如何在Google BigQuery SQL中预测按相同订单id分组的交易的客户流失？

我对BigQuery中的SQL非常陌生。我试图根据客户的订单id和开始日期预测客户状态

规则

同一订单id的客户状态必须相同

必须根据下一个订单ID（交易）或上一个订单ID预测客户状态

这是我的密码

select week_start, t.account_id, t.order_id, date_start,date_ended,

from unnest(generate_date_array(date('2018-12-31'), date('2019-2-11'), interval 1 week) )  week_start cross join
     (select distinct account_id
      from t
     ) a left join
     t
     on t.account_id = a.account_id and
        t.reporting_week_start_date = week_start
order by  a.account_id,week_start

我的代码的输出

week_start | account_id  | order_id  | date_start   | date_ended   |
2018-12-31 |    1        |    1001   |   2019-01-01 |  2019-01-15  |
2019-01-07 |    1        |    1001   |   2019-01-01 |  2019-01-15  |
2019-01-14 |    1        |    1002   |   2019-01-15 |  2019-01-27  |
2019-01-21 |    1        |    1002   |   2019-01-15 |  2019-01-27  |
2019-01-28 |    1        |    1003   |   2019-01-29 |  2019-02-04  |

期望输出

week_start | account_id  | order_id  | date_start   | date_ended   | Customer_Status
2018-12-31 |    1        |    1001   |   2019-01-01 |  2019-01-15  |  First Time
2019-01-07 |    1        |    1001   |   2019-01-01 |  2019-01-15  |  First Time
2019-01-14 |    1        |    1002   |   2019-01-15 |  2019-01-27  |  Recurring
2019-01-21 |    1        |    1002   |   2019-01-15 |  2019-01-27  |  Recurring
2019-01-28 |    1        |    1003   |   2019-01-29 |  2019-02-04  |  Churned

---

如何在大查询SQL中执行此操作？谢谢。

在分析了您的案例之后，我找到了您可以用来对客户进行分类的规则。因为您想在BigQuery上对每个客户进行分类，所以所有规则都是硬编码的

您提到分类应基于下一个和上一个订单id，但我也使用了账户id字段。出于这个原因，我使用了两种方法

下面的示例代码应该合并到您当前的查询中，我使用您当前的输出作为源输入。我遵循以下算法：

1）对首次客户进行分类。因此，我创建了临时表new_c

2）对定期客户进行分类，然后创建rec_c临时表

3）使用最后一张临时表搅动的客户

4）根据源输入（您当前的输出）连接所有表，在该阶段，它被处理为复制状态，就像我们有两个“首次”客户状态一样，依此类推

下面是代码，请注意，我使用了稍微不同的列名：

    #First selecting the new costumers and changing the namwes of some columns so we can use left join in the end
WITH
  new_c AS (
  SELECT
    _account_id__ AS acc,
    _order_id__ AS oo,
    week_start_ AS wk_nc,
    CASE
      WHEN ((LAG(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)IS NULL) AND (LAG(_order_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)IS NULL )) THEN 'First time'
      WHEN (LAG(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC) != _account_id__ ) THEN 'First time'
  END
    AS status
  FROM
    `test-proj-261014.sample.customer` ),

  #Now, we classify the customers who are Recurring
  rec_c AS (
  SELECT
    _account_id__ AS acc_rc,
    _order_id__ AS oo_rc,
    week_start_ AS wk_rc,
    CASE
      WHEN ((LAG(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)= _account_id__ ) AND (LAG(_order_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)!= _order_id__) AND (LEAD(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC) = _account_id__ ) ) THEN 'Recurring'
  END
    AS status_rc
  FROM
    `test-proj-261014.sample.customer` ),

  #Last, the Churned customers
  churn_c AS (
  SELECT
    _account_id__ AS acc_c,
    _order_id__ AS oo_c,
    week_start_ AS wk_ch,
    CASE
      WHEN ((LEAD(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)!= _account_id__ ) AND (LAG(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)= _account_id__ )) THEN 'Churned'
      WHEN ((LEAD(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC) IS NULL)
      AND (LAG(_account_id__) OVER (PARTITION BY _account_id__ ORDER BY _order_id__ ASC)= _account_id__ )) THEN 'Churned'
  END
    AS status_churn
  FROM
    `test-proj-261014.sample.customer` )

  #In the end, all the temporary tables are joined together and we handle same status customers.
SELECT
  week_start_,
  _account_id__,
  _order_id__,
  _date_start___,
  _date_ended___,
  CASE
    WHEN status IS NOT NULL THEN status
    WHEN (LAG(status) OVER (PARTITION BY acc ORDER BY oo ASC) ='First time'
    AND LAG(oo) OVER (PARTITION BY acc ORDER BY oo ASC)=oo)THEN 'First time'

    WHEN status_rc IS NOT NULL THEN status_rc
    WHEN (LAG(status_rc) OVER (PARTITION BY acc_rc ORDER BY oo_rc ASC) ='Recurring'
    AND LAG(oo_rc) OVER (PARTITION BY acc ORDER BY oo ASC)=oo_rc) THEN 'Recurring'

    WHEN churn_c IS NOT NULL THEN status_churn
    WHEN (LAG(status_churn) OVER (PARTITION BY acc_c ORDER BY oo_c ASC) ='Churned'
    AND LAG(oo_c) OVER (PARTITION BY acc ORDER BY oo ASC)=oo_c) THEN 'Churned'

END
  AS final_status
FROM
  `test-proj-261014.sample.customer`
INNER JOIN
  new_c
ON
  _account_id__ = ACC
  AND _order_id__ = OO
  AND week_start_ = wk_nc
INNER JOIN
  rec_c
ON
  _account_id__ = acc_rc
  AND _order_id__ = oo_rc
  AND week_start_ = wk_rc
INNER JOIN
  churn_c
ON
  _account_id__ = acc_c
  AND _order_id__ = oo_c
  AND week_start_ = wk_ch ;

---

定义客户状态的规则是什么？