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šŸŒ® QBR Prep: Benchmarking ABM Success

Demonstrating correlation vs. causation from your ABM efforts.

Whatā€™s up everyone! Welcome to šŸŒ® Taco Tuesday, a weekly newsletter by ForgeX.

In here we share the latest and greatest around our Account-Based GTM research, provide our perspective on trending topics, and highlight whatā€™s new at ForgeX.

Send us any questions or topics we should break down here ā¬‡ļø

Lack of a Standardized ABM Data Model

Youā€™re getting ready for the upcoming QBRā€¦

You partnered with your RevOps team to pull all of the data around your defined ABM metrics.

But there are two GLARING questions that your presentation fails to answer:

  1. ā€œHow is my program performing vs. my peers?ā€

  2. ā€œDo these metrics prove causation vs. a mere correlation?ā€

Hang tightā€¦ weā€™re working on it!

Over the past 60-days, weā€™ve been asked to share benchmark data around ā€œengagement performanceā€ more times than we can count.

šŸ—£ļø Our answer: we donā€™t have this (yet), and neither does anyone else.

šŸ§ Hereā€™s why:

  1. The legacy Demand Waterfall (2006 version) that was created by SiriusDecisions is STILL the underlying architecture most VCā€™s and C-suite executives defer back to.

  2. A standardized data model that is built for an account-based motion AND has wide-scale adoption doesnā€™t exist; agencies, ABM platforms and internal teams all build different variations.

If it feels like we lack a common language around measurement and reporting architecture - itā€™s because we do.

Every organizationā€™s GTM motion is different, so naturally there will be slight variationsā€¦ but there still needs to be a standardized architecture that holds naming conventions, definitions and stages that allow marketers to speak apples-to-apples.

How to Benchmark Success

So we donā€™t have a standardized ABM data modelā€¦ now what?

Use your internal data to generate benchmark data āœ…

The main objective of doing so is to demonstrating that your account-based efforts and success are due to causation, and not a mere correlation.

  • Causation: refers to a relationship where one event directly results in the occurrence of another event.

  • Correlation: describes a scenario where two or more variables or events are associated with each other in some manner but does not necessarily imply that one causes the other.

Here are 2 pathways we recommend leveraging.

#1 Benchmarking: Against a Control Group

Internally Benchmarking ABM

Implementation:

  • Create two groups:

    1. A ā€œtreatment groupā€ (your target account list) that is exposed to the initiatives within the ABM program.

    2. A ā€œcontrol groupā€ that is not.

  • Both the treatment and control groups should include ā€˜look-alikeā€™ accounts that share similar attributes in order to foster comparability.

  • Track the same metrics for both groups throughout the ABM program, referencing the performance metrics of the control group as a baseline.

When we recommend this:

  • This is our top choice šŸ†

  • This method is particularly valuable in isolating the effects of ABM from other variables, providing a clearer picture of causation rather than mere correlation.

  • This approach is ideal for organizations looking for a rigorous analysis of ABM effectiveness and those who can ensure the integrity and comparability of the control and treatment groups over the evaluation period.

#2 Benchmarking: Pre-ABM Impact vs. Post-ABM Performance

Internally Benchmarking ABM

Implementation:

  • Pull all historical data related to your ABM target account list prior to the implementation of the ABM program. Ensure the historical timeframe chosen provides a substantial data set (do not only pull 2-weeks worth of historical data).

  • This should be the same data that will be leveraged in the account-based data model you plan on utilizing in your ABM program to measure success.

  • Conduct a thorough analysis of how your ABM target account list performed historically to establish a baseline.

When we recommend this:

  • You are unable to leverage a control group.

  • Your organization has a stable historical dataset and external market conditions have remained relatively constant.

Whatā€™s New at ForgeX?

šŸŒ® Research & Insights

Access the Guide Below

šŸŒ® Events

Upcoming:

  • 1.) ABM Platform Readiness: What You Need to Know

    • When: 5/8/24 @ 12:30pm ET

    • With: 

      • Anne Murlowski, VP of Marketing @ Terminus

      • Davis Potter, CEO @ ForgeX

    • Weā€™ll Discuss:

      • šŸ‘‰ How to determine when it's the right time to invest in an ABM Platform

      • šŸ‘‰ Evaluation criteria you should be using to choose the right tech for your organization

      • šŸ‘‰ The red flags to watch out for while having your initial conversations with vendors

  • 2.) How to Hire an Account Based Marketing Expert

    • When: 5/9/24 @ 12:00pm ET

    • With: 

      • Max Spanier, Founder and CEO @ Sloane Staffing

      • Davis Potter, CEO @ ForgeX

    • Weā€™ll Discuss:

      • šŸ‘‰ The key skills and experience to look for in an ABM hire

      • šŸ‘‰ Proven strategies for attracting top ABM talent

      • šŸ‘‰ How to develop a winning interview process for screening ABM candidates

Join +400 ABM leaders and become a ForgeX member to access our full research library, step-by-step frameworks, benchmark data and community.

Have an awesome rest of the week yā€™all!

LFG,

Davis