Google Analytics's Custom Dimension Shows NULL Value in BigQuery

[adnandmth]

I have Google Analytics UA linked to BigQuery and I see there are lots of generated data having NULL value in a specific custom dimension.

I was trying to understand under what circumstance this could happen? is it a bug in BigQuery or is it something our developer should check as to why the custom dimension values were not set?

[caryna]

Hi @adnandmth,

Welcome to the Google Cloud Community!

From what I gather, you're observing a significant amount of null values for your custom dimension in BigQuery.

Below are the potential culprits for this issue:

• The custom dimension may have been implemented incorrectly due to syntax errors or missing logic.
• There might be problems with collecting or sending data, causing the custom dimension value to be lost before reaching Google Analytics.
• If you are using data sampling, some data points with your custom dimension value might be excluded from the export.
• There might be a schema issue in BigQuery. It's possible the custom dimension is mapped incorrectly.
• Lastly, it could be an issue with data processing.

To dive deeper, try the following steps:

• Analyze the Data: You should verify your data between BigQuery and your raw data in Google Analytics to ensure there are no data discrepancies. 
• Check Google Analytics: Connect with your developer to examine if the custom dimension is implemented correctly. Check for any conditions or logic errors that might prevent the dimension from being set.
• Verify Schema: Consider checking BigQuery Schema and Google Analytics Schema to ensure they are matched.

You can also check the suggested answer on Stack Overflow: Google Analytics's Custom Dimension Shows NULL Value in BigQuery

I hope the above information is helpful.

[DataSavvy]

Hi @adnandmth the issue with NULL values in your custom dimension could be caused by a few common factors:

1. Data Collection Configuration

Check if the custom dimension (index=3 in your case) is correctly set up in Google Analytics.

Make sure it’s being populated with data from your website or app. Sometimes, a missing tag or incorrect variable mapping can lead to blank values.

2. Sampling or Data Limits

If your Google Analytics account handles a high volume of traffic, sampling might impact data completeness.

Additionally, limitations in the free-tier version of Google Analytics can sometimes lead to inconsistencies.

3. User Journey Gaps

If the custom dimension is conditionally set based on specific user actions or events, ensure that all relevant scenarios are accounted for in your tracking setup.

It’s possible that some users aren’t triggering the condition needed to populate the dimension.

4. BigQuery Schema

Double-check that your query logic is handling NULL values correctly. While your SQL seems fine, you might want to review the pipeline that transfers data from GA to BigQuery to ensure nothing is being dropped or misinterpreted.

Suggestions to Resolve This

Debug Your Tracking Setup

• Use tools like Google Tag Assistant or GA Debugger to check if the custom dimension is consistently being populated across different user journeys.

Review Your ETL Process

• If you’re using a third-party tool or script to extract data, confirm that it isn’t dropping or misinterpreting certain records during the transfer.

Enhance Your Analytics Workflow

• If sampling or data transfer is a recurring issue, consider using an ETL/ELT solution to extract GA data directly into BigQuery. Tools like Windsor.ai allow custom configurations to pull data from Google Analytics without sampling, ensuring a more complete and reliable dataset.

By systematically reviewing these areas, you should be able to identify and fix the cause of the NULL values.

Let me know if you need further assistance or clarification!