How to Check Invalid Clicks in Google Ads (Step by Step)

Most advertisers never see this data, because the columns are hidden by default. Many guides stop at the column path. This guide goes further: how to segment the numbers, how to tell a normal rate from a worrying one when Google publishes no benchmark, what the column leaves out, how to cross-check it against GA4 and your CRM, and the point where reading data should turn into requesting a credit.

If you are already sure you were billed for invalid clicks and want the money back, skip to our guide on Google Ads invalid click credits. This post is about finding and reading the data first.

Step 1: Add the Invalid Clicks Columns

The columns live in the standard campaign table. Google documents this path for the Invalid clicks column in its About invalid traffic page; Invalid click rate sits next to it in the same column list:

1. In the left navigation, open the Campaigns menu and click Campaigns.
2. Click the Columns icon above the data table.
3. Click the search icon next to "Modify columns for campaigns".
4. Search for "Invalid clicks".
5. Tick Invalid clicks and Invalid click rate. If you run video or other interaction-based campaigns, also tick Invalid interactions and Invalid interaction rate.
6. Select Apply.

Save the column set if you want it to persist across sessions. Without that, the next person on the account opens a default view and never sees the numbers.

Two definitions matter here. Google's API reference describes invalid clicks as the "number of clicks Google considers illegitimate and doesn't charge you for", and invalid click rate as "the percentage of clicks filtered out of your total number of clicks (filtered + non-filtered clicks)". So the rate's denominator includes the filtered clicks themselves. If a campaign shows 900 clicks and 100 invalid clicks, the rate is 100 out of 1,000, which is 10%, not 11%.

Step 2: Segment the Numbers by Network, Device, Time and Click Type

A single campaign total hides the pattern you are looking for, so segment it. Use the Segment icon above the same table. Google's API reference lists the segments these metrics support, and that list is the honest guide to what the interface can break down:

• Network (Google Search, Search Partners, Display and so on). This is usually the most revealing split. If a Search campaign's invalid clicks sit almost entirely on Search Partners, that is a different problem from invalid clicks on Google Search itself, and the fix (opting out of partners) is different too. Our Search Partners lead quality guide covers that trade-off.
• Device. A rate that is flat on desktop and climbing on mobile points toward app inventory or accidental taps rather than a determined attacker.
• Time: day, week, month, quarter and day of week. Weekly is the most useful grain for spotting change.
• Click type, which separates headline clicks from calls, sitelinks and other click types.

What is not on the list matters as much. Google's API reference does not list hour, location, ad group, keyword or search term as segments for these metrics, so don't expect those breakdowns. For hourly patterns you need your own click logs, which our post on detecting click fraud before it ruins your campaign walks through.

For a recurring view, build the same thing in Report Editor (Campaigns menu, then Report Editor): campaign as the row, network and device as dimensions, clicks, invalid clicks and invalid click rate as metrics, scheduled weekly. It turns a one-off check into a habit.

Step 3: Read the Rate Against Your Own Baseline

There is no official normal rate. Google states: "There is no industry standard for a normal invalid traffic rate." The industry invalid traffic rates you see quoted in articles usually come from programmatic ad verification and measure impressions across open-web inventory, not clicks filtered inside Google Ads, so lifting them into your account produces a false comparison. We cover the qualitative differences between campaign types in our invalid traffic benchmarks by campaign type, and those are deliberately directional rather than numeric.

What you can build is a baseline for your own account:

1. Export weekly invalid click rate per campaign, segmented by network, for the last 8 to 12 weeks.
2. Note the typical week and the highest week for each row. Brand Search, non-brand Search, Search Partners and Display will each settle at a different level, so never average them together.
3. Flag any week that lands clearly above that row's own previous high, or a steady climb across three or four weeks. Those thresholds are our working rule of thumb, not a Google standard. Adjust them to how volatile your account is.
4. Check what changed that week before calling it fraud. Google itself notes that a spike "doesn't always indicate invalid traffic"; budget or bid increases, new keywords and seasonal demand all move click volume.

Read the direction of the number carefully. Google's own wording is that "higher numbers show that Google caught and removed more invalid interactions" from your metrics and your bill. A rising rate is not money lost. It is evidence that a campaign is attracting invalid traffic, which is a reason to ask how much of that traffic is getting past the filter and being billed.

One more caution: Google keeps reviewing traffic after the click, and invalid activity found before the billing cycle ends is removed from your campaign metrics. The figures for the last few days can still change, so judge trends on completed weeks.

What the Invalid Clicks Column Shows and What It Does Not

This is the section most guides skip, and it decides how much weight you can put on the number.

The most important row is the third one. Filtered clicks were never charged, so they cost you nothing directly. The clicks that hurt are the ones that looked valid to Google, were billed, and still never had a buyer behind them. By definition, they are not in this column.

The second most important row is the fourth. You cannot exclude what you cannot identify, and Google does not show which IPs or devices it filtered. That is why the column is a thermometer, not a treatment.

Check Credits Separately in Billing

Invalid clicks found before billing are filtered; invalid clicks found after billing come back as credits, and they are reported in a different place. According to Google Ads Help, go to the Billing menu, open Summary, and look for "Invalid activity" under the Adjustments dropdown in the month card. Credits also appear on later invoices and in transaction history as negative values.

For a campaign-level view of those credits, Google offers the Invalid Activity Credit Report: in Report Editor, open the Template gallery and choose the "Invalid Activity Credit Report: Search & PMax" template. It reports credited clicks, credited interactions and credited amount by campaign and network, along with adjusted cost, CPC, CTR and conversion metrics. It covers Search and Performance Max only. Reading that report in depth belongs to the credits guide, so we will not repeat it here.

Cross-Check Against GA4 and Your CRM

The invalid clicks column tells you what Google caught. Your analytics and your CRM tell you what got through. The comparison between them is where billed invalid traffic shows up.

Google Ads clicks versus GA4 sessions. These will never match exactly. Google's clicks and sessions troubleshooter lists the usual causes: Google Ads filters out invalid clicks while Analytics reports all sessions, a user may click an ad several times in a short period, a user may leave before the Analytics tag loads, and GCLID stripping or tag problems break the link. So do not chase the absolute gap. Watch for a change in the gap: one campaign where clicks rise and sessions do not, with no tracking or landing page change, deserves a closer look.

Engagement quality in GA4. Build an exploration filtered to the suspicious campaign and look at engagement time, engaged sessions, new user share, city and device. Clusters of near-zero engagement from one location or one device type are the pattern. Our guide to detecting and filtering bot traffic in GA4 has the exact exploration setup.

Outcomes in the CRM. This is the check nothing else replaces. Join leads back to their campaign (via GCLID or UTM), then compare qualified lead rate and closed revenue by campaign and network. A campaign whose invalid click rate is rising, whose GA4 engagement is falling and whose leads are junk is telling you the same story three ways. A campaign with a rising invalid click rate but steady qualified leads is probably being protected adequately by Google's filters.

Keep Google's own caveats in mind as you do this. Its About invalid traffic page notes that "An IP address isn't always unique to one device", because shared networks and NAT can put many users behind one address, and that a low conversion rate doesn't always mean invalid interactions. Patterns across several signals are evidence. One odd number is not.

Where Performance Max Reporting Differs

Performance Max shows a campaign-level Invalid clicks figure like any other campaign, so the column path above works. The differences are in what sits around it:

• Credits are better covered than for most campaign types. The Invalid Activity Credit Report includes Performance Max and breaks credits down by network, while Display, Video, Demand Gen and App campaigns are not covered by it.
• Channel performance reporting does not replace the invalid clicks column. Google has made channel performance reporting available in all Performance Max campaigns, and the API supports segmenting PMax results by network. But the channel report documentation does not mention invalid clicks, so treat it as a way to find weak channels by cost and conversion quality, not as an invalid click breakdown. Our Performance Max channel reporting guide covers how to use it.
• There is still no keyword or placement attribution for invalid clicks. In a blended campaign, that makes the GA4 and CRM cross-checks more important, not less.

When to Escalate to a Credit Request

Reading the data is the right response most weeks. Escalate when the evidence suggests invalid clicks were billed, not just filtered:

• A click spike on one campaign that GA4 sessions and CRM leads do not confirm.
• Repeat visits from the same sources, visible in your own logs, with no conversions.
• Clicks from locations you do not target.
• A sustained rise in invalid click rate on a campaign, alongside falling lead quality, with no change on your side to explain it.

Google investigates only traffic from the last 60 days, so the clock matters. Gather IPs, user agents, GCLIDs, date ranges and the affected campaigns while they are fresh. The credits guide explains what is realistically recoverable, and our invalid click dispute template gives you the wording and field-by-field structure for the Click Quality Form. For the underlying definitions Google uses, see our glossary entry on invalid traffic.

Where ClickFortify Fits

The gap in Google's reporting is the click-level view: which source, which device, how it behaved, and whether it was billed. ClickFortify fills that gap for Google Ads. It scores every click on 200+ signals, syncs confirmed offenders into your Google Ads IP exclusions automatically, and keeps an evidence trail for every block, which you can use in an invalid-click credit request. That gives you the click-level view the Invalid clicks column cannot.

It does not replace Google's filtering, and it does not change what Google decides to credit. Its job is to stop repeat sources before their clicks are billed, so there is less to reconcile at month end. To see the difference on your own account, run ClickFortify's 7-day free trial on Google Search and compare the sources it flags in the first week against your Invalid clicks column for the same days.

The Bottom Line

Checking invalid clicks in Google Ads takes two minutes: Campaigns, Columns, search "Invalid clicks", Apply. Reading them well takes longer. Segment by network, device and week, judge each campaign against its own history rather than an imported benchmark, and remember that the column only counts what Google already caught for free. The clicks that cost you money are the ones it missed, and you find those by comparing Google's numbers with GA4, your CRM and your own click logs.