The Problem: 

How can I easily measure all of the aspects of ABM and give credit to individual team members?

The Solution: 

Convert all marketing activities to revenue as a common currency and then attribute credit to the team.

Course Content

Total learning: 8 lessons Time: 1 hour


Jenn Steele

One of my business school professors described me as "Often unexpected; never boring." I have a couple different degrees from MIT and Simmons School of Management. I have experience in pretty much all the major business units. I've worked at companies with fewer than 10 employees and 10s of thousands of employees. You'd probably recognize some of those companies, like HubSpot and Amazon. Others you've never heard of, like some of the law firms at which I spent the first part of my career.

1. Overview

Today we’re going to learn about measuring ABM without drinking too much, or rather losing your mind. We’ll figure out how I failed to measureABM at my last job, learned that it was all about the data, stupid, where I’m the stupid, learn about how to give credit where it’s due, and how that actually restores your sanity.

2. First Attempt At ABM Frustrations

But first a little bit about me. See, I really like wine. It’s my primary hobby, in fact. And so I really like having a healthy relationship with wine, and in having a healthy relationship with wine that also means that I have to, well, learn how to do things without drinking too much shall we say. So, let me take you back to my last job.

Once upon a time, I worked at a big data startup in Seattle and we weren’t having a really great time, honestly. We’d spent two years invested in our inbound marketing model, we were trying to do some enterprise sales, and my enterprise sales team was, honestly really cranky. They were really cranky with marketing, they were really cranky with our pipeline creation, and they were super cranky with our closed rate. They were really just unhappy with the status quo.

So we started doing some research. We started looking at, okay what happens when inbound fails, or okay what happens when sales cant figure out who to come up with at scale. And after doing all of this research, we decided that we were going to do account-based marketing. And get it, funnel cakes on this slide? So we looked at a bunch of the stuff on flipping my funnel, we look at a bunch of the stuff on how to account based marketing, and we realized that with our focus on enterprise sales, we really needed to move forward with this and kind of leave out inbound model a bit.

So we built our tech stack. This is Demandbase’s tech stack slide, I figured they wouldn’t mind too much if I used it for their conference. But anyhow, so we built our tech stack on, we identified all of our target accounts, we presented this to the sales team, we presented this to the product team, everybody was really, really excited and we were off and running. We had new energy in our BDRs because they felt really confident that marketing had their back, and they weren’t just beating us up for the crappy leads that they got from inbound marketing.

So everything seemed to be going really well. We did this for a quarter or two, and then I realized that I forgot one thing. So this is Morgan. She was my Digital Marketing Manager and she was measuring herself on net new leads. Meanwhile back at the ranch, the sales team was measuring themselves on account penetration and tiered accounts, and that wasn’t good. So we decided to change how we measured digital marketing and ABM. We decided we really needed to unify the two. That digital marketing needed to also measure, well herself in this case, on was she bringing in leads from our target accounts.

So I dove in because I was the designated data geek and holy moly. We were using HubSpot for marketing automation and Salesforce and was trying to stitch the data between HubSpot and Salesforce and it was a nightmare. I couldn’t make anything play together and we got to the point that Morgan, my poor Digital Marketing Manager, could only manually figure out how anything was happening post-opportunity. So instead of taking three hours every month to report out on our inbound efforts, she was taking three days to map the data to each other.

I mean, honestly we kind of gave up. We just decided that three days was an unacceptable period of time and that we were just kind of gonna go with ABM and go with what Salesforce told us. And let’s just say that it was demoralizing at best to my Digital Marketing Manager because suddenly she’s not measured to anything? And what she’s doing doesn’t matter to sales? I mean that’s horrible.

3. Data Is The Difference

And then I moved to Visible in an entirely unrelated event. No really, they came after me, and as you can see here customers love us, we like dogs, and we’re growing fast. We’re still hiring across all functions in case you’re wondering.

And at Visible, everything was ABM. Absolutely everything. There’s chocolates in boxes, there’s tiered accounts, there’s outreach campaigns, Imean it is the epitome of ABM, and no one was suffering. In fact, there’s a big demand function and they’re all being measured just fine alongside inside sales, alongside direct mail, nothing’s wrong. I mean, what made it different? What in the world was the difference in these worlds? I mean, I’m pretty technically competent, so I was like, I didn’t think you could measure it quite honestly if I couldn’t measure it. That’s a little arrogant, but I hope you get the idea.

And it turns out the big difference is, well, data. Before in my old environment, I just didn’t have the right data. And after in my Visibleenvironment, I did.

4. Gathering The Data & Giving Credit

So let’s take a look at this. So what made the data special? When you think about it in marketing, every single one of our channels has different success metrics. In paid media, we’re looking at CPM, CPC, CPL, it’s cost-per-stuff. If we’re doing events, badge scans, registrations, did you demo at my kiosk. Email, open rate, click rate. Sales, calls, emails sent. I mean everything is measuring themselves by something different and quite honestly, translating that all to each other is really tough. But at Visible, there was no stitching together of these silos, everything translated into a common currency which was, well, revenue.

Let’s put it this way. So in my old environment, I was basically trying to shop and make a purchase and my wallet was full of yen and euros and dollars. Whereas at Visible, it was almost like everything had already been converted to dollars so it’s easy to figure it out and make that purchase.

Visible also gave credit to absolutely everybody where it was due. Everyone felt really comfortable working toward a common goal.

5. Data Points For Everything & Matching Accounts

So I dug in and tried to figure out, well how? How does this work? And here’s how. Visible aligns marketing to revenue with data. Visible basically uses data to convert everything into that common currency.

Step one, Visible creates a data point for well, absolutely everything. Is it an online marketing touch, like Marketo or Facebook or Google AdWords? Well then it gets a data point that we call a touch point. Is it offline, is it a Salesforce campaign, again a touch point. Is it a sales activity like a call, or a reply to email, again a touch point. So we’re taking the disparate currencies of marketing and converting them all to touch points.

Then in order not to lose your mind with ABM, you have to attach all leads to accounts, right. This was the problem that I had at my last job, where if we were for example marketing to Google, and a lead had come in through Google, we couldn’t tie it back to all of our Salesforce efforts with the Google account. So Visible has a lead to account mapping that creates a relationship based on four factors, in this order. And honestly, they’re kind of blending-ly obvious, right. There’s stuff that humans can do all the time, but when you get to scale it’s really hard to do by hand.

So we match email domain of the lead and the website of account, website of each record, lead, and account, right. If you’re all coming from we’re gonna see you all the same way. Our developers wrote a fuzzy match based on lead company name and account name. And then of course email domains, right. vs., those would be matched the same thing.

6. Giving Credit To All Touch Points

Now step three’s what’s interesting. So we have everything in the common currency of a touch point. So how do we give credit to those touch points? And this is where we have a custom model based on machine learning algorithm that actually weighs touch points by its stage of our pipeline. So for example, our machine learning algorithm told us that our three most valuable touch points were the anonymous first touch, the lead creation, and the MQL stages.

So basically what that means is the touch point closest to each of those, and of course, anonymous first touch is literally how they first found us, lead creation is literally how we first go their email address, but the touch point closest to that stage then gets the credit. Here you can see that first touch is 26%, lead creation 22%, and MQL is 20%. Our machine learning model told us that as you get further down the funnel, the touch points actually have less of a weight in determining whether that deal’s gonna close.

So then we’ve assigned, oh let me go back to that slide for a moment. So we now have 100% here, and basically, we take the revenue of that deal and we allocate it as you see here by the weights by stage. So you can see here, opportunity creation and $100,000 deal would get 10%, or $10,000, assuming I’m doing my math right.

So then we actually roll everything up. We aggregate everything by weights and stages, so you can see here we have an uneven number of deals and that’s because, right, you get 10% of the revenue or 10% of the deal. So for organic search, 4.5 deals and $104,000 in revenue. Events, 8.9, $155,000 in revenue. And finally, we see what content and activities play wherein the funnel and wherein the touch point so we can then actually give credit to the humans, right. We’ve got more than one content developer so they need their own credit in different ways.

7. A Happy Ending

And low and behold, everybody gets credit! Demand gets credit, events gets credit, content gets credit, sales gets credit, everybody gets credit. And well, it’s really easy that way for us to work together as a team. Our minds go back to normal as the slide says. Oh, as in a side, well Morgan my Digital Marketing Manager now works at Boeing as a Project Manager.

8. Key Takeaways

So I’ve got some key takeaways here. Number one, don’t forget to consider everyone in your ABM rollout, that was obviously a big mistake of mine. I honestly thought, hey we’re all great, just telling my marketing team that we’re doing this means that they will all appropriately change behavior. And while it’s nice to think that my marketing teams across the years have always been absolutely brilliant and absolutely able to take the smallest cues from everything, that’s not honestly the case. People will tend to keep doing what they’re doing unless you educate them. And this was my failing in that I really needed to tell Morgan, my Digital Marketing Manager, hey we’re moving to ABM, let’s talk about how we’re gonna measure.

Number two, it is all about the data. Without the right data to convert my siloed data into touch points, there’s no way I could get everything together.

Number three, appropriate credit is happy humans. I love the way that we work together at Visible, I love the way that sales and marketing don’t argue about who’s generating what because we’ve got reports that tell us every month by the revenue we generated this month, who gets the most credit for it. And everyone knows it’s weighted according to our machine learning algorithm, which then allows us to then, you know, kind of trust it.

So that’s all I’ve got. I hope you’ve learned a little something about measuring ABM without losing your mind, or drinking too much.


Jenn Steele

One of my business school professors described me as "Often unexpected; never boring." I have a couple different degrees from MIT and Simmons School of Management. I have experience in pretty much all the major business units. I've worked at companies with fewer than 10 employees and 10s of thousands of employees. You'd probably recognize some of those companies, like HubSpot and Amazon. Others you've never heard of, like some of the law firms at which I spent the first part of my career.