Trust Your Numbers Again — All of Them
When Google Ads, Google Analytics, and your own sales numbers all show something different for the same week, the standard fix is picking one system as the source of truth and documenting why the others differ — not chasing every dashboard until it matches. Webclat builds that documented tracking layer, so a gap between platforms becomes explainable instead of a monthly argument.
Every platform tells you a different number for the same week — Google Ads says one thing, Google Analytics says another, and your own sales ledger says a third.
You spend the Monday meeting defending a number instead of using it, and by the end nobody in the room actually trusts any of the three.
What we implement
We give your team one documented source of truth for what counts as a "conversion," a "session," and a "customer," and route the numbers most likely to go missing through your own server first — what's called server-side tracking.
What you get
- ▸One number everyone in the room agrees is the real one, with every other platform's gap to it explained instead of argued about.
- ▸Ad spend decisions based on what actually happened, not on what a browser or an ad platform chose to report.
- ▸Fewer internal errors caused by two teams using "conversion" to mean two different things.
a retailer whose Google Ads dashboard and Shopify ledger disagreed every week might find, after reconciliation, that most of the gap was refunds and attribution-window timing rather than a real tracking failure — leaving a much smaller, genuinely fixable gap behind. Illustrative scenario, not a measured result.
Questions worth asking first
▸Why don't my Google Ads numbers match Google Analytics?
They use different attribution models, different conversion windows, and different definitions of a "conversion." Neither platform is lying to you - each is answering a slightly different question.
▸Is it possible to get every platform to show the exact same number?
No, and chasing that is the wrong goal. Different systems measure different things by design. The realistic goal is one documented source of truth and an explainable gap to everything else.
▸Why does my analytics data not match my Shopify or POS sales?
Analytics tools typically record a purchase at checkout completion. Your store's own ledger reflects the full order lifecycle — refunds, cancellations, and adjustments included. Both can be correct at once, answering different questions.
See where this shows up in your own data.
A data audit maps this use case against your actual tracking, so the plan is specific to your stack, not generic advice.