The real question: where is the growth ceiling?
Before any decision could be made, a more fundamental diagnosis was needed: was the declining ROI a campaign problem, or a structural shift in the market? The first audit made that question answerable — and the answer shaped the entire project.
By 2024, the global AI writing tool market had become one of the most saturated advertising categories. Competitors include ChatGPT, Squibbler and dozens of other tools — with larger budgets and stronger domain authority. In this environment, every penny spent has to work.
The product: a B2C SaaS AI writing tool, in English, targeting a global audience. The funnel: visitor → registration → (demo) → purchase. The budget: a limited daily spend. The campaign had been running since November 2023 — but without reliable data.
The audit: what was blocking good decisions?
Conversion tracking was not set up in Google Ads
GA4 data was not being measured; the connection between Clarity and Tag Manager was broken — there were no UX insights. Search Console SEO results were also being ignored.
2 active campaigns were running, but without conversion value tracking
- Performance Max: 0.15% conversion rate, 25 conversions, Ft11,950/conv.
- Broad match search: 1.05% conversion rate, ~92.5 conversions, Ft14,348/conv.
Auto-apply recommendations were running, no geo breakdown, no remarketing
Auto-apply allows Google to independently change campaign settings — which rarely leads to good results on a limited budget.
First step — tracking foundation: Full GA4 + Tag Manager + Google Ads connection, enhanced conversion setup with custom code snippets, removal of redundant tags, stopping auto-apply. Only after this did it make sense to optimise anything.
The decision process: 4 hypotheses, structured testing
The point of this project was not to "optimise what's running" — but to ensure that every intervention had an explicit assumption and a measurable outcome. We started with four concrete hypotheses and let the data decide in every case — even when the result wasn't what we expected.
The numbers: monthly summary
Only after tracking was set up did the full funnel become visible for the first time — Revenue, CAC, registration-to-purchase rate and ROI month by month.
| Month | Revenue | Total CAC | Reg → Purchase | ROI | Spend |
|---|---|---|---|---|---|
| April | Ft3–5M | Ft9,257 | 3.89% | 165% | Ft1.5–2M |
| May | Ft4–6M | Ft12,193 | 4.03% | 79% | Ft2.5–3M |
| June | Ft2–4M | Ft14,234 | 3.41% | 25% | Ft2–2.5M |
| July | Ft3–5M | Ft13,881 | 3.39% | 40% | Ft2.5–3M |
The market context: what matters beyond the numbers
Behind the numbers lies an important structural factor that can't be ignored. During the project period, the AI writing tool market was still relatively new globally — but it was just beginning to saturate rapidly.
As the market matured, CPCs kept rising without pause. ChatGPT, Squibbler and similar major players were continuously increasing their advertising pressure — the CAC levels that were once achievable were being structurally eliminated by the market.
This is an important lesson for any category where well-capitalised competitors are present: CPC inflation is not a campaign failure. A smaller-budget player cannot beat a competitor who is pushing up auction prices with a 10–100× larger budget. In this situation, the strategic question is not "how do we reduce CPC" — but how do we reduce dependence on a single channel.
What this means in practice: if a market is saturating quickly (AI, fintech, SaaS categories), the historical paid advertising CAC data can be misleading. Last year's numbers can't be used as future benchmarks. Channel diversification (email, SEO, Meta) is not a luxury — it's a defence against CPC inflation.
The real bottleneck: not the ads, but the funnel
After three months of data, it became clear that campaign optimisation has its limits. Registration CAC is consistently low — between Ft360–490 — and campaigns continuously deliver registrations. The question is: why does only 3–4% of those become a paying customer?
This is the key metric. If this goes from 3% to 5% with the same traffic, the revenue impact is greater than any campaign optimisation could achieve. At this point, the job of advertising is done — email, onboarding and the offer take over from here.
This is an important insight for every SaaS entrepreneur: paid advertising is the top of the funnel. If the bottom is leaky — if registered users don't buy — then more ad budget doesn't solve anything, it just makes the problem more expensive.
Next steps to increase conversion rate: remarketing with a 3–7 day cycle, email nurturing sequence after registration, dedicated landing pages for each target market, and Meta ads to reduce Google dependency.
Summary lessons
The strategic takeaway: what would an advisor do differently?
The most important insight from these three months isn't a specific setting — it's a decision framework. Every intervention is a hypothesis. Some work, some don't. The difference is whether you measure precisely enough to know which is which — and whether you have the discipline to stop what isn't working.
The other lesson: ad account optimisation has a natural ceiling. If there's a hole at the bottom of the funnel — if registrations aren't converting to purchases — more budget doesn't fix it, it just makes the problem more expensive. The real decision starts at that point: what's worth changing inside the funnel?
If campaigns are running in your account but you're not sure they're built on reliable data — I'm happy to walk through an audit with you. Get in touch →