Unlocking First Click Attribution: A Step-by-Step Guide with BigQuery and GA 4 Raw Data

In the world of digital marketing, understanding the customer journey is crucial for optimizing campaigns and maximizing ROI. One of the most effective ways to gain insights into this journey is through attribution modeling. First click attribution, in particular, helps you identify the initial touchpoint that leads to a conversion. By leveraging BigQuery and Google Analytics 4 (GA 4) raw data, you can build a robust first click attribution model that provides actionable insights.

Introduction to First Click Attribution

First click attribution gives credit to the first interaction a user has with your brand before converting. This model is particularly useful for understanding the effectiveness of your initial marketing efforts and identifying which channels or campaigns are driving the most awareness.

Why Use BigQuery and GA 4?

BigQuery is a powerful, serverless data warehouse that allows you to analyze large datasets quickly and efficiently. GA 4, on the other hand, provides detailed user interaction data that can be exported to BigQuery for advanced analysis. Together, these tools offer a comprehensive solution for building a first click attribution model.

Setting Up Your Environment

Before diving into the technical details, ensure you have the following:

• A Google Cloud Platform (GCP) account with BigQuery enabled.
• A GA 4 property set up and linked to BigQuery.
• Basic knowledge of SQL and Python.

Exporting GA 4 Data to BigQuery

To start, you need to export your GA 4 data to BigQuery. This can be done through the GA 4 interface:

1. Go to your GA 4 property.
2. Navigate to Admin > Data Streams.
3. Select the data stream you want to export.
4. Click on ‘BigQuery Linking’ and follow the prompts to link your GA 4 property to BigQuery.

Building the First Click Attribution Model

Once your data is in BigQuery, you can start building your first click attribution model. Here’s a step-by-step guide:

Step 1: Identify the First Click

First, you need to identify the first interaction for each user. This can be done by querying the GA 4 data to find the earliest event for each user.

WITH first_clicks AS (
  SELECT
    user_pseudo_id,
    MIN(event_timestamp) AS first_click_timestamp
  FROM
    `your_project.your_dataset.events_*`
  GROUP BY
    user_pseudo_id
)
SELECT
  fc.user_pseudo_id,
  fc.first_click_timestamp,
  e.event_name,
  e.event_timestamp
FROM
  first_clicks fc
JOIN
  `your_project.your_dataset.events_*` e
ON
  fc.user_pseudo_id = e.user_pseudo_id
WHERE
  e.event_timestamp = fc.first_click_timestamp

Step 2: Aggregate Data

Next, aggregate the data to understand the distribution of first clicks across different channels and campaigns.

SELECT
  channel,
  COUNT(DISTINCT user_pseudo_id) AS first_clicks
FROM
  first_clicks
GROUP BY
  channel
ORDER BY
  first_clicks DESC

Step 3: Analyze and Visualize

Finally, analyze the aggregated data to identify trends and insights. You can use tools like Google Data Studio or Tableau to visualize the data and create reports.

Best Practices and Tips

Here are some best practices to keep in mind:

• Regularly update your data to ensure your model is current.
• Use filters to exclude irrelevant data, such as internal traffic or bot activity.
• Combine first click attribution with other models for a holistic view of your marketing efforts.

Conclusion

Building a first click attribution model with BigQuery and GA 4 raw data provides valuable insights into your marketing efforts. By understanding the initial touchpoints that lead to conversions, you can optimize your campaigns and improve your ROI. With the steps outlined in this guide, you’re well on your way to unlocking the power of first click attribution.

For further reading, check out these resources:

• Google Analytics 4 Help Center
• BigQuery Documentation
• Think with Google: Attribution Modeling