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GA4 Demographics for Specific URLs: Explorations & BigQuery

5 min read
4 minutes ago

Since the rollout of Google Analytics 4 (GA4), many analysts and marketers have had to change the way they think about website metrics, user behavior, and data segmentation. One of GA4’s popular features is the ability to explore detailed demographic information about your users. But what if you want to drill down even further—say, uncovering demographic data for specific URLs or pages on your website? While GA4 doesn’t offer this segment natively in standard reports, there are effective workarounds using Explorations and BigQuery.

This article dives into how you can analyze user demographics for specific URLs in both GA4’s Explorations feature and BigQuery exports. Whether you’re a digital marketer, data analyst, or UX designer, this breakdown will help you unlock deeper insights into who’s visiting specific parts of your site.

Understanding GA4’s Demographics Data

GA4 provides demographic data like age, gender, interests, and location—but there’s a twist: it’s user-based, not session-based. That means the platform assigns demographics during a user’s session across multiple pages instead of per pageview. Additionally, demographic data is sampled and available only if Google’s consent requirements are met, leading to incomplete datasets for some users.

Despite these limitations, combining demographics with specific URLs can reveal significant user behavior patterns when done correctly.

Method 1: Using GA4 Explorations

Explorations in GA4 offer an intuitive, drag-and-drop interface to flexibly analyze your data. While they’re more powerful than standard reports, they still require some thoughtful configuration to compare demographics against specific URLs.

Step-by-Step Setup:

  1. Navigate to Explore in the GA4 interface.
  2. Choose a Free-form Exploration or Segment Overlap type based on your needs.
  3. Add Demographic dimensions such as:
    • Age
    • Gender
    • Country
  4. Use the dimension Page path + query string or just Page path to isolate the URL.
  5. Create a filter to include only specific URLs or patterns like /product-page/.
  6. Drag demographics into rows and metrics like Users or Engaged Sessions into columns for comparison.

The table that emerges gives you a snapshot of who’s visiting that specific URL. You might notice that certain pages over-index on late Millennials or that a content section primarily attracts users from specific regions.

While this is helpful, there are two main caveats to consider:

  • Sometimes the data lacks sufficient coverage, meaning certain demographics show as “Not set.”
  • Granularity is limited. You can’t do advanced filtering or aggregations directly in Explorations.

That’s where BigQuery can really shine.

Method 2: Using BigQuery for Deep Analysis

If you have GA4 connected to BigQuery—which we highly recommend—you gain full access to your raw event-level data. This means you can run SQL queries to segment demographics for specific URLs with high precision.

GA4’s BigQuery export organizes data on a per-event basis in a nested JSON structure. Every user attribute, event, and parameter is included, making it a data goldmine—with the caveat that you’ll need to get comfortable with SQL and table joins.

Example SQL Query:


SELECT
  user_properties.value.string_value AS age_group,
  geo.country AS country,
  event_params.value.string_value AS page_path,
  COUNT(DISTINCT user_pseudo_id) AS users
FROM
  `project.dataset.events_*`,
  UNNEST(event_params) AS event_params,
  UNNEST(user_properties) AS user_properties
WHERE
  event_name = 'page_view'
  AND event_params.key = 'page_location'
  AND user_properties.key = 'age'
  AND event_params.value.string_value LIKE '%/your-page-slug%'
GROUP BY
  age_group, country, page_path
ORDER BY
  users DESC;

This type of query helps answer questions like:

  • Which age ranges visit my service pages most?
  • Are certain geographies spending more time on my blog posts?
  • Do lifestyle-affinity groups behave differently by landing pages?

You can also join this data with other tables for revenue attribution or user retention analysis—things that aren’t easily accomplished in GA4’s web interface.

Cool Use Cases for Demographics by URL

This approach isn’t just impressive on paper—it has real-world applications. Here’s how different teams might use these insights:

Marketing Teams:

  • Refine ad targeting for audiences that already show organic interest in certain products.
  • Identify gender or age splits to optimize messaging and calls-to-action.

Content Strategists:

  • Discover the types of content that attract international audiences.
  • Adjust tone and multimedia elements based on prevalent demographic stats.

UX Designers:

  • Design page elements that resonate with a core user base.
  • Streamline navigation for older age groups if they frequent high-bounce pages.

Tips for Clean Analysis

To get the most from merging URL data with demographics, keep these best practices in mind:

  • Use naming conventions for pages, especially if your URLs are dynamic.
  • Filter bots and internal traffic early in your BigQuery pipeline.
  • Set up user properties or custom parameters if the standard GA4 demographic dimensions aren’t enough.
  • Stitch user sessions carefully. One user can generate multiple events—don’t double-count them.

Overcoming Data Coverage Gaps

One of GA4’s idiosyncrasies is its incomplete demographic data coverage. Only a subset of users in compliant markets get labeled for demographics. So how do you work around this?

  • Use larger sampling windows in Explorations—like 90 days instead of 30—to build a solid base.
  • Correlate with additional metadata in your warehouse like CRM data or email segmentation, when possible and compliant with privacy laws.
  • Segment by proxy indicators—such as traffic channel or device category—that often correlate with demographics.

Final Thoughts

The combination of GA4 Explorations and BigQuery transforms demographic reporting from a high-level overview into a precise, URL-specific insight machine. Whether you need a top-level breakdown for a marketing report or want to dissect micro-behaviors by audience group, these two tools offer immense flexibility.

By marrying specific content URLs with detailed user traits, businesses can better serve their audiences—not through guesswork, but through data-backed strategy.

In a digital world where personalization is no longer optional, diving into “GA4 demographics by URL” could be the key to the thriving user experience you’ve been aiming for.