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The AI Overview Traffic-Loss Calculator: A Published Formula to Estimate What Zero-Click Costs Each Keyword

A published, reproducible formula with sourced constants and worked examples for calculating how many clicks and dollars an AI Overview costs each keyword.

Bottom line

Multiply a keyword's monthly search volume by its historical CTR, its AI Overview trigger rate, and a CTR drop factor of 0.47 to 0.62 (Pew Research Center and Seer Interactive, 2025) to get lost clicks. SE Ranking / SE Visible and Semrush flag per-keyword AI Overview triggers; Ahrefs Brand Radar sizes AIO impression volume.

Last updated September 2026.

Your rank tracker still says position 3. Your traffic report says something else entirely. That gap is not a tracking bug. It is an AI Overview sitting on top of the result, and it is costing you a specific, calculable number of clicks every month.

Most teams treat that number as unknowable. It is not. Three organizations have already published the raw click-behavior data needed to calculate it: how often an AI Overview appears, how much it cuts organic click-through rate when it does, and how many searches end without any click at all. This piece turns those three data points into one formula you can run per keyword, today, without waiting for a vendor’s proprietary “AI visibility score.”

The formula

Lost Clicks per Month = Search Volume × Historical CTR × AI Overview Trigger Rate × CTR Drop Factor

Then, to turn clicks into money:

Lost Revenue per Month = Lost Clicks per Month × Conversion Rate × Value per Conversion

Four inputs feed the first line:

  • Search volume. The keyword’s average monthly search volume, from any keyword research tool.
  • Historical CTR. The organic click-through rate that keyword earned before an AI Overview started appearing, pulled from Google Search Console or a position-based benchmark.
  • AI Overview trigger rate. The percentage of tracked checks where Google actually shows an AI Overview for that exact query. This is not the same as “AI Overviews exist for this topic.” Trigger rate is query-specific and needs to be measured, not assumed.
  • CTR drop factor. How much of the remaining organic CTR the Overview removes when it appears. This is the one constant with two credible, sourced values, and picking between them is the judgment call the next section walks through.

The sourced constants behind it

Two independent studies measured how much an AI Overview cuts organic click-through rate, and they landed on different numbers because they measured different things.

ConstantValueSource
Click rate on searches without an AI summary15%Pew Research Center, 2025
Click rate on searches with an AI summary8%Pew Research Center, 2025
CTR drop factor, conservative0.47 (a 47% relative drop)Derived from Pew Research Center, 2025
Organic CTR on queries without an AI Overview1.62%Seer Interactive, 2025
Organic CTR on queries with an AI Overview0.61%Seer Interactive, 2025
CTR drop factor, aggressive0.62 (a 62% relative drop)Derived from Seer Interactive, 2025
US Google searches ending without any click68%SparkToro, 2026

Pew Research Center tracked the real browsing behavior of 900 U.S. adults across 68,879 Google searches and found people clicked a traditional result in 8% of visits with an AI summary present, against 15% without one. Seer Interactive tracked organic CTR across a large keyword panel and found a steeper drop: 1.62% down to 0.61% in the same period, comparing queries with an Overview to queries without one.

Neither number is wrong. They measure different populations of queries with different methods. Pick 0.47 as your conservative estimate for informational and narrative queries. Pick 0.62 as your aggressive estimate for commercial, product-comparison, and shopping queries, where an Overview often ships with a full product carousel and leaves even less reason to click through.

The 68% zero-click figure from SparkToro is not part of the multiplication. It is context: two out of every three US Google searches already end with no click at all, AI Overview or not. The formula above measures the additional loss an Overview adds on top of that baseline, on the specific keyword you are checking.

Worked examples: ecommerce, SaaS, and local service

Run the same four inputs through three different businesses and the dollar impact looks nothing alike, even when the click math is nearly identical.

Ecommerce

VariableValue
Keyword”best waterproof hiking boots”
Monthly search volume5,000
Historical organic CTR6%
AI Overview trigger rate85%
CTR drop factor0.62 (aggressive, product-comparison query)
Lost clicks per month158
Conversion rate2%
Average order value$120
Lost revenue per month$379

That is roughly $4,550 a year at risk from one keyword, before you count the customers who never come back for a repeat purchase.

SaaS

VariableValue
Keyword”best project management software for remote teams”
Monthly search volume2,200
Historical organic CTR4.5%
AI Overview trigger rate70%
CTR drop factor0.47 (conservative, informational query)
Lost clicks per month33
Lost clicks per year396
Trial signup rate8%
Lost trial signups per year32
Trial-to-paid rate20%
Lost paying customers per year6
Average first-year contract value$3,600
Lost first-year revenue$21,600 a year

SaaS funnels have more steps than ecommerce, so the formula’s output (lost clicks) is only the starting point. Carry it through your own trial and close rates before you report a dollar figure to anyone.

Local service

VariableValue
Keyword”emergency plumber columbus ohio”
Monthly search volume320
Historical organic CTR12%
AI Overview trigger rate55%
CTR drop factor0.62 (aggressive, read-and-call query)
Lost clicks per month13
Lost clicks per year156
Click-to-booked-job rate18%
Lost jobs per year28
Average job value$310
Lost revenue per year$8,680

That is from a single local keyword with only 320 monthly searches. Local, high-intent queries carry a lot of value per click, so even a modest trigger rate moves real money.

Build the worksheet in 5 minutes

Copy these column headers into a blank spreadsheet, one row per keyword, and you have a reusable worksheet without waiting on anyone to build one for you.

Keyword | Monthly Search Volume | Historical CTR | AI Overview Trigger Rate | CTR Drop Factor | Lost Clicks per Month | Conversion Rate | Value per Conversion | Lost Revenue per Month

Fill the first five columns per keyword, then let the last two columns do the multiplication. Sort the finished sheet by lost revenue and you have a prioritized list of exactly which keywords deserve a content fix first, instead of a gut feeling about which ones “seem important.”

Where to get each input

Historical CTR comes from Google Search Console for any keyword with enough impressions to be reliable, or from a position-based CTR benchmark when a keyword is too new or too low-volume for Search Console to report on cleanly.

AI Overview trigger rate is where SE Ranking / SE Visible and Semrush fit best. Both run per-keyword AI Overview trigger detection: you load your tracked keyword list, and the tool reports back the percentage of checks where an Overview actually appeared for that exact query, updated on a recurring schedule instead of a one-time manual check.

AIO impression volume, the scale of demand already sitting behind an Overview across a whole topic, is Ahrefs Brand Radar’s specific fit. It helps you decide which keyword clusters to run through the formula first, before you spend an afternoon on a low-volume query that was never worth the analyst time.

Conversion rate and value per conversion come from your own analytics: GA4 for ecommerce and SaaS conversion rates, your CRM for trial-to-paid rates and contract values, your booking system for local service job values.

The all-in-one option is Temso. It tracks AI Overview presence across your keyword set continuously, across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Microsoft Copilot, and its built-in AI SEO agent can turn a rising trigger rate straight into a prioritized content fix instead of just a line on a dashboard. It is the one tool here built to cover monitoring and the fix in a single workflow, rather than the input-gathering step alone. Plans start at $89 a month, with unlimited projects, users, and recommendations on every tier, and a 15% discount if you pay yearly.

A limit worth stating

These constants are averages across large keyword panels, not a guarantee for your specific query. Seer Interactive notes individual keyword CTRs can swing 0.8 to 1.2 percentage points around its published average, which is a wide range relative to a 1.62% baseline. Treat the formula’s output as a serious, defensible estimate for prioritization, not an audited revenue figure. And these two constants describe classic Google AI Overviews specifically; a fuller AI Mode results page suppresses clicks further still, so use this formula as a floor for that surface, not a ceiling.

What to do with the number

Run the worksheet on your top 20 keywords by search volume this week. Sort by lost revenue, not lost clicks, since the two rankings rarely match. Fix the highest-dollar keyword first: a tighter direct answer near the top of the page, clearer structure, and content built to be the source an Overview actually cites.

If you would rather have the trigger-rate column update itself instead of rechecking search results by hand every week, Temso runs that detection continuously and routes the highest-value gaps into a content fix. See the full comparison of tools that cover this work at /rankings/aeo-tools, and the scoring approach behind this site’s coverage at /methodology. Unfamiliar terms along the way are defined in the /glossary.

FAQ

How do I calculate traffic loss from AI Overviews?

Use this formula: Lost Clicks per Month equals Search Volume multiplied by Historical CTR, multiplied by the AI Overview Trigger Rate, multiplied by a CTR Drop Factor of 0.47 to 0.62. Multiply that result by your conversion rate and average order or contract value to get lost revenue. Run it once per keyword, not once for your whole site, since trigger rate and CTR vary sharply by query.

What is a CTR drop factor and which number should I use?

The CTR drop factor is the share of organic click-through rate an AI Overview removes from a query. Pew Research Center (2025) measured a 47% relative drop, from a 15% click rate down to 8%. Seer Interactive (2025) measured a 62% relative drop, from 1.62% organic CTR down to 0.61%, comparing queries with and without an Overview in the same period. Use 0.62 for commercial, product-comparison, and shopping queries, where the Overview often includes a full product carousel. Use 0.47 for informational and narrative queries, where the Overview reads more like a summary paragraph.

How do I find a keyword's AI Overview trigger rate?

SE Ranking / SE Visible and Semrush both run per-keyword AI Overview trigger detection: load your keyword list and get back the percentage of tracked checks where Google actually showed an AI Overview for that exact query. Ahrefs Brand Radar adds AIO impression volume on top of that, useful for sizing how much total search demand around a topic already sits behind an Overview. Without a tool, approximate a trigger rate by checking a query five to 10 times over two weeks and recording how often an Overview appears.

Does this formula work for ChatGPT, Perplexity, and Microsoft Copilot, or only Google AI Overviews?

The two published constants, 0.47 and 0.62, are specific to Google AI Overviews, since Pew Research Center and Seer Interactive both measured Google search behavior. The four-variable structure (search volume, historical CTR, trigger rate, CTR drop factor) works for any answer surface, including ChatGPT, Perplexity, Gemini, and Microsoft Copilot, but you need a CTR drop factor sourced from that specific engine. Do not reuse the Google constants for a different engine's click behavior.

What do I use for historical CTR if I do not have Search Console data for a keyword?

Use a position-based CTR benchmark as a stand-in, not a guess. Most rank trackers, including SE Ranking / SE Visible and Semrush, publish an organic CTR-by-position curve pulled from aggregate search data; plug in the position that keyword currently holds. Switch to your real Google Search Console number the moment that keyword earns enough impressions to be statistically meaningful, usually a few hundred impressions or more over the reporting window.

How many keywords should I run through this formula before I trust the total?

Start with your top 20 to 50 keywords by search volume, sorted by how often each one triggers an AI Overview. That set usually accounts for most of the total traffic at risk, since AI Overview trigger rates concentrate on head and mid-tail informational and commercial queries. Running the formula across a full keyword list of thousands adds precision but rarely changes the strategic picture your top 50 already show you.