Why it isn't converting
How to fix low conversion rate: start at the drop
Changing the headline, the colors and the form all at once tells you nothing. Start with the one step where visitors stop, fix that step, and send the same visitors back.
How do I fix a low conversion rate?
Find the step where the most visitors leave, then fix that step before any other. A conversion rate is the share of visitors who finish one goal, so one weak step drags the whole number down, and editing an unrelated page changes nothing you can measure. Analytics shows the drop between steps but not why a visitor left at that step. A simulated test sends visitors through the same path and shows the exact screen where each one stopped, with a screenshot.
What this looks like in a report
“Three plans and none of them says what the cheapest one leaves out. I would have to start a trial just to find out if it sends invoices to clients. I will try the next tool.”
The fix. List what each plan includes in one line under its price. Move the Start free trial button below that list, not only to the top of the page.
An illustration. Run a test to see your own.See a real sample report
One weak step pulls the whole rate down
A conversion rate is a ratio, so it falls when one step is much weaker than the rest. A site can have a good landing page and a broken sign-up form, and the overall rate looks the same as a site with a weak headline. Owners usually rewrite the headline for a week, because it is the easiest thing to see. Meanwhile the sign-up form keeps losing the same people. Before you change anything, list the steps, count the visitors who reach each one, and find the largest drop between two neighboring steps. That drop is where to start.
- Visits to each step, for the same dates, from the first page to the finished goal
- A later step showing more visitors than the one before it, which points to a counting fault
- The one page where most visitors leave, viewed on a phone at its real width
- The first thing on that page a stranger cannot read in five seconds
- Whether the fix moved the stop point, or only changed a number on the dashboard
How it works
- 01
Write the path and count each step
List every page a buyer passes through, from the first visit to the finished goal. Pull the visitors who reached each step for the same dates. Wrong: one overall rate for the whole site. Right: one rate for each pair of neighboring steps.
- 02
Find the largest drop and check its count
Compare each step with the one before it and mark the biggest loss. If a step shows more visitors than the step before it, an event is firing twice or on the wrong page. Fix the count before you touch the page.
- 03
Change one thing and send the same visitors back
Change the single item you found, such as a button label or the number of form fields. Run the same task on the same path again and compare where the visitors stop. Keep the change only if they get further.
Count each step before you change a word
The first fix is measurement, and it is the one most owners skip. Take the path from the first visit to the goal and put a count on every step, using the same dates for each. A rate for the whole site hides which step is weak. A good headline can still sit above a sign-up button that fails on phones, and only the step counts show that. If a later step shows more visitors than the step before it, stop and fix the tracking first. Those counts are wrong, and every rate built on them is wrong too.
The headline gets rewritten because it is easy to edit
A headline, a hero image and a button color are the fastest things to edit, so they get edited first. A new headline only helps visitors who read it and keep going. If the sign-up form is where people stop, a new headline above it sends more visitors to the same form, and the form loses them in the same place. Ask which screen the visitors who leave are standing on, then edit that screen.
A stop point is better evidence than a drop in the report
Analytics says the drop is at the sign-up form. It does not say whether the visitor saw the form, got stuck on a password rule, or left because the form asked for a company size they did not have. A simulated visitor is sent through the same path and stops on a screen, with the field it was on and a screenshot. If three of five simulated visitors stop at the same password field, that is a different problem from three stopping at the price, even though both show up as one drop in the report. Write the fix from the stop point, then send the same visitors through again and see who gets further.
What you get with Mimiq
- 01
Run it by hand, or on every pull request
Paste a link and a task in the app and watch the visitors work. Or run them on every preview deploy: the GitHub Action comments on the pull request, any other CI can call the MCP endpoint, and your coding agent can run it too.
- 02
Bugs and usability problems in one report
The browser records errors and failed or slow requests on the step they happened. The visitors say where the wording or the steps confused them, and where they left.
- 03
Visitors that behave like your audience
Each visitor is a different profile with a reason to be there, matched to who the page is for, described by you, or built from your own customers.
- 04
A prompt to fix each problem
Every problem comes with a fix to paste into Cursor, Claude Code, Lovable or any coding agent, and one prompt hands over the top problems at once. Then send the same visitors through again.
- 05
Follow every visitor
See each visitor's whole path, step by step with screenshots, and what it was thinking at every step. Ask any visitor a question.
The browser records relevant JavaScript errors and failed or slow app requests encountered during the run, attached to the step where they occurred. The visitors are simulated: they find problems, they do not predict how many real people will convert.
Each new headline or price can move the drop to another step
A fix often moves the drop instead of removing it. A clearer headline sends more visitors to a pricing table that is hard to read on a phone. Send the same visitors through the path again after each change and see who gets further. If the path goes behind a login, give visitors a test account so they reach the screens after it. Check the pricing page on phones after every design change, since layout changes are where drops hide.
Starter
Try it on one launch
About 4 tests of 5 visitors
- Visitors on your landing page, signup and checkout
- Where they left and why, with a fix to copy for each problem
- Run it in the app or on every pull request
- Ask any visitor a question, included
- Test accounts and protected previews
Builder
Test every build
About 20 tests of 5 visitors
- Everything in Starter
- Credits refill each month, and what is left rolls over once
- Cancel anytime
Pro
Test every release, as a team
About 60 tests of 5 visitors
- Everything in Starter
- Credits refill each month, and what is left rolls over once
- Cancel anytime
Scale
Test at scale, every day
About 240 tests of 5 visitors
- Everything in Starter
- Credits refill each month, and what is left rolls over once
- Priority support
- Cancel anytime
Questions
What is a good conversion rate to aim for?
It depends on the offer, the traffic and what counts as a conversion, so no single figure fits every site. Compare your rate with your own earlier weeks and with each traffic source on its own. Mimiq does not give a target rate, and it does not predict how many real visitors sign up.
Can a simulated test show that my fix raised the rate?
No. A simulated visitor shows whether they reach the next step and where they stop, which is evidence for a fix, not a result. The rate moves only when real visitors meet the change, so read it in analytics for a few weeks afterward. Before you ship, run the same visitors again to confirm the stop point moved.
Should I fix the traffic or the page first?
Check the traffic first, because no page can convert a visitor who never wanted the product. Look at the source and the search or ad term behind the visits that leave straight away. If the traffic is right and the drop sits on a page, fix the page. Both questions can be answered from your analytics before any test runs.
What does a simulated test add that analytics does not?
Analytics counts visitors at each step. A simulated test runs a visitor through the same steps in a real browser and shows what they saw, clicked and typed, the screen where they stopped and a screenshot of it. It cannot tell you how many real people would make the same choice. Use both: the counts show where the loss is, and the test shows why.
Keep reading
Send visitors and see what breaks first.
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