Marketing Suite

CTR Calculator

Work out the click through rate of your ads from clicks and impressions — and see where it sits against Google Search, Display and Shopping benchmarks.

CTR

Clicks ÷ impressions × 100

Clicks per 1,000 impressions

CTR × 10 (= CTR in ‰)

Channel benchmark

Display Shopping Search Top

Clicks by CTR

What is CTR? Click through rate as a measure of relevance

Your click through rate (CTR) measures what share of the people who saw an ad or a search result actually clicked it. It is the first honest signal you get about whether a creative or a headline is relevant — long before conversion rate and cost per acquisition have anything to say. A high CTR means the ad copy and the targeting match what the audience was looking for.

Click through rate formula: clicks over impressions, times 100

CTR (%) = clicks ÷ impressions × 100

How to calculate CTR, and what 2 % actually looks like

A Google Search campaign returns 1,200 clicks on 60,000 impressions:

Clicks 1,200
Impressions 60,000
1,200 ÷ 60,000 × 100 = 2.0 %

CTR benchmarks by channel — and what counts as a good click through rate

Orientation by channel and network:

Google Search 3–5 %
Google Shopping 1–2 %
Display network < 0.5 %
Top performers, Search 8–12 %
YouTube TrueView 0.5–1.5 %
LinkedIn Ads 0.3–0.8 %

A channel comparison only takes you so far. CTR on its own says nothing about profitability — it has to be read alongside conversion rate and cost per click, because a rate that beats the benchmark while the traffic never converts is an expensive kind of success.

What a higher click through rate is actually worth

Clicks rise linearly with CTR: at the same reach, every additional percentage point buys you impressions ÷ 100 extra clicks. The chart above is that straight line; enter a target CTR and the calculator works out the gain at an unchanged budget. With large impression counts the leverage is considerable — moving from 2 % to 3 % on 60,000 impressions is 600 more clicks without spending another cent.

How to improve CTR: ad copy, extensions and targeting

  • Put the keyword in the headline: when the searched term appears in bold in your title, CTR rises noticeably — relevance is recognised in a fraction of a second.
  • Use strong calls to action: «Buy now», «Start a free trial» or «Order today» create urgency and raise the probability of a click.
  • Add ad extensions: sitelinks, callouts and structured snippets visibly enlarge the ad and give it more clickable surface.
  • Test systematically: run headlines and descriptions against each other. Small differences in wording can double CTR — always measure within the same auction.

Background & sources

CTR varies widely by channel (search versus shopping versus display) and by industry — the figures above are orientation, not targets.

Frequently asked questions

CTR meaning — and why a high rate is not automatically good
Click through rate is the share of people who saw an ad or a search result and clicked it. Formula: CTR (%) = clicks ÷ impressions × 100. A CTR of 2 % means 2 of every 100 people who saw the ad clicked. A very high CTR alongside a weak conversion rate usually points at poor targeting: plenty of people click, none of them buy.
How is CTR calculated?
Divide clicks by impressions and multiply by 100: CTR (%) = clicks ÷ impressions × 100. With 1,200 clicks on 60,000 impressions the CTR is 2.0 %. The same figure expressed per thousand impressions is simply CTR × 10.
What is a good CTR?
On the Google Search network 3–5 % is a solid benchmark; top performers reach 8–12 % or more. On the Display network CTR is typically below 0.5 %, and for Google Shopping good values sit at 1–2 %. CTR alone is not a mark of quality — it always has to be judged together with conversion rate and cost per acquisition.
What influences CTR most?
The relevance and design of the ad itself: keywords from the search query in the ad text, a clear call to action, and extensions such as sitelinks that enlarge the visible surface. Even small changes to headlines and descriptions can shift CTR noticeably in an A/B test.