The original intention of the development of an APP is to obtain revenue. When an APP is developed, it needs scientific statistics of APP data and precise positioning and operation to obtain the maximum revenue.
1. Why does the APP want to do data analysis?
Simply put, it is to maximize revenue, achieve high APP conversion rate, and bring traffic to the enterprise or individual.
1. Make corresponding adjustments through data analysis, reduce investment for modules with small usage or no clicks, or make adjustments 2. 3. Through the data analysis, to open the market, better iterative products, more users
Now, APP products are not only focusing on the number of new users, focusing on user activity and product conversion, product development prospects, how much revenue the product brings, and so on.
2. What are the key indicators that apps should pay attention to?
The key indicators of APP data analysis are analyzed from users, terminals, versions, logs, and regions.
1. The user
The scale and quality of users are the most intuitive data, and APP operators need to focus on them.
(1) Add a user
New users New users who register or download the APP at different time ends.
The number of new users is the basic index to measure the promotion of APP. The number of new users can distinguish whether the promotion is trial or not, whether the promotion plan needs to be adjusted, and so on.
(2) Active users
Active users are counted in different dimensions by year, month and day. By viewing the active users, the usage and survival of the APP can be analyzed.
Detailed data can also be queried according to the region, phone model, APP version and other auxiliary data.
(3) Cumulative users
Cumulative users are all registered users. You can view the total number of users in a certain period of time. Detailed data can also be queried according to the region, phone model, APP version and other auxiliary data.
(4) Startup times
Startup times are the statistics of APP opening times. You can select time, region, APP version, mobile phone brand, etc., to filter the data, which can be used as the basic indicators of APP conditions, and the usage and survival rate of apps can be estimated.
Terminal 2.
Terminal data refers to the statistical data of mobile phone brands and models. Device models can see the number of users, distribution of mobile phones and other data.
Data such as new users, active users, accumulative users and startup times of mobile phones of different brands can be seen respectively. Data can be summarized through different time, region, version and channel dimensions to analyze market share ratio and make decisions.
Version 3.
Version statistics refer to the number of users in different APP versions as the APP version iterations, and maintenance policies are determined based on the number of different versions. According to different versions of apps, data such as specific newly added users, active users, cumulative users and startup times can be seen. At the same time, screening data from different dimensions can help decision makers find priorities.
4. Log
Log statistics are divided into two parts, event statistics and crash log statistics. APP development In order to better understand user needs, need to plan and design APP, APP demand collection, burial point is necessary.
Event statistics is to calculate the click times of user events by setting buried points in the APP, draw the scope of APP use, and determine the interest points of users.
The crash log is used to collect the crash occurrence after the launch of APP, which provides the basis for version iteration and better serves users. The crash log should contain the specific crash time, crash cause, crash version number, phone brand, and channel information, so that the fault can be quickly located and repaired.
5. The regional
Regional statistics refer to the summary statistics of data in different geographical locations. For example, 200 people were added to Hangzhou, Zhejiang Province. Accurate regional statistics will see the difference between different regions, business focus is different, regional promotion is very key.
Regional statistics should include new users, active users, cumulative users, startup times and other data display. Data should be screened in time, region and other dimensions to clearly see the regional differences and serve as the basis for promotion decisions.
Third, summary
APP operation needs various statistical data. Through data analysis, the best operation plan can be made to maximize the interests of enterprises or individuals.
Native apps require developers to set their own statistics and burial points.
Web app or hybrid app can decide whether to develop or automatically access the statistical module according to the selected framework. Data can be automatically collected to facilitate viewing and exporting.