Question

我正在做简单的多渠道归因探索，并且陷入了对用户会话进行分组的问题。

例如，我有简单的会话表：

client channel time converted
1   social  1   0
1   cpc     2   0
1   email   3   1
1   email   4   0
1   cpc     5   1
2   organic 1   0
2   cpc     2   1
3   email   1   0

每行包含用户会话和 converted 列，该列显示用户是否在特定会话中进行了转换。

我需要对引导每个用户和每次转化的转化进行分组，因此完美的结果应该是：

client channels time converted
1 [social,cpc,email] 3  1
1 [email,cpc]        5  1
2 [organic,cpc]      2  1
3 [email]            1  0

通知用户3，他没有被转换，但我需要进行会话

Answer 1

您需要分配一个组。为此，converted的反和看起来像是正确的事情：

select client, array_agg(channel order by time) as channels,
       max(time) as time, max(converted) as converted
from (select t.*,
             sum(t.converted) over (partition by t.client order by t.time desc) as grp
      from t
     ) t
group by client, grp;

Answer 2

以下是用于BigQuery标准SQL

#standardSQL
SELECT 
  client, 
  STRING_AGG(channel ORDER BY time) channels,
  MAX(time) time,
  MAX(converted) converted 
FROM (
  SELECT *, COUNTIF(converted = 1) OVER(PARTITION BY client ORDER BY time DESC) session
  FROM `project.dataset.table` 
)
GROUP BY client, session 
-- ORDER BY client, time

您可以使用问题中的示例数据来测试，玩游戏，如下例所示

#standardSQL
WITH `project.dataset.table` AS (
  SELECT 1 client, 'social' channel, 1 time, 0 converted UNION ALL
  SELECT 1, 'cpc', 2, 0 UNION ALL
  SELECT 1, 'email', 3, 1 UNION ALL
  SELECT 1, 'email', 4, 0 UNION ALL
  SELECT 1, 'cpc', 5, 1 UNION ALL
  SELECT 2, 'organic', 1, 0 UNION ALL
  SELECT 2, 'cpc', 2, 1 UNION ALL
  SELECT 3, 'email', 1, 0 
)
SELECT 
  client, 
  STRING_AGG(channel ORDER BY time) channels,
  MAX(time) time,
  MAX(converted) converted 
FROM (
  SELECT *, COUNTIF(converted = 1) OVER(PARTITION BY client ORDER BY time DESC) session
  FROM `project.dataset.table` 
)
GROUP BY client, session 
ORDER BY client, time

有结果

Row client  channels            time    converted    
1   1       social,cpc,email    3       1    
2   1       email,cpc           5       1    
3   2       organic,cpc         2       1    
4   3       email               1       0

如何按转换后的行对用户会话进行分组

2 个答案: