Monetate Introduces Three-Part Predictive Decisioning Platform

Marketing personalization provider Monetate has launched Prediction Decisioning, a platform designed to help marketers deliver personalized campaigns that leverages a combination of machine learning sophistication and the "human element of marketing," according to David Brussin, chief product officer at Monetate.

The Decisioning platform is made up of three components—Predictive Analytics, Predictive Audience, and Predictive Action. Together, the tools will make one-to-one marketing a more attainable reality with a flexible and comprehensive approach to personalization. "One-to-one marketing is daunting. It's a really intimidating concept for marketers," Brussin says. "But the alternative is just a one-size-fits-all approach, and today, that approach is largely being rejected in favor of deep personalization," he adds.

Personalization at scale is challenging, and to achieve it, some marketers have even gone the route of relying on machine learning for campaign effectiveness. While machines can deliver the scale that marketers are looking for, there's always a need for a human touch, and Monetate's decisioning platform brings the human and machine components together seamlessly, Brussin says. "At Monetate, our philosophy is that you can't replace the passion and creative energy of a marketer. With predictive decisions, we're surrounding the energy that the marketer brings with science to focus that energy and amplify the effect," he explains.

The first element of the decisioning engine is Predictive Analytics, which helps marketers determine the next important group of people to pay attention to. The tool not only prioritizes groups, but also provides context on what is known about the group, and how it's different from other audience groups. The two other solutions, Predictive Audience and Predictive Action, are designed to suit two different styles of marketing campaigns.

Predictive Action is built for marketers who prefer to think of the experience and content first. In this case, the marketer's challenge is to determine the best ways to present certain types of content to a specific group of people. "With Predictive Action, Monetate can figure out and predict the fit of each piece of content to an individual," Brussin says. Predictive Audience, on the other hand, is for marketers that start with people rather than content. The tool zeroes in on a defined audience set and seeks to identify the individuals who make it up. Predictive Audience and Predictive Action are an extension of the Predictive Analytics component, and can work simultaneously, Brussin says.

Monetate client Johnston & Murphy, for example, has used the technology to market more effectively to its female customers. The company is primarily a men's clothing and accessories retailer, but has women's merchandize as well. Johnston & Murphy's marketing team knew that multiple female audiences were out there and used Predictive Audience to identify who those women were. "It's about getting a deeper understanding of exactly who is in an audience set and delivering very personalized content to those people," according to Brussin. "It's scalable, but still requires the creativity that marketers bring to the table."

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