SalesPredict, a predictive B2B marketing solutions provider, announced the release of its new Predictive Revenue Automation platform, which enables users to launch fully-automated predictive advertising campaigns via a new integration with AdRoll.
The integration will allow marketers to use SalesPredict’s predictive scoring, segmentation and insights to pinpoint the best potential leads, and launch a campaign to target them using display networks and Facebook advertising. Twitter integration is planned for the near future.
The additional capabilities are part of the company’s efforts to “put predictive at the top of the funnel” and help marketers “bring in the highest quality leads from the very start,” said Sahil Mansuri, SalesPredict Vice President of Product Marketing, in an interview with Demand Gen Report. “A B2B marketer is handcuffed by the limited options inside a B2C channel like Facebook or Twitter. We’re solving that challenge.”
By combining predictive analytics with a company’s internal CRM and marketing automation system data — as well as the open Web and third-party data sources — SalesPredict aims to provide scores and insights that will allow B2B marketers to target the right prospects from the beginning of the buyer journey, and in turn drive revenue more effectively. “You’re only spending money on serving advertising to people you know beforehand are A and B leads,” Mansuri added.
Integrating predictive into more key marketing functions can allow marketers to align with sales for a revenue-centric approach, said SalesPredict Co-founder and CEO Yaron Zakai-Or, in a release. “Instead of using predictive scoring and insights to filter lead for quality retroactively, savvy marketers can now use predictive at the top of the funnel and throughout the customer journey as a lens through which to view all interactions — to define which accounts and leads to pursue, to effectively target demand gen and email campaigns, and eventually, to decide which content to send prospects and which events to participate in.”
