Targeting multiple buyers and higher price tags makes measurement even more critical, but often more complex for ABM practitioners. Because EnterpriseDB was able to track the overall engagement of target accounts and gain a deeper understanding of their propensity to buy, the company saw an increase in overall pipeline, even while its number of opportunities decreased.

When the open source-based data platform company brought on James McNamee as its Senior Director of ABM one year ago, EnterpriseDB was looking to move towards a targeted account-based revenue model to help them better target and engage accounts with higher opportunities for annual recurring revenue (ARR).

Starting with its target account list of 4,000 in North America, McNamee and his team broke the list into four tiers to prioritize its ABM initiatives on top-tier accounts, while serving lower-tier accounts with traditional demand generation.

“We’re trying to create a traditional demand-gen-type measurement approach for ABM,” said McNamee, in an interview with ABM In Action. “However, the key difference is that ABM is influencing the sale overtime, and it’s a longer runway to see results with ABM. Patience is a big thing here, but as long as we can track engagement trends, how opportunities are progressing and how many plays we’re running with accounts, it’s an easy story for us to tell.”

Using PathFactory, McNamee’s team is positioned to better understand how stakeholders within target accounts are consuming the company’s content. Having deeper insight — down to the number of minutes stakeholders are spending with content — enables EnterpriseDB to better identify accounts that have the best chance of buying. The company then uses Rekener, a BI tool, to pull Engagio and Salesforce data into a single location to gain a holistic view of account engagement.