How To Interpret Your Bounce Rate In Google Analytics And How To Improve This Information.
What is a “Bounce rate” in Google analytics? To many people who use Google analytics, the “Bounce rate” numbers are a bit of a mystery. What exactly is “Bounce rate” and what information do these numbers provide us?
There are two ways you can look at what a bounce rate tells you.
It is the number, expressed in a percentage of traffic to your website, that either is:
1) a visit to any of your web pages by a person who does not visit any other page.
or
2) a visit to any of your web pages by a person who does not stay longer than 10 seconds.
The trouble with both these definitions is that they are not clear enough. In both cases the information they provide is spectacular but the depth needed to interpret this is sorely lacking.
Indeed both definitions leave us wondering what the visitor to a webpage actually did.
On top of that, we are left to wonder if the visitor to our webpage might have lingered for a longer period than 10 seconds. There are many instances in which this could be the case.
The only certainty we really have is knowing that the surfer has seen only one page and no other.
There is a hack around this and it has the added advantage that you will get better information from Google analytics.
Under this line in your urchin code:
pageTracker._trackPageview();
you add:
setTimeout(‘pageTracker._trackEvent(\’NoBounce\’, \’NoBounce\’, \’Over 10 seconds\’)',10000);
The “10000″ number refers to the number of milliseconds you want to wait before triggering the above code, so if you want it to trigger after 12 seconds, you need to set this number to “12000″.
Now you have set your tracking code to record all visits that last longer than 10 seconds.
This allows you to get the precise number of visits that do not need to be considered as a “bounce” according to definition number two by providing the precise number of visits that really stay less than 10 seconds. It will give you a better insight into visitor engagement.
Google Real Time Keyword Data
Keyword catcher is about real-time results, so by now you can deduce from this fact that we are real-time keyword data aficionados.
The power of real-time data is that it brings you much closer to what is happening out there right now. This allows your intuition to follow through on small leads that might lead to big results.
It’s also very stimulating to look at real-time data streams, which is why the latest real-time keyword content finding source from Google is a real gem to add to the keywords tools you might want to consider when you are short of inspiration.
When you use the following search query string in your browser, Google will open up a web page in your browser that will present you with a real-time published data stream related to the keyword you type into the search box.
Google’s Real Time Data Stream for the word “Apple”
http://www.google.com/search?esrch=RTSearch&tbs=rltm%3A1&tbo=u&hl=en&q=apple
So now, when you publish your content or article, you can keep an eye on this page to see when Google’s spiders will have crawled your server and picked it up. personally, I wouldn’t waste too much time staring at the page for it might be a while before your title appears.
I tested it with this page. Just before publishing it, I typed in the main keyword I targeted and I kept my beady eye on the data stream for a couple of minutes. At first I thought that I had not used the correct keyword. So I opened a new page with another term: “Google”. (It is in the title!)…
Then I thought: “Maybe the spiders only will come once a week because I set the “All in one SEO plugin in Wordpress to “weekly” for blog posts. ” I also noticed that the real time data included tweets, so I tweeted this post. I did not see the post appear, so I guess that a limited amount of servers are being tracked for this and I was not about to waste any more time to find out.
On the other hand, if you want to check whether a certain keyword really has tough competition, it is safe to say there will be many publications related to this keyword. As an example, you could try to type in “Apple” and “diet” and compare the number of publications that appear, for example, in a time span of one hour.
Last I looked, “diet” had about a rate of 14 to 15 content items per hour while “Apple” had a rate of about 600 published items per hour! Mind you, my point of view is European, which means this publishing rate is due in late evening to early night. It stands to reason that the frequency of published items will vary according to location and time of day.
You will probably notice that a rate of 14 publications per hour provides for a rather static data stream while a rate of 600 publications per hour provide for a very lively and and quickly paced update rate.
Also please remember that this query string relates to a page that is currently in beta phase of testing and that Google is still tweaking it, so that by the time you read this, it is quite possible that the page will behave differently than the way I described it.
In any case, this is yet another very interesting and powerful research tool that will provide you with an important indication as to the intensity of publications for certain keywords.
