How to Run 7-Figure ABM Campaigns on LinkedIn With a Team of One
The four Claude skills that do the ABM grunt work, from strategy to reporting
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Dear GTM Strategist!
Last year, one of the pieces you told me you loved most was Emilia Korczynska’s “Lean ABM” playbook - the one where she showed, with real numbers and screenshots, how Userpilot built $900,000 in pipeline in 135 days without spending a cent on pricey ABM platforms. No fluff, no “$400M pipeline from seven emails” nonsense. Just LinkedIn ads, a scrappy toolstack, and a lot of discipline.
Well, she’s back, and the game has moved.
Since then, Emilia scaled that same motion to 5x the ad budget - and pulled it off with a leaner team than before, three people instead of seven. Her edge this time is a set of Claude skills she built to handle the ABM grunt work that used to eat entire afternoons: the reporting, the auditing, the “wait, is our messaging mix still on-strategy” math that nobody enjoys doing by hand every week.
When she offered to write the follow-up, I said yes before she finished the sentence. This is exactly the kind of thing I want us all wrestling with right now - how AI changes the actual day-to-day work, in the “here’s the repo, here’s what it does” sense, not the theoretical one.
Here’s what you’ll walk away with:
The full ABM journey mapped as five stages - strategy, design, launch, audit, and report - so you can see where the effort actually goes.
Four Claude skills you can copy, each owning one job: sizing realistic goals against your budget, executing the campaign, auditing live ads, and reporting on pipeline.
A budget-sizing model that tells you whether your revenue goal is even possible with the money and numbers you have today.
A system to keep campaigns on-strategy as you swap ads in and out, so your messaging mix doesn’t drift off-plan.
The receipts: how this approach helped drive roughly $10 in pipeline for every $1 spent.
Emilia was also one of the first ones who believed in GTM Strategist, so it’s my personal pleasure to host her. I’ll let Emilia take it from here.
When I started our first ABM campaign (on LinkedIn) at Userpilot exactly two years ago - it was very successful and brought in $600,000 in pipeline in the first three months (I documented the whole journey in the Growth Unhinged article with Kyle Poyar) - and was already at $900,000 the following month (and was featured in this edition of GTM Strategist!). It sounded like a dream come true - over $10 in pipeline from every $ spent on LinkedIn - but the amount of work required to pull it all together was absolutely brutal, the revops were like eating glass, and we made strategic mistakes that probably cost us 50% of our ad spend.
We had a pretty big team working on the ABM campaigns back then as well: two full-time performance marketers managing LinkedIn ads, a GTM engineer, two graphic designers creating the ads and landing pages, myself, Director of Demand Gen, and Demand Gen Content Manager. Now - we’re spending 5 x more budget on LinkedIn ads than when we started (a six figure ad budget!) but we only have 3 people working on the ABM campaigns (1 performance manager, one content manager, and one graphic designer!)
What’s changed?
Claude Code entered the scene.
I’m far away from these click-baity posts saying “I replaced my entire marketing team with Claude Code.” But for various reasons, we had some big changes in our team over the last year or so - and when some team members left it simply turned out that we managed to make our processes so much more efficient with Claude Code agents and Cowork skills - that we didn’t actually need to replace them with new hires anymore.
Here’s what we’re automating now - and I’ve bundled some of the workflows as Claude Code/Cowork skills and plugins you can easily install with one command or by uploading a zip folder from this GitHub repo.
P.S. Fun fact - I actually haven’t used Claude Code to write this post - I still like to do some things *old school* - so if you spot an odd typo - that’s on me 😅
ABM Strategy Skill - are your revenue goals realistic with your current budget & numbers?
Before we launched our first campaign - I did a couple of months of research, tried different tools, and talked to a few LinkedIn ads agencies for about 2 months. There wasn’t really one “cut-and-dry” recipe for running an ABM program using LinkedIn ads (which is why I tried to document everything I did in this guide) nor a dedicated tool for this use case (which is why my husband built me a custom solution, which later evolved into ZenABM, and is now living a life of its own 😅 - P.S. I’m using it as the “ACME Inc” company in most of the skill outputs here because I can’t share any of Userpilot’s sensitive pipeline/deal data.)
So we made a lot of strategic mistakes:
Splitting our audience into tiny segments that were too small and that cost us way too much to serve ads to;
Creating too elaborate “ABM Stages” to move companies down the different “funnel stages” that didn’t reflect the real buyer’s journey - and were often too small to serve ads to, so companies were getting stuck in limbo instead of getting served more “Bottom of the funnel” ads.
Spreading our budget too thinly across too many campaigns - running many campaigns with very small budgets to these granular, fragmented audiences meant we were severely underfunding every single campaign, losing most auctions and having really poor audience penetration
Putting too many ads in the ad sets with a small budget - again - spreading our budget so thin that some of the ads we spent so much time creating weren’t serving at all - and the rest could get so few clicks per day that it took a very long time to actually deliver the campaign to enough people to learn whether it resonated with the audience or not.
At over $20,000 in ad spend per month and pretty good creatives - a lot of these problems could be masked for a good amount of time - but they were affecting us adversely and I bet we could have achieved even better results if we knew how to use the LinkedIn ad performance and conversion metrics to estimate a realistic budget and number of ads needed to achieve our revenue goals.
You may say it’s a “skill issue” - but since we launched, I talked to a few dozen other Demand Gen teams and a lack of clear strategy is a common problem.
So this is exactly where the ABM Strategy Claude Skill comes into play - it asks you about your campaign revenue goals, average deal size, your planned campaign budget, your website conversion rate to demo/trial and your qualification and close rates - and then fetches your LinkedIn ad metrics (free via ZenABM’s MCP server) like the average CPM, cost per click to landing page and the eCTR to calculate the realistic number of clicks you need to deliver to your website + how much they would cost you - and then calculates how many accounts and members you need to reach to realistically get this number, how many ads you can afford to run at a time (to avoid spreading your budget too thin) and how long it will take you to reach your goal with your budget!
It then proposes the LinkedIn Campaign structure (how many ads you can run) and which ad formats you should focus on based on your previous results:
Executing your ABM Campaign Strategy
OK, now the fun part - you know:
how many ads you should create (and in what format),
how much of your budget you should allocate to each one,
what angle/job-to-be-done you should use for each based on your target audience.
Now it’s time to roll up your sleeves and actually create the ads.
This used to take us a long time (think weekly cycles) to do when we were doing it completely manually. Luckily I came up with this Notion Database because at our scale (at one point we were running 17 different campaigns at a time - and we’ve launched & tested 2000+ ads in the last 2 years!) we wouldn’t be able to do project management without it, keep track the production status of the ads (with database properties), or make sure the designer executes the right brief, and the performance manager uploads the right image and ad copy to the right campaign:
We initially used to brainstorm the ads & fill the whole database completely manually.
Then - I’ve built another Claude Skill that actually executes the campaign plan. It creates the whole campaign outline based on the strategy, ad briefs - and even the ad mockups (I would still advise working with a real, human designer for polishing those 😁). Again, you can download it from this repo or directly here, and install it in your Claude Cowork or Code.
Here’s what the Campaign Outline looks like (an example done for my husband’s company):
And here’s one of the briefs it actually generated for this campaign:
Auditing Your Campaigns and Reporting on Performance
Last but not least - ABM campaigns are never set-it-and-forget-it.
You need to monitor your campaign and ad performance at least on a weekly basis - and turn off underperforming ads (for me - typically ones with > 1000 impressions and < 0.4% eCTR).
But there’s a catch here - while turning the underperforming ads off, you need to remember to replace them with new ones - and to keep the campaign on track - keep the number of ads and the right ratio of messaging in accordance with your strategy.
That is - if in your strategy you planned to have eight ads, two of which were supposed to be about analytics, three about onboarding, and three more about MCP server, AI agents and in-app surveys - you need to make sure that ratio holds every time you swap ads in and out.
And then - are all your ads hitting the benchmark for their ad format? Are some decaying?
Which companies have engaged the most last week and are ready for sales outreach?
Which ad formats performed the best? Where did we spend the most of our budget? Did we allocate it to the most efficient ad formats?
I’ve created a Routine in Claude Code for myself to audit our account on a weekly basis and send me a report + a Slack update (especially useful given I have a weekly executive meeting where I need to report on all our results on a Monday). It also includes other sources (e.g. Google Ads, GA4 and Search Console - that require various API connections and service accounts), so it’s outside the scope of this article - but I’ve created two Claude skills included in this repo that will guide you further.
ABM Audit
/linkedin-abm-audit a diagnostic skill that evaluates your ABM Campaign(s) performance in the last 30 days.
The skill looks at the last 30 days versus the previous 30 days in your LinkedIn Campaign Manager and CRM (via the MCP I mentioned earlier) and hunts for problems.
What it does:
It pulls spend, impressions, clicks, landing-page clicks and engagements, builds a scorecard (spend, ads live, CPC, CPM, CTR and effective cost per landing-page click), and runs an “ad-count model” from the strategy skill that compares how many click-driving ads you’re running against how many your budget can actually support.
It classifies every ad by its ad format and compares each format’s performance against ZenABM’s 2026 B2B SaaS benchmarks (grading link formats on effective CPC-to-landing-page, not raw CPC)
It tells you which formats influence most of your pipeline and ABM deals, watches for decaying ads and impression-hogging accounts, and outputs prioritized red/green flags plus a concrete, ordered fix list - all wrapped in a branded “[Company] LinkedIn Ads & ABM Audit” HTML and PDF. Its whole reason to exist is to tell you what’s broken and exactly what to change.
ABM Report
/linkedin-abm-report is the reporting counterpart - it uses the same data sources, benchmarks and math, but sends you a monthly recap for a stakeholder/exec audience rather than a to-do list.
It covers the last full calendar month compared to the month before, and summarizes what happened:
total spend
pipeline and deals influenced
your best campaigns, formats and individual ads,
the companies engaging with your ads most,
How your different ad sets (by format) performed against the benchmarks
month-over-month changes + a short set of recommendations and next steps.
Conclusion
The honest takeaway isn’t that AI replaced our demand-gen team - but it made us a lot more efficient and data-driven.
Running ABM on LinkedIn has always been about juggling many hard jobs together:
getting the strategy right
executing dozens of ads without losing the plot
and auditing relentlessly so you kill what’s decaying and double down on what’s working.
Two years ago, each of those jobs took several people and days to get done.
What changed is that most of that work is now structured enough to hand to a Claude skill - the math, the briefs, the benchmarks, the weekly fix list - so a much leaner team can run a bigger budget without the strategy falling apart.
So if you’re staring down your own ABM program - whether you’re about to spend your first $5k or you’re already past six figures - start with the strategy skill to stress-test your revenue goals, use execution to get the ads built, and let the audit and report keep you accountable every month. Grab them from the repo (one command, or upload the zip into Claude Cowork or Code), point them at your own numbers, and skip the half-a-budget’s worth of mistakes I had to make first.
Maja here. Thanks, Emilia, for these insights and skills.
The ABM process has really changed a lot with AI and new tools - so here’s the summary of what we have learned today:
Before you go - my friend Ben Williams just published a report on the State of AI Search for Dev Tools. His team tested how five AI platforms (ChatGPT, Perplexity, Gemini, Google AI Mode, and xAI) answer real buying questions across 43 categories, then traced 126,814 citations to see which sources actually shape the answers.
It’s wild to see how each platform picks sources differently, so AEO is definitely not an easy game. We have covered the best AEO strategies in this Substack before, and we’re far from finished.
Let’s go to market!
Maja
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