👋 Hi, it’s Kyle Poyar and welcome to Growth Unhinged, my weekly newsletter exploring the hidden playbooks behind the fastest-growing startups.

VP of Marketing Emilia Korczynska went viral on LinkedIn last month when she shared her 90-day ABM journey. “It’s brutal,” she wrote. “There are no playbooks.”

But she powered through, ultimately turning ABM into a profitable pipeline channel for Userpilot. And today she’s writing the (very) tactical playbook that she wished someone gave her *before* getting started. (This is the tenth installment of my popular Future of GTM series.)

It’s been exactly three months since our marketing team at Userpilot launched our first ever account-based marketing (ABM) campaign, and the results are in: over $650,000 in pipeline in 90 days, with $12 in pipeline per $ spend.

While these early results are promising we were thrown into the ‘deep end’ since none of us had done ABM before (our ACV wasn’t quite “there” for ABM before). For the past five years, Userpilot’s growth has come almost 100% from inbound - with the majority from organic SEO traffic. At our peak in early 2024, we would publish up to 150 content pieces per month, driving 235,000 monthly visitors. But at some point SEO content started to bring diminishing returns. After a year of ups and downs (with extreme SERP volatility), our SEO traffic finally settled around the same place where we started. And we also noticed something more fundamental - as our product became more robust and our prices increased (in 2024, we almost doubled our ACV!) - our conversion rate from SEO started slowly decreasing.

In July our CEO called me out for having built a ‘siloed marketing department’ - with every function paddling independently towards their own goals, without collaborating much, and definitely without creating the much-wanted ‘flywheel effect’. It was time for me to act - and ABM or die trying…

The first thing I learned about ABM is that it’s brutal. There are no playbooks. Most ABM resources are very high-level (‘strategic’), and there’s a painful lack of tactical resources on how to set the campaigns up.

And no wonder - no one wants to share exactly how they set up their campaigns and what were their “winning formulas” (ad formats etc.) - let alone how much they’ve spent on their campaigns and what ROAS they’ve achieved!

And yet - before even starting to work on our first ABM program - we had to (somehow) answer a lot of the questions:

Of course, it’s easier to answer these questions with the power of hindsight - it wasn’t like we had all of the answers before starting our first campaign. But we learned a lot through trial and error - and hopefully this post will allow you to avoid some of the growing pains and (costly) mistakes we initially made.

One thing we knew from the beginning was that we wanted to start from running a “1:many” ABM campaigns, targeting many accounts (with a shared characteristic) with ads. This play can be used to identify accounts with intent from the SAM to be included in more personalized campaigns and outreach.

Based on their engagement level (“account score”), we would pass them on to the next stage -- targeting them with different (more solution- and product-oriented) ads, and at some point, with personalized BDR outreach. The question was: at which point?

We decided to align the ABM campaign stages with different stages of the “awareness funnel”, but still needed to figure out account scoring and “thresholds” for each stage. One resource that helped us decide on it was Kyle’s article about GTM metrics 2.0.

We used it (tweaking it slightly) to decide on our campaign stages, stage benchmarks (how many accounts we’re expecting to move from one stage to another), and revenue goals and budget (we combined that with our historical ad cost and conversion rates, qualification rates, close rates, and expected ACVs to calculate a reasonable budget to hit our revenue targets).

We decided to structure our ABM campaign stages as follows:

The accounts in each state are then shown different content (ads). The further down the funnel, the more product-oriented the content.

If this sounds simple – it is. But, surprisingly, it wasn’t easy to arrive at this *simple* account scoring model. At first we really overcomplicated things, adding a combination of factors such as page visits (qualitative/intent signals) and weights to specific ads/ page visits.

This proved to be too hard to execute. We learned the hard way that website visitor deanonymization was too unreliable to use for consistent account scoring. The accounts we were targeting simply wouldn’t show up in any website visits, even though we knew they landed on the landing pages for the ABM ads we created specifically for them.

So we decided to simplify the account scoring, using only quantitative ad engagement data from Linkedin in our CRM and qualitative aspects (i.e. which ad campaigns they engaged in) to personalize the BDR outreach.

To apply the scores to accounts, we push the company-level engagement data from LinkedIn Campaign Manager to Hubspot. As of January 2025, you can’t do this natively. We initially used Fibbler for pushing quantitative ad engagements (number of impressions, engagements and clicks per account), and then decided to also push qualitative data (which campaigns the account engaged with specifically) with ZenABM.

This allows us to understand the intent behind the engagement, as we structured our campaigns so we can gauge whether the prospect is interested in e.g. onboarding, analytics, or switching from a competitor.

We push that intent into company properties on HubSpot and use the information for personalising BDR outreach, and customizing further campaigns.

Since the campaigns are already segmented by intent (12 in our case), we can then create a workflow to assign the respective intent(s) in a custom multiple checkboxes company property on the company level based on the campaign names/intent coming in from ZenABM. When the BDRs do the prospecting themselves and create leads, the associated company’s intent(s) gets copied to the lead level as tags. This makes the next steps more relevant -- as they are based on what the company members are already engaged with.

We then created active accounts lists in HubSpot with list membership based on being in a specific ABM stage and the thresholds of “cumulative LinkedIn Ad Engagement/ Clicks”. We have a separate list for each stage of each campaign:

Using list membership and a workflow, we update the “ABM stage” company property:

How did we know how many accounts we should target, or what budget to set? After we decided to use Kyle’s post as rough ABX benchmarks (not sure if that was his intention!), we then set a revenue goal for this initiative and ACV - and worked our way backwards (knowing our close rate and qualification rate).

We set a goal of $3,500,000 in qualified pipeline with an annual budget of of $350,000. The “pipeline per dollar spent” is another important metric we decided to follow in order to see if our campaigns are on track.

Given this relatively modest initial budget, we started using only LinkedIn Ads. We’ve also set up a separate no-follow entity (lookalike website that functions as a set of landing pages) for ABM ad destinations and are planning to use it for running retargeting ads on Google Display networks. (We also toyed with using our lead lists directly on Google Display, but the match rates were too low to run them – nobody’s using company emails on Google accounts…).