Burning My Own Budget on Ads after 15 Years Building Marketing SaaS
What happens when a tech person stops building the tracking and starts spending the budget.
I’ve spent my whole career building MarTech SaaS products on the tech side. Been involved in setting up all the behind-the-scenes stuff that makes ad tracking actually work. The pixels, the server-side events, the attribution pipelines... I’ve seen it all from the engineering side.
But I’d never actually ran my own ads. Never spent my own budget. Never stared at a campaign dashboard wondering if I just lit money on fire.
Until now.
Why Ads? Why Not Just Get Referrals Like Everyone Else?
Here’s the thing. Most fractional CTOs get their clients through referrals. And the data backs it up... 90% of fractional executives rely on their network for new clients. Only 13% use paid advertising.
And sure, I’ve got a solid network across the US and Germany. But referrals have a cold start problem. Even with a big network, you’re just waiting for someone to think of you at the right moment.
Cold outreach works too, I’ve learned that from other fractional CTOs. But it requires serious dedication and way more patience than I had. You’re playing the long game.
I wanted results faster. Not because I need 100 customers. I want max 3-4 simultaneously. But I want them to be a perfect match. The kind of engagement where my expertise creates real impact and where there’s room for upside beyond just billing hours.
So I went with Meta ads.
The Setup: Where MarTech Experience Pays Off
This is where being a tech person running their own ads gets interesting.
Most founders launch Meta ads with the basic tracking snippet and hope for the best. The problem? Ad blockers and iPhone privacy settings silently eat 30% of your data. You’re making budget decisions on incomplete information without even knowing it.
So I set up a proper tracking stack. In plain English: I made sure the data reaches Meta through two independent channels instead of one, with safeguards so nothing gets counted twice. On top of that, I added my own analytics layer to see the full picture... not just what Meta chooses to show me.
For the more technical folks, here’s the breakdown:
Client-side Meta Pixel for browser-based tracking
Server-side Conversions API (CAPI) that bypasses ad blockers and iOS privacy restrictions
Event deduplication so Meta doesn’t double-count conversions when both channels fire
Reverse proxy routing tracking through my own domain for higher data quality
PostHog tracking every single step in the pipeline, from first click to conversion
If this sounds like the kind of setup you need, WhatsApp me.
If you haven’t heard of PostHog... think of it as an open-source alternative to tools like Google Analytics plus Mixpanel or Amplitude. I use it to see exactly what happens after someone clicks my ad.
And here’s the AI part... I built the dashboards using AI. There’s a thing called PostHog MCP that basically lets AI tools plug directly into services like PostHog and talk to them. So instead of spending hours manually clicking through dashboard builders, I described what I wanted to see in plain language and AI generated the dashboards for me. That’s the kind of leverage AI gives you when you know what to ask for.
The Experiment: 4 Pains x 2 Formats
I launched with a structured test. Four different pain points that SaaS founders typically face, each in two formats: image and video. Eight ad variations total, all driving to my website.
Started with broad audience targeting since it often outperforms micro-targeted campaigns. The algorithm finds patterns you’d never think to target manually.
Then I watched who engaged with what.
And here’s what I learned: my funnel was too generic to cover all four pains effectively. But that’s exactly the point of running the experiment. Now I know which pain resonated the most and which audience to narrow down on.
I also learned that broad targeting can backfire. My ads were getting a lot of attention from developers instead of the founders and CEOs I was actually trying to reach. So I narrowed down the targeting. Lesson learned: clean data signals help the algorithm, but you still need to tell it who you’re talking to.
One topic in particular sparked a lot of reactions... good and bad... among founders and devs. Highly risky, kind of nasty topic. But well, that’s me. I like sparking emotions and challenging beliefs for good. More on that in upcoming posts.
The Consultant Move: AI Can’t Replace This
I hired a consultant to help me set things up right. Campaigns, ad sets, budget limits, optimizing for leads vs. first meaningful contact.
And here’s something I’ve learned recently as a good habit:
Always bring in a human expert, even when you’re capable yourself.
Sure, you can ask AI for campaign structure advice. I literally build AI integrations for a living. But here’s what AI can’t do... it can’t stop you from freaking out when your first $300 disappears with zero results. It can’t talk you off the ledge when you’re about to kill a campaign too early. It can’t share that gut feeling from having managed thousands of campaigns.
Human relationships and emotions are priceless. AI is an incredible tool for execution and analysis. But the human element... the reassurance, the pattern recognition from years of experience, the ability to say “relax, this is normal, give it three more days”... that’s something no model can replicate.
I use AI to build dashboards, generate tracking code, analyze data patterns. I use humans to make better decisions under pressure.
What’s Next
I’m starting a blog series on the topics that resonated in my ads. The ones that sparked debate, made people uncomfortable, got founders thinking differently.
But I’m also gonna explore every channel. Not because I need dozens of clients. Because I want every client to be a perfect match. The kind where I know I can actually move the needle.
For the ones who aren’t a perfect match with me personally? I’m building relationships with other fractional leaders I can confidently recommend.
Because doing right by people matters more than closing a deal.
Looking back, the biggest surprise wasn’t the technical setup. That part I knew. It was how different it feels when it’s your own money, your own brand, and your own future on the line.
Well, stay tuned.
If you’re a founder dealing with any of this, happy to help: WhatsApp, Calendly, LinkedIn
