Post by account_disabled on Feb 24, 2024 9:24:48 GMT
Product dimension data-The main flow distribution is based on the distribution diagram of the main flow page, and the functional modules that can be focused on. EX: The figure below shows the distribution of traffic in the monthly mini -program homepage. Daily recommendations, content selection and other modules are the main traffic distribution points. In addition, the homepage flow distribution is reflected according to the heat map, and the adjustment action is made according to the visual habits. EX: The daily recommended traffic is the largest.
The click -through rate of the homepage resource level can fully reflect the user's interest.keyword high -frequency word on the search page can also reflect the interest in active search related content, especially the user's custom keyword search, high frequency high -frequency search, high -frequency frequency The analysis anand layout of words can further improve the quality of user operation. 4. Product dimension-Page traffic breakpoints In general, the exit rate and the number of visitors of the page access can reflect the attractiveness of different second-level pages to users. To this end, we can see the mini program through these two data indicators. Follow the page node. As shown in the figure below, there Jiangsu Mobile Number List is a large breakpoint between the traffic between the page B and the C. The user's loss is more and can focus on it. It can be dug down from this, and detailed disassembling different pages, especially the interview pages of content -type applets,
the number of people/staying time for sharing pages. 5. Time dimension-Main data comparison In addition to the analysis of traffic pages and secondary pages, in order to better understand user habits, you need to compare the data indicators of users in different time periods. Conversion applets pay more attention to GMV and conversion rates. Content -type applets mainly pay attention to the following indicators: the main data index comparison of the product: activeness = active number/total number of visits, the average residence time, the interview page jump rate; Page exit rate, combined with the operation adjustment strategy, analyze the reasons for growth/decline. Of course, according to the flow trend, it can judge the peak period of traffic at the peak period of time granularity, combined with the traffic data of the interviewed page, and judge the efforts of operation。
The click -through rate of the homepage resource level can fully reflect the user's interest.keyword high -frequency word on the search page can also reflect the interest in active search related content, especially the user's custom keyword search, high frequency high -frequency search, high -frequency frequency The analysis anand layout of words can further improve the quality of user operation. 4. Product dimension-Page traffic breakpoints In general, the exit rate and the number of visitors of the page access can reflect the attractiveness of different second-level pages to users. To this end, we can see the mini program through these two data indicators. Follow the page node. As shown in the figure below, there Jiangsu Mobile Number List is a large breakpoint between the traffic between the page B and the C. The user's loss is more and can focus on it. It can be dug down from this, and detailed disassembling different pages, especially the interview pages of content -type applets,
the number of people/staying time for sharing pages. 5. Time dimension-Main data comparison In addition to the analysis of traffic pages and secondary pages, in order to better understand user habits, you need to compare the data indicators of users in different time periods. Conversion applets pay more attention to GMV and conversion rates. Content -type applets mainly pay attention to the following indicators: the main data index comparison of the product: activeness = active number/total number of visits, the average residence time, the interview page jump rate; Page exit rate, combined with the operation adjustment strategy, analyze the reasons for growth/decline. Of course, according to the flow trend, it can judge the peak period of traffic at the peak period of time granularity, combined with the traffic data of the interviewed page, and judge the efforts of operation。