Here's a puzzle that every Shopify merchant running both Meta and Google ads should solve.
Open Meta Ads Manager. Note your conversion count for last week. Let's say it's 120.
Open Google Ads. Note the same period. Let's say it's 95.
Total reported conversions: 215.
Now open your Shopify admin. Check actual orders for the same period. It's 147.
Where did the other 68 conversions go?
They didn't go anywhere. They never existed. Both platforms claimed the same 68 orders. Your marketing performance looks 46% better than reality.
How double attribution works
The mechanics are straightforward. A customer's journey might look like this:
Monday: Sarah scrolls Instagram and sees your Meta ad. She pauses, looks at the product, maybe even visits your site. She doesn't buy.
Wednesday: Sarah searches Google for "best [your product category]." She clicks your Google Shopping ad. She browses but doesn't buy yet.
Friday: Sarah decides to purchase. She goes directly to your site (or clicks another ad) and completes the order.
What Meta reports: One conversion. Sarah clicked a Meta ad within the 7-day attribution window. Credit: Meta.
What Google reports: One conversion. Sarah clicked a Google ad within the attribution window. Credit: Google.
What Shopify records: One order. One customer. One payment.
Two platform conversions. One actual sale. This isn't a bug in either platform's reporting. Both are doing exactly what their attribution models are designed to do: claim conversions within their attribution windows. The problem is that nobody is reconciling the total.
The scale of the problem
Overlap isn't occasional. It's structural and it scales with your spend.
The more you spend on both platforms, the more overlap you'll have. This is because:
Shared audiences. Your Meta audience and your Google audience aren't separate populations. They're the same people using different apps at different times of day. A customer who sees your Instagram ad in the morning and your Google Shopping ad in the afternoon is one person in two attribution windows.
Broad targeting amplifies overlap. If you're using broad targeting on Meta (which Meta increasingly recommends) and broad match on Google, both platforms are finding the same high-intent customers. They're competing for the same conversions and both claiming credit.
Retargeting doubles the effect. If you're running retargeting on both platforms, the overlap is even higher. A customer who visited your site is now being retargeted by Meta AND Google. Whichever ad they click before converting, both platforms had a touchpoint in the window.
For most Shopify merchants running significant spend on both platforms, overlap falls in the 15–40% range. At the high end — merchants spending similar amounts on both platforms with broad targeting and retargeting — overlap can exceed 40%.
What overlap does to your ROAS
The math is direct. If 30% of your reported conversions are double-counted, your blended ROAS is inflated by roughly 30%.
Worked example:
- Monthly spend: $5,000 Meta + $3,000 Google = $8,000 total
- Meta reported revenue: $20,000 (4.0x ROAS)
- Google reported revenue: $12,000 (4.0x ROAS)
- Combined reported revenue: $32,000
- Blended reported ROAS: 4.0x
But if 30% of conversions overlap:
- Actual unique revenue: ~$24,000
- True blended ROAS: 3.0x
That's a full ROAS point of inflation from overlap alone — before accounting for cannibalization or creative fatigue.
See your own estimated numbers with our True ROAS Calculator.
Why neither platform will fix this
This problem has existed since the first merchant ran ads on more than one platform. Neither Meta nor Google has an incentive to fix it, for the same reason neither has an incentive to show lower conversion numbers: fixing it would mean reporting fewer conversions, which would mean merchants might spend less.
Meta can't see your Google data. Google can't see your Meta data. Neither can detect that they're both claiming the same order. And even if they could, the structural incentive is to claim credit, not to defer it.
Some third-party attribution tools attempt to solve this with multi-touch attribution (MTA) — distributing credit across touchpoints rather than giving full credit to each. This helps, but it has limitations: MTA still only works with the touchpoints it can observe, and it can't determine whether the customer would have bought without any ads at all.
The only complete solution is to match platform-reported conversions against actual orders at the source — your Shopify store — and identify where the same order appears in multiple platform reports.
How to detect your overlap
Quick method: the total test
Add up all platform-reported conversions for a week. Compare to Shopify orders.
- If the platform total is within 10% of Shopify: low overlap
- If it's 10–25% higher: moderate overlap
- If it's 25%+ higher: significant overlap
This takes two minutes and gives you a directional answer.
Better method: revenue matching
Instead of conversion counts, compare revenue. Add Meta's reported revenue + Google's reported revenue. Compare to Shopify's total revenue from those channels.
Revenue matching is more accurate because it accounts for order value differences. A few high-value double-counted orders can inflate revenue more than conversion counts suggest.
Best method: order-level matching
The most precise approach matches individual orders across platforms. For each Shopify order, check: did Meta claim this conversion? Did Google? If both did — that's an overlap event.
This requires cross-referencing timestamps and order values across three data sources (Shopify, Meta, Google). It's too tedious to do manually for most merchants, but tools that connect all three accounts can automate it.
Ripplux uses a 24-hour time window for order matching — if both platforms report a conversion within 24 hours of a Shopify order with matching revenue, it's flagged as overlap.
What to do about it
Overlap isn't something you "fix" in the traditional sense. You can't tell Meta and Google to coordinate their attribution. What you can do is:
Know your real number. Once you understand that your blended ROAS is inflated by 20–30%, you can make budget decisions based on the true number instead of the reported one. This alone prevents overinvestment in underperforming channels.
Optimize against true metrics. Instead of optimizing each platform's ROAS independently (which incentivizes overlap), optimize for total Shopify revenue relative to total ad spend. This is your true blended ROAS, and it's the only number that correlates with actual profit.
Test channel allocation. Run experiments where you shift budget between platforms and measure the impact on total Shopify revenue — not platform-reported conversions. If shifting $1,000 from Meta to Google doesn't change total revenue, that $1,000 was overlapping.
Accept the constraint. Some overlap is unavoidable when running multi-platform campaigns. The goal isn't zero overlap — it's knowing how much overlap exists so it doesn't distort your decisions.
For the full picture of how overlap combines with cannibalization and creative fatigue to inflate your numbers, read What Nobody Tells You About Your ROAS.