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.
“We also look at account volume, number of opportunities and pipeline value. Then we tie in the number of plays running against those accounts because management wants to know what we’re doing with those targeted accounts,” said McNamee. “The goal is to increase the velocity of opportunities, create better executive alignment between marketing and sales, expand our new ARR and then ultimately begin leveraging customers as brand advocates.”
The company evaluates its account list on a quarterly basis to guarantee engaged accounts are being focused on. “It’s a fluid process,” said McNamee. “We’re watching engagement trends in accounts over time, and once they hit the threshold, we can bring that to sales and we can cycle accounts out that aren’t engaging.”
EnterpriseDB has seen some unique results since taking an account-based revenue approach in the early part of 2018. In Q4 2017, McNamee noted that his team generated 631 opportunities. In Q1 2018, the company generated only 423 opportunities. However, the value of pipeline “went up almost $3 million dollars,” according to McNamee, “highlighting how the quality of opportunities went up considerably.”
McNamee added that, looking at Q4 2017 over Q1 2018, the company has seen:
“We’re trying to bridge the gap between traditional demand gen and this new world of ABM,” said McNamee. “You have to measure that influence that happens in between before you can start talking about the revenue you’re driving.”
McNamee noted that they keep its threshold for marketing qualified accounts (MQA) low because it’s driven by how many minutes are assigned to certain activities. For example, a simple web page visit will generate one minute, whereas an executive conversation will generate 100 minutes.
The threshold for an account to become an MQA for EnterpriseDB is 20 engagement minutes — with a minimum of two stakeholders with five minutes each — over the last three months. “When it becomes an MQA, that’s when you start digging into the engagement because it can get very subjective since you’re applying actual minutes,” said McNamee. “It’s similar to lead scoring, but different because we control what the threshold is for engagement minutes.”
McNamee and his team are now working on building an attribution model that enables him to provide insight to leadership that will help tie ABM and sales efforts with key accounts to the bottom line. He added that he is considering having this attribution model based on engagement minutes.
“My ‘Aha!’ moment here is that if I do ABM with SDRs and we’re creating meetings for sales reps, then we can watch from there on how plays are performing,” said McNamee. “I know that our ABM efforts sourced that stage-zero opportunity, and if it closes, I can pretty much bring it back to where it began. That’s the closest I can get to the traditional demand gen measurement of influence for ABM.”