

“Today’s most sophisticated agencies and demand-side platforms are using classic machine learning techniques to identify prospects with a high likelihood to purchase. While this technique identifies the right customer to target, it does nothing to reveal the best message for that customer. For example, one customer may be particularly enamored by a luxury car’s exterior while another may be more interested in the engine under the hood. Dynamic predictive segmentation reveals these customers’ differing preferences, so agencies can exploit them by delivering the right content to each¹.”

“Data companies, publishers and media platforms have a huge opportunity to increase the value of the data they are providing, by offering clients dynamically segmented predictive vs. descriptive audiences that provide not just state of the art machine learning predictions, but also the contextually relevant factors associated with those predictions”, says Dave Irwin, CMO of simMachines. “Not only does this application provide a significant upgrade in precision and relevancy, it does so at a much greater rate of speed than is currently possible with traditional statistical approaches, allowing providers to run “what if” scenarios on demand for their clients to find new previously undiscovered opportunities.“

¹Capture The Customer Moment with Predictive Dynamic Segmentation, Forrester Research, January 2018