Plug Conversion Leaks at Speed Using VWO Copilot, An AI-Powered CRO Assistant

You see the leaks on your website.

The drop-offs after the second scroll. The form that never gets submitted. The product page that gets visits but no clicks. 

You know where users are slipping away—but by the time your team finishes digging through the data, you’ve already lost potential customers.

Back then, the big rush came during Black Friday, holiday sales, or campaign launches. That’s when you’d move fast, patch the leaks, and make the most of the spike. 

Now, that urgency is constant. 

User behavior changes daily. Campaigns run 24 / 7.  Even small friction can cost you.

The old way of doing CRO just can’t keep up. Analysis takes too long. Fixes come too late.

That’s where generative AI changes the game by understanding context, generating answers on demand, and automating repeatable tasks. 

This blog shows how VWO Copilot, your AI-powered optimization assistant, helps you fix conversion leaks faster in a world where speed and context are everything.

The ‘new’ leaky bucket problem

Leaks are any points in the funnel where users abandon, disengage, or fail to convert. They’re often hidden and can occur at every stage—from landing pages to checkout.

Generally, identifying these leaks requires jumping between multiple tools: heatmaps, session recordings, form analytics, surveys. Insights have to be manually stitched together, making the process slow and reactive. And by the time patterns are clear, the opportunity has often passed.

CRO is effective, but it entails a lot of steps. From data gathering to hypothesis formation and test execution, the process is thorough—but often not fast. 

Customer journeys are fragmented. Attention spans are short. The window to optimize is shrinking everyday. Waiting weeks to launch a test means missed revenue and lost growth.

This is exactly the challenge that VWO Copilot has been built to solve. It doesn’t replace the fundamentals of CRO—it enhances them with speed, clarity, and sharper focus. In other words, Copilot condenses what used to take weeks into just a few prompts and delivers actionable results in minutes.

How VWO Copilot makes leak-fixing smarter and faster

VWO Copilot is an AI-powered assistant designed to sharpen business decision-making and dramatically reduce the lag between observation and optimization. Below is how Copilot helps you detect, prioritize, and plug leaks faster and more effectively:

AI-automated behavioral analysis

Diagnose leaks faster by cutting through data clutter.

When you suspect a drop-off on a key page—say, the pricing or checkout step—the traditional approach involves scanning multiple dashboards: heatmaps, scrollmaps, rage clicks, funnel views, session recordings. Each tells a different part of the story, and pulling them together into one clear insight takes time. Plus, digging through endless data and recordings takes up valuable time—which is better spent on making strategic decisions.

Copilot solves this by bringing it all together. It can scan heatmaps and session recordings as separate sources if you want to explore specific friction points in detail—like scroll drop-offs or hesitation around a form.

Or, it can consolidate insights from both sources to surface broader behavioral patterns and potential optimization opportunities. 

Either way, Copilot returns a clear, human-readable summary of what’s going wrong and provides actionable recommendations to fix the leak—faster than manual analysis ever could.

AI-generated surveys and AI-summarized survey reports

Sometimes, it makes more sense to hear directly from users instead of relying solely on interpreting heatmaps or session recordings—especially when you’re unsure why a leak is happening. Their feedback can reveal what the data can’t.

But creating the right survey, summarizing results, and turning them into action can take days or even weeks.

Copilot simplifies the entire loop. You can ask it to generate questions based on the goal you want your survey to achieve. Let’s say your goal is to understand why users abandon sign-up after reading the feature list on your media website. You can keep iterating until the questions meet your expectations.

Further, Copilot summarizes survey responses, highlights key takeaways, and even recommends what you can test to address the issues users pointed out.

AI-generated testing ideas

When leaks appear like users bouncing from your checkout page, you can’t afford to wait weeks to brainstorm what to test next. That’s also where Copilot steps in.

Just enter the URL of your leaking page—say, the cart or checkout page—and specify your goal, like “reduce drop-offs.” Copilot instantly returns personalized test ideas tailored to that leak. These could include simplifying form fields, tweaking CTA placement, or adding trust signals like secure payment badges.

Instead of staring at a blank document or repeating old tests, you get AI-generated ideas grounded in behavioral science and aligned with your conversion goals. It removes the friction in ideation, helping you move from insight to experiment faster so fewer users fall through the cracks.

AI-automated variation creation

Once you identify what needs to be tested or fixed, say, moving a CTA above the fold or changing headline copy, you often need to loop in design or dev teams. That creates delays. But how do you remove design and dev bottlenecks?

With Copilot, just type a prompt like “Create a variation with shorter copy and highlight the free trial button,” and the editor builds the variation automatically.

No code. No handoffs. No wait.

This is just one example. You could try “A version with a minimalist layout and larger product image” or “A variation with prominent testimonials .”

With Copilot, your variation ideas are almost endless and you can explore them aplenty without touching code.

AI-powered segment generation

Not every drop-off should alarm you. Some exits are natural—users who bounce within seconds, click accidentally, or aren’t ready to convert. But others leave behind signals you shouldn’t ignore: they’ve engaged, clicked, even added to cart—but didn’t convert. 

Once your test has run, Copilot helps you dig deeper, not just into overall metrics but into how each segment reacted to the experiences. Just enter a prompt like, “Show me users aged 25 to 34 from Berlin who came from our Facebook Ads campaign and showed uplift on the variation.” Copilot identifies the exact segment and how it behaved in the test, so you know what to target in your next test and personalization campaign.

AI can handle much of the manual work required for insights, allowing us to focus on tasks that AI can’t do, like understanding and translating data into new customer experiences. I don’t think we are too far off from a tool like this, where much of the heavy lifting during the research phase is cut down, allowing the marketer to focus on strategy and implementation.
Ilan Hurwitz, Founder at Clever Conversions. Source. 

Using AI to prevent conversion leaks across industries

The structure of user funnels varies widely across industries. Understanding these patterns is the first step to fixing leaks. Let’s look at how VWO Copilot can intelligently adapt to each of these paths and help teams stop revenue loss where it matters most.

a) SaaS

Let’s consider a SaaS analytics platform where users are landing on the homepage, browsing to the pricing page, but dropping off before clicking on any of the plans. You’ve identified the leak in the funnel—but now need to understand why it’s happening.

Homepage → Pricing Page → ❌ Clicks on Plans (Drop-off)

Copilot pulls together insights from heatmaps, scrollmaps, and rage click data for the pricing page and delivers a clear summary: most users don’t scroll beyond the first fold, and many repeatedly hover over the “Enterprise” tier without clicking—suggesting hesitation or confusion.

It also reviews session recordings and flags a common pattern—users pause at the comparison table, then exit. No need to watch hours of footage!

Let’s say your goal is to understand why users drop off from the pricing page without clicking on a plan. Copilot generates a survey tailored to your goal—understanding why users drop off without selecting a plan. The responses echo what the behavior data shows: users are unsure about what’s included in each tier, want more clarity on ROI, and expect social proof before committing.

You can now ask Copilot to create a variation for testing on the pricing page. For example, you might prompt it to display text alternatives for pricing plans, add testimonials, or enlarge the CTA button”

Or, simply provide the pricing page URL and a goal, say, reducing bounce from the pricing page and increasing plan signups, and Copilot will generate test ideas tailored to that objective.

If you want to test these changes on a specific audience, Copilot can generate the segment for you. Just describe it: for instance, “new users from Los Angeles using Google Chrome.” 

With that one prompt, Copilot builds the logic, defines the segment, and gets you ready to launch a personalized experiment, without needing to dig through filters or manually configure segment rules.

b) Retail / eCommerce

Suppose a lifestyle eCommerce brand notices that users are viewing product pages, adding items to cart, but abandoning at the final checkout stage. The team suspects it’s related to shipping friction, but wants to validate that quickly.

Homepage → Product Page Views → Add to Cart → ❌ Checkout Abandonment (Drop-off at Shipping Step)

Copilot scans heatmaps and session recordings to pinpoint exactly where users experience friction. It shows that:

• Most drop-offs occur right after the shipping cost is revealed.
  
• Rage clicks cluster around the shipping method dropdown.

Now, you’ve got the insights, but you’re thinking — wouldn’t it be even better if the test ideas were backed by solid scientific principles?

Just enter the checkout page URL into Copilot, and it will instantly generate personalized testing ideas based on your optimization goals, backed by scientific principles. For example, if you want to reduce international cart drop-offs, Copilot might suggest:

• Highlighting free shipping thresholds early in the flow
  
• Adding delivery date near the shipping options
  
• Displaying reassurance badges like “100% secure checkout” near the CTA

To accelerate the process further, you can prompt Copilot to generate a variation by adding estimated delivery dates next to shipping options, highlight free shipping at the top, and place a ‘100% secure checkout’ badge near the payment button.

AI will likely make everything more efficient. We have to wait and see how far this will go. I hope that AI can help us draw better learnings from many experiments combined so we make better products for happier and healthier lives. Also, personalization (like recommenders) might improve due to AI.

Rube de Boer, Lead Conversion Manager at Online Dialogue. Source. 

c) Hospitality

Take a travel booking platform. Users search for hotels, click on listings, but exit without initiating a reservation. The data shows a pattern, but it’s buried in too many dashboards.

Hotel Search → Hotel Listings Clicked → ❌ No Booking Initiated (Drop-off before Reservation Start)

Copilot will pull insights from recordings and scroll maps to highlight friction—like refund terms buried in tabs or CTAs positioned too low.

Want targeted ideas to improve conversions? Ask Copilot for test ideas around reducing drop-offs before bookings, making cancellation policies more visible, boosting trust through reassurance signals, or driving urgency with limited-time offers on hotel listings.

You can even skip to implementation with a prompt like: “Create a variation where the refund policy is visible upfront and the booking CTA is more prominent and urgency-driven.”

Next, prompt: “Create a segment of mobile users from New York who viewed hotel listings but didn’t start booking.” Copilot will use that segment logic to help you narrow down testing only to users who match this behavior.

Or let’s say you didn’t set pre-test segmentation. Copilot still doesn’t stop at surface-level results. It quickly analyzes your reports and highlights monetizable segments that showed strong engagement on either the control or the variation.

For example, it might identify a group of highly engaged users from Boston who clicked a promo banner for local discounts, or a segment of millennial travelers who converted more frequently on the control layout. These insights help tailor follow-up messaging or regional campaigns with higher relevance.

Manually spotting these patterns can be time-consuming, but Copilot simplifies the process and uncovers fresh opportunities for deeper segmentation, follow-up personalization, or new test ideas.

In the near future, we’ll be able to unify all our research and experimentation programs, moving beyond the constraints of a website by integrating it with AI that personalizes experiences based on user input. You can actually prompt it—I’ve been experimenting across different areas, and it’s exciting. I think many companies will soon ask themselves, ‘Do we hire a CRO agency or consultant?’ and instead just say, ‘Hey ChatGPT, here’s my URL—what’s going on?’ That shift is already happening.

Jim Martin, Founder & Managing Director at Align Digital. Source. 

Conclusion

Surprised by what Copilot can already do? You’re not alone. But soon, this level of intelligence will be the new norm.

When you’re not bogged down by dashboards, filters, and formatting tests, you finally get the space to think big and move fast. 

AI won’t replace the CRO mindset—it simply clears the runway, giving your team the freedom to ask sharper questions and make smarter bets.

Take a free trial, explore everything we’ve outlined, and decide for yourself.