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Analytics and tracking
Measure what actually pays.
GA4, server-side conversion tracking and attribution rebuilt so every channel is judged on one definition of a conversion instead of on its
The short version.
Almost every reporting argument is really a measurement argument. Meta claims a conversion, Google claims the same one, GA4 shows neither, and the meeting turns into a debate about which dashboard to believe. That is a tracking problem, and it
We rebuild the measurement layer so there is one definition of a conversion and every channel is judged against it. That means server-side conversion tracking: we built and run the Conversions API endpoints for Meta, TikTok, X and LinkedIn on our own stack, plus offline event imports so the algorithms learn from
We audit ourselves the same way. A tracking boundary audit on our own analytics found that 56% of recorded traffic was localhost from our own development machines, and that a cloned copy of a client site was firing our tags. Both were fixed by moving the tracking gate to an allowlist. It is exactly the class of defect that quietly invalidates a year
The same discipline runs deeper for apps. For one client we maintain a warehouse pipeline with eight marts producing cohort ROAS and payback curves, which is the level of measurement app analytics requires. On the web side this work sits under website optimization and feeds paid advertising
The loop, start to finish.
Measurement decays as platforms, browsers and consent rules change. The loop keeps one definition of a conversion true
Step 01
Boundary audit
What is being counted, what is being dropped, and what is being counted that should not be. Internal, staging and cloned traffic found and
Step 02
One definition
A single conversion and value agreed in writing, then applied to every platform so channel comparisons stop depending on whose dashboard
Step 03
Server-side wiring
Conversions API endpoints for Meta, TikTok, X and LinkedIn, plus offline imports so CRM stages feed
Step 04
GA4 and consent
Event schema, consent handling and tag hygiene rebuilt so the numbers are both accurate and lawful
Step 05
Reconcile
Platform reports compared against the shared definition every cycle, with gaps explained rather than
One number everyone can argue from.
Meetings stop being about dashboards
When every channel is judged on the same conversion, the discussion moves to what to do with
Algorithms learn on outcomes
Server-side events and CRM imports give Meta, Google and LinkedIn the qualified and closed stages the browser
Decisions improve over time
Clean data builds a history you can trust. Every optimization after that is made on evidence instead of
Done for you.
Server-side conversions
Conversions API endpoints for the ad platforms, plus offline imports so CRM stages
GA4 and tag hygiene
Event schema, consent handling, and a tracking gate that keeps internal, staging and cloned traffic out of
One conversion definition
A single agreed conversion and value, applied across platforms, so channel comparisons stop depending on whose dashboard
Case studies
Measured on what pays, proven.
AI
How an AI Fitness App Achieved 8.54 ROAS with Strataigize
Appomate
Appomate: From 5% Qualified Leads to 80% in 30 Days
Analytics & Tracking, answered.
Why do Meta, Google and GA4 all report different numbers?
Because they use different attribution windows, different models and different data sources, and browser tracking loses events before any of them see it. The fix is not picking a favourite dashboard. It is agreeing one conversion definition, sending it server-side, and reconciling the platforms
What is a Conversions API and do we need one?
It is a server-to-server way of sending conversions to an ad platform, so events survive ad blockers, iOS restrictions and cookie loss. If a meaningful share of your revenue comes from paid, you need one. We have built these for Meta, TikTok, X
Can you fix tracking without touching our site?
Partly, and the partial version is worse. Tag manager changes go a long way, but server-side events and clean click identifiers usually need a small amount of work in the site or the CRM. We scope that
What does this cost?
Website optimization starts at $4K per month with a typical range of $4K to $10K, published on our pricing page. A one-off measurement rebuild can also be scoped as a
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