Google Analytics(GA4) BigQuery

In this sample data application, we use Google Analytics (GA4) data to analyze visitor behavior on your web pages.

The application aggregates and visualizes the pages that visitors viewed immediately before arriving at a specific page on your website. This analysis provides insights such as:

  • “Many visitors view the pricing page before signing up for a paid plan."
  • "Visitors check specific use case pages before going to the pricing page.”

These insights enable informed decisions like “enriching the use case pages on the website.”

By changing the URL as shown in the image below, you can easily see the visitor behavior history for any page on your website.

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How to Use

To use this sample application, first synchronize your data from Google Analytics to BigQuery.

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Step 1: Create a Connection

In the Data section of the workspace, create a connection with BigQuery linked to Google Analytics.

Be sure to name this connection as bq_google_analytics.

The config function in ./src/sql/ga_data_extraction.sql specifies bq_google_analytics as the connection. Therefore, you can also edit this file to use the name of the connection you created for it to work correctly.

Refer to the following for connecting with BigQuery.

Connect with BigQuery

Create a connection with BigQuery.

Update the FROM clause in src/sql/ga_data_extraction.sql to use the project_id and dataset from the connected BigQuery.

  • PUT_YOUR_PROJECT_ID: The project_id of your connected BigQuery
  • PUT_YOUR_DATASET: The dataset of your connected BigQuery
-- Config section omitted.
SELECT user_pseudo_id,
    (
        SELECT
            value.string_value
        FROM
            UNNEST(event_params)
            WHERE
            key = 'page_location'
    ) AS page_location,
    (
        SELECT
            value.string_value
        FROM
            UNNEST(event_params)
            WHERE
            key = 'page_referrer'
    ) AS page_referrer,
    event_timestamp
FROM `[PUT_YOUR_PROJECT_ID].[PUT_YOUR_DATASET].events_*`, UNNEST(event_params)
WHERE
    event_name = 'page_view'

Specify the URL of the conversion page as target_link for analysis.

(e.g., “https://www.morph-data.io/pricing”)

  • src/python/calculate_traffic_flow.py: Change the default value of target_link to your site’s conversion URL.
  • src/python/visualize_traffic_flow.py: Change target_link as described above.
  • src/pages/index.mdx: Change target_link as described above.

If an error occurs in Step 3, execute the files from Steps 2 and 3 individually to identify the problematic file.

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Step 4: Check Results from Pages

Once the settings in Step 2 are configured correctly, you can access the output of the sample application from the Pages section.

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