Case studies

Three tracking problems and what changed.

Real production work across measurement scale, server-side migration and attribution repair.

10M+events per month

Moory / Sweden

From 600K to more than 10M monthly events.

CONTEXT

From one store to multiple markets

Moory is Sweden's largest boat accessories store. The work began in 2021 with the TagPilot GTM for WooCommerce plugin, followed by early implementations of Enhanced Conversions and Microsoft UET.

WORK AND RESULT

Server-side tracking at catalogue scale

We built and maintained the server-side setup, added Consent Mode and more advertising platforms, then repeated the architecture for Moory's multi-market expansion. It now handles more than 10 million events each month and calculates profit in real time across a catalogue of more than 50,000 products.

There is no plugin or company in the world that deserves a 5 star review more than these guys. Big thumbs up from Sweden!
Christoffer, Moory

99.8%GA4 accuracy

Cataleya / Romania

A complete server-side migration in two weeks.

CONTEXT

Replacing a legacy all-in-one setup

Cataleya is a Romanian ecommerce store specializing in personalized gifts. Its team needed to replace a previous all-in-one plugin and improve the accuracy of GA4 transaction data.

WORK AND RESULT

A complete migration in two weeks

We moved the full setup to server-side Google Tag Manager in two weeks. The completed implementation covered Consent Mode, Google Ads, Meta, Pinterest and TikTok, and reached 99.8% GA4 accuracy.

I'm glad to let TagPilot do their magic ensuring everything is tracked correctly and accurately, so I can rely on data when scaling our ads.
Vlad, Cataleya

2-3xrevenue over-reporting

Supplements ecommerce / Lithuania

Revenue over-reporting hid actual campaign performance.

PROBLEM

Reported revenue did not match sales

A Lithuanian supplements store found that Google Ads was reporting two to three times more revenue than the business had actually generated. The apparent ROAS did not reflect campaign profitability.

RESULT

Attribution repaired

We corrected the attribution model and resolved the data discrepancies. The team could then evaluate its existing campaigns using accurate revenue and their actual business results.

Start with context

Bring us the numbers that do not agree.

We can determine whether the problem belongs in collection, consent, attribution, deduplication or reporting, then define the repair.

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