SQL計算復購率

需求背景:
訂單表中有每筆訂單的下單時間、用戶ID、訂單金額等信息,需要統計每個月在接下來幾個月用戶復購情況。

create table order_info(
order_id int primary key,
user_id int,
amount decimal(10,2),
create_time datetime
);

insert into order_info values
(101,11211,749.00,'2020-01-01 00:04:00'),
(102,75205,939.00,'2020-01-05 09:15:00'),
(103,81384,349.00,'2020-01-08 22:19:00'),
(104,50437,687.00,'2020-01-11 22:17:00'),
(105,30321,658.00,'2020-01-12 22:18:00'),
(106,49811,355.00,'2020-01-16 22:18:00'),
(107,30352,363.00,'2020-01-19 22:24:00'),
(108,30362,435.00,'2020-01-22 22:18:00'),
(109,30363,270.00,'2020-01-27 22:19:00'),
(110,30324,552.00,'2020-01-30 22:22:00'),
(111,11211,692.00,'2020-02-04 08:35:00'),
(112,75205,536.00,'2020-02-09 11:03:00'),
(113,81384,478.00,'2020-02-13 09:32:00'),
(114,30362,675.00,'2020-02-17 11:18:00'),
(115,30363,723.00,'2020-02-20 08:47:00'),
(116,30324,914.00,'2020-02-21 10:48:00'),
(117,49262,444.00,'2020-02-24 18:35:00'),
(118,12074,617.00,'2020-02-29 20:16:00'),
(119,50437,911.00,'2020-03-02 12:35:00'),
(120,30321,695.00,'2020-03-14 23:53:00'),
(121,12074,275.00,'2020-03-15 15:38:00'),
(122,81384,1066.00,'2020-03-18 16:49:00'),
(123,30362,431.00,'2020-03-23 09:01:00'),
(124,27727,687.00,'2020-03-25 15:38:00'),
(125,27727,858.00,'2020-03-28 17:44:00');

select * from order_info;
+----------+---------+---------+---------------------+
| order_id | user_id | amount  | create_time         |
+----------+---------+---------+---------------------+
|      101 |   11211 |  749.00 | 2020-01-01 00:04:00 |
|      102 |   75205 |  939.00 | 2020-01-05 09:15:00 |
|      103 |   81384 |  349.00 | 2020-01-08 22:19:00 |
|      104 |   50437 |  687.00 | 2020-01-11 22:17:00 |
|      105 |   30321 |  658.00 | 2020-01-12 22:18:00 |
|      106 |   49811 |  355.00 | 2020-01-16 22:18:00 |
|      107 |   30352 |  363.00 | 2020-01-19 22:24:00 |
|      108 |   30362 |  435.00 | 2020-01-22 22:18:00 |
|      109 |   30363 |  270.00 | 2020-01-27 22:19:00 |
|      110 |   30324 |  552.00 | 2020-01-30 22:22:00 |
|      111 |   11211 |  692.00 | 2020-02-04 08:35:00 |
|      112 |   75205 |  536.00 | 2020-02-09 11:03:00 |
|      113 |   81384 |  478.00 | 2020-02-13 09:32:00 |
|      114 |   30362 |  675.00 | 2020-02-17 11:18:00 |
|      115 |   30363 |  723.00 | 2020-02-20 08:47:00 |
|      116 |   30324 |  914.00 | 2020-02-21 10:48:00 |
|      117 |   49262 |  444.00 | 2020-02-24 18:35:00 |
|      118 |   12074 |  617.00 | 2020-02-29 20:16:00 |
|      119 |   50437 |  911.00 | 2020-03-02 12:35:00 |
|      120 |   30321 |  695.00 | 2020-03-14 23:53:00 |
|      121 |   12074 |  275.00 | 2020-03-15 15:38:00 |
|      122 |   81384 | 1066.00 | 2020-03-18 16:49:00 |
|      123 |   30362 |  431.00 | 2020-03-23 09:01:00 |
|      124 |   27727 |  687.00 | 2020-03-25 15:38:00 |
|      125 |   27727 |  858.00 | 2020-03-28 17:44:00 |
+----------+---------+---------+---------------------+

解析思路:
第一步:查詢每個月下過單的用戶

select month(create_time) as dt,user_id 
from order_info 
group by month(create_time),user_id;
+------+---------+
| dt   | user_id |
+------+---------+
|    1 |   11211 |
|    1 |   75205 |
|    1 |   81384 |
|    1 |   50437 |
|    1 |   30321 |
|    1 |   49811 |
|    1 |   30352 |
|    1 |   30362 |
|    1 |   30363 |
|    1 |   30324 |
|    2 |   11211 |
|    2 |   75205 |
|    2 |   81384 |
|    2 |   30362 |
|    2 |   30363 |
|    2 |   30324 |
|    2 |   49262 |
|    2 |   12074 |
|    3 |   50437 |
|    3 |   30321 |
|    3 |   12074 |
|    3 |   81384 |
|    3 |   30362 |
|    3 |   27727 |
+------+---------+

第二步:查詢每個月下過單的總用戶數

select month(create_time) 月份,count(distinct user_id) 總用戶數 
from order_info 
group by month(create_time);
+------+----------+
| 月份 | 總用戶數 |
+------+----------+
|    1 |       10 |
|    2 |        8 |
|    3 |        6 |
+------+----------+

第三步:將每個月下過單的用戶的查詢結果作爲臨時表進行自連接,用月份和用戶ID判斷是否復購,計算次月的復購用戶數

select t1.dt 自然月份,t2.dt 復購月份,count(distinct t2.user_id) 復購用戶數 
from (select month(create_time) dt,user_id from order_info group by month(create_time),user_id) t1 
join (select month(create_time) dt,user_id from order_info group by month(create_time),user_id) t2 
on t1.user_id=t2.user_id and t1.dt < t2.dt 
group by t1.dt,t2.dt;
+----------+----------+------------+
| 自然月份 | 復購月份 | 復購用戶數   |
+----------+----------+------------+
|        1 |        2 |          6 |
|        1 |        3 |          4 |
|        2 |        3 |          3 |
+----------+----------+------------+

第四步:復購率=復購用戶數/總用戶數

select 自然月份,復購月份,復購用戶數,總用戶數,round(復購用戶數/總用戶數,2) 復購率 
from 
(select t1.dt 自然月份,t2.dt 復購月份,count(distinct t2.user_id) 復購用戶數 
from (select month(create_time) dt,user_id from order_info group by month(create_time),user_id) t1 
join (select month(create_time) dt,user_id from order_info group by month(create_time),user_id) t2 
on t1.user_id=t2.user_id and t1.dt < t2.dt 
group by t1.dt,t2.dt) a 
join 
(select month(create_time) 月份,count(distinct user_id) 總用戶數 
from order_info 
group by month(create_time)) b 
on a.自然月份=b.月份;
+----------+----------+------------+----------+--------+
| 自然月份  | 復購月份 | 復購用戶數  | 總用戶數  | 復購率  |
+----------+----------+------------+----------+--------+
|        1 |        2 |          6 |       10 |   0.60 |
|        1 |        3 |          4 |       10 |   0.40 |
|        2 |        3 |          3 |        8 |   0.38 |
+----------+----------+------------+----------+--------+
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