Free AB Testing Tools: What You Get and Where Limits Bite

Free AB testing tools are real, but each one limits something: the number of tested visitors, the features, or the time you can use it. The practical question is not whether a free option exists but whether its limit is one you will hit before you learn anything useful.

The four kinds of “free”

People searching for free AB testing tools usually find one of these, and they behave very differently.

Type	Example from public sources	What you give up
Permanent free tier	VWO Starter, listed as free up to 50,000 monthly tested visitors	Paid features; some 2026 teardowns report it withdrawn for new accounts
Time-limited trial	Most paid platforms	The clock; you must finish tests before it ends
Free plan for the platform, not the feature	BusinessMCP Free plan	The testing feature itself; its page says the CRO engine starts on Scale
Do it yourself	Your own code plus analytics	Your time and statistical safety nets

The VWO detail comes from BusinessMCP’s VWO comparison, which also notes that some 2026 teardowns report the free Starter plan being withdrawn for new accounts. Confirm on VWO’s site before building a plan around it.

Key takeaway: a free tier that caps visitors is not the real constraint for most small sites. Conversions are. If you get 20 sign-ups a month, no tool will give you a trustworthy answer in a few weeks.

What free tiers typically leave out

Read the plan page for these gaps before you install anything.

• Heatmaps and recordings. These are what tell you what to test. They are often sold as an add-on. BusinessMCP lists heatmaps and replay from its Growth plan at $79/mo on its session replay page, so its free plan does not include them.
• Advanced targeting. Splitting only mobile visitors or only a campaign is commonly a paid feature.
• Support and integrations. Free users rarely get hands-on help.
• Statistical guardrails. Some tools show a winner badge at any time. That invites the mistake described in AB testing mistakes.

A free do-it-yourself setup

If you have a developer or can edit your site, you can run a basic test at no software cost.

1. Pick one page and one goal, such as a form submission.
2. Randomly assign each visitor to A or B once, and keep them in that group on return visits.
3. Log the group and the goal event in the analytics you already have.
4. Compute the required sample size beforehand with a calculator such as Evan Miller’s sample size calculator.
5. Run until you reach that sample, then compare conversion rates with a two-proportion test.

This works, but you take on the risks a tool would manage: unequal splits, flicker, and the temptation to peek. For step 5, see the two-proportion z-test.

When a free tool is the right call

Free is sensible when you are learning how experimentation works, when your traffic is high enough that the visitor cap will not bind, or when the test is a one-off. It is a weak choice when you need to test often, need a record of past experiments, or lack the time to babysit a homemade setup.

For teams with a GitHub-hosted site, one paid alternative is worth knowing about as a benchmark. BusinessMCP includes A/B testing in its Scale plan at $199/mo, with flat month-to-month billing and no visual editor. That is not free, but it bundles analytics and replay, which can replace several tools. Whether it is a better deal than a free tier depends on whether you will use those extras.

Reading the fine print on visitor caps

A cap such as “50,000 monthly tested visitors” sounds generous, and for many sites it is. The fine print still matters in three ways.

First, find out what the tool counts. Some vendors count only visitors enrolled in an active experiment, others count every visitor on a page carrying the snippet. If you leave the snippet on the whole site, you may exhaust a free allowance on pages you are not even testing.

Second, check what happens at the cap. Some tools pause experiments, some stop collecting data, and some bill automatically. A paused test during a campaign spike wastes exactly the traffic you most wanted to use.

Third, remember that a high cap does not mean high power. Statistical power depends on conversions, not visits. A page with 30,000 monthly visitors and a 1% conversion rate produces around 300 conversions a month in total, split across variants. Detecting a small relative lift on that base takes many weeks, as the sample size guide shows.

Free versus paid, in numbers you can check

A fair comparison uses the figures vendors publish, not impressions. BusinessMCP’s comparison page lists Convert Experiences at $299/mo billed annually, Kameleoon Starter from $495/mo and its own Scale plan at $199/mo. It also lists Optimizely and AB Tasty as custom-priced, with third-party estimates in the tens of thousands per year. Set those against a free tier and the gap is obvious, but so is the gap in what you receive: paid plans generally add support, heatmaps, targeting and, in some cases, an assistant that proposes tests. Whether that is worth it depends on how often you will test. One test a quarter rarely justifies a subscription; a test every fortnight usually does.

A decision rule

Ask three questions. How many conversions per month does the page you want to test actually get? If it is under a few hundred, test larger changes or use before/after comparisons, labelled as weaker evidence. Do you need a visual editor? If yes, the free field narrows quickly. Can you commit to finishing a test before a trial expires? If not, avoid trials.

Our broader guide to the best AB testing tools covers paid options once you outgrow free ones, and AB test sample size shows how to tell whether your traffic is enough in the first place.

Bottom line. Use a free tier to learn, not to scale. Budget for the day the cap or the missing heatmaps start costing you more in lost learning than a paid plan would cost in cash.

Two practical habits make any free setup safer. Keep a simple experiment log with the hypothesis, the dates, the sample size you planned and the result, including the losers; free tools rarely keep that history for you, and a spreadsheet is enough. And write the decision rule before launch: what difference would make you ship B, and what would make you keep A. Tests with a rule written in advance are far less likely to end in an argument about which number to believe. If you later move to a paid platform, that log and those rules transfer with you, which is more than can be said for a vendor dashboard.

If you used Google Optimize before it ended and are hunting for a replacement, our guide to Google Optimize alternatives maps former users to current options. The full pricing and plan details referenced above are on BusinessMCP’s own site at https://businessmcp.com/pricing, so confirm them there.