retention

Calculates the user retention rate within a specified period of time. This function accepts 1 to 31 conditions and evaluates whether each condition is true. If the condition evaluates to true, 1 is returned. Otherwise, 0 is returned. It eventually returns an array of 0 and 1. You can calculate the user retention rate based on this data.

Syntax

ARRAY retention(ARRAY input)

Parameters

input: an array of conditions. A maximum of 31 conditions can be passed in. Separate multiple conditions with commas.

Return value

Returns an array of 0 and 1. The number of 0 and 1 is the same as the number of input conditions.

The evaluation starts from the first condition.

• If the condition evaluates to true, 1 is returned. Otherwise, 0 is returned.
• If the first condition is not true, the current position and its following positions are all set to 0.

Examples

1. Create a table named test and insert data.

   CREATE TABLE test(
       id TINYINT,
       action STRING,
       time DATETIME
   )
   ENGINE=olap
   DUPLICATE KEY(id)
   DISTRIBUTED BY HASH(id);
   
   INSERT INTO test VALUES 
   (1,'pv','2022-01-01 08:00:05'),
   (2,'pv','2022-01-01 10:20:08'),
   (1,'buy','2022-01-02 15:30:10'),
   (2,'pv','2022-01-02 17:30:05'),
   (3,'buy','2022-01-01 05:30:09'),
   (3,'buy','22022-01-02 08:10:15'),
   (4,'pv','2022-01-02 21:09:15'),
   (5,'pv','2022-01-01 22:10:53'),
   (5,'pv','2022-01-02 19:10:52'),
   (5,'buy','2022-01-02 20:00:50');

2. Query data from test.

   MySQL > select * from test order by id;
   +------+--------+---------------------+
   | id   | action | time                |
   +------+--------+---------------------+
   |    1 | pv     | 2022-01-01 08:00:05 |
   |    1 | buy    | 2022-01-02 15:30:10 |
   |    2 | pv     | 2022-01-01 10:20:08 |
   |    2 | pv     | 2022-01-02 17:30:05 |
   |    3 | buy    | 2022-01-01 05:30:09 |
   |    3 | buy    | 2022-01-02 08:10:15 |
   |    4 | pv     | 2022-01-02 21:09:15 |
   |    5 | pv     | 2022-01-01 22:10:53 |
   |    5 | pv     | 2022-01-02 19:10:52 |
   |    5 | buy    | 2022-01-02 20:00:50 |
   +------+--------+---------------------+
   10 rows in set (0.01 sec)

3. Use retention to calculate user retention rate.

   Example 1: Evaluate user behavior against the following conditions: view commodity page on 2022-01-01 (action='pv') and place an order on 2022-01-02 (action='buy').

   MySQL > select id, retention([action='pv' and to_date(time)='2022-01-01',
                                 action='buy' and to_date(time)='2022-01-02']) as retention 
   from test 
   group by id
   order by id;
   
   +------+-----------+
   | id   | retention |
   +------+-----------+
   |    1 | [1,1]     |
   |    2 | [1,0]     |
   |    3 | [0,0]     |
   |    4 | [0,0]     |
   |    5 | [1,1]     |
   +------+-----------+
   5 rows in set (0.01 sec)

   In the result:

   • Users 1 and 5 meets two conditions and [1,1] is returned.

   • User 2 does not meet the second condition and [1,0] is returned.

   • User 3 meets the second condition but does not meet the first condition. [0,0] is returned.

   • User 4 meets no condition and [0,0] is returned.

   Example 2: Calculate the percentage of users who have viewed commodity page on 2022-01-01 (action='pv') and placed an order on 2022-01-02 (action='buy').

   MySQL > select sum(r[1]),sum(r[2])/sum(r[1])
   from (select id, retention([action='pv' and to_date(time)='2022-01-01',
                               action='buy' and to_date(time)='2022-01-02']) as r 
   from test 
   group by id 
   order by id) t;
   
   +-----------+---------------------------+
   | sum(r[1]) | (sum(r[2])) / (sum(r[1])) |
   +-----------+---------------------------+
   |         3 |        0.6666666666666666 |
   +-----------+---------------------------+
   1 row in set (0.02 sec)

   The return value is the user retention rate on 2022-01-02.

keyword

retention, retention rate, RETENTION