Why Google Ads, Meta, GA4, and Shopify All Show Different Numbers

Open your four dashboards for the same month and you'll see four realities: Meta claims ₱900K, Google Ads claims ₱600K, GA4 shows ₱1.1M total, and Shopify — the only one counting actual money — says ₱1.3M. Meta plus Google alone exceeds what some stores actually made.

Nobody is lying. Each system answers a different question with different rules, and the sooner you stop expecting them to match, the sooner you can make decisions with them. Here's what each number really means and which one deserves your trust.

TL;DR

The numbers can never match. Different attribution windows, different credit rules, different tracking methods. Reconciliation isn't the goal — knowing each system's bias is.

Ad platforms grade their own homework: each claims every conversion it touched, so their totals overlap and inflate.

Shopify (or your CRM) is ground truth for totals but knows little about what caused them; GA4 is the neutral referee with its own blind spots.

What matters is whether each gap is stable. A stable gap is a lens you can steer through; a shifting, unmeasured one makes every budget decision fiction.

What each system actually counts

Meta Ads Manager. Counts a conversion when someone who clicked (7-day default) or viewed (1-day) an ad converts — even if they arrived through Google search two days later. View-through credit especially inflates retargeting: your existing customers see ads in the feed, buy like they always would, and Meta takes the win.

Google Ads. Same self-grading, different windows, plus its own quirk: branded search. Someone who saw your product on TikTok, googled your brand name, and clicked the ad above your own organic listing counts as a Google Ads conversion — for a customer another channel created.

GA4. The closest thing to a referee: data-driven attribution across channels, so it splits credit instead of double-counting. But it's blind where cookies die — iOS, ad blockers, cross-device journeys — so it systematically under-reports paid social in particular. Neutral, and incomplete.

Shopify / your CRM. Counts orders and revenue — reality. But its "sales attributed to" reports use their own simplified logic, so treat Shopify as the authority on how much and a weak witness on why.

So: Meta + Google can exceed Shopify because both claimed the same orders; GA4 sits below the platforms because it splits credit and loses cookies. Every store shows this pattern. Yours isn't broken — it's typical.

Which number to steer by

Use each system for what it's structurally good at:

Budget decisions → total contribution margin after ad spend, from Shopify/CRM data, trended weekly. If ad spend rises and this number doesn't follow within your purchase cycle, the platforms' claims are inflated regardless of what they report. The full framework is in high ROAS but no profit.

Comparing campaigns inside one platform → that platform's numbers. Meta's bias applies roughly equally to campaign A and campaign B, so relative comparisons survive.

Channel mix questions → GA4, plus judgment about its paid-social blind spot.

The tie-breaker for big calls → turn something off for two weeks and watch Shopify. Crude, unpopular, and the only test attribution can't argue with.

When the gap IS a problem

A stable gap is workable. These patterns mean something is actually broken:

The gap suddenly widens with no strategy change — usually a tag stopped firing, a pixel got duplicated, or consent banners started eating events.

Platform conversions exceed store orders — not revenue, order counts. That's double-firing events, not attribution philosophy.

GA4 and Shopify disagree wildly on totals — these two should be reasonably close; a 30%+ gap points at implementation, not attribution.

Numbers that match too perfectly. Platform and store matching exactly usually means someone imported store conversions into the platform and it's reporting your data back to you as its achievement.

Diagnosing which case you have is a tracking audit: duplicate events, missing CAPI deduplication, wrong conversion sources, consent configuration. The checks are in the Google Ads audit checklist and the Meta audit checklist, and the deeper setup work in ecommerce tracking setup.

The uncomfortable summary

Perfect attribution died with the third-party cookie, and every dashboard now shows you a confident estimate wearing the costume of a fact. The businesses that navigate this well don't chase reconciliation — they pick one commercial scoreboard (margin after ad spend, or cost per closed client), keep platform tracking clean enough to compare campaigns, and validate big decisions with real-world tests.

Want your numbers untangled?

Related reading:

High ROAS but No Profit

E-commerce Attribution Models

GA4 and Google Ads Integration