There’s a question that anyone working in B2B marketing will have heard more than once:
“But how do we know marketing actually caused that?”
It’s a fair question.
It’s also a question that can send you down a rabbit hole pretty quickly.
Because B2B buying journeys are messy. They’re long. They involve lots of people, lots of interactions and usually plenty happening that marketing had absolutely nothing to do with. So when we were asked to demonstrate the commercial impact of an ABM programme for a global cybersecurity client, we didn't try to attribute every opportunity back to an ad, email or event.
We tried something different.
That's what this edition of Inside the Work is about.
Inside the Work is where we share what we're learning from doing the work – the tactics that deliver, the approaches we believe in, and the ideas we think are worth trying.
And this time, we're looking at a measurement approach that helped us answer one deceptively simple question:
Are the accounts we're marketing to performing better than the ones we're not?
Stop trying to take credit for everything
The programme had been running for some time, which meant we had plenty of marketing data.
Engagement. Content consumption. Campaign responses. All the usual stuff.
Useful? Yes.
Enough to prove that ABM was making a commercial difference?
Not really.
We needed to connect the programme to the things the business actually cared about: pipeline, bookings and account progression. But we also needed to be realistic.
If an account bought something, we couldn't credibly say marketing had single-handedly caused it.
Sales had been involved. Existing relationships mattered. Market conditions mattered. A hundred other things might have mattered.
So rather than trying to prove direct attribution, we looked for correlation with commercial performance. That distinction turned out to be pretty important.
Find something worth comparing yourself against
We created a control group of comparable accounts that weren't part of the ABM programme.
And that comparison needed to be as close to apples-for-apples as we could reasonably make it.
There's not much value in comparing your biggest strategic accounts with a random collection of smaller customers and declaring victory when the first group unsurprisingly generates more revenue.
We also looked backwards.
Before comparing performance during the programme, we established historical baselines for both the ABM accounts and the control group.
We could ask:
How were these two groups performing before we intervened?
And then:
What happened to the gap once the programme started?
Now you're getting somewhere.
Don't just measure marketing things
The next part sounds obvious.
But I don't think we do it often enough. We tracked what happened commercially: pipeline, bookings, opportunity progression.
And we looked at those measures across the whole group of accounts over time, rather than getting distracted by individual success stories.
That helped us see whether there was a meaningful difference between accounts receiving the ABM treatment and similar accounts that weren't.
And there was!
The analysis gave us evidence that the ABM accounts were outperforming the control group commercially. It also helped us see something else: Accounts that had been in the programme for longer were showing stronger results than those with less exposure.
That's important in ABM.
Because if you only judge a long-term account strategy using short-term campaign windows, you're quite likely to kill something before it's had the chance to work.
Did marketing cause it?
Here's where I'd resist the temptation to get carried away.
Did our analysis prove that marketing caused every pound of additional pipeline?
No.
And I think pretending otherwise would actually have weakened the argument. What it gave us was credible evidence that the accounts receiving ABM activity were performing differently from comparable accounts that weren't – against a historical picture that helped us understand where both groups had started.
That's a much more defensible story.
And, ultimately, a more useful one.
Because measurement shouldn't be about marketing trying to grab credit from sales. The commercial outcome belongs to everyone who helped create it.
The job of measurement is to understand whether what we're collectively doing is making a difference.
What I'd take from it;
There are four things I'd recommend to anyone trying to prove the commercial value of ABM.
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Get your comparison right. A control group only tells you something useful if the accounts are genuinely comparable.
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Go beyond marketing metrics. Engagement matters, but eventually you need to connect your activity to pipeline, bookings, progression or whatever commercial outcomes the business actually values.
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Design the measurement before you start. It's much easier to establish baselines and control groups at the beginning than reverse-engineer them when someone asks for an ROI slide 12 months later.
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And finally, don't overclaim.
Correlation isn't attribution.
That's OK.
In complex B2B buying journeys, a credible indication that marketing is contributing to better commercial performance can be far more convincing than an attribution model everyone secretly knows is pretending the world is simpler than it really is.
In this case, that evidence helped demonstrate the incremental impact of the programme and build the case for continuing the investment.
Which, for me, is what good measurement is there to do. Giving the business enough confidence to make the next decision.
