What Is the CTR Calculator?
Click-through rate (CTR) is one of the clearest signals of how compelling your ad, email, or search listing really is. This calculator turns two raw numbers — your clicks and your impressions — into a single percentage that tells you how often people who saw something actually clicked it. It works the same way worldwide and applies to Google Ads, Meta ads, email campaigns, organic search results in Google Search Console, and more.
How to Use It
You only need two inputs:
- Number of Clicks — how many times users clicked your link, ad, or button.
- Number of Impressions — how many times the item was shown (loaded or displayed).
Enter both whole numbers and the tool instantly returns your CTR as a percentage. If impressions are left at zero, the calculator safely returns 0% instead of dividing by zero, so you never get an error.
The Formula Explained
The calculation behind the tool is straightforward:
$$\text{CTR} = \frac{\text{Clicks}}{\text{Impressions}} \times 100\%$$Clicks are divided by impressions to get the proportion of viewers who clicked, then multiplied by 100 to express it as a percentage. A higher CTR means your message resonates with the people seeing it.
Worked Example
Suppose your search ad earned 250 clicks from 10,000 impressions. Plug those into the calculator:
- \(250 \div 10{,}000 = 0.025\)
- \(0.025 \times 100 = \textbf{2.5\% CTR}\)
So 2.5% of everyone who saw your ad clicked through. If you doubled clicks to 500 with the same impressions, your CTR would rise to 5%.
Frequently Asked Questions
What is a good CTR? It depends on the channel. Google Search ads often average around 2–5%, display ads under 1%, and email marketing roughly 2–5%. Compare against your own past performance rather than chasing a universal number.
Why is my CTR 0%? Either you recorded no clicks, or your impressions were zero. The calculator returns 0% whenever impressions are zero to avoid an undefined result.
Can CTR be over 100%? Not in normal use — that would mean more clicks than impressions, which usually points to tracking errors, bot traffic, or double-counted clicks. Double-check your data source if you see this.
