# How to extract GA4's event sequencing in BigQuery using the new batch fields

> Google Analytics 4 (GA4) exports event data to BigQuery, enabling detailed user behavior analysis. However, GA4 batches events before sending them, making GA4 event sequencing in BigQuery more complex. Fortunately, three fields—batch_event_index, batch_ordering_id, and batch_page_id—help provide precise sequencing information. For a full schema of the GA4 export, head over to google documentation. This article breaks down these fields in a clear, practical way and shows how to use them togethe

Source: https://www.measurelab.co.uk/insights/blog/extract-ga4-event-sequencing-bigquery-batch-fields/  
Author: Katie Kaczmarek  
Published: 2025-02-24  
Updated: 2025-07-31

Google Analytics 4 (GA4) exports event data to BigQuery, enabling detailed user behavior analysis. However, GA4 **batches** events before sending them, making GA4 event sequencing in BigQuery more complex. Fortunately, three fields—batch_event_index, batch_ordering_id, and batch_page_id—help provide precise sequencing information.

For a full schema of the GA4 export, head over to [google documentation](https://support.google.com/analytics/answer/7029846?hl=en#zippy=%2Cevent).

This article breaks down these fields in a **clear, practical way** and shows how to use them together to **reconstruct a user's journey** in GA4 BigQuery exports.

### **batch_event_index: The Order of Events Within a Batch**

Ever wondered if GA4 sends events in real time? **Spoiler alert: it doesn’t!** GA4 often groups multiple events together in a batch before sending them to improve efficiency. This means that events can **arrive at the same time** even if they actually happened in a specific order.

#### **What is batch_event_index?**

- **Shows the order of events within a batch**, based on when they actually happened on the user’s device.
- Makes sure that even if events are sent together, we can still analyse them in their **true sequence**.

#### **Example: Events in a batch**

Picture this: A user interacts with a webpage and does the following:

1. Clicks a button
2. Scrolls down
3. Views a product

If GA4 sends these events as a batch, they might appear in BigQuery like this:

Even though they were transmitted together, `batch_event_index` keeps the correct **event order intact**.

#### **Why this matters**

- Prevents misleading event sequences
- Helps analyse **multi-step interactions** correctly
- Useful for debugging when actions happen close together

### batch_ordering_id: How GA4 sends batches

While `batch_event_index` helps us analyse **event order within a batch**, `batch_ordering_id` tells us the **order of different batches sent from a page**.

#### What is batch_ordering_id?

- **A steadily increasing number** that increments every time GA4 sends a new batch of events.
- Helps separate events that were sent in **different network requests**.

#### Example: Two separate batches

A user browses a website and interacts with multiple elements. Due to network optimisation, their browser sends two batches of events instead of one.

What this tells us:

- The **first two events** (`button_click`, `scroll`) were sent in **batch 1**.
- The **next two events** (`view_product`, `add_to_cart`) were sent in **batch 2**.
- Within each batch, **batch_event_index keeps track of the order**.

#### **Why this matters**

- Helps track how events are grouped before being sent
- Avoids misinterpreting event order due to delayed network requests
- Useful for debugging and optimising event tracking

### **batch_page_id: Tracking Events Across Pages**

We’ve talked about tracking **event order on a single page**, but what about users navigating across **multiple pages** in one session? That’s where `batch_page_id` comes in.

#### **What is batch_page_id?**

- A sequential number assigned to each page a user visits.
- Increases each time the user navigates to a new page.
- Ensures that all events from the same page share the same `batch_page_id`.

#### **Example: Multi-Page Journey**

Let’s say a user moves through a website:

1. **Homepage** (`batch_page_id = 1`)
2. **Product Page** (`batch_page_id = 2`)
3. **Checkout Page** (`batch_page_id = 3`)

#### **Why this matters**

- Makes multi-page journey analysis much easier
- Helps group events by where they happened
- Avoids confusion when users navigate quickly between pages

### **How to use these fields together for customer journey analysis**

To **accurately reconstruct** a user’s journey, we need to use all three fields together.

#### **Example Query: Rebuilding a customer journey in BigQuery**

```
SELECT 
  user_pseudo_id, 
  event_name, 
  event_timestamp, 
  batch_page_id, 
  batch_ordering_id, 
  batch_event_index
FROM `project.dataset.events_*`
WHERE _TABLE_SUFFIX = FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY))
ORDER BY user_pseudo_id, batch_page_id, batch_ordering_id, batch_event_index;
```

#### **How this works**

- Groups user interactions by page (`batch_page_id`)
- Orders batches of events sent together (`batch_ordering_id`)
- Preserves the order of events within each batch (`batch_event_index`)

This lets us accurately **rebuild a user’s journey step-by-step**, even when GA4 sends events in batches.

### **Final thoughts**

GA4’s batching system improves efficiency, but it also adds complexity. By using `batch_event_index`, `batch_ordering_id`, and `batch_page_id`, we can reconstruct user interactions with confidence. These fields are essential for:

- Tracking user behaviour across multiple pages
- Ensuring event order integrity within batches
- Analysing engagement patterns **without guesswork**

Using these fields in BigQuery unlocks **deeper insights into customer journeys**, helping you make **better, data-driven decisions**.

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