User life state analysis

1. Overview

1.1 Concept

Classify and analyze the life status of existing customers. Two dimensions are used here: "Time since last login" and "Time since the first login". According to these two dimensions, customers can be simply divided into four categories.

• New users: Customers who have just logged in/purchased a product within a short period of time.

• One time users: After logging in/purchasing products within a short period of time, customers who will not continue to purchase in the near future.

• Loyal users: Customers who have been logging in/purchasing products for a long period of time and are still buying in the near future.

• Lost users: Customers who have logged in/purchased products for a long period of time, but no longer have purchased recently.

1.2 Problems solved

You can understand the current market competitiveness of the company and implement different marketing actions for different types of customers.

2. Method of operation

2.1 Prepare data

1) Create a new self-service dataset, select the FineBI embedded table "User retention data", and check a few fields, as shown in the figure below:

2) Add "Group Summary" and drag the fields into the group column and summary column respectively.

Among them, click the drop-down of the "Earliest activation time" and select the "Earliest time", and click the drop-down of the "Login time" and select the "Latest time".

In this way, the time of the last purchase and the time of activation of each user (that is, each contact number) can be calculated.

3) Since this sample table only has data before "2020-10-21", we will use "2020-10-21" as the "Today's date", as shown in the figure below:

Click "Add column" and enter the formula: TODATE("2020-10-21").

4) Add a new column to calculate "Last login since" and "Activation date since", as shown in the figure below:

5) Add a new column to classify users, as shown in the following figure:

Activation time is less than or equal to 180 days, and the last login is within 60 days: New users;

Activation time is less than or equal to 180 days, and the last login is more than 60 days: One time users;

Activation time is greater than 180 days, and the last login is greater than 60 days: Lost users;

The activation time is greater than 180 days, and the last login is within 60 days: Loyal user;

6) Save and update the self-service dataset.

2.2 Make a dashboard

Use the above data to make two components, as shown in the following figure:

As can be seen:

• The proportion of one time users and lost users is very high and the proportion of lost users is much larger than the number of new users, and the competitiveness is reduced.

• The proportion of loyal users is very small and the customer base is weak.