GA4 Explorations: How to Use the Analysis Hub

By Emily Redmond, Data Analyst at Emilytics · April 2026

TL;DR: Explorations (Analysis Hub) is where you ask questions and get answers. Build custom reports with dimensions, metrics, segments, and filters. Use funnels to spot drop-off, cohorts to track user groups, and path analysis to see user journeys.

Standard GA4 reports are useful for checking metrics. Explorations are where real analysis happens. This is where you answer questions like "Why are mobile users abandoning cart?" or "Which landing pages have the highest conversion rate?" or "What's the user journey for people who churn?"

If you're not using Explorations, you're leaving 80% of GA4's power on the table.

What Is an Exploration?

An exploration is a custom report you build from scratch. You choose:

• Dimensions: Rows (traffic source, country, landing page, etc.)
• Metrics: Columns (users, conversions, revenue, sessions)
• Filters: Only show certain data (organic traffic only, mobile only)
• Segments: Compare groups (users who converted vs. didn't)
• Visualization: Table, scatterplot, timeline, funnel, cohort, path

Think of it like building a spreadsheet: pick your axes, your data, your view. Explorations are infinitely flexible.

Creating Your First Exploration

The Freeform Report (Simplest)

The freeform exploration is just: dimensions + metrics + filters.

1. Go to GA4 → Explore (bottom left)
2. Click Create new exploration
3. Select Freeform exploration
4. You'll see:
   • Tab 1 (Variables): Dimensions, metrics, filters available
   • Tab 2 (Settings): Date range, segments
   • Tab 3 (Visualization): How to display data

Step 1: Add Dimensions

Click Tab 1, go to Dimensions.

Choose what you want in the rows of your report. Examples:

• Source/medium: traffic source (organic/google, paid/google, direct, etc.)
• Country: location of traffic
• Device category: desktop, mobile, tablet
• Landing page: which page users landed on
• Event name: which events fired

Example: You want to see which traffic sources drive the most conversions. Drag Source/medium to the dimensions area.

Step 2: Add Metrics

Go to Metrics and pick what you want to measure. Examples:

• Users: Unique users
• Conversions: Total conversions (if you've marked events as conversions)
• Conversion rate: Conversions / sessions
• Revenue: Total purchase value
• Event count: Total events fired
• Average session duration: Minutes per session

Example: Drag Conversions and Conversion rate to the metrics area.

Step 3: Add Filters (Optional)

Filters narrow the data. Example: "Only show mobile traffic" or "Only organic search."

Click Add filter. Choose:

• Dimension: What to filter by (Device category, Country, etc.)
• Operator: Contains, equals, doesn't contain, etc.
• Value: The specific value (Mobile, United States, etc.)

Example: Add filter → Dimension: "Device category" → Equals → "Mobile"

Now the report shows only mobile traffic.

Step 4: Choose Visualization

By default, GA4 shows a table. You can change it:

• Table: Standard rows and columns (best for most reports)
• Scatterplot: Two metrics plotted against each other (best for correlation)
• Timeline: Metrics over time (best for trends)
• Geo: Map of traffic by country
• Pie chart: Breakdown of one metric (best for composition)

For your first report (traffic source + conversions), a table is perfect.

Step 5: Save

Click Save exploration at the top. Name it (e.g., "Conversions by Traffic Source"). You can come back and edit it later.

Types of Explorations (Beyond Freeform)

GA4 has five exploration types, each answering different questions:

1. Freeform (What We Just Did)

Use for: Answering any question. "Which pages convert best?" "What's the breakdown of users by country?" "How many events per user?"

Best for: Getting your feet wet.

2. Funnel Exploration

Use for: Spotting where users drop off. "Users land → View product → Add to cart → Checkout → Purchase."

Example setup:

1. Click Create new exploration → Funnel exploration
2. Add steps:
   • Step 1: page_view (landing page = /products)
   • Step 2: view_item event
   • Step 3: add_to_cart event
   • Step 4: begin_checkout event
   • Step 5: purchase event
3. Run

GA4 shows you:

• How many users reached each step
• Drop-off rate between steps
• Breakdown by dimension (e.g., which traffic sources drop off most?)

This is one of the most useful reports. You immediately see where users abandon.

💡 Emily's take: I've debugged more product issues using funnel analysis than anything else. A sudden drop-off at "add to cart"? Usually a checkout bug. Drop-off at "view product"? Usually bad landing page targeting. The funnel tells you where to look.

3. Cohort Exploration

Use for: Tracking user groups over time. "How do users who signed up in April behave vs. May?" or "Do free users eventually convert?"

Example setup:

1. Click Create new exploration → Cohort exploration
2. Cohort dimension: How to group users (usually signup date, but could be traffic source, country, etc.)
3. Behavior metrics: What to measure (conversions, revenue, retention)
4. Date range: How far back to look

GA4 shows a table where:

• Rows = cohorts (April signups, May signups, etc.)
• Columns = weeks/months after joining
• Values = the metric (retention %, revenue, conversions)

Use this to answer: "Do users who join in April have higher lifetime value than users who join in May?"

4. Path Exploration

Use for: Understanding user journeys. "What pages do users visit before converting?" or "What's the most common path to a purchase?"

Example setup:

1. Click Create new exploration → Path exploration
2. Path: What to track (page path, events, etc.)
3. Starting point (optional): Start with a specific event
4. Ending point (optional): End with a specific event

GA4 shows a Sankey diagram (flow chart) of how users move through your site.

Example: Start with "landing page," end with "purchase," and see what pages users visit in between.

5. User Journey

Use for: Detailed understanding of individual user behavior. "What did user X do from day 1 to conversion?" (Privacy note: You can only see this for non-personally-identifiable aggregates unless you have user consent.)

Less common than others, but useful for specific investigations.

Advanced Exploration Techniques

Segments (Comparing Groups)

Segments let you compare two user groups in one report.

Example: Compare "users who converted" vs. "users who didn't convert."

1. In the report settings, click Segment comparison
2. Add a segment: "Sessions with conversions > 0"
3. Add another: "Sessions with conversions = 0"
4. Run

Now each metric is broken down by segment. You immediately see the difference: average session duration for converters (5 min) vs. non-converters (2 min). That insight drives product decisions.

Multiple Metrics and Comparisons

Add multiple metrics to a single report to see correlations.

Example: Pages by "Users," "Event count," "Conversion rate," and "Average session duration."

This gives you a holistic view: page X has lots of users but low conversion rate. Why? Maybe it's a well-trafficked landing page but needs better CTA. Or it's a blog page that drives awareness but not direct conversions.

Date Ranges and Comparisons

Compare two date ranges (week-over-week, year-over-year).

1. In Settings, change the date range
2. You can also do a Comparison: Set a date range and compare to "Previous period"

Example: Compare this week's conversion rate to last week. If it's down 20%, something changed. What?

Common Explorations to Build

For All Businesses

For Ecommerce

For SaaS

Tips for Better Explorations

1. Start simple: One dimension, one metric. Add complexity once you understand the basics.

2. Use filters to zoom in: "All traffic" is often too broad. "Mobile organic traffic" is actionable.

3. Segment to compare: "Converters vs. non-converters" often reveals insight that "all users" hides.

4. Watch for sampling: Large reports might be sampled (estimated from a subset). If you see a note, narrow the date range or add filters to get unsampled data.

5. Export and share: Click the download icon to export a report as CSV or as a link to share.

6. Save useful explorations: You'll repeat the same analyses. Save them so you don't have to rebuild.

Frequently Asked Questions

Q: What's the difference between a freeform exploration and a standard report? A: Standard reports are pre-built by Google. Explorations let you customize fully. Explorations are more flexible; standard reports are faster if you know what you're looking for.

Q: Can I compare two properties in one exploration? A: No, explorations are single-property. If you need to compare two properties, run the exploration in each and manually compare.

Q: Why is my exploration showing "Unsampled" or "Sampled Data"? A: Large datasets are sampled for speed. Unsampled data is accurate; sampled is estimated. To get unsampled data, narrow your date range or add filters.

Q: Can I automate explorations (run them daily)? A: Not natively. You'd need to export to BigQuery and set up a script, or use a third-party tool.

Q: How do I share an exploration with my team? A: Copy the link (share icon in the top right). Anyone with access to the GA4 property can view it. You can also export to PDF or CSV.

The Bottom Line

Explorations are where analytics becomes actionable. Move beyond "how many users?" to "where are we losing users?" and "what's different about users who convert?"

Start with one exploration (try the funnel for your key conversion). Get comfortable. Build more. Soon you'll be spotting trends and insights that no standard report would show.

For building custom dashboards to monitor key metrics, see How to Build a Custom GA4 Dashboard From Scratch.

Emily Redmond is a data analyst at Emilytics — the AI analytics agent that watches your GA4, Search Console, and Bing data around the clock so you never miss what matters. 8 years of experience helping founders and growth teams turn data noise into clear decisions. Say hi →