Conversion rate optimization
Conversion rate optimization tools that find the leak first
Conversion rate optimization tools help you find why visitors do not buy or sign up, then test fixes. UserExplorer combines funnels, replay, heatmaps, form analytics and surveys, and its AI researcher ranks the problems by how many sessions and how much revenue they touch.
- Funnels show where visitors drop
- Replays, heatmaps and form analytics show why
- Surveys and AI interviews ask visitors directly
- AI researcher ranks issues with evidence sessions
Paths after /pricing, last 7 days
Sample dataOne in three leave from pricing. Open the 970 exit sessions in one click.
Research before testing
Most tests fail because the hypothesis was a guess
Conversion rate optimisation software is often bought as a testing tool, yet the quality of a test depends on the idea behind it. A button colour test chosen in a meeting rarely moves revenue. A test built on what hundreds of visitors struggled with usually has a much better chance.
UserExplorer is the research half of the CRO loop. It shows the exact step where visitors leave in a conversion funnel, the fields that stall them in form analytics and the clicks that go nowhere. You run the change with your own testing or release process and measure it on the same funnel.
The toolkit
Everything a CRO team usually buys separately
One snippet, one segment builder, one place to keep evidence for each hypothesis.
Funnels
Conversion and drop-off for any sequence of pages or events, split by traffic source, device and campaign.
Session replay
Watch the visits behind a drop-off, with idle time skipped and frustration moments marked.
Heatmaps
Click, move and scroll maps per page and device, so you see whether the offer is even seen.
Form analytics
Field level drop-off, hesitation time and refills on checkout, signup and lead forms.
Frustration signals
Rage clicks, dead clicks and error clicks counted per page and element.
Voice of the visitor
Exit surveys and short AI interviews that ask hesitant visitors what stopped them.
Prioritise
A ranked list of problems instead of a pile of recordings
Watching replays one by one does not scale past a few dozen sessions. On paid plans the AI researcher reads thousands of them, groups the recurring problems and ranks each group by the number of affected sessions and, when you send purchase data, the revenue at stake.
Every item on the list links to the replays, heatmap areas and survey answers that support it. Take the list into your planning meeting and the discussion moves from opinions to evidence. Read how it works on AI user research.
AI researcher
Read 1,284 sessions, sample dataYou asked
Why do users drop off at signup?
31% abandon signup at step 3 because phone verification fails on mobile.
- SMS code not delivered on 2 of 3 carriers in the US
- Users tap Send code 4 times on average, then leave
- Desktop completes the same step at 88%
Evidence sessions
Hypothetical worked example
What one fixed checkout problem could be worth
This is an illustrative example with made up numbers, not a result from any customer. Imagine a store with 200,000 visits a month, a 2.0 percent conversion rate and an average order of 80 dollars. That is 4,000 orders and 320,000 dollars of monthly revenue.
Suppose replays and form analytics show that a postcode field rejects valid formats on mobile, and fixing it lifts conversion from 2.0 to 2.1 percent. The store would get about 200 extra orders, or roughly 16,000 dollars a month. The Growth plan costs 499 dollars a month, or 249 dollars a month billed yearly.
Your numbers will differ, and some fixes change nothing. The point of the example is the method: size each problem by sessions and revenue before you spend design and engineering time on it, and check the outcome on the same funnel afterwards. Plan prices are on the pricing page.
The loop
A CRO cycle that starts with evidence
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Step 1
Measure the funnel
Define the path to purchase or signup and find the step with the largest loss.
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Step 2
Find the cause
Open replays, heatmaps and form data for that step, or ask the AI researcher what visitors there have in common.
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Step 3
Ask visitors
Add an exit survey or AI interview on the step to hear the reason in their words.
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Step 4
Ship and compare
Release the fix or test it, then compare the same funnel and segment before and after.
FAQ
Questions teams ask before they start
What are conversion rate optimization tools?
They are tools that help you understand and improve the share of visitors who complete a goal, such as a purchase or signup. They usually include analytics, funnels, session replay, heatmaps, form analytics, surveys and A/B testing.
Does UserExplorer run A/B tests?
No. UserExplorer focuses on finding and sizing problems and measuring the outcome on funnels. You run tests with your existing testing tool or release process and compare segments in UserExplorer.
How does the AI researcher prioritise issues?
It groups sessions that show the same problem, counts how many sessions and visitors each problem touches and, when purchase data is connected, estimates the revenue involved. Each item links to its evidence.
Is it suitable for ecommerce and SaaS?
Yes. Ecommerce teams use it on product pages, cart and checkout. SaaS teams use it on pricing, signup and onboarding, where it pairs with product analytics.
Which plan should a CRO team start with?
Startup covers replay, heatmaps, funnels and form analytics with 50 AI analyses. Growth adds asking the AI researcher, surveys and AI interviews with 400 AI analyses. Every plan has self serve checkout.
Can I try it before paying for a plan?
After signup you get a one time demo with 500 sessions or 7 days, whichever comes first, without AI features. You can also see a sample AI report on our demo data on the homepage.
Fix the leak that costs the most
See where visitors drop, why they drop and which problem to fix first, with evidence your team can check.