So let’s look at how both exit rate and dwell time

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Compare with bounce rate. Exit rate Exit rate shows the percentage of sessions that ended on a particular page. For example, imagine that three people visit your website, and their sessions look like this: 02 bounce rate All of the sessions started on page A, which has a bounce rate of 33%. Both B and C have bounce rates of 0% because no session started on those pages. The exit rate looks different, though: The exit rate for page A = 33% The exit rate for page B = 100% The exit rate for page C = 0% None of the three visitors exited the site from page C, one exited on page A (from three sessions with A in them), and two exited on page B (from two sessions with B in them). Dwell time Dwell time is the amount of time between a user clicking on a search result and returning to the SERP.


Unlike bounce rate, it’s not a metric you’ll find in Google Analytics. The SEO community created indian phone number it because it’s thought to be a possible ranking factor. You can technically set up custom dwell time tracking in GA, but that’s way out of the scope of this article. How to interpret and use bounce rate the right way The rule of thumb with analytics is to know what you’re looking for and then use filters and segments to isolate and investigate that data. And that means looking at data with common traits. For example, looking at bounce rates for different channels doesn’t make sense because it’s aggregated across all campaigns and landing pages. 2 source medium report Our advice is never to look at bounce rates on aggregated reports like this. Bounce rates differ from page to page, so you’ll always want to include the landing page dimension into your reports, then choose a channel you want to analyze.



In my case, I went to the Landing Pages report (Behaviour > Site Content > Landing Pages), then removed the default “All Users” segment and applied an “Organic Traffic” segment instead: 3 landing pages report To narrow things down further, we’ll look for a common trait in the “Landing Page” dimension and exclude statistically insignificant pages. We can do this by filtering for product pages with the word “apparel” in the URL (common trait), and excluding pages with one hundred sessions or fewer (statistically insignificant): 4 filters ga SIDENOTE. You can use Weighted Sort instead of excluding low traffic pages when possible. It just doesn’t work for segmented reports like this one. The result is a report where bounce rate analysis makes sense. 5 filtered report Still, it’s important not to get too carried away by your average bounce rate because popular pages skew that number.