We can measure Pogo Sticking with Google Tag Manager . We can create an event with HTML5 called Story.pushState() that allows us to put our URL in the user history with the variables we want.
In this way, when the user clicks on the back button, they are redirected to a page on our site in milliseconds , which allows us to know if the user clicked on the browser's back button and thus collect relevant information for later analysis.
Using this strategy does not affect the user, since it is imperceptible to him.
For Arturo, Google Analytics is a very useful tool as a database, but it is not a single analysis tool. This is because it only offers 17% of the total data and must be complemented with other tools.
Other metrics that complement Analytics data, in addition to Search Console, are:
Number of Queries vs Pogo Sticking
X axis : Average position
Y axis : Pogo sticking percentage
Color of the circle : Cluster to which it belongs
Circle size : Number of queries/searches
User Experience (UX) Analysis - Queries vs Pogo Sticking
There is a pattern in this graph: when pogo sticking is greater than 20%, the number of circles is fewer and smaller, meaning that Google thinks that this user behavior is bad and reduces the number of keywords for which it ranks that content.
However, below 20% of Pogo Sticking, there are a lot of circles and the size is larger. This means that for Google there is a positive behavior , that is, the user finds what he was looking for and, in addition, future doubts.
Prints vs Pogo Sticking
X axis : Average position
Y axis : Pogo sticking percentage
Color of the circle : Cluster to which it belongs
Circle size : No. of prints
User Experience (UX) Analysis - Impressions vs Pogo Sticking
The effect is the same as in the previous case, except for the behavior of a loadrunner protocol email address cluster. This means that there is a cluster where user behavior is different from that of the rest of the web.
Does this mean that it is wrong? No. User behavior can be different for each website, and even different for each cluster of the same website.
Each section of a website may have different behavior thresholds.
“Whisker Box” Diagram
To know the point/threshold from which the results are good or bad, we need to make a "Box Whiskers" diagram.
We are not only interested in optimizing pages, we are interested in having a KPI that tells us from what result something is good or bad.
The Box-Whisker plot is used to visualize data with asymmetric values , since, in the end, pogo sticking distribution data is asymmetric.
As Arturo shows in the example, in that case the median (not the average) of the behavior indicates that above 12% of pogo sticking the results would not be good.
User Experience (UX) Analysis - Diagram
Each cluster on our page works differently, so, as in the previous examples, there are two clusters above the median whose behavior is different.
We cannot apply a user behavior rule to our entire website.
In addition, we also see that outliers appear (those that are outside the graph) which are the first ones we must attack. To do this, we must combine these results with the number of impressions that these data have and look for patterns to improve.
Twitter Tools 3. How can we optimize our clusters?
Web Architecture
First, it is interesting to understand how the architecture of the website in question works. Generally, the architecture is usually the following:
User Experience (UX) Analysis - Web Architecture
This architecture is fine, but is it real? Does Google send users to the home page or to internal pages? How do users behave? This architecture does not reflect the real behavior of users on a website.
For Arturo, the relationship between clusters is more important than the architecture of the website, since clusters serve Google to measure authority.
Furthermore, Arturo points out that:
Links outside the cluster hurt us.
If we link everything to everything on a website, it is a problem. Everything within the same cluster is well linked, but the rest of the links are not positive.
How does user experience affect SEO?
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