Phishing Simulation Rate Calculator

Every rate here uses delivered emails (sent minus bounced) as the denominator, so campaigns of different sizes can be compared. A falling click rate and a rising report rate are both signs of progress.

Also called: Phishing click rate calculator

  • Last updated
  • Formula tested against reference values

Your numbers

Count each person once, however many times they clicked.

Result

Click rate
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Calculating…

Data submission rate
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Report rate
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Clickers who submitted data
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Reports per click
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Delivered emails
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How to use this calculator

  1. Enter or choose emails sent.
  2. Enter or choose bounced or not delivered.
  3. Enter or choose recipients who clicked.
  4. Enter or choose recipients who submitted data.
  5. Enter or choose recipients who reported it.
  6. The click rate updates as you type. Use Copy result or Share to keep it.

Method

Delivered = Sent − Bounced; Click rate = Clicked ÷ Delivered × 100; Submission rate = Submitted ÷ Delivered × 100; Report rate = Reported ÷ Delivered × 100

Clicked, Submitted, Reported
unique recipients who did each action

Worked example

  1. Delivered = 1,000 − 20 = 980.
  2. Click rate = 98 ÷ 980 = 10%; report rate = 147 ÷ 980 = 15%.
  3. Submission rate = 29 ÷ 980 = 2.96%; reports per click = 147 ÷ 98 = 1.5.

Of 980 delivered emails, 10% were clicked, 2.96% led to submitted data and 15% were reported.

What the result means

Compare campaigns of similar difficulty only; a harder lure will raise the click rate without anyone getting worse. More reports than clicks (a ratio above 1) suggests people recognise and escalate phishing.

Assumptions and limits

  • Counts are unique recipients, not total clicks.
  • Anyone who submitted data also clicked.
  • Email security tools that pre-open links can register false clicks; remove them before calculating.

Questions

Why use delivered rather than sent emails?

Bounced emails never reached anyone, so counting them would make every rate look lower than it is.

What is a good click rate?

There is no universal benchmark because lure difficulty varies so much. Track your own trend with comparable templates.