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GA4 tells you 60% of users abandoned at checkout step 2. VWO Funnels tells you which 60% — and lets you click straight into recordings and design an A/B test for that specific step.
Who this is forTeams on VWO Growth+ with a multi-step conversion flow (checkout, signup, lead form, trial activation). If you're running paid traffic and your funnel conversion is below industry benchmark, step-by-step analysis is the cheapest way to find where the leak is.
What you'll need
Step 1
Insights → Funnels → Create Funnel. Each step is a URL or event match. 3-6 steps is the right range — fewer is uninteresting, more is noise.
In the left sidebar, click Insights → Funnels → Create Funnel.
Name the funnel: 'Checkout funnel — May 2026' or 'Trial signup funnel'. Specific names matter for filter discoverability later.
Add the first step: pick "URL Equals" (exact) or "URL Contains" (pattern). Step 1 is usually a top-of-funnel page like /pricing or /products/main.
Add subsequent steps in order. Example checkout funnel: /cart → /checkout → /checkout/shipping → /checkout/payment → /checkout/review → /thank-you. Example trial signup: /pricing → /signup → /signup/verify-email → /onboarding/step-1 → /dashboard.
Cap at 6 steps. Beyond that, drop-off rates per step get small and sample sizes per step get tiny — the chart stops being readable.
For SPAs with virtual page changes, use VWO Custom Conversions (event-based) as funnel steps instead of URLs. Fire vwo.event("track", "step_completed") from your app code at each milestone.
Step 2
Funnels analyze sessions within a date range. Default is last 7 days; widen to 30 days for slower funnels. Filter by source/device to compare segments.
Above the funnel chart, set the Date range. Last 7 days for high-traffic checkout funnels. Last 30 days for slower funnels (trial signup with email verification).
Apply filters to compare segments: Traffic source (google/cpc vs organic), Device (desktop vs mobile), Country (US vs everything), Visitor type (new vs returning).
Save the filtered view as a 'Funnel' so you can switch between segments quickly. Example saved funnels: 'Checkout — desktop', 'Checkout — mobile', 'Checkout — paid traffic only'.
The funnel chart updates live as you change filters. Watch how drop-off rates shift between segments — mobile drop-off at step 3 might be 70% while desktop is 30%, which is the entire CRO insight you need.
Cap saved funnel variants at 5-6. More than that is unmanageable for most teams.
Step 3
VWO shows session count + % drop-off per step. The biggest drop-off step isn't always the highest-leverage step — it's the biggest where users still have intent.
Funnel chart: each bar is a step. The number above is sessions entering that step. The % below is drop-off from the previous step.
First read: which step has the highest % drop-off? That's your headline finding.
Second read: which step has the highest absolute lost sessions × intent? A 50% drop at step 1 might be normal 'tire-kickers leaving.' A 30% drop at step 4 (200 → 140 sessions) is intent-loss where users had committed effort — and is therefore more recoverable.
Compare against a baseline: industry checkout funnels typically lose 20-40% per step. If your step-2 drop is 15%, you're winning there. If it's 60%, that's the problem step regardless of position.
Watch month-over-month: did a recent deploy move drop-off at any step? VWO's Funnel Trends view (Pro+) graphs this over time.
Step 4
Below each step's bar is a 'View Recordings of users who dropped off' link. This is where VWO Funnels earns its tier.
Click the bar for any step where drop-off is concerning. A panel opens with "View Recordings" of users who entered that step but didn't advance.
Click into 5 recordings. Watch each at 2x speed. The patterns are usually obvious within the first 2 recordings.
Common patterns at checkout step drop-offs: shipping cost shock (users see the total, scroll back, leave); confused form field (users click 3 times, can't figure out what's wrong, abandon); missing payment method (users scan for Apple Pay/PayPal, don't see it, leave).
Each pattern is an A/B test hypothesis. Write each down. Score by frequency (how many recordings show it) and effort to fix.
Pro workflow: combine Funnels + Form Analytics (next tutorial). For drop-off at form steps, Form Analytics shows which specific field users abandon at — recordings show why.
Step 5
The funnel chart looks one way for all users and another way per segment. Comparing segments reveals which audience needs which fix.
Duplicate your funnel: Funnels → click the funnel → Duplicate. Rename to "Checkout — mobile only". Apply Device = Mobile filter.
Compare side by side with the desktop version. Mobile drop-off at form steps is usually 2-3x desktop — different fix priorities.
Same exercise for paid vs organic traffic. Paid traffic often drops off at pricing more aggressively (they expected something different from the ad).
Same for new vs returning users. Returning users skip more steps; new users get stuck at unfamiliar UI.
After comparing 3-4 cohorts, you'll have 3-4 distinct test backlogs: 'mobile fixes', 'desktop fixes', 'paid-traffic fixes', 'new-user fixes'. Prioritize by spend × drop-off lift.
Step 6
Right-click any step in the funnel and select 'Create A/B Test on This Step.' VWO carries over the URL and segment filters automatically.
Once you've identified the drop-off step and the hypothesis (from recordings), turn it into a test immediately.
In the funnel chart, right-click the problem step → Create A/B Test on This Step. VWO pre-fills the test with the step's URL and any segment filters you had applied.
Design the variant addressing the recordings-confirmed friction. Example: recordings showed users abandoning at shipping cost reveal → variant shows free-shipping threshold prominently above cart total.
Set the primary goal as a deeper-funnel conversion (e.g., test on checkout step 2, but track goal as /thank-you reached). This ensures the variant lifts END-OF-FUNNEL conversion, not just step-2-to-step-3 progression.
Calculate sample size from the segment that enters this step. Sample size for a step-3 test = sessions reaching step 3, not total site sessions. Often this means longer test duration than expected.
Step 7
When you ship a fix targeting a specific step, the funnel chart should show drop-off at that step improve. If it doesn't, the fix didn't work.
Before shipping a fix, screenshot the current funnel chart and note the drop-off % at the target step. This is your baseline.
Ship the fix. Wait 7-14 days for new data to accumulate.
Open the funnel for the same date range as before but after the deploy date. Compare the drop-off % to the baseline.
If drop-off at the target step improved by 3-10% — fix worked. If unchanged — the fix didn't address the real problem. Watch recordings post-deploy to see what users are doing now.
Beware regression at adjacent steps: improving step 2 might push users into step 3 unprepared, where they drop off harder. The funnel TOTAL conversion is what matters, not any single step.
Common mistakes
Defining a 10-step funnel
What goes wrong: More steps = smaller sample per step = harder to read. A 10-step funnel where each step has 30 sessions is unreadable noise. Team spends 30 minutes/week staring at the chart and ships no fixes. Wasted $400-900/mo on Growth/Pro capacity not paying back.
How to avoid: Cap at 3-6 steps. Pick the steps that matter most. Sub-funnel additional steps separately if needed.
Reading the funnel without watching recordings
What goes wrong: Funnel shows 50% drop-off at step 3. Team assumes 'the form is too long' and ships a shortened form. Drop-off doesn't move because the real issue was a JavaScript error breaking the Submit button. Funnel chart alone misled the fix. Wasted 1-2 weeks of dev time + ~$3,000-8,000 in opportunity cost.
How to avoid: For every drop-off worth investigating, watch 5+ recordings of users who dropped at that step. The recording reveals the WHY; the funnel only shows the WHERE.
Comparing different time windows accidentally
What goes wrong: Funnel 'before fix' was last 7 days during a quiet week. Funnel 'after fix' was last 7 days during a Black Friday spike. The drop-off rate looks different but it's because traffic mix changed, not the fix. Team congratulates itself on a fix that didn't actually move the metric. ~$5,000-15,000 in continued lost conversions over the following quarter.
How to avoid: Hold the date range constant. Either compare same-period-last-year, or wait until you have at least 14 days post-deploy data to compare against the 14 days pre-deploy. Avoid event-driven traffic spikes in the comparison.
Including internal/bot traffic in the funnel
What goes wrong: VWO tracks all sessions by default. If your team browses checkout to QA the site, those sessions pollute the funnel. On low-traffic pages, 5 internal sessions/day can mask or invert real user behavior. Decisions get made on contaminated data — usually 1-2 misguided fixes per quarter at $2,000-6,000 each in wasted dev cycles.
How to avoid: Settings → IP Exclusion — add your office IP, home IPs, VPN IPs. Re-run the funnel after 7 days of clean data.
Not segmenting by device
What goes wrong: Combined desktop + mobile funnel shows 40% step-3 drop-off. Team 'fixes' the step on desktop. Mobile drop-off was actually 60% (the source of the average) and went unaddressed. Mobile conversion stays flat; the fix was on the wrong device. On a $30K/mo paid-traffic account with 60% mobile, ~$3,000-9,000/mo in mobile revenue uncaptured.
How to avoid: Always create a desktop-only and mobile-only version of each funnel. Compare side by side. Fix the worst-performing device first.
Stopping after one funnel iteration
What goes wrong: Team sets up the funnel, ships one fix, sees minor improvement, declares victory. Funnel chart sits unused for the next 6 months. The next 5 step-by-step optimizations that would have compounded into 30% conversion lift go unfound. On a $50K/mo ad-spend account, ~$15,000-30,000 in unrealized conversion lift over 6 months.
How to avoid: Treat Funnels as a quarterly recurring exercise. Pick the worst step. Ship a fix. Measure. Pick the next worst step. Repeat. Conversion lifts compound.
Recap
Done — what's next
How to set up a VWO A/B test the right way
Read the next tutorial
Hand it off
Funnels + Recordings + A/B tests together is VWO's highest-leverage workflow. A specialist running this loop on a $50K/mo ecom checkout typically finds 2-4 fixable drop-offs per quarter and ships fixes that compound into 10-25% conversion lift over 90 days. Match with a vetted CRO specialist from $14-16/hr — typical engagement $500-1,200/mo.
See specialist rates
VWO tracks sessions captured (limited by your plan's MTU allowance and IP exclusions). GA4 tracks all sessions firing the configured events. On Growth plan, VWO may sample 80% of GA4's session count — same funnel shape, slightly different absolute numbers. VWO's strength is the linked recordings + integrated test creation; GA4's strength is unsampled absolute counts.
Yes via Custom Conversions. Fire vwo.event("track", "step_completed") from your site at each conversion milestone, then build a funnel referencing those events instead of URLs. Required for SPAs where URL doesn't change between funnel steps.
At least 200 sessions through step 1 for directional patterns. 500-1,000 for confident comparisons across segments. Below 200, step-by-step drop-off rates swing wildly with small numbers and you'll chase noise.
Limited. You can screenshot the funnel chart and embed in a doc, but you can't hand a non-VWO user an interactive funnel. Pro+ has scheduled email digests — useful for sending weekly funnel snapshots to execs.
By default it tracks within a single session. To track multi-session funnels (visit pricing today, sign up next week), enable User Identification (Settings → Visitor Identification → User ID mode) and push a stable user ID from your site code. Then funnels can stitch sessions per user.
Yes by combining Funnels with Personalize. Create an audience segment like "Reached /checkout/payment but didn't complete in last 7 days." Then run a personalization (e.g., abandoned-cart discount banner) targeting that audience next time they visit. Most effective on returning-user funnels.
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A/B testing in VWO is 20% setup and 80% statistical discipline. Most teams skip the sample-size math, call winners early, and ship 'wins' that don't hold. This is the workflow that produces tests you can actually trust.
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Clarity is free and the install is famously easy — but the choices you make in the first 45 minutes (data masking, retention, project ownership) are hard to undo later. This walkthrough gets the configuration right the first time.