This article mainly introduces some commonly used models for data analysis: event analysis, funnel analysis, heat map analysis, retention analysis, event flow analysis, user group analysis, user scrutiny, distribution analysis, and attribution analysis. 1. Event Analysis In the analysis of user behavior data, an event refers to a certain behavior of the user operating the product, that is, what the user does in the product, which is translated into descriptive language as "operation + object". Event types include: browse pages, click on elements, browse elements, modify text boxes, etc. A consumer email list complete event should contain the following aspects: User Information: Information describing the user.
For example, user access or login ID Time information: the time the event occurred Behavioral information: what behavior the user did Behavior object information: on which objects the user's behavior acts. For example, if button A is clicked, page consumer email list B is browsed, and text box C is modified, then the distribution of A, B, and C is the object of user behavior. Event analysis is the most basic of all data analysis models, which refers to analysis operations such as statistics, latitude subdivision, and screening of indicators of user behavior events.
For example, for the event "click to add to cart button", we can use "clicks" or "number of clicks" to measure, the corresponding indicators are "click to add to cart button" and "click to add to cart button" respectively number of people”. Measurement results can be presented in line charts, vertical bar charts, horizontal column charts (bar charts), cousins, numerical values, bubble charts, etc. The line graph of event analysis can be used to observe the trend of continuous change of one or more data indicators, and can also perform year-on-year data analysis with the previous period as needed.