Expect a structural gap of roughly 30%, not zero. On a 14-location home-services network, the share of bookings matchable back to a click sat in a 0.56–0.83 band across settled windows — and a full forensic investigation found no ad-platform setting that explained the variance.

On this page

• What causes the gap between Google Ads and my CRM?
• What is not causing the CRM attribution gap?
• What did I get wrong the first time?
• How do I compute my match rate correctly?
• What should I do once I know my match rate?

What causes the gap between Google Ads and my CRM?

Three causes, none of them faults:

• Customers dialling a number that is not the tracked one — a static number, a listing, a truck, a fridge magnet.
• Booking later, outside the window or across a session boundary.
• Cross-device journeys.

What is not causing the CRM attribution gap?

This is worth stating because it saves months.

A runtime investigation across 13 sites confirmed the click identifier was captured, transmitted to the booking system, and the tracked number swapped correctly — identical on the best-matching and the worst-matching accounts. Duplicate tag containers and JavaScript errors did not correlate. No redirect, consent or competing-tracker issue. The call-extension theory was refuted, because call share did not track the match rate.

Every ad-platform setting was identical between healthy and apparently-broken accounts: auto-tagging on everywhere, the maximum lookback window everywhere, the same tracking template, the same final-URL suffix, customer data terms accepted everywhere.

The conclusion: it is not the website, and it is not a Google setting. The gap is downstream capture.

What did I get wrong the first time?

The per-account match figures ranged 0.46 to 0.91, which reads like several locations have badly broken tracking. Decomposed over the full settled window, the real band was a tight 0.56 to 0.83. The headline spread was short-window noise.

Acting on the snapshot would have meant managing several healthy locations bluntly on the basis of a measurement artifact.

Two further ways to get this number wrong, both seen in the same investigation:

1. A stale stored factor overstated brokenness and triggered the wrong fallback handling.
2. Using the aggregate conversions column understated the gap badly — it ran up to 2.13× the biddable count because it included legacy and duplicate booking actions. Never compute the match rate from the aggregate.

How do I compute my match rate correctly?

Booked jobs from the ad platform, by conversion date, summed over the actual booking actions only, divided by bookings from your own system — both sides over the same fully settled weeks.

Weeks ending roughly three weeks ago or older. The freshest one or two weeks read artificially low because of upload lag, not because performance dropped.

What should I do once I know my match rate?

Use it to correct your economics, not to panic. If Google sees 60% of your bookings, then the cost per booked job it implies is overstated by roughly 1 ÷ 0.6, and any target you set against it is tighter than you intended.

The lever that actually raises coverage is enhanced conversions for leads plus consistent hashed customer data on every booked lead — lifting coverage materially — on the order of a third again on a poorly-matched account. That buys measurement accuracy. It does not automatically create room to spend.

Related questions

My Conversions and All Conversions columns don't match — which one should I actually judge on?

Neither, until you have segmented it. `All conversions` is a sum over every conversion action attached to the account, not a count of people or events. Read the full answer.

Should I have more than one primary conversion action, or does that double-count my conversions?

Yes it double-counts, and sometimes that is fine. The real question is not how many primaries you have — it is what your bidding is actually optimising toward, and the primary flag is not a reliable answer to that. Read the full answer.

Should I switch my Google Ads conversion action from form fills to booked jobs?

Yes, and it is usually the single highest-value change available to a home-services account. Smart Bidding optimises toward whatever you feed it, so a form-fill goal buys you people who fill in forms. Read the full answer.

Written by Usama Khan, who runs Google Ads for e-commerce brands and home-services companies at AdventurAds. Figures are from accounts under active management and are anonymised. Last reviewed 2026-08-26.