CTR Calculator

Find your click-through rate in seconds. Enter your ad impressions and number of clicks to see your CTR, plus the average number of impressions per click.

Results
Click-Through Rate
The percentage of impressions that result in a click.
Impressions per click1 click for every N impressions

CTR formula

Click-Through Rate
CTR = Number of Clicks ÷ Ad Impressions × 100

Divide the number of clicks an ad received by how many times it was shown, then multiply by 100 to get a percentage. If an ad gets 500 clicks from 5,500 impressions, CTR = (500 ÷ 5,500) × 100 = 9.091%. CTRs can be relatively small, so retaining a few decimal places can make comparisons more useful.

What counts as an impression vs. a click

An impression is counted each time an ad is shown to someone, whether or not they interact with it. A click is counted when someone actually clicks the ad. For this calculator, the number of clicks must not exceed the number of impressions. The calculation assumes each impression represents one opportunity for a click.

Frequently asked questions

How do you calculate CTR?

Divide the number of clicks by the number of impressions and multiply by 100. For example, 500 clicks from 5,500 impressions gives (500 ÷ 5,500) × 100 = 9.091% CTR.

What's a good CTR?

It varies enormously by platform, ad format, audience, and industry. CTR is most useful when compared with your own past campaigns or with benchmarks for the same platform, ad type, and audience rather than against a single universal target.

Does a higher CTR always mean a better ad?

Not necessarily. CTR measures how compelling an ad is at getting a click, but says nothing about what happens after — a high-CTR ad that attracts clicks from people unlikely to convert can perform worse overall than a lower-CTR ad that reaches a more relevant audience.

Why is CTR shown with three decimal places here instead of two?

CTR can be a small percentage, so three decimal places provide more precision when comparing campaigns. For example, 0.125% and 0.135% would both lose useful detail if rounded to the nearest whole percent.