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Published: April 21, 2016
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A typical business-to-business (B2B) brand now has a staggering amount of data in its arsenal, and the marketing department’s goal is to use that data to deliver more effective results than ever before. Enter predictive marketing, which uses machine learning to deliver more accurate insights about how best to encourage sales from existing and new customers.
"Goals for predictive analytics span across the customer funnel. A VB Insight study found that 33% of US marketers polled cited customer acquisition as the most important, but four other measures followed closely behind."
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Primary Objective for Big Data/Unstructured/Predictive Analytics According to US* Marketing Professionals, July 2015 (% of respondents)
Extent to Which Their Company Practices Select Areas of Data-Driven Marketing According to US Ad/Marketing Professionals, July 2015 (% of respondents)
Data: The Engine Powering Predictive Technology
Types of Data Used for Predictive Marketing According to Marketing Executives in North America, April 2015 (% of respondents)
US B2B Marketing Professionals Who Are Scoring Their Leads, Sep 2015 (% of respondents)
Most Essential Criterion for Personalization Success According to US Marketers, Jan 2016 (% of respondents)
Ways in Which Marketing Executives in North America Use Predictive Marketing Technologies, April 2015 (% of respondents)
Measuring Predictive Marketing’s Value
Effect of Predictive Analytics on Their Business According to US B2B Marketing Decision-Makers, Aug 2015 (% of respondents)
Metrics Used to Measure the Success of Predictive Marketing According to Marketing Executives in North America, April 2015 (% of respondents)
Usage and Awareness of Predictive Marketing at Their Company According to US B2B Marketing Professionals, Sep 2015 (% of respondents)
Tactics that Occupied vs. Will Occupy Their Time/Resources According to US Digital Marketing/Media Practitioners, 2015 & 2016 (% of respondents)
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