“I think the tracking might be off, but the campaigns seem to be working.” This is one of the most expensive sentences in ecommerce advertising. It treats conversion tracking as a reporting preference rather than a foundation that everything else depends on.
Inaccurate tracking does not just produce wrong numbers in a dashboard. It actively directs the ad spend in the wrong direction, causes bad decisions that cannot be undone retroactively, and often costs more over time than fixing the tracking would have.
The Compound Effect of Wrong Data
Start with how Google’s bidding algorithms work. Target ROAS and Target CPA bidding strategies make thousands of real-time micro-decisions based on the conversion data in the account. Every auction outcome is fed back into the model. The model improves as the data improves. Or it degrades as the data degrades.
When conversion tracking is inflated (double-counting, wrong revenue values, or counting adds-to-cart as purchases), the algorithm believes performance is better than it is. It raises bids in confidence. It spends more aggressively. It enters auctions it would have passed on if it knew the actual conversion rate.
The result is not just inflated numbers in the report. It is actual over-spending. The algorithm is bidding based on phantom performance that does not exist. Every auction it wins based on inflated data costs real money for a real click that produces real, lower-than-expected return.
When tracking is deflated (missing conversions, delayed firing, tracking that breaks for certain browsers or devices), the algorithm underestimates performance. It reduces bids. It passes on auctions it should have entered. The campaign under-spends relative to its opportunity.
Neither direction is neutral. Both are actively costly.
The Decision Layer
Beyond the algorithmic consequences, bad tracking affects every human decision made about the account.
A store that reports 4x ROAS on bad tracking makes budget decisions based on 4x. It allocates more spend because the number looks profitable. It may turn off Search campaigns to consolidate budget into Shopping because Shopping “performs better” when in reality Shopping appears to perform better only because its tracking is capturing more of the credit.
A store that reports 1.5x ROAS on bad tracking considers shutting down Google Ads entirely. It runs the analysis showing the channel is barely covering costs. It hires someone to figure out why performance is so poor. All of this happens while the actual performance may be 3x or better.
I have reviewed accounts in both situations. In the first case, the store was overinvesting in a channel that was genuinely profitable but not as profitable as reported. In the second case, the store was about to turn off a channel that was actually working well. Fixing the tracking in both cases completely changed the decision.
What “Sort of Working” Actually Means
Most tracking problems are not complete failures. They are partial failures. Some conversions fire correctly. Some do not. The result is a mix of accurate and inaccurate data that is harder to identify than total failure because the reports still show conversions, the ROAS is in a plausible range, and nothing looks obviously broken.
In this state, decisions are being made on a corrupted average. The real performance might be 2.5x; the reported performance is 3.2x. The difference between those numbers affects budget decisions, ROAS target setting, and product-level investment. Over a year of ad spend, the cumulative misdirection adds up to real money.
The problem with partial failures is that they require active checking to find. A complete tracking failure is obvious: no conversions at all. A partial failure requires someone to compare conversion data against backend order data, examine which purchase paths are captured and which are not, and build a picture of where the gaps are.
The Opportunity Cost Problem
There is a cost of under-attribution that is less obvious than over-spending but equally real.
When conversions are undercounted, campaigns that are genuinely working well report poor ROAS. The natural response is to reduce budget or shut them down. The store loses the contribution from those campaigns going forward.
If a campaign was actually acquiring new customers at a profitable cost and the tracking showed it as marginally unprofitable, every month it runs with reduced budget (or not at all) is a month of customer acquisition the store did not get. That is not a recoverable loss. Those customers who would have bought are simply not customers.
Undercounting conversion value (recording conversions but at wrong revenue amounts) causes a different version of this problem. If high-value orders are systematically undercounted and low-value orders are over-represented in the conversion data, the algorithm optimizes toward low-value orders. Budget flows toward whatever audience produces the cheap conversions. High-value customer segments are underserved.
What Fixing Tracking Actually Costs
There is a real cost to fixing conversion tracking correctly. For a Shopify store, a proper tracking implementation with enhanced conversions, correctly passed revenue values, deduplication logic, and verification against actual order data typically takes a few hours to a few days of skilled work.
This is not a large cost relative to most Google Ads budgets. A store spending 5,000 dollars per month on ads that had bad tracking for six months has spent 30,000 dollars on campaigns operating with degraded data. The one-time fix cost is a fraction of that.
The reason stores delay is often that the problem is not visible. The dashboard shows numbers. They look roughly plausible. Nobody is complaining about an error message. The tracking “works” in the sense that something is being recorded. The fact that it is recording wrong things is only visible when someone explicitly checks.
A Quick Check Anyone Can Do
You do not need to understand the technical setup to do a basic check. Take any single month. Look at the total number of purchase conversions Google Ads reports for that month. Compare it to your total Shopify orders for the same month (all orders, not just those attributed to Google).
If Google Ads reports more conversions than you had total orders across all channels, something is seriously wrong. Double-counting, non-purchase events being counted as purchases, or a date discrepancy.
If Google Ads conversion count is in a plausible range relative to total orders (accounting for the fact that not all orders come from Google Ads), check whether the total revenue in Google Ads conversion value tracks approximately with actual Google-attributed revenue in Shopify. If it does not, revenue values are not being passed correctly.
This is a rough check, not a full audit. But it catches the most egregious problems and tells you whether further investigation is warranted.
Getting This Fixed
Bad conversion tracking is the most fixable problem in Google Ads, and fixing it has compounding benefits: the bidding algorithms immediately have better data to work from, future campaign decisions are made on accurate information, and any audit or performance review reflects reality.
Getting the tracking right before anything else is how I approach every new store engagement. If you are uncertain about the accuracy of your conversion data, this is the most important thing to address. Reach out at adnanagic.com/#contact.
Part of the Google Ads for Store Owners series, written for ecommerce owners who want their ad spend to actually work.
Related Posts
- Shopify Owners: Why Your Google Ads Conversion Numbers Are Probably Wrong
- Your Google Ads ROAS Looks Great but Your Bank Account Disagrees: Why
- A Google Ads Account Audit: What I Check and What It Usually Finds
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