Predictive Analytics in B2B Marketing: Using Data Decisively, at Every Stage of the Funnel - eMarketer
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Predictive Analytics in B2B Marketing: Using Data Decisively, at Every Stage of the Funnel

eMarketer Report

By: eMarketer

Published: April 21, 2016

Jump to: Executive Summary | Table of Contents | List of Charts

Executive Summary

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.

  • As B2B marketers become more data-driven, predictive analytics allows their methods to become more fine-tuned and sophisticated.
  • Predictive models, built from past customer touchpoint data, guide marketers by estimating which of their actions are most likely to pay off in the future.
  • Using this and other data allows for more efficiency at all points of the marketing funnel. Common applications include finding new prospects, lead scoring and increasing lifetime customer value through upselling and churn prediction. Other uses, such as personalization, still need refinement.
  • Measuring the return on investment (ROI) of predictive marketing can be a challenge for B2B brands, but benchmarking past performance or A/B testing against strategies that didn’t use predictive marketing indicate the method is adding value.
  • In general, B2B companies are slowly adopting predictive marketing and using the technology within their marketing technology stack. However, it remains uncertain whether this is the year it goes mainstream.

"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."

Table of Contents

Data’s Evolution in Marketing: A Predictive Future

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Predictive Marketing: Putting Insights into Action

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The Current State of B2B Predictive Marketing Adoption

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Editorial and Production Contributors

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10 charts are included in the full report:

Predictive Analytics in B2B Marketing: Using Data Decisively, at Every Stage of the Funnel

Primary Objective for Big Data/Unstructured/Predictive Analytics According to US* Marketing Professionals, July 2015 (% of respondents)

Data’s Evolution in Marketing: A Predictive Future

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)

Predictive Marketing: Putting Insights into Action

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)

The Current State of B2B Predictive Marketing Adoption

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)