GA Bounce Rate vs Time on Page
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I have a niche site that attracts between 50 to 100 visitors a day. For the past several weeks we've been working on a new article and the with aid of social media have attracted 2,000 visitors in the first 24 hours of posting, a dramatic spike in daily visits. Visitors are spending about 10 to 12 minutes reading the article and then leave our site. So, the GA bounce rate is quite high at about 95%. Does Google know this is a compelling article for our niche based on the number of visits and time spent reading the page? Will the high bounce rate affect the article's PR, or do they also consider the time on the page?
Best,
Christopher -
Hi Christopher
Don't worry about the high bounce rate, most single page blogs face the same problem and it won't affect PR...
I would however suggest that somewhere on the page you link off to other relevant content. This will encourage users to browse your website giving you more engagement and reducing your bounce rate at the same time!
Steve
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Just some background on GA and bounce rate and time on page. GA calculates time on page (using a default setup) by looking at the time between page loads.
If someone lands on your page (1 pageload) spends 20 min reading and then closes the browser you would have a visit with a single pageview but 0 time on page. This is because there was not a second page load (say clicking to another page on your site) to calculate the difference.
There are a couple of issues here if you just consider time on page and time on site. On a single page view visit, your time on site and time on page will be 0. If someone visits 4 pages and spends 2 minutes on pages 1-3 but then finds the article they want on the 4th page and spends 20 min there. Guess what? You dont get any credit for the time spent on the most important and longest visited page - the 4th one.
Similarly, GA looks at bounces as single page view visits with 0 time. Your bounce rate will be really high if you have a bunch of single page view visits, even if the visitor spends 20 min average on that page.
We had an issue like this and there is a way to look at this differently.
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You can setup events on the page (scrolling down the page, hovering over a menu etc) and when those events are logged in GA, it signals the time difference and you get credit for time from the page load to the logged event.
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You can setup an event "ping" that runs in the background. As long as the window is open, the ping can be sent at various intervals so that GA has a time difference between that event and the initial page load. Obviously, if someone leaves a window open, you are logging time for someone on the page who is not engaged, but you may feel that this is better than getting no credit. You can also limit when the ping is sent as well.
Another variant (when focusing more on Bounce rate vs time on page) is to have the ping run once at 30 seconds after page load. You can then have all the other visits who do not reach the 30 second mark then effectively be counted as a bounce in GA. This would not give you as much accuracy as total time on the page, but you would get a better snapshot of interactivity from that bounce threshold. That threshold could be 5 sec, 10 sec or 120 sec - just depends on the goal of your site.
If you take a little time to work with you config on GA, it can give you the information that is a little more actionable etc. and find a happy medium on Bounce and Time on page. It is all about 1) when the first ping should fire, 2) how often you should send additional pings or events and 3) when the last ping is sent. If you look at the Google reports, I would suggest putting a ping in the middle of the default time slots for how they group user time on page (as an example).
As far as how Google uses bounce rate, there are some conspiracy theorists that say that Google looks at your GA data for ranking. I am not of that group. Your concern about Bounce rate and ranking is more related to what Rand mentioned in a recent WBF on the "Pogo stick" problem.
http://moz.com/blog/solving-the-pogo-stick-problem-whiteboard-friday
This has nothing to do with your GA data and everything I mentioned above. Google tracks for itself clicks out of SERPs on links and then sees how long you spend on a site before you come back to the Google SERP. This is Google's own tracking and nothing to do with GA as Google does not need GA to calculate this. They look at how you move in and out of a Google page back and forth. A search result may have a high click through, but if Google sees people coming back to the search result time and time again, they may question the quality of that site. What is the threshold for this etc? Hard to tell. Your bounce rate will give you an insight to what Google is measuring, but again, users may not be going back to Google, but just closing the browser. The two are closely related, but are separate measures.
Regardless, I would suggest you do some custom configs of GA on your site to give you more information about user behavior of time on those pages. Use that information to find your "problem pages" and then get them fixed. This should also improve any Pogo Stick metrics that Google is measuring, plus you are probably going to make your users happier and that is really what this is all about.
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Hi Christopher,
You shouldn't need to worry about your high bounce rate in this case. There are many websites that have high bounce rates that are extremely relevant and useful to visitors.
For instance if, if I Google, "pollen forecast minneapolis mn" and click on a link from Weather.com, see the forecast for the day and bounce within 3 seconds... that is actually good. The page is serving its purpose and giving the user reliable information quickly.
Now in your case, with the high bounce rate and the long time on the page, I would assume Google would be able to figure out that you have some great piece of content, like a story, or a video that is truly captivating an audience.
I would not worry about this in the least.
Thumbs up on driving visitors to your site. Keep up the good work!
Mike
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