Calculating current user return rate in BigQuery

Question

I am trying to calculate CURR (current user return rate, see https://lloydmelnick.com/2019/02/05/lifetime-value-part-26-my-most-valuable-retention-kpis/) with data imported from Firebase into BigQuery.

I tried to create three columns to identify whether the user was active 2 weeks ago, 1 week ago, and this week, but it doesn't seem to be working. I want to see users who are active this week and was ALSO active 2 weeks and three weeks ago.

This is the query I have tried:

SELECT
  COUNT(DISTINCT user_pseudo_id)
FROM(SELECT
  user_pseudo_id,
  IF( days_from_today >13 AND days_from_today <21, 1, 0) AS prev_week,
  IF( days_from_today >6 AND days_from_today <14, 1, 0) AS last_week,
  IF( days_from_today <7, 1, 0) AS this_week
FROM(
SELECT
    DATE_DIFF(CURRENT_DATE(), DATE(TIMESTAMP_MICROS(event_timestamp)), day) AS days_from_today,
    user_pseudo_id
  FROM
    `dataset.events_2019*`
  WHERE
    event_name = 'user_engagement'
  GROUP BY
    days_from_today,
    user_pseudo_id))
    WHERE prev_week=1
    GROUP BY prev_week, last_week, this_week

score 1 · Accepted Answer · answered Mar 14 '19 at 17:12

Doing some modification in your query, this worked for me:

SELECT
  user_pseudo_id
FROM (
  SELECT
    user_pseudo_id,
    MAX(IF( days_from_today >13 AND days_from_today < 21, 1, 0)) AS prev_week,
    MAX(IF( days_from_today >6 AND days_from_today <14, 1, 0)) AS last_week,
    MAX(IF( days_from_today <7, 1, 0)) AS this_week
  FROM (
    SELECT
      DATE_DIFF(CURRENT_DATE(), DATE(TIMESTAMP_MICROS(event_timestamp)), day) AS days_from_today,
      user_pseudo_id
    FROM
      test_table
    WHERE
      event_name = 'user_engagement'
    GROUP BY
      days_from_today,
      user_pseudo_id)
  GROUP BY
    user_pseudo_id)
WHERE
  prev_week = 1

Playing with some dummy data:

WITH test_table as (
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1552208299000000 as event_timestamp union all
  select 2 as user_pseudo_id, 'user_engagement' as event_name, 1552079299000000 as event_timestamp union all
  select 3 as user_pseudo_id, 'user_engagement' as event_name, 1552186299000000 as event_timestamp union all
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1551024899000000 as event_timestamp union all
  select 2 as user_pseudo_id, 'user_engagement' as event_name, 1551024899000000 as event_timestamp union all
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1551523899000000 as event_timestamp union all
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1552024899000000 as event_timestamp
)
SELECT
  DATE_DIFF(CURRENT_DATE(), DATE(TIMESTAMP_MICROS(event_timestamp)), day) AS days_from_today,
  user_pseudo_id
FROM
  test_table
WHERE
  event_name = 'user_engagement'
GROUP BY
  days_from_today,
  user_pseudo_id
ORDER BY 2, 1

Which gives this dataset:

  days_from_today   user_pseudo_id   
1        4               1   
2        6               1   
3        12              1   
4        18              1   
5        6               2   
6        18              2   
7        4               3

Here the user that acceded previous week are 1 and 2

Running the query with dummy dataset:

WITH test_table as (
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1552208299000000 as event_timestamp union all
  select 2 as user_pseudo_id, 'user_engagement' as event_name, 1552079299000000 as event_timestamp union all
  select 3 as user_pseudo_id, 'user_engagement' as event_name, 1552186299000000 as event_timestamp union all
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1551024899000000 as event_timestamp union all
  select 2 as user_pseudo_id, 'user_engagement' as event_name, 1551024899000000 as event_timestamp union all
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1551523899000000 as event_timestamp union all
  select 1 as user_pseudo_id, 'user_engagement' as event_name, 1552024899000000 as event_timestamp
)
SELECT
  user_pseudo_id
FROM (
  SELECT
    user_pseudo_id,
    MAX(IF( days_from_today >13 AND days_from_today < 21, 1, 0)) AS prev_week,
    MAX(IF( days_from_today >6 AND days_from_today <14, 1, 0)) AS last_week,
    MAX(IF( days_from_today <7, 1, 0)) AS this_week
  FROM (
    SELECT
      DATE_DIFF(CURRENT_DATE(), DATE(TIMESTAMP_MICROS(event_timestamp)), day) AS days_from_today,
      user_pseudo_id
    FROM
      test_table
    WHERE
      event_name = 'user_engagement'
    GROUP BY
      days_from_today,
      user_pseudo_id)
  GROUP BY
    user_pseudo_id)
WHERE
  prev_week = 1

Gives the user 1 and 2 as result. Which should be your desired result. You can play with this query to build different analysis results that you want.

Calculating current user return rate in BigQuery

1 Answers1