Given the importance of data in today’s marketing landscape, predictive analytics is becoming a powerful tactic for marketers. Predictive analytics—software that enables users to make predictions based off data—can help marketers make the most of the wealth of data available to them.
For lead generation alone, predictive analytics can make a difference: Radius’ 2016 B2B Demand Generation Benchmark Study survey uncovered that B2B marketers that applied predictive analytics to demand generation met their objectives 55% of the time, compared to 30% for those not using predictive analytics.
“The marketing role is, now, more than ever, that of a revenue driver,” Katie Gregorio, senior director product marketing at Radius, said. “Marketers are increasingly tasked with helping sales improve close rates.”
Software analytics company New Relic knows the value of predictive analytics. The company teamed up with Infer’s predictive sales and marketing platform to achieve impressive results. Using Infer’s applications, New Relic was able to prioritize and forecast all of its sales and marketing efforts, ultimately seeing an almost 10x conversion for top leads.
“As a result of implementing predictive analytics into our sales and marketing stack, the marketing team now has insight into, and can more effectively target, the most valuable personas and segments for greater impact,” Baxter Denney, VP of Growth Marketing at New Relic, told Marketing Dive.
New Relic is active across the marketing board with services including paid search, banner ads, retargeting campaigns, and social and physical community events and conferences. Denney that predictive analytics helped the company identify potential prospects for its online trials and drive other types of engagement.
“Our sales team needed helping keeping pace with a rapidly expanding sales pipeline,” Denney said. “Using Infer’s predictive scoring, we were able to immediately identify and convert great leads that had been buried in our nurture database.”
New Relic used Infer to create fit and behavior scores based on certain conversion types among its customer base and how those types relate to the likelihood of conversion. The entire process included a joint effort between the marketing and sales teams, indicating the value of organizational alignment when putting data to use.