Optimize related content recommendations-make it easier for users to find the information they need

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An article before the blog--Optimizing the website navigation design, introduced how to evaluate the website navigation function and the optimization based on the analysis. But later discovered that it omitted the Google Analytics a very useful function--navigation Summary, literally translates is "the navigation summary", but appears to use "the page upstream and downstream" (Baidu statistics name, takes over to borrow first) analysis more apt. It can well analyze the implementation of the site navigation (the point is that the navigation function of the effective click or operation), the following to introduce this function.

Better measure the degree of navigation implementation

First, take a look at the Navigation Summary report in GA for the Navigation index page of my "article feature Recommendation" (This feature is under the top Content tab of the content module):

　　

From the image above you can see how many times the page has been browsed (Figure 1), how much of the proportion of the visits is from outside the station to enter this page to start to visit the site (Figure 2), how much of the proportion of visits from the site inside the page to jump to this page (Figure 3), How much of the proportion of visits left the site after browsing the page (Figure 4), the percentage of visits from the page to the other pages of the site (the 5,4 and 5 parts of the picture are now seemingly problematic), and the top 10 upstream pages of the site ( The page that the user was in before browsing the page, labeled 6, and the downstream page (the next page that was browsed immediately after the page, note 7 in the figure), and their respective percentages. Note that there are sometimes the same URI addresses on the upstream and downstream pages as the selection page, for example, you select the Home page (/) for analysis, upstream and downstream pages also appear on the home page address (/), this is mainly due to the refresh operation, GA will page refresh statistics to pageviews inside.

With this feature, we no longer need to make a rough estimate of how many visits left on the site and may have clicked on the link to the navigation page via the Navigation page's departure rate (Exit Rate). And through navigation summary we can not only see how many visits have left directly from the navigation page, but can also measure effective clicks more accurately by analyzing the downstream pages of the navigation page, excluding those that refresh, return, or tune to other non-navigable list pages. Add the link to the Navigation page (%clicks), which is the effective click conversion of the Navigation page (CTR), which is the implementation of the navigation function index. For example, the above table, excluding the return of the first page (/), page Refresh (/featured-topics/) and jump to the pages in the Non-navigation page (/about/,/site-map/, etc.) these clicks, the rest of the implementation of the navigation function of the effective Click added is the navigation function of the implementation degree, Unfortunately, the upstream and downstream pages on GA can only display the top 10.

Above is the previous article on the optimization of navigation design content supplement, in fact, the page upstream and downstream analysis is a very effective Web site analysis method, not only can be used to analyze the degree of navigation, the following introduction of its another application-related content recommended effect analysis.

Website related content recommendation

　　

Blog before an article-optimize the website information architecture introduced most of the site may be based on tree structure to build, but the original tree structure itself there is a problem is the leaf node (or the content node of the site) there is no direct link between That is, users can not jump from a lower content page directly to another layer of content page, you need to return to the home page or the middle navigation index pages to enter other content pages, from the article's tree structure diagram also embodies, the underlying page is not directly connected lines. So many sites will be at the end of the content or sidebar to provide relevant content recommendations, for example, Amazon, Taobao and other E-commerce Web site product page will have the same category, the same price of products recommended, or users in the purchase of the product at the same time also purchased the product recommended, watercress on the books, music, The movie page also provides recommendations for related content.

Many of these functions are based on the content-related algorithm to achieve, before the article-up marketing, Cross marketing and association recommendations introduced based on user behavior of the association recommendation method. In fact, many blogs have similar functions, that is, the end of each article related articles, the following image is my blog e-commerce site RFM analysis of this article List of related articles:

　　

I am using wordpress plugin--yet Another Related Posts plugin to achieve this function, according to the introduction of Plug-ins, it is through the calculation of the title of the article, Body, label and classification of the relevance of the first few show to the page. This function is very good, it has opened the passage between the article page, perhaps the user after reading an article also wants to browse the related article, then the relevant content recommendation provides a very good way, users do not need to fall back to the content of the search page, directly click on the line, to help users more convenient, fast positioning to the information to seek.

Related content recommendation effect analysis

The relevant content of the site recommended functions are many of the use of machine algorithms to automatically generate, so from a certain level, the algorithm will be good or bad, we need to evaluate the effectiveness of the function through analysis, so as to continuously optimize the algorithm. And the analysis based on user browsing behavior is the most effective way to evaluate the effect of the function, so the website analysis has its place, and the navigation summary on GA described above is very suitable for the analysis of the relevant content recommendation effect tool. Here is the E-commerce site RFM analysis of this article in the upstream and downstream page analysis for example to see the effect of the plug-in I use how it works:

　　

From the list of upstream and downstream pages, look at the percentage of content pages and other content pages. Which pages have the highest rate of inflow and outflow, and then compare it to the rankings in the recommended list of relevant content on the site, so that the relevance of the site's functionality is consistent with the relevance of the user's eyes, To verify the performance of the function.

If the algorithm is adjusted, it can also use this method to check the ratio of upstream and downstream page conversion before and after the adjustment of the algorithm, so as to measure whether the relevant content recommendation function is optimized after the adjustment of the algorithm. And we have to do is through the continuous optimization of the relevant content of the proposed algorithm to the content of the site's relevance ranking and the user's expectations of content as far as possible, so that the relevant content on the page is what users want to find content, so as to meet the needs of users.

Here are a few questions to note:

Perhaps a content page will have more than one relevant recommendation module, or there will be many links to other content pages, in the GA report is the sum of all inflow and outflow, so if only to evaluate the effect of a recommendation module, you need to distinguish the link in the module, perhaps the URL parameter will be a solution.

Notice the change in the content recommended by the time interval of the data and the change of the content of the website. The default time interval on GA is the first one months, you can select the appropriate interval for analysis and comparison, pay attention to the content of the site to update the impact of the relevant content recommendations.

Some of the relevant content of the recommendation is not two-way, such as in the purchase of MP3 page recommended earplugs, and in the purchase of earplugs may not recommend the MP3, so sometimes it is necessary to the upstream and downstream pages of the analysis, pay attention to the direction of transformation.

Above is what I think of the Google Analytics navigation summary features two examples of applications, you are not thinking more applications, welcome to share your views.

Original link: http://webdataanalysis.net/personal-view/optimize-related-content/