GA4 Custom Funnels: 7 Templates That Actually Tell You Something Useful

Here's the thing about GA4's funnel exploration: most marketers set up one funnel (usually checkout), check it twice, and then never look at it again. Which is a shame, because custom funnels are probably the most underused feature in GA4 that could actually change how you make decisions.

I've been building funnels in GA4 since the forced migration panic of 2023, and I've learned something important: the default templates everyone copies from Google's help docs are fine. But they're also generic enough to be almost useless for making actual business decisions.

The funnels that matter are the ones that answer specific questions you're actually asking. "Where are people dropping off?" is too vague. "Are mobile users abandoning cart at shipping or payment?" is actionable.

Let's build seven funnels that actually tell you something worth knowing.

Why Most GA4 Funnels Are Basically Decorative

Before we get into the templates, let's talk about why most funnels fail. (Yes, your funnels can fail. It's not just a visualization—it's supposed to drive decisions.)

The problem is usually one of three things:

You're tracking vanity metrics. A funnel that shows "90% of people who view a product page don't buy it" is technically data. It's also completely useless because of course they don't—most product page views are browsing, not buying intent.

Your steps are too broad. "Homepage → Product → Checkout → Purchase" tells you nothing about the twelve micro-decisions happening between product view and checkout click. That's where people actually leave.

You built it once and forgot about it. Funnels aren't set-it-and-forget-it. Your site changes. User behavior changes. Black Friday traffic behaves differently than February traffic. A funnel from March might be completely irrelevant by November.

The funnels below solve these problems by being specific, actionable, and tied to actual business questions.

Template 1: The "Actual Purchase Intent" Funnel

What it tracks:

1. Add to cart
2. Begin checkout
3. Add shipping info
4. Add payment info
5. Purchase

Why it matters: This skips the browsing phase entirely and only tracks people who've shown real intent. You're not measuring window shoppers—you're measuring people who wanted to buy but didn't.

The magic happens when you segment this by traffic source. Paid social might have great add-to-cart rates but terrible checkout completion. Organic might convert slower but complete more purchases. That's a budget allocation decision right there.

The detail everyone misses: Add a condition to step 1 that excludes cart additions in the last 30 seconds of a session. Those are usually accidental clicks or people using cart as a wishlist. You want genuine intent.

Template 2: The "Content Engagement to Conversion" Funnel

What it tracks:

1. Blog post view (specific category or topic)
2. View any product page
3. Add to cart
4. Purchase

Why it matters: Most content marketers have no idea if their blog actually drives revenue. They track page views and time on page and call it success. This funnel connects content to cash.

I built this for an e-commerce client selling outdoor gear. Turns out their "beginner hiking tips" content had a 23% higher conversion rate than "advanced mountaineering" content, even though the advanced stuff got more traffic. They shifted content budget accordingly. Revenue increased. Everyone was happy.

Pro tip: Create separate funnels for different content categories. Don't lump all blog traffic together—the patterns will be completely different.

Template 3: The "Mobile vs Desktop Reality Check" Funnel

What it tracks:

1. Session start
2. Product view
3. Add to cart
4. Begin checkout
5. Purchase

The twist: Build this twice—once filtered for mobile, once for desktop. Put them side by side.

Why it matters: Everyone knows mobile converts worse. What they don't know is where it converts worse. Is it at checkout? Or are mobile users not even making it to product pages?

In my experience, the drop-off point is usually not where you think. I've seen sites where mobile users add to cart at the same rate as desktop but abandon at shipping info because the form is a nightmare on small screens. That's a UX fix, not a traffic problem.

What you'll probably discover: Your mobile experience is worse than you think, but fixable. Usually it's one specific step that's broken, not the entire flow.

Template 4: The "Email Actually Works" Funnel

What it tracks:

1. Session start (source = email)
2. Click on promoted product/category
3. Add to cart
4. Purchase

Why it matters: Email marketing gets blamed for low ROI all the time. But is the email bad, or is the landing experience bad? This funnel separates email effectiveness from site effectiveness.

Create different versions for different email types: promotional, abandoned cart, newsletter, transactional. They'll perform wildly differently, and you need to know which ones are worth the effort.

Reality check moment: If people are opening emails and clicking through but not converting, your email isn't the problem. Your site is. Stop A/B testing subject lines and fix your landing pages.

Template 5: The "Free Shipping Threshold" Funnel

What it tracks:

1. Add to cart (cart value < free shipping threshold)
2. View cart
3. Add another item
4. Begin checkout (cart value > threshold)
5. Purchase

Why it matters: Free shipping thresholds are supposed to increase average order value. This funnel tells you if yours actually works or if it's just annoying people.

You'll need to set up a custom event for "cart value crosses threshold" if you haven't already. Worth the 30 minutes of dev time.

What good looks like: At least 30% of people below the threshold should add another item. If it's lower, your threshold might be set too high, or your "you're $X away from free shipping" messaging isn't prominent enough.

Template 6: The "Search Intent" Funnel

What it tracks:

1. Site search (capture the search term)
2. Click on search result
3. Add to cart
4. Purchase

Why it matters: People who search are high-intent users. If they're searching and not converting, either your search results are bad or you don't carry what they're looking for.

The real value is in the search terms. Export the funnel data and look at which searches convert and which ones don't. The non-converting searches are either product gaps or search algorithm failures.

Example from real life: A client's search data showed tons of searches for "waterproof" products that didn't convert. Turns out their search algorithm wasn't recognizing "waterproof" as a synonym for "water-resistant" (which is what they called it in product descriptions). One search config change, conversion rate up 18% for those queries.

Template 7: The "New vs Returning Customer" Funnel

What it tracks:

1. Session start
2. Product view
3. Add to cart
4. Begin checkout
5. Purchase

The twist: Build it twice—one filtered for new users, one for returning users.

Why it matters: New and returning customers behave completely differently. New customers need more convincing, more information, more trust signals. Returning customers need speed and simplicity.

If your returning customer funnel shows drop-off at checkout, you've probably added friction in the name of "optimization" that annoys your best customers. (Looking at you, mandatory account creation.)

What to do with this data: If new customer conversion is terrible but returning is great, you have a trust problem, not a product problem. Fix your first-impression elements: social proof, reviews, return policy visibility, security badges. If returning customer conversion is dropping, you're probably making it harder for people to buy from you than it used to be. Simplify.

Actually Using These Funnels (The Part Everyone Skips)

Building funnels is easy. Using them is where everyone falls apart.

Here's what actually works: Pick two funnels that matter most to your business goals right now. Not all seven—two. Check them weekly. Set up a 15-minute calendar reminder. Look for changes, not just absolute numbers.

Is the drop-off point moving? That's interesting. Did it change after your site update last week? That's actionable. Is mobile suddenly performing worse? Something broke.

The patterns matter more than the percentages. A 5% drop in step 3 completion might be noise. A 5% drop that's been consistent for three weeks is a problem.

Export your funnel data monthly. GA4's interface is fine for quick checks, but you want historical data you can compare. Throw it in a spreadsheet. Make a simple chart. You're looking for trends, and GA4's UI isn't great for that.

The Segments That Make These Funnels Actually Useful

Every funnel gets exponentially more valuable when you segment it. Here are the segments worth applying:

Traffic source: Paid vs organic vs direct vs email behave completely differently. A funnel without source segmentation is like weather data without location—technically information, but not actually useful.

Device category: We covered this with Template 3, but it applies to all funnels. Mobile isn't just "worse desktop." It's a different user context entirely.

Geography: If you ship internationally, conversion rates by country will vary wildly. Sometimes it's your shipping costs. Sometimes it's payment methods. Sometimes it's trust in international e-commerce. You can't fix what you can't see.

Time-based cohorts: New vs returning users (Template 7), but also first-time visitors vs people on their 5th visit. The journey is different.

What GA4 Funnels Can't Tell You (And What to Do About It)

Let's be honest about the limitations. GA4 funnels show you where people drop off. They don't tell you why.

You're seeing that 60% of mobile users abandon at checkout. Great. Is it because the form is broken? Because shipping costs are too high? Because they got distracted? GA4 doesn't know.

This is where you need qualitative data. Session recordings (Hotjar, Microsoft Clarity). User testing. Customer surveys. The funnel tells you where to look. The qualitative data tells you what you're looking at.

Practical approach: When a funnel shows a problem, watch 10-20 session recordings of people who dropped off at that step. You'll see the pattern. Usually it's obvious once you watch real people struggle with your site.

The Biggest Mistake Everyone Makes

Here it is: building funnels that match your org chart instead of user behavior.

Marketing wants to measure campaign effectiveness. Product wants to measure feature adoption. E-commerce wants to measure checkout flow. So you build three separate funnels that don't talk to each other, and nobody gets the full picture.

Users don't care about your org chart. They have one journey. Build funnels that follow that journey, then segment the data to answer different team's questions.

A user who clicked an email, read a blog post, viewed three products, and then purchased crossed four different team's territories. That's one funnel with multiple entry points, not four separate funnels.

Start Here

If you're looking at these seven templates and feeling overwhelmed, start with Template 1 (Actual Purchase Intent) and Template 3 (Mobile vs Desktop).

Those two will give you the most immediate, actionable insights for the least setup effort. Build them today. Check them weekly. Make one change based on what you see.

Then add the others as specific questions come up. "Is our content driving revenue?" → Template 2. "Is our email working?" → Template 4.

Funnels are answers to questions. Start with the questions that matter most to your business right now. The rest can wait.

And for the love of data, actually look at them more than once. The insight isn't in the setup—it's in the patterns you spot over time.