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Introduction: In the realm of web analytics, calculating the exit rate of a webpage is crucial for understanding user behavior. This metric allows you to gauge the appeal of your webpages and optimize them to enhance ad revenue.

Exit Rate Definition:

The exit rate is the percentage of visitors who exit your website through a specific page. This metric identifies where users are leaving, aiding in pinpointing areas for improvement. For instance, if 100 users visit Page A and 40 exit through that page, the exit rate for Page A is 40%.

Calculating Exit Rate:

Let’s break down the exit rate calculation using an example:

  • Website: Alpha.com
  • Page: Homepage
  • Pageviews: 5,000
  • Exits: 1,000


  1. Determine Pageviews: Count the number of times the page is visited (Homepage of Alpha.com has 5,000 pageviews).
  2. Determine Exits: Identify how many users leave the site from that specific page (1,000 exits from the Homepage of Alpha.com).
  3. Calculate Exit Rate: Use the formula: Exit Rate = Exits / Pageviews. For Alpha.com’s Homepage: 1,000 / 5,000 = 20%.

Exit Rate vs. Bounce Rate:

Exit rate and bounce rate are often confused, but they have subtle differences:

  • Exit Rate: Percentage of users leaving after browsing a specific page.
  • Bounce Rate: Percentage of users leaving immediately after landing on a page.

Frequently Asked Questions (FAQ):

How to Calculate Exit Rate?

  1. Determine the number of pageviews.
  2. Determine the number of exits.
  3. Apply the exit rate formula: Exit Rate = Exits / Pageviews.

Can Exit Rate Be Negative?

No, exit rate cannot be negative as both exits and pageviews are non-negative values.

What Is Bounce Rate?

Bounce rate is the percentage of users leaving the website after visiting the landing page, which is their first page on the site.

Exit Rate Example:

If 200 people visit a webpage, and 100 exit, the exit rate is calculated as exits divided by pageviews (100 / 200), resulting in a 50% exit rate.

This guide provides a comprehensive understanding of exit rate, its calculation, and differentiating it from bounce rate in the context of web analytics. Optimize your website by interpreting these metrics effectively!