Analysis on five important data of site backstage

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Background data analysis I think for most of the webmaster is more dislike, because the face of a bunch of cold data, I think a lot of people will feel boring. However, the optimization can not be separated from the data analysis, only the ability to master the data analysis to understand the problems of our site. So, even if the data is not so cold, now that you have set the optimization of this bowl of rice, you are doomed to learn the data analysis. So what do we need to focus on the data analysis? Today, I will share some of the data of my daily major analysis with CNZZ data statistics.

Analysis of one: site traffic source analysis

Traffic is the pursuit of every site, many webmaster daily data will first look at the background flow and PV data, and then directly through the high and low flow data evaluation of the progress of the work. In fact, this view is not entirely right. We should also focus on analyzing the other data of the site, especially the traffic source of the site. We can analyze from which entrance the nearest traffic flows through the flow source, and then develop a better strategy for the outside chain construction according to this trend.

For example, the author previously found that the source of the background traffic from the search questions and answers in the flow, the reason is because earlier in search to ask you to leave a link, the first, the author found that the author of the site if the form of a question and answer platform to do the chain will get good results, so began to search and answer, Baidu know to do the chain, Sure enough, in these several channels in the flow has been rising trend, so I think the source of the analysis flow is also the site outside the chain construction of an important link.

Analysis Two: Site of the visited page data

What visitors like, this is the question that every optimizer asks the most when building content. It's true that when we build content we have to stand on the user's side and analyze it. So how do we know what visitors like? We can analyze the data of the pages that are being interviewed. Through the data analysis of the visited pages, we can visually see the number of visitors to the page, stay time, bounce rate and so on. These are helpful for building content that users like.

Analysis Three: PV data analysis of the site

PV data can be very good from the side of the site to show the user experience is friendly. We can not be blunt, if the higher the PV value, then your site's user-friendly experience of the better. Of course, this is only one of the factors. Of course, the search engine is not the PV value to the constant user friendly experience, because the well-known PV data can be done through irregular means brush.

Analysis of four: visitor data

The visitor's returning to the guest can well reflect the site's user viscosity is enough "sticky". A successful site can not only rely on a high ranking, more importantly, to develop a group of loyal visitors. For this we can analyze the viscosity of the site from the user in the background data. A high rate can reflect the site has a good viscosity can continue to attract visitors, so as to have a stable flow.

Analysis of the regional analysis of visitors

Each site in the visitor area distribution will be different, special search engine more and more localized, in different regions search for the same keyword, search results may be different. Then we need to analyze the visitor's main routing area through the visitor area distribution data in the backstage data. Then you can according to specific regions in a number of regional strong blog forum to promote, such as from the image above the data we can find that the author's site in the user has 90% of Fujian province, while in Guangdong, Beijing and Jiangsu have a certain user base, the author can be aimed at this point, in some regional interest blog, forum, etc. to promote.

Data analysis work may be a more boring work, but I think we optimize the staff if we can through reasonable data analysis, and then work out to meet their own site optimization strategy, I think all the optimization work will be twice the effort. This article by the British trousers http://www.wydsb.com finishing edit, reprint please keep the source.