B2B Marketing Blog

How to Measure ABM Without Drinking Too Much

By Jenn Steele
Jun 5, 2018
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This story starts a few years ago. I was head of product marketing at a big data company, and my senior director of inside sales and I realized we had a big problem: after years of trying to get a good lead flow going through inbound marketing, our sales team still felt like they were starving for viable leads. In the absence of qualified inbound leads, inside sales would haphazardly try to find good target accounts, and they weren’t having much luck.

What could we do to make sure we were generating high quality leads so that the sales team would be happy? What could we do with limited resources? How could marketing and sales work together to generate more pipeline?

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After some concerted research efforts, we landed on adopting an account-based marketing strategy (although we did brand it the Account-Based Sales & Marketing (ABS&M) strategy to make sales feel more included). We invested in new technology like Outreach.io and built out our new account-based marketing tech stack. We defined our ideal customer profile (ICP), and our inside sales team built out tiered account lists.

With our shiny new technology and hot sales & marketing strategy, we were off and running!

After a few months, while watching a Bizible webinar on ABM, I realized that I forgot one key thing: I didn’t tell my digital marketing manager that we no longer cared only about net new leads. So she was busy generating net new leads and dutifully reporting her performance—which is exactly what we told her to do—but we didn’t actually care about net new leads anymore.

We changed how we measured our marketing and had done a bunch of trainings with our team around ABM. We were going all in on account-based everything.We cared about account penetration. We cared about whether our marketing efforts brought in leads from our target accounts, but she was completely disregarding any leads from existing accounts!

I mistakenly thought that simply telling my marketing team that we made some changes would naturally flow through to change their behaviors. It’s easy for me, as a marketer, to assume that my marketing team was waaaay smarter than my sales team and would simply pick things up as we went along. I learned a valuable lesson in change management and communication: never assume that people understand the impact of a big shift.

I apologized profusely to my digital marketing manager over a drink or three, and she said she’d make the change. But when it came time for that first month’s reporting, she came to me with a problem: she couldn’t figure out how to make the numbers work.

I dove in and—holy moly! When it came to measurement we tried to stitch together our marketing automation data with our CRM data and it was an unmitigated disaster. We could only manually figure out anything about how our marketing performed after sales created an opportunity. We had to track everything in a spreadsheet and meet for a couple of hours every month to try to reconcile leads with accounts and pipeline. Eventually, we hit the bar and gave up.

Drinking

In an unrelated event, I moved to Bizible a few months later, where the sales and marketing teams were doing nearly 100% ABM. From account-based direct mail to account-based digital ads, everything seemed to be running smoothly and somehow everything measured just fine.

I had to figure out what made it different. It turns out that the answer was simple: DATA.

Back at my previous job—and was also true at ALL my previous jobs—marketing data lived in silos. Each channel had its own metrics, which we were never able to truly unify, despite countless ugly spreadsheets. Bizible stays out of ugly spreadsheets by creating a data layer with a common currency: the touchpoint. By measuring everything in touchpoints, email and events and paid search can be easily compared against each other.

It’s night and day. With Bizible’s data layer, every interaction, no matter the channel, gets tracked and measured to revenue from the first anonymous touch to closed-won. And every touchpoint has granular, normalized data. Of course, while doing ABM, touchpoints must attach to leads and contacts, which then roll up to opportunities and accounts through lead-to-account mapping. No more hours of meetings trying to do the manual mappings, and definitely fewer hours in the bar drowning my sorrows.

But how do we give credit to hard-working folks like my former digital marketing manager? With all the data available for every buyer journey, the next step is distributing the revenue credit to each of the efforts that made an impact along the journey. Bizible’s custom model (backed by our machine learning algorithm) distributes revenue credit based on specific weights for funnel stages. If an ABM program made an impact anywhere in the funnel, it receives credit.

Custom-Model

To measure the success of ABM efforts, we aggregate the touchpoint credit however we want to see the data. We can look at revenue by channel, by campaign, by ad, etc.

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At Bizible, using Bizible, measuring ABM finally made sense. It’s shockingly easy and automatic. Everyone receives the credit they deserve, and, importantly, my drinking has gone back to normal (wine is my primary hobby, so that’s a good thing).

So what did I learn about measuring ABM in my old job versus my current one at Bizible?

  1. Don’t forget to consider everyone in your ABM rollout
  2. It’s all about the DATA
  3. Appropriate credit = happy humans

Oh, and my old digital marketing manager is now a project manager at an aerospace company. She SWEARS it’s unrelated to the ABM measurement snafu, but I’m unconvinced...

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