Hi friends - This is the last of our 4 part series on ABM (account based marketing) from our lovely guest author - Ms Corrina Owens.
The key takeaways -
Traditional digital marketing is broad. Account-based marketing is precise. ABM is focused on targeting a sliver of your TAM called TRM (total relevant market).
Contrary to popular belief, ABM is not only effective for enterprise sales and can work for SMB and mid-market as well. But for enterprise, it really should be table stakes.
Getting started with ABM doesn't require any new technology (right away). You already have everything you need to test this right now.
The most successful ABM campaigns have two things in common 1) the voice of your customer (your best sellers) and 2) IRL experiences - go beyond digital.
Your first sign it’s working is engagement data. But you need a strategy and process to act on that engagement data for it to drive the ultimate outcome —> more revenue. A custom GPT (+ Corrina) might be able to help.
More on the last point ^ in this week’s final article.
Enjoy!
How to know if ABM is working + custom GPT
“This is all great, Corrina, but how will I know if ABM works?”
First…
You’ve aligned on the ICP and buying signals
You’ve picked your target accounts
You even got your team to buy-in to this thing called ABM
So now what?
💡 Now, you start to get activity from these accounts. That engagement data is the first sign it’s working. People from your target accounts are responding, clicking, viewing, and RSVPing.
But simply collecting the engagement data is not enough, you have to know what to do with it.
Unfortunately, I’ve seen plenty of companies build the most beautiful tech stacks in the world, with dashboards combining reports from all their vendors, designed to surface every signal under the sun.
But when those systems don’t reflect how your business actually thinks and sells? That data just sits there and gets ignored altogether.
Sound familiar?
That’s why I started building a custom GPT for ABM programs
One of my clients had all the data: outreach metrics, campaign engagement, and firmographic intent, but the person managing the account had no idea where to focus—or what actions to take next when looking at these account engagement reports.
So I trained an LLM to help.
Not just on what signals to look for (like case study views + recent hiring + high-fit industry)... but on how we respond when that pattern shows up. Not with a generic sequence, but with a thoughtful, contextual touchpoint rooted in the buyer’s world.
After a dozen or so iterations of me providing feedback, correcting the LLM, I felt confident that it could get an account rep 99% of the way there for them, without them having to manually sift through reports.
They’d drop in their weekly view, and the LLM would surface quality engagement and recommendations for next steps. 🙏
Curious what it looks like in practice? Take a peek at the custom GPT here. 👀
Finally, after you start 1) collecting engagement data and 2) acting on engagement data with intention…you should ultimately see more deals created + a faster sales cycle (aka more revenue).
Now you’re reaching the right people at the right time with the right context. 👏
If you stuck around with me this long, thank you. I hope I was able to paint a clearer picture of what ABM can look like in practice and maybe even what to avoid when you’re trying to prove it out.
Need some more help getting started?
I help Seed to Series C B2B SaaS companies launch account-based GTM motions that don’t just look good on paper, but actually help revenue teams hit their target, even with lean headcount.
And if you’re looking for a bit of help or guidance for how to do this at your org, I’d love to chat. Please reach out anytime on LinkedIn, or feel free to grab a spot on my calendar.
Want to learn more about how I help startups increase their revenue by 150-590%? 👀
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With love and gratitude,
