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retention

Description

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) BUCKETS 8;

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

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