How are you handling Google and Meta both claiming credit for the same conversion?

RankBlaze

RankBlaze

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Running both Google Ads and Meta Ads for a client. Total reported conversions: Google says 140 for the month, Meta says 95. Backend (Shopify) shows 160 actual orders.

So the platforms are claiming 235 combined conversions for 160 actual purchases. That's a 47% inflation. Both platforms are using their own attribution windows and both are claiming assists that don't exist.

I know this is a known problem. But the client is asking why the "total ROAS" across both platforms looks so much better than the actual business results.

How do you explain this to clients without making it sound like the platforms are lying (even though kind of they are)? And what's your method for actually evaluating true channel contribution when both channels are running simultaneously?

Currently using the blended approach (total revenue / total spend) but it doesn't give channel-level insight.
 
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yeah this is just normal attribution overlap tbh, I usually show Shopify as source of truth + explain Meta/Google are both taking credit for same users unless you run a proper dedup setup (GA4 + server-side + UTMs), otherwise you just look at blended ROAS not platform ROAS.
 
Get rid of Both of the networks.... Stop using them
 
Yeah this is just normal attribution overlap ,both platforms are crediting the same purchase, not creating extra ones.

I usually explain it like: “Google + Meta are both reporting influence, not unique sales,” then we only trust Shopify as source of truth and use platform data for direction, not totals.

For actual split, I look at incrementality (holdouts / geo tests) or just run blended MER and judge which channel is more efficient under the same total revenue, not claimed ROAS.
 
Classic attribution overlap, trust Shopify as source of truth and use MER for total ROAS, both platforms just end up double claiming conversions.
 
just tell client they both assisted in the sale and use triple whale or simple ga4 utm tracking to see the real first/last touch attribution.
 
Pretty normal, I tell clients platform attribution shows influence not actual sales, and I use Shopify plus GA4 data as the source of truth for reporting.
 
i tell clients platform numbers show who influenced the sale, not unique orders, so i use Shopify/blended revenue as source of truth and treat Google/Meta attribution as directional not exact
 
Yeah this is normal when running Google and Meta together both platforms use different attribution windows so they often claim the same sale. I just treat Shopify as the real source of truth and use Google and Meta data only to understand what influenced the purchase not to add them together.
 
this is pretty common when someone clicks a meta ad first and later converts through google search. both platforms think they influenced the sale, so they both take credit.
 
I usually explain that platform numbers show attributed conversions, not exact extra sales.
 
My process is simple: find a topic I like, check keyword difficulty with a free tool, and then see if the top results are easy to compete with.
 
I usually explain that ad platforms report based on their own tracking, so I focus on backend data and blended ROAS to see the real business impact.
 
I usually tell clients that both platforms can claim the same conversion because they track it differently. It doesnt mean either one is fake, just different attribution models. Backend orders are the real source for reporting, while platform data helps me optimize campaigns. Looking at blended performance first then checking each channel trends works better for me.
 
This is pretty normal. Platform ROAS is more like “who touched the customer” not who actually caused the sale.
I usually trust Shopify/backend for the real numbers and use platform data for optimization signals only.
For channel contribution, test budgets, look at assisted conversions, incrementality tests, and blended ROAS over time.
Clients usually understand it when you explain every platform is taking credit for the same customer.
 
Thats pretty normal, i always use backend sales as the source of truth and treat platform numbers as attributed not actual orders
 
RankBlaze said:
Running both Google Ads and Meta Ads for a client. Total reported conversions: Google says 140 for the month, Meta says 95. Backend (Shopify) shows 160 actual orders.

So the platforms are claiming 235 combined conversions for 160 actual purchases. That's a 47% inflation. Both platforms are using their own attribution windows and both are claiming assists that don't exist.

I know this is a known problem. But the client is asking why the "total ROAS" across both platforms looks so much better than the actual business results.

How do you explain this to clients without making it sound like the platforms are lying (even though kind of they are)? And what's your method for actually evaluating true channel contribution when both channels are running simultaneously?

Currently using the blended approach (total revenue / total spend) but it doesn't give channel-level insight.
Click to expand...
Have you tried turning one channel down for a week just to see how much the total sales actually change?
 
I stopped comparing Google and Meta conversions directly because both platforms are looking through their own lens. The real number is always your store revenue and profit. Use platform data to see trends, but don’t expect their attribution reports to match reality.
 
I usually explain that each platform has its own attribution model, so I focus on blended ROAS, incrementality tests and backend data to judge the real performance.
 
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