I calculated active user in bigquery which is linked with GA by user_pseudo_id
but it shows different value with (Explorations[GA4] -> Free-form exploration -> active user)
how can i calculate same value with ga4 in bigquery?
Related
I do have my GA4 property connected to Bigquery. I use my own user_id for tracking - its available once someone logs into my app.
For some reason, when I'm trying to build a report User ID string vs Unique Users, some ID's have more than 1 Unique User reported. Showing an example on the attached image.
Why is that and how I can fix that situation? I'd expect that one ID = One User
User ID vs Number of Users
How user are counted in firebase analytics?
I launched the query below, but I have an higher number in GA dashboard (9k user and 3.5k new user) instead of BigQuery (7.190)
SELECT count(distinct user_pseudo_id) as user
FROM `pn.analytics_nid.events_*`
WHERE _TABLE_SUFFIX BETWEEN '20210302' AND '20210308'
and how to calculate in Big Query new users?
I am not sure how to calculate the number of users on firebase console.
You can count new users like bellow,
SELECT count(distinct user_pseudo_id) as user
FROM `pn.analytics_nid.events_*`
WHERE _TABLE_SUFFIX BETWEEN '20210302' AND '20210308'
AND event_name = 'first_open'
btw, precisely it depends on your definition of "new user". So take a look this link for first_open meaning.
https://support.google.com/firebase/answer/9234069?hl=en
I am using a query to calculate daily retention on my Firebase Analytics data exported to BigQuery. It is working well and the numbers match with the numbers in Firebase, but when I try to filter the query by a cohort of users, the numbers don't add up.
I want to compare the results of an A/B test from Firebase, and so I've looked at the user_property "firebase_exp_2" which is my A/B test, and I've split up the users in each group (0/1). The retention numbers do not match (at all) the numbers that I can see in my A/B test results in Firebase - actually they show the opposite pattern.
The query is adapted from here: https://github.com/sagishporer/big-query-queries-for-firebase/wiki/Query:-Daily-retention
All I've changed is adding the following under the "WHERE" clause:
WHERE
event_name = 'user_engagement' AND user_pseudo_id IN
(SELECT user_pseudo_id
FROM `analytics_XXX.events_*`,
UNNEST (user_properties) user_properties
WHERE user_properties.key = 'firebase_exp_2' AND user_properties.value.string_value='1')
Firebase says that there are 6,043 users in the Control group and 6,127 in the Variant A group, but my numbers are 5,632 and 5,730, and the retained users are around 1,000 users more than what Firebase reports.
What am I doing wrong?
The export to BigQuery happens on a daily basis and each imported table is named events_YYYYMMDD. Additionally, a table is imported for events received throughout the current day. This table is named events_intraday_YYYYMMDD.
The additions you made are querying from events_* which is fine. The example uses events_201812* though which would ignore the intraday table. That would explain why your numbers a lower. You are missing users added to the A/B test during the current day.
I have Google Analytics integrated to Bigquery and I'm trying to write a query to fetch Active Users that should match with the number on GA Portal.
Here's the query I've written;
SELECT
date(date) as date,
EXACT_COUNT_DISTINCT(fullVisitorId) as daily_active_users,
FROM TABLE_DATE_RANGE([<project_id>:<dataset>.ga_sessions_],
TIMESTAMP('2018-01-01'),
TIMESTAMP(CURRENT_DATE()))
group by date
order by date desc
The numbers I get in response are somehow related to the ones Google Analytics shows me, but they aren't a 100% accurate.
The numebers I get in return are slightely higher than the ones on the portal and I assume I need to put a where clause to filter a property GA might be filtering on the portal.
Your query looks fine to me. Assuming that you're looking at the same GA view as the one linked to BigQuery, I think that the problem could be sampling.
Even if the GA UI says that "This report is based on 100% of sessions.", try to export it as an Unsampled Report and check the numbers (in my experience, the users metric sometimes doesn't match between unsampled reports and default reports without sampling).
Our organization is in e-commerce and users are looking to change a filter everyday with a different list of items, and none of the users will have their own license, just read-only access. The data is connected through Google Big Query, is there a way to have this bulk filter upload capability without the License owners having to touch the filter each time?
Example
Product ID is the filter
Monday: they have a list of 10,000 ID's they want to check sales for
Tuesday: They have a new list of 4,000 different ID's they want to check sales for.
Without clicking each ID each time, is there a way to just upload a list, csv, google sheet etc.
We thought users can upload a list of Product ids to Google sheets which can map to a BigQuery table. We can use it to join with the sales table and get the relevant data. However this becomes unmanageable when we have more than 1 user as users might step on to others data.
Any suggestions/recommendations are welcome. Our team is pretty new to Tableau as such. Let me know if any additional details are needed.
Have you tried changing the filter type to "Multi Values (custom list)" and then having the report user paste their list into the filter? See below: