The four Cs of B2B targeting: Using company, customer, channel and contextual data to shrink the audience bullseye

The combination of highly focused audience populations and much more precise industry, account and buyer persona-based segments make using deterministic approaches to plan, target, deploy and optimise media and marketing programmes in a business-to-business (B2B) environment a major challenge. Recent media benchmarking data confirms that hyper-pareto economics of audience targeting in B2B marketing can dramatically improve the yield and business impact of investments in paid, owned, earned and shared media programmes. This paper builds on existing academic research into audience targeting by adding qualitative interviews with 100 B2B marketing leaders and specific case examples from Terminus to examine how leading marketers are using probabilistic analytical approaches to shrink the audience bullseye and improve the business impact of media. The paper explores how B2B marketers are taking advantage of advances in analytics and artificial intelligence (AI) to combine company, customer, channel and context data from a variety of internal and external sources to model highly targeted and accurate audiences and segments. It provides a blueprint for how the best marketers are using internal company, opportunity and sales coverage data from customer relationship management (CRM) and first party customer engagement data from paid, owned, earned and shared digital marketing channels as the foundation for targeting audiences and identifying signals of interest, consideration, response and intent. It shows how marketers can further supplement this targeting data foundation with third party contextual data around account structures, audience graphs and buyer intent to continuously improve targeting accuracy with closed loop analysis of customer response data. Shrinking the audience bullseye in this manner allows marketers to improve the financial impact of marketing investments by a third or more, by targeting marketing programmes and resources to prospects in specific accounts, job roles and sales territories while zeroing in on the fraction of prospects who are actively in the market to buy at any time.

Authors

Institutions

Publication Details

Journal
Applied marketing analytics
Published
2024-12-01
DOI
https://doi.org/10.69554/zubn7528
Citations
1
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
1.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The four Cs of B2B targeting: Using company, customer, channel and contextual data to shrink the audience bullseye

R Howarth, Stephen G. Diorio
1 citations
Applied marketing analytics
Digital Marketing and Social Media
1.13
article

The four Cs of B2B targeting: Using company, customer, channel and contextual data to shrink the audience bullseye

R Howarth, Stephen G. Diorio
article en
1 citations

Abstract

The combination of highly focused audience populations and much more precise industry, account and buyer persona-based segments make using deterministic approaches to plan, target, deploy and optimise media and marketing programmes in a business-to-business (B2B) environment a major challenge. Recent media benchmarking data confirms that hyper-pareto economics of audience targeting in B2B marketing can dramatically improve the yield and business impact of investments in paid, owned, earned and shared media programmes. This paper builds on existing academic research into audience targeting by adding qualitative interviews with 100 B2B marketing leaders and specific case examples from Terminus to examine how leading marketers are using probabilistic analytical approaches to shrink the audience bullseye and improve the business impact of media. The paper explores how B2B marketers are taking advantage of advances in analytics and artificial intelligence (AI) to combine company, customer, channel and context data from a variety of internal and external sources to model highly targeted and accurate audiences and segments. It provides a blueprint for how the best marketers are using internal company, opportunity and sales coverage data from customer relationship management (CRM) and first party customer engagement data from paid, owned, earned and shared digital marketing channels as the foundation for targeting audiences and identifying signals of interest, consideration, response and intent. It shows how marketers can further supplement this targeting data foundation with third party contextual data around account structures, audience graphs and buyer intent to continuously improve targeting accuracy with closed loop analysis of customer response data. Shrinking the audience bullseye in this manner allows marketers to improve the financial impact of marketing investments by a third or more, by targeting marketing programmes and resources to prospects in specific accounts, job roles and sales territories while zeroing in on the fraction of prospects who are actively in the market to buy at any time.

Applied marketing analyticsVol. 10(3)
Software (Spain) (ES)
Openalex Percentile: Top 14%
Digital Marketing and Social Media
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.