Experiments

Experiments let you run two versions of a form head-to-head and measure which one actually converts better — so you change your forms based on evidence, not opinion. Formtoro splits your storefront traffic between the two versions, tracks conversion and revenue for each, and tells you when the result is statistically trustworthy.

How a test worksCopy Anchor Link

Every experiment has two arms:

• Control — the form you already have. Its identity stays stable: embeds, integrations, and analytics keep pointing at it no matter how the test ends.
• Variant — the challenger. Either a duplicate of the control that you edit, or another published form you pick.

While the test runs, each visitor is assigned to one arm and always sees the same arm on every visit — assignment is deterministic per visitor, so nobody flip-flops between versions mid-test. You choose the traffic split when you create the test (50/50 by default). Both arms are always served to the control form's audience, so the two versions are compared against the same visitors.

A form can only be in one active experiment at a time, in either role.

Run your first experimentCopy Anchor Link

Open Experiments in the navigation and click New experiment. One modal walks you through it:

1. Pick a form to test. The picker lists your published forms — a form needs at least one saved version to qualify. Forms already in an active experiment appear disabled, labeled with the experiment they belong to.
2. Choose where the variant comes from.
   • Duplicate the control form (the default) — Formtoro clones the control as a new form. You then edit the copy in the builder to create the change you want to test.
   • Use an existing form — pick another published form as the challenger. If its audience differs from the control's, you'll see a heads-up: starting the test aligns the variant's audience to the control's.
3. Configure the test. Give it a name (pre-filled as "{form} — A/B Test") and set the traffic split slider — anywhere from 5% to 95% to the control, in 5% steps.

Click Create draft. This creates the experiment but does not start it — no traffic is split yet.

You land on the experiment's detail page. From here:

• Open either form (each arm card links straight into the builder) and make the change you want to test — a different headline, offer, image, or flow. Test one meaningful change at a time, or you won't know what caused the difference.
• When you're ready, click Start test. Starting publishes the latest saved version of both forms and begins splitting traffic. If one of the forms is turned off, a banner lists the blockers with a one-click Turn on form fix.

While the test runsCopy Anchor Link

• The Forms list shows who's in a test. Forms in an experiment carry an A/B Test pill plus a Control or Variant pill — click them to jump to the experiment.
• Audiences stay in sync. The variant's audience is locked in the builder while the test is active; audience changes you make on the control mirror to the variant automatically. This keeps the comparison fair.
• Leave the forms alone. You can still open either form in the builder, but changing a form mid-test muddies what the results mean. Make your edits before starting, or end the test and run a new one.
• Name and split are locked after start. You can edit the test's name and traffic split only while it's a draft — changing the split mid-flight would change the meaning of data you've already collected.
• Formtoro watches the test's health. If someone turns off one of the forms while the test runs, the experiment page shows a warning — one arm is getting no traffic and the results are being skewed — with a one-click Turn on form recovery.

You can Pause a running test at any time (traffic stops splitting; visitors see your forms as normal) and Resume it later.

Reading the resultsCopy Anchor Link

The experiment page shows the two arms side by side. By default it covers the whole test — from the moment you started it through to now, or through to the day it finished — so the significance verdict weighs every visitor the test has seen rather than an arbitrary recent slice. The date picker narrows that window if you want to look at a particular stretch; a range wider than the test is trimmed to the days the test actually ran, and the header always names the window you are looking at.

Under the page title you'll see when the test started and, once it's over, when it ended — the same dates the Experiments list shows.

Within that window, each arm card leads with two rates side by side:

• Opt-in rate is the headline number for each arm — submissions as a share of unique visitors who saw the form. This is the rate the test is judged on: the arm with the higher opt-in rate wears a Leading badge once both arms have traffic, and the significance banner is computed on it.
• Sub → conversion answers the next question — of the people this arm signed up, how many went on to buy? It's the share of signups (submissions that gave you an email or phone) with at least one attributed order — the same subscriber-grain definition as the Sub → conversion tile on the Analytics overview. A repeat buyer counts once. An arm can win on opt-in rate and lose here, which is exactly the trade-off you want to see before promoting a winner.
• Traffic — viewers, submissions, completions, and dismissals. Each counts people, not events: a shopper who reloads the form, or returns on another day or device, is one viewer. Submissions here means everyone who sent a step, which is not the same as the Forms tab's Subs — that counts only the people who gave you contact details. Where the two differ, read the arm cards as a measure of engagement.
• Revenue — revenue per visitor, attributed orders, and net revenue (after refunds), so you can see whether the "winner" actually makes more money.
• Pooled totals sum both arms — the experiment's overall footprint.

Above the cards, a banner tells you how much to trust what you're seeing:

• "Not enough data yet to call a winner" — the sample is still too small for the math to mean anything. A 100% opt-in rate on three visitors is noise, not signal. Keep the test running.
• "Not yet statistically significant" — there's data, but the gap between the arms could still be luck. Let it run longer.
• "Significant at 95% confidence" — the difference is real with 95% confidence, and the banner names which arm is winning.

Be patient. Most tests need hundreds of visitors per arm — often a week or two of traffic — before a trustworthy verdict emerges. Ending a test the moment one arm pulls ahead is the most common way to ship the wrong form. Significance is a nudge, not a gate: you can always declare a winner manually, but the banner tells you when the data has your back.

Ending a testCopy Anchor Link

From the experiment page's top bar:

• Declare winner — the decisive move. A modal shows both arms with their opt-in rates; the leading arm is pre-selected, but you pick. On confirm, traffic splitting stops, the winning version keeps serving your storefront, and the losing form is turned off — it stays in your forms list, so you can reuse it later or archive it to free up a form slot. If the variant won, its design is carried over to your original form — so every embed, integration, and report that pointed at your original form keeps working, now serving the winning version. If the data is still thin, the modal warns you before you commit. Declaring a winner ends the test permanently.
• End test — stop collecting data without picking a winner yet. The results stay available on the page.
• Cancel test — abandon the experiment. No changes are applied to either form.

An experiment's status moves through Draft → Running (with optional Paused detours) and ends as Completed, Promoted, or Discarded — always visible as a badge in the Experiments list. Drafts and running or paused tests sit under Active tests; finished ones move beneath them to Previous tests, each with the dates it started and ended, and stay there so you can revisit any test's results later.

Next stepsCopy Anchor Link

• Analytics & submissions — the metrics behind your experiments, for every form.
• Building forms — craft the variant you want to test.
• Audience filtering — who is eligible to see your forms.
• Luigi, your AI assistant — ask "How are my A/B experiments doing?" for a plain-language readout.