Website Data analysis: Understand the site page click

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Sometimes we need to understand the site page of each link click, especially the homepage and some of the middle page, this site content layout, user experience optimization can play a very good guiding role. The old version of Google Analytics has site Overlay (site overlay map) function, you can view the site home page Click Distribution, the new version of the feature renamed to In-page Analytics, you can view in the content module, Here is a screenshot of my blog:

As shown in the picture, GA's in-page analytics displays the click Conversion rate of each clickable link in the page in the form of bubbles (CTR, click Through Rate), where the click conversion rate of each link in the page is calculated by the number of clicks of the page link divided by the number of page views. , which is used to show that the user is more inclined to go to the next page when browsing the current page, and the specific clicks will be displayed after the mouse moves to the corresponding link.

In fact, the use of GA in-page analytics not only can observe the click of each link in the page, you can also observe the page current display part of the click on the ratio, such as the previous image of the page display part of the Click for the 1-41%=59%, the bottom of the picture shows there are 41% The clicks are below the current display section. This feature can actually tell us some very useful information, users are more inclined to browse the page in which screen to click? Because most of the site's pages are not at the end of a screen, users browse the complete content often need to use the mouse wheel or to pull down, Then most users will be concerned about the page in the first few screen content, the function of each screen of the click ratio distribution can tell us some clues.

Let's explain the concept of what a screen is. Here a screen mainly refers to the user in the open page does not pull down when the length of the page can be displayed, which is related to the computer's monitor and screen resolution, such as my blog home page in my notebook open about 4 screen more than a little, The number of screens that may need to be displayed under a lower-resolution monitor will increase, requiring more drop-down, and a high-resolution display with a screen that can be displayed longer and may no longer require 4 screens.

The content of the user browsing the page is limited, and users of the content of interest and patience is also limited, users tend to focus attention to the content of a sudden, so the front part of the page will certainly have more users attention, and with the continuous drop, the latter part of the content of the focus gradually reduced, We can look at this partial reduction process based on the data provided by In-page Analytics:

According to the click distribution of my blog's homepage, more than 60% of the clicks occurred in the first screen, the second screen basically occupies about 30% of the clicks, the third screen in 6%-7%, the following all left a few screens only 2%-3% of the page click accounted for, we can use the click of the thermal graph analysis to get similar page click Distribution. Someone might say that most of your blogs are centered on the first and second screens, after a few screens of the number of links are relatively small, so the click of the two screen is very high is also reasonable, there is some truth, but even if the first screen and the second screen has an approximate density of clickable links, Can see the second screen compared to the first screen or a large number of attenuation, you can click Getoux and other tools to see the page each screen invalid clicks, the basic can see the distribution of the situation is probably in line with the above law, a large drop in the screen, after a few 3 screen.

If you pay close attention to the various portals at home and abroad, you can see the design of the page length of the portal site at home and abroad there are obvious differences. Can try to go up and down Yahoo! Main Station, BBC, CNN and other foreign mainstream portals, basically the length of the homepage of these sites designed in 3-4 screen, and then look at several domestic portals, NetEase 5 screen, Tencent close to 6 screen, Sina is the horror of 8 screens (are based on my own notebook on display). So if most of the users browsing the site's habits and my blog using Google in-page Analytics analysis of the results of the above, then the domestic portal after the first few screens of content has become a basic device, because 100 people inside only 2-3 individuals will be concerned about these content.

In the previous work to share "how to effectively enhance the content exposure Click rate" also mentioned similar problems, we must pay special attention to the first page of the content quality and presentation, because this part of the content will dominate the site content exposure click. It is obvious that a website's homepage browsing volume probably occupies the whole station 20% to 30% (because the website design is different), and the first screen of the home page occupies more than 60% of the concern, so you can see the first screen on the entire site is how important.

Of course, another important user of the In-page analytics function is to analyze the clicks of each content list or module, and click on the blog sidebar "category catalog" and "tag" two modules below:

As shown on the left, it is obvious that users prefer to view the content of the blog through the "category catalog," What categories do users like to click? A little out of my expectation, "data analysis methods" and "Web analytics tools" Two directories are more popular, presumably everyone likes reading and learning the contents of tools and methods, In the future, as much as possible to collate some of this content.

New V5 version of the Google Analytics In-page Analytics not only support the homepage of the click Statistics, in the Content module site content pages We can see the top of the "Navigation Summary" The label is next to the "In-page" label, GA has supported all the pages of the click Map, and are free, you simply select the appropriate page after clicking on the "In-page" tab can be viewed.

Each page has a click distribution statistics, so for the page each module or list of effect evaluation becomes much simpler, as my previous article--Optimization related content recommendation is to use "navigation Summary" to evaluate the relevant content recommendation module of the Click Effect, Here you can try to use In-page analytics to analyze data performance:

The right picture is the "related article" recommendation module, below the "T test and Card test" article, you can see that the recommended 5 articles have a good click conversion rate, but it is clear that the number 2nd in the "Improve user satisfaction" This article is not enough data to force, Perhaps the user does not like to click on this kind of content to look more empty title.

There's a detail in the picture. Do you notice that the recommendation module of "related articles" is just the upper part, below there are two links to the previous and next published articles, and just "Next: Comparison test settings and analysis" is related to the article recommended modules have duplicates, and the click conversion rate shown here is 5.7 %, in fact in the In-page analytics this function inside the page of the same link GA is not to distinguish, that is, GA only identify URL as the identity, do not distinguish this URL link in the page location, The approximate statistic logic should be the number of clicks of a link in a page for referral is the link URL of the page to browse the number of pageviews, so a page of repeated links in the output of clicks should be based on all the same number of links Click Total calculated, the value is exactly the same. For example, "Comparison test settings and analysis," the link in the "T test and Card side Inspection" Article page will appear in 3 places, including the two in the picture and the right sidebar guide to the next link, the 3 places shown in the Click Conversion rate is the total of the 3 click of the sum calculated, the value is exactly the same.

This process of GA makes it difficult to evaluate the click Effect of a module, because the number of clicks cannot be distinguished from that module, or because of other clicks of the same link. Of course, there are still a lot of solutions, you can add parameters to the module's links, such as the "related article" module, the link is brought to the from=related-content, you can also use the GA event tracking (events Track) and the virtual page of the two ways , specific reference to the user clicks on the site and the objectives of the introduction.

Although the content of the article is usually edited in the weekend, but because Monday everyone is busy, so choose to release in Tuesday or Wednesday, I hope you have time to look carefully.

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