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4) Realize
That is, to obtain income, which is mainly used to business email list measure the commercial value of the product. We can analyze it by monitoring indicators such as the transaction rate.
Key indicators: ARPU, ARPPU, payment rate (to distinguish new and old users), customer unit price, LTV, etc.
5) Self-propagation
It is mainly based on the attraction of products, marketing, celebrities and other events, so that users can spontaneously spread virally and expand user groups.
Key indicators: share button clicks, user sharing landing page visits, fission coefficient, etc.
1. Funnel analysis
The core difference between the funnel model and the pirate model is that the funnel model does not focus on the 5 indicators of orientation, but differentiates it hierarchically.
The funnel model monitors users at each conversion level according to the process, and finds the optimization points at each level; draws their conversion paths for users who do not operate according to the process, and finds space that can improve the user experience and shorten the path. We can Analyze the conversion rate of each step in the process by trending, comparing and segmenting:
Trend: Analysis from the change of the time axis, suitable for monitoring the effect of improving or optimizing a process or one of the steps;
Comparison: Identify problems with certain products or applications by comparing the conversion rates of purchase or usage processes between similar products or services;
Segmentation: Segment the performance of sources or different types of customers in terms of conversion rates, and find some high-quality sources or customers, usually used to analyze the effect and ROI of website advertising or promotion.
For example: For e-commerce products, the ultimate goal is to allow users to buy products, but the conversion rate of the entire process is determined by the conversion rate of each step. At this time, we can monitor the conversion rate of users at each level through the funnel analysis model, find weak links in the conversion path, optimize products in a targeted manner, improve user experience, and ultimately increase the overall conversion rate.
2. Retention Analysis
Retention analysis is an analysis model used to analyze user participation/activity, that is, the process of converting initial new users into active users and loyal users. With the change of statistics, relevant personnel can see the changes of users at different stages, so as to judge the stickiness of the product to users.
For example, for an e-commerce platform, the user's 7-day retention rate in the last 30 days (as shown in the figure below) shows that the user retention rate is relatively low. Next, divide users into different groups according to regions, ages, behaviors, etc., observe the differences in retention, and find product optimization points.