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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.
The full article is available to subscribers to the journal.
Author's Biography
Stephen Diorio is an established authority in commercial transformation, go-to-market strategy and revenue operations. For over 30 years, he has helped over 100 leading brands to re-engineer their commercial strategies, systems and operations to become more data driven, digital and accountable. Mr Diorio has authored research papers and books that connect growth investment to firm value including: ‘Revenue Operations: A New Way to Align Sales and Marketing, Monetize Data, and Ignite Growth’ (Wiley, 2022).
Rich Howarth As Chief Executive Officer for Terminus Software, Mr Howarth has helped create the account based marketing category and develop revenue marketing products that enable companies to more efficiently go to market. Over the last 30 years, Mr Howarth has held executive positions across engineering, marketing and product management at IBM, CA Technologies and Broadcom. He is passionate about taking ideas and turning them into successful products and businesses.
Citation
Diorio, Stephen and Howarth, Rich (2024, December 1). The four Cs of B2B targeting: Using company, customer, channel and contextual data to shrink the audience bullseye. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 10, Issue 3. https://doi.org/10.69554/ZUBN7528.Publications LLP