How to Compare ROAS Across Meta, Google, and TikTok in One Report
by Trivas.ai
|
6 min read
Sep 08, 2026
Pull ROAS for the same week from Meta, Google, and TikTok, and you'll get three different stories about how well your ads are performing. Meta says 5.2x. Google says 3.8x. TikTok says 6.1x. None of them are lying, exactly, but none of them are telling you the whole truth either. If you're trying to figure out how to compare ROAS across Meta, Google, and TikTok in one report, the real work isn't pulling the numbers. It's making them mean the same thing before you compare them.
Why ROAS Looks Different in Every Ad Platform's Dashboard
Start with attribution windows, because that's where most of the gap comes from. Meta defaults to a 7-day click, 1-day view window. That's generous. A customer who clicked an ad a week ago and bought yesterday still gets counted, which inflates Meta's number relative to platforms with tighter defaults.
Google Ads is its own puzzle. Depending on whether an account uses data-driven attribution or last-click, the same conversion can get credited differently, and that shift alone can move reported spend efficiency by a meaningful margin.
TikTok adds a tracking problem on top of the attribution problem. If the pixel and the Events API aren't both configured correctly, conversions either lag by a day or two, or get counted twice. Either way, the ROAS number on the dashboard isn't trustworthy without checking both.
Then there's the deeper issue: each platform only sees itself. A customer who saw a TikTok ad, then searched the brand on Google and clicked a search ad, then bought, gets counted as a conversion by both TikTok and Google. Add up the platform-reported ROAS from all three channels and you're not looking at your business, you're looking at three overlapping claims to the same sale.
The Real Cost of Comparing ROAS Manually
Most marketing leads know all this already, which is exactly why they end up in a spreadsheet every Monday. Pull a CSV from Meta Ads Manager, one from Google Ads, one from TikTok. Paste them into tabs. Build a pivot table. That's 2 to 3 hours a week, easily, for a mid-size DTC team.
And it's fragile. Change a column header in an export, switch a currency format, and the pivot table breaks silently. Nobody notices until the numbers look wrong three weeks later.
The bigger problem is what gets left out. Blended ROAS calculated by hand rarely accounts for discounts, refunds, or shipping costs. So the spreadsheet says 4.5x when the real number, after refunds and promo codes, is closer to 3.6x. That gap looks small until you're deciding whether to push another $20K into a channel based on it.
And because the report is manual, it's also late. Budget decisions that should happen Monday morning wait until Tuesday or Wednesday because someone's still reconciling three CSVs.
What a Unified Multi-Channel ROAS Report Actually Needs
A report that actually answers how to compare ROAS across Meta, Google, and TikTok needs four things, and skipping any one of them brings back the same distortions.
First, spend data pulled from each platform's API directly, not exported by hand. APIs don't change column headers on you overnight.
Second, revenue tied to actual orders, from Shopify or Amazon, not to whatever conversion event the ad platform claims. The platform's version of "a sale happened" is not the same as your order management system's version.
Third, one attribution window and one attribution model applied consistently across all three channels. Doesn't matter if you pick 7-day click or 1-day click, just pick one and apply it everywhere. Otherwise you're comparing Meta's generous math against Google's stricter math and calling it analysis.
Fourth, net revenue, not gross. Subtract discounts and refunds before you divide by spend. Skip this step and every ROAS number in the report is overstated, sometimes by a lot.
How Trivas Builds This Report on Redshift
This is the actual mechanics of it, on our end. Trivas pulls raw spend and order data into Amazon Redshift, and normalizes currency and date fields across Meta, Google, and TikTok as part of that pipeline. No manual reconciliation between formats.
The dashboard layer then applies one attribution logic across all three channels. A 5x on Meta and a 5x on TikTok mean the same thing in the report, because they're built on the same window and the same revenue definition. That sounds basic, but it's the part most spreadsheet setups skip.
Wingman AI sits on top and flags week-over-week ROAS shifts past a threshold you set, so you're not opening three separate ad accounts just to check if something moved. If TikTok ROAS drops 25% in a week, you get a flag, not a surprise three weeks later.
And the reports refresh on their own. No Monday morning CSV ritual required.
Reading Blended vs Platform-Level ROAS Correctly
Once the data's clean, you still have to read it right, and this is where a lot of teams trip up.
Blended ROAS
What it shows: Total revenue divided by total ad spend across every channel
Best used for: Board updates, high-level trend tracking
What it hides: Which specific channel is actually driving the growth or the drag
Platform-level ROAS
What it shows: Revenue and spend broken out per channel, using the same window and model
Best used for: Budget allocation decisions, spotting which channel to scale or cut
What it reveals: That TikTok is scaling at 2.1x while Meta holds steady at 4x, for example, a distinction blended ROAS completely erases
Watch for the trap of judging a channel purely on its own ROAS number. TikTok top-of-funnel campaigns often run at a lower ROAS but drive incremental awareness that shows up later as a Google search conversion. Cut TikTok because its number looks weak in isolation, and you might be quietly starving your Google performance too.
One more rule: keep the time window identical across all three platforms when you're looking at trend lines. Comparing Meta's default 7-day window against TikTok's default 1-day window isn't a comparison, it's noise.
Quick Gut-Check: Calculate ROAS by Hand First
Before you automate any of this, check your math manually once. The formula is simple: net revenue from a channel divided by ad spend on that channel. Net means after discounts and refunds, not before.
Run that using a ROAS calculator against actual order data pulled from Shopify, then compare it to what the platform dashboard is telling you.
If the two numbers are close, fine. If they're off by more than 15 to 20%, that's not rounding error. That's a sign the attribution window or conversion tracking setup on that platform needs a second look before you build anything more permanent on top of it.
Getting a Multi-Channel ROAS Report Running
The fastest way to see this working is to just connect the accounts. Start a trial, link Meta, Google, and TikTok alongside your Shopify or Amazon order data, and let the platform pull real numbers instead of theorizing about what they'd look like.
Most teams have a working blended and per-channel ROAS dashboard within a day of connecting accounts. Not a week, not after a data migration project, a day.
If your setup involves custom attribution logic, a non-standard stack, or multiple storefronts feeding into one brand, it's worth talking to a founder directly rather than trying to force it into a generic dashboard. And if you're just starting to think through this stuff, our blog has more on where multi-channel attribution tends to go wrong.
Content author and contributor at Trivas.ai, sharing insights on e-commerce analytics, business intelligence, and data-driven strategies to help businesses grow.
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