使用 Postgresql 进行 RFM 分析

Question

我正在尝试使用 Postgresql 查询创建 RFM 分析。但是，我还没有完全完成对 Recency 维度的查询。本文启发的查询 "https://cooldata.wordpress.com/2014/03/25/an-all-sql-way-to-automate-rfm-scoring/ "
Recency 维度的标准是

最后一个订单在 2 个月内 = 5
最后一个订单在 4 个月内 = 4
6 个月内的最后一个订单 = 3
最后一个订单在 8 个月内 = 2
最后一个订单在 10 个月内 = 1

以下是我一直试图完成的查询

WITH rfm AS

(SELECT email,
 SUM((total_incl_tax)) AS cash,
 MAX(decode(order_order.order_date, 2016-01-01, 5, 2016-02-01, 4, 2016-03-01, 3, 2016-04-01, 2, 201605-01, 1)) AS recency,
 COUNT(DISTINCT(order_date)) AS frequency
 FROM order_order

 GROUP BY email)


SELECT rfm.email,
CASE
WHEN rfm.cash >= 2000000 THEN 5
WHEN rfm.cash > 1500000 THEN 4
WHEN rfm.cash > 1000000 THEN 3
WHEN rfm.cash > 500000 THEN 2
WHEN rfm.frequency > 4 THEN 5
WHEN rfm.frequency = 4 THEN 4
WHEN rfm.frequency = 3 THEN 3
WHEN rfm.frequency = 2 THEN 2
WHEN rfm.frequency = 1 THEN 1
else 1

END  + rfm.frequency AS rfm_score
--+ Five_years.recency

FROM rfm
GROUP BY rfm.email, rfm.cash,rfm.frequency
ORDER BY rfm.email

错误是：

ERROR: function decode(timestamp with time zone, integer, integer, integer, integer, integer, integer, integer, integer, integer, integer) does not exist Hint: No function matches the given name and argument types. You might need to add explicit type casts. Position: 186

我认为错误出在这一行

MAX(decode(order_order.order_date, 2016-01-01, 5, 2016-02-01, 4, 2016-03-01, 3, 2016-04-01, 2, 2016-05-01, 1)) AS recency

是否有任何建议可以将错误行修改为新近度维度的标准？谢谢

Answer 1

Postgres 中没有 decode() 函数。您可以将其替换为另一个 CASE 语句：

WITH rfm AS
(
     SELECT email,
     SUM((total_incl_tax)) AS cash,
     MAX(
         CASE
          WHEN order_order.order_date = '2016-01-01' THEN 5
          WHEN order_order.order_date = '2016-02-01' THEN 4
          WHEN order_order.order_date = '2016-03-01' THEN 3
          WHEN order_order.order_date = '2016-04-01' THEN 2
          WHEN order_order.order_date = '2016-05-01' THEN 1
         END
        )   as recency,
     COUNT(DISTINCT(order_date)) AS frequency
     FROM order_order
     GROUP BY email
 )
SELECT rfm.email,
CASE
    WHEN rfm.cash >= 2000000 THEN 5
    WHEN rfm.cash > 1500000 THEN 4
    WHEN rfm.cash > 1000000 THEN 3
    WHEN rfm.cash > 500000 THEN 2
    WHEN rfm.frequency > 4 THEN 5
    WHEN rfm.frequency = 4 THEN 4
    WHEN rfm.frequency = 3 THEN 3
    WHEN rfm.frequency = 2 THEN 2
    WHEN rfm.frequency = 1 THEN 1
    else 1
END  + rfm.frequency + rfm.recency AS rfm_score
FROM rfm
GROUP BY rfm.email, rfm.cash,rfm.frequency
ORDER BY rfm.email

进一步阅读：Decode equivalent in postgres

使用 Postgresql 进行 RFM 分析

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