Most businesses can see how many people visit their website. Very few can tell you how many of them tried to get in touch — and almost none can tell you which ad, post or search brought the ones who did.
I rebuild that missing layer: every enquiry counted, traced back to the click that produced it, and turned into something the ad platforms can actually optimise toward.
The problem I usually find
Analytics is installed and reporting happily, so nobody suspects anything. But the ways people actually make contact bypass it completely — contact forms that post to an external handler, buttons that only scroll down the page, and links out to LinkedIn or WhatsApp. None of them produce a page view, so none of them is recorded.
The result is a business that knows its traffic and cannot answer the only question that matters: did any of this bring us customers? Until that is fixed, every ad budget is being spent on a guess.
What that fix is worth — a recent rebuild, measured
- Enquiries measured: 0 of 3 routes → 3 of 3
- Page weight: 11.58 MB → 1.21 MB (a single image was 6.67 MB, now 102 KB)
- Pages search engines could index: 1 → 116
- Google ad click ID captured, so an enquiry traces to the exact click that paid for it
- Search description was still the site builder’s placeholder — rewritten for an actual buyer
- Heading structure and schema corrected for search and AI answer engines
💼 What I can do for you
- Audit your tracking and tell you plainly what is and is not being counted
- Set up conversion tracking that works with off-site forms, booking tools and DM links
- Capture ad click IDs so paid spend can be judged on customers, not clicks
- Cut page weight so you stop paying for visitors who leave before the page loads
- Fix the technical SEO that decides whether you appear at all
- Prepare the site for AI answer engines, so it can be quoted and not just linked
- Set up ad accounts properly — conversion-led, with the wrong traffic excluded
🧠 Technologies Used
- GA4 + Google Tag Manager – events, key events, DebugView verification
- Google Ads / Meta / LinkedIn – conversion import and click-ID attribution
- Python + FastAPI – the crawler and audit engine behind the findings
- PostgreSQL – measurement facts, provenance and history
- schema.org JSON-LD – Person, Organization, Product, FAQPage
- Playwright – automated verification that every event actually fires
How I work
I start with an audit, because there is no point optimising numbers that are not real. You get a plain-language report of what is broken, what it is costing, and what I would fix first — and you can verify every claim in it yourself.
Next, we will fix where money is lost to make ROI and other KPIs improve.
Lastly, whole marketing flow with be automated with AI but final decision making approved human, who will be responsible for final outcome, one person you can talk and get whole picture.