GA4 Funnel Exploration: How to Spot Exactly Where Users Drop Off

By Emily Redmond, Data Analyst at Emilytics · April 2026

TL;DR: Funnels show each step of a conversion process and drop-off rates between steps. Use funnel explorations to identify bottlenecks (e.g., "50% of users drop off at checkout").

A funnel shows the path to a goal. Most users never reach the end. A funnel exploration shows exactly where they leave. That's where optimization happens.

What Is a Funnel?

A funnel is a series of steps leading to a conversion. Example ecommerce funnel:

1. Land on site (1,000 users)
   ↓ 80% move forward
2. View a product (800 users)
   ↓ 70% move forward
3. Add to cart (560 users)
   ↓ 60% move forward
4. Start checkout (336 users)
   ↓ 75% move forward
5. Complete purchase (252 users)

Final conversion rate: 252 / 1,000 = 25.2%

But the funnel shows where the big drops happen:

• Landing → product view: 20% drop (80% conversion)
• Product view → add to cart: 30% drop (70% conversion)
• Add to cart → checkout: 40% drop (60% conversion) ← Biggest drop

The biggest drop (checkout) is where to focus optimization efforts.

Creating a Funnel Exploration

Step 1: Define Your Steps

Before you build, decide on your funnel steps. Examples:

Ecommerce funnel:

1. Land on product page
2. View product details
3. Add to cart
4. Start checkout
5. Add payment info
6. Complete purchase

SaaS funnel:

1. Land on pricing page
2. Click "Get Started"
3. Enter email
4. Verify email
5. Complete onboarding
6. Activate first feature

Lead gen funnel:

1. Land on landing page
2. Scroll to form
3. Start filling form
4. Submit form
5. Receive confirmation email

Each step should be a discrete event or page.

Step 2: Create the Exploration

1. Go to GA4 → Explore
2. Click Create new exploration
3. Select Funnel exploration
4. Name it (e.g., "Checkout Funnel")

Step 3: Add Steps

1. Under "Funnel steps," click Add step
2. Choose your first step:
   • Event: User fired a specific event (e.g., view_item)
   • Page: User viewed a specific page (e.g., /cart)
3. Add conditions if needed (e.g., "Event = view_item AND item_category = 'shoes'")
4. Save step

Repeat for each step (usually 3-7 steps).

Step 4: Run the Funnel

Click Run and GA4 shows:

• Step name: Each step in the funnel
• Users: How many reached that step
• Conversion rate: % who reached that step (of first step)
• Drop-off: % who didn't move to the next step

Interpreting a Funnel Report

Example output:

Insights:

• Step 1 → 2: 30% drop (30% of users who viewed products don't add to cart). Check: Is your "Add to cart" button visible? Is the product compelling?
• Step 2 → 3: 30% drop (30% of cart users don't proceed to checkout). Check: Cart page UX. Are there hidden fees or shipping costs surprising users?
• Step 3 → 4: 20% drop (most users who start checkout do add payment). This is good.
• Step 4 → 5: 10% drop (most users who add payment do complete). Good.

The biggest optimization opportunity is step 1 → 2 (30% drop rate).

Advanced Funnel Techniques

Segment the Funnel

Compare drop-off rates across groups (desktop vs. mobile, organic vs. paid).

1. Create a funnel
2. In the Settings tab, enable Segment comparison
3. Add a segment (e.g., "Device category = mobile")
4. Add another segment (e.g., "Device category = desktop")
5. Run

Now you see:

• Mobile funnel: 1,000 → 600 → 360 → 180 (18% final conversion)
• Desktop funnel: 1,000 → 800 → 640 → 512 (51% final conversion)

Mobile conversion is WAY lower. This directs optimization efforts (mobile UX fixes).

Compare Traffic Sources

1. Create a funnel
2. Segment by: Source/medium
3. Compare organic vs. paid vs. direct

Paid traffic might drop faster at checkout (price sensitivity). Organic might drop at product view (relevance mismatch). Different issues, different fixes.

Add Filters

Narrow the funnel to a specific audience.

Example: "Show me the checkout funnel for returning customers only."

1. Create funnel
2. Add filter: "Is returning visitor = True"
3. Run

Compare returning vs. new customer funnels. Returning customers might convert better (already know the product).

Common Funnels to Track

Ecommerce

Discovery → Conversion:

• View product
• Add to cart
• View cart
• Start checkout
• Add payment
• Purchase

Key metric: Where's the biggest drop? Usually cart → checkout (shipping costs) or product view → add to cart (product needs better photos/description).

SaaS

Acquisition → Activation:

• Sign up page view
• Email entered
• Email verified
• Account created
• First login
• First feature used

Key metric: Where do new users drop? Usually email verification (people don't check email) or first login (product is confusing).

B2B

Awareness → Sales-Ready:

• Read case study
• Download whitepaper
• View pricing
• Request demo
• Attend demo
• Become SQL (sales-qualified lead)

Key metric: Usually demo attendance. Demos are expensive; no-shows waste money.

Using Funnel Insights to Improve Conversion

Example: 40% of users drop off at "Add to cart"

Hypothesis: The add-to-cart button is hard to find.

Test: Make the button bigger, change its color, move it higher on the page.

Measure: Compare funnel drop-off before and after.

Example: 60% of mobile users drop at "Start checkout"

Hypothesis: Mobile checkout flow is slow or confusing.

Test: Simplify mobile checkout to 3 steps instead of 5. Use guest checkout.

Measure: Compare mobile vs. desktop drop-off before and after.

Example: Paid traffic drops faster than organic

Hypothesis: Ad copy doesn't match product. Users expect something different.

Test: Update ad copy to match actual product/landing page.

Measure: Compare paid traffic funnel before and after.

Funnel Insights Report

GA4 also has a built-in Funnel Insights feature (in some reports). It automatically flags:

• Unexpected drop-offs
• Changes from past periods
• Segments with notably different drop-off rates

Check these automatically generated insights.

Frequently Asked Questions

Q: What's the difference between a funnel exploration and the Shopping Behavior report? A: Shopping Behavior is ecommerce-specific and auto-configured. Funnel explorations are customizable for any sequence of events/pages.

Q: Can I see the actual users in a funnel step? A: Not directly in the funnel report. But you can create an audience for each step, then analyze that audience's properties.

Q: Why does my funnel have only 2 people in step 1? A: Either your funnel is defined wrong (events/pages aren't firing), or you genuinely have low traffic. Check event firing in Real-Time.

Q: Can I reorder funnel steps after creating them? A: Yes. In the funnel settings, drag steps to reorder them.

Q: How far back can I look in a funnel? A: As far back as your data retention goes (2 months default, 14 months with extension, unlimited in BigQuery).

The Bottom Line

Funnels show you where users leave. Drop-off rates show you where to focus. A 40% drop at one step vs. 10% at another is a massive signal.

Build a funnel for your core conversion process. Check it weekly. When you see a big drop, investigate and optimize. Even a 5% improvement in drop-off rates can dramatically increase your overall conversion.

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 →