The Best A/B Testing Tools in 2026

The A/B testing market looks very different than it did two years ago. Google sunset Optimize and never replaced it. VWO and AB Tasty are merging into one company. OpenAI bought Statsig. Webflow absorbed Intellimize. If your shortlist is a few years old, it is out of date.

Here is the honest 2026 rundown of the tools worth knowing - what each is actually good at, how it does the statistics, and who should use it. We build and run experiments for a living (and we make our own testing app, more on that at the end), so this is the list we would hand a friend.

First, the tool that is gone

Google Optimize was the free on-ramp for a generation of marketers. It was shut down on September 30, 2023¹, with no direct replacement - Google now points people to third-party tools. If a blog post still recommends it, that post is stale. Anyone who relied on it has already had to move on, which is part of why the market reshuffled.

The enterprise platforms

Optimizely (Web Experimentation) is still the heavyweight. It is a full digital-experience platform with serious experimentation at its core. Its Stats Engine uses a sequential, "always-valid" frequentist method², which means it is designed to be peeking-safe - you can look at results as they come in without inflating false positives. It is powerful, it is expensive, and it is enterprise-only. If you have the traffic and the budget, it is hard to beat for rigor.

VWO and AB Tasty are best discussed together now, because in January 2026 their parent (Everstone) announced they are merging³ into a single company. Historically: VWO is a polished mid-market-to-enterprise suite (A/B, multivariate, plus heatmaps, recordings and surveys) using a Bayesian engine; AB Tasty is strong in European retail with experimentation plus AI personalization. Both are excellent. The caveat for 2026 is consolidation - roadmaps and branding are still settling, so buy with an eye on where the combined product is heading.

Kameleoon is the enterprise option for teams that care about server-side testing and data residency (it is French, GDPR-by-design, popular in regulated industries). Its standout is statistical flexibility: you can run frequentist, Bayesian, sequential or CUPED depending on the test. Notably, it has stayed independent through the merger wave - a selling point if vendor churn worries you.

The independent and developer-friendly picks

Convert.com (Convert Experiences) is the one agencies quietly love. It is privacy-first, transparent about pricing, and stays out of your data. It supports both frequentist and Bayesian stats, integrates cleanly with GA4 and the rest, and is meaningfully more affordable than the enterprise tier. In a market full of acquisitions, its independence is part of the pitch.

Statsig comes from the product-experimentation world (feature flags, metrics, warehouse-native analytics) and has a genuinely generous free tier, which makes it a favorite of engineering-led teams. The headline: OpenAI acquired Statsig in September 2025, with its founder becoming OpenAI's CTO of Applications⁴. Statsig says it continues as a standalone product - worth knowing, not necessarily a dealbreaker.

GrowthBook is the leading open-source option. You can self-host it for full data ownership, it is warehouse-native (bring your own data), and it does Bayesian and frequentist stats with CUPED and sample-ratio-mismatch checks built in. Its pricing is seat-based rather than traffic-based, so it scales cheaply for high-volume sites. If you have engineers and want control, start here.

Landing-page testers (a different category)

Unbounce and its peers (Leadpages, Instapage, Swipe Pages) are not site-wide experimentation platforms - they are landing-page builders with built-in A/B testing. Unbounce's "Smart Traffic" uses AI to auto-route visitors to the variant most likely to convert for them. If your testing is mostly about paid-traffic landing pages, this category is simpler than a full experimentation tool. If you need to test your actual store or app, it is not the right fit.

How to choose

• Match the statistics to your traffic. Lower-traffic sites benefit from sequential methods (peeking-safe) or CUPED (variance reduction) so tests resolve faster. Optimizely, Kameleoon and GrowthBook give you those levers.
• Frequentist vs Bayesian is not a war. Both are fine. For the full picture, see our research comparing the two frameworks. What matters is that the tool reports significance honestly and you do not stop the test early on a peek.
• Weigh vendor stability. With the giants consolidating, an independent (Convert, Kameleoon, GrowthBook) is a reasonable hedge.
• Size your tests before you buy. Many teams pick a tool, then discover they do not have the traffic to detect the lifts they care about. Run the numbers first with a free sample size calculator.

Where CazyAB fits

We built our own A/B testing app, CazyAB, because running experiments for ecommerce clients every day showed us where the existing tools get heavy. It is focused on what actually moves store revenue - clean experiment setup, revenue-aware reporting, and honest significance - without the enterprise overhead. CazyAB launches on July 6, 2026; you can get early access at ab.cazyweb.com. And whatever tool you run, our free A/B test significance calculator will check whether your result is real before you ship it.

If you would rather have a team plan, build and run the experiments for you, see how our CRO program works.