Are your Google Ads conversions actually real?

They are partially real and largely inflated — a view-through conversion credits your ad for a conversion by a user who saw the ad (without clicking) then converted later, which captures some genuine awareness-driven influence but also claims credit for conversions that would have happened through organic search, direct traffic, or other channels regardless. Across audited accounts, 40–70% of view-through conversions fail a holdout test (the conversion happens without the ad being shown too). For direct-response campaigns, view-throughs are almost always double-counting organic demand; for awareness campaigns, a discounted share is reasonable. The Conversion Quality Audit shows your view-through percentage per campaign and recommends whether to weight them at 100%, a discounted share, or exclude them from bidding.

Generally no for performance campaigns (Search, Shopping, PMax's shopping component) — view-throughs inflate reported ROAS in a way that doesn't reflect actual business value, and including them trains Smart Bidding toward traffic that does not incrementally convert. Include them, optionally at a discounted rate (say 30–50%), for awareness-focused campaigns (Display, YouTube) where the ad's job is to drive later intent. The rule of thumb: if you would report this ROAS to a CFO expecting causally-attributable revenue, exclude view-throughs. The Conversion Quality Audit recommends the view-through inclusion setting per campaign based on the campaign's role in your funnel.

Google's internal benchmarks claim 70–90% accuracy on modeled conversions (conversions estimated rather than directly observed, used to fill gaps from iOS privacy, consent denials, and cross-device), but independent testing suggests real accuracy is closer to 50–70% in high-privacy markets. Modeled conversions scale up as consent mode denial rates rise — in GDPR-heavy markets they can account for 40–60% of Google Ads' reported conversion volume. This matters because Smart Bidding treats modeled conversions identically to verified ones when calibrating bids. The Conversion Quality Audit quantifies your modeled conversion share per campaign and flags campaigns where the share exceeds 30% as having degraded bidding signal.

Four diagnostic checks: (1) compare Google Ads conversion count against your backend order count for the same date range — if Google Ads exceeds backend by 20%+, something is double-firing, (2) check whether you have both GA4 conversion import AND native Google Ads tag active on the same event, (3) verify 'Count: One' vs 'Every' setting on each conversion action matches your business intent, (4) inspect network requests on your thank-you page for duplicate conversion pixel fires. Most double-counting traces to cause 2 or 3. The Conversion Quality Audit automates all four checks and flags the specific conversion actions with deduplication risk.

Anchor on your backend order system (Shopify, WooCommerce, Stripe, CRM) as ground truth — that's the number you actually got paid for. Compare daily backend orders to Google Ads' attributed conversions and GA4's attributed conversions. If Google Ads says 500 and backend says 200, the 300 gap is some mix of view-through, modeled, cross-device, and double-counting. Work backward from the gap rather than trying to validate each conversion individually. The Conversion Quality Audit produces a daily reconciliation chart showing backend actual, Google Ads attributed, and GA4 attributed on one timeline so you see exactly where the gap sits.

Probably not real in the sense of being causally attributable — PMax's channel mix typically includes 60–70% Display and YouTube impression volume, both of which generate view-through conversions aggressively when the same user later converts via another channel. A 70% view-through rate means PMax is largely claiming credit for conversions that would have happened anyway through organic search, direct, or other paid channels. The fix is to disable view-through conversions for PMax bidding (or set the view-through window to 1 hour instead of 1 day) and observe whether 'real' conversion volume holds up. The Conversion Quality Audit runs this comparison for you and quantifies the share of your PMax conversions that are click-through vs view-through.

When a user denies tracking cookies, Google uses three signal sources to model the conversion: (1) cross-site logged-in behaviour from users in the same cohort who did consent, (2) aggregated pattern data from advertisers with similar conversion funnels, (3) device-level and network-level signals (timing, geolocation, session characteristics) that correlate with historical conversions. The output is a probabilistic attribution that Google then reports as a conversion, with no indication in the UI that it was modeled rather than observed. In consent-mode-heavy markets this can reach 40–65% of reported conversions. The Conversion Quality Audit estimates your modeled share per campaign by comparing observed conversion rate pre- and post-consent-mode implementation.

Google does not disclose this directly in the UI — you have to infer it. The rough method is: compare your consent-denial rate (visible in GA4's consent signal reports) against your Google Ads conversion volume, and assume Google is modeling conversions for the denied-consent user share. In the UK, consent denial averages 20–30%, so roughly 15–25% of Google Ads conversions in a UK account are modeled. In Germany that rises to 40–60%. The Conversion Quality Audit produces your specific modeled-conversion estimate and shows its impact on your effective CPA after stripping modeled conversions out.

Smart Bidding calibrates to whatever conversion signal it receives — if 40% of your conversions are modeled, view-through, or cross-device estimates that don't represent real outcomes, the algorithm bids on traffic that 'converts' at the modeled rate but produces no actual revenue. Reported ROAS stays stable or improves while true business ROAS degrades, which is why accounts sometimes see deteriorating revenue despite 'improving' Google Ads metrics. Fixing conversion signal quality (setting high-intent events as Primary, excluding view-throughs for bidding, removing duplicates) is almost always more impactful than changing the bid strategy itself. The Conversion Quality Audit produces a Signal Health Score for each campaign showing how trustworthy its conversion data is for bidding.

A 2.5x gap is well outside the normal 15–35% discrepancy range and indicates a concrete tracking problem rather than structural difference. The most common causes: (1) a lead-gen form counting form-loads as conversions rather than submissions, (2) view-through conversions inflating the count by 2–3x (common for PMax and Display), (3) the conversion action set to 'Every' instead of 'One' for repeat form submissions, (4) duplicate conversion pixel fires. Lead-gen accounts typically see this pattern when Google Ads treats any form interaction as a conversion while CRM only records verified contacts. The Conversion Quality Audit reconciles your reported conversions against a CRM upload and identifies which of the four causes applies.