# Best A/B testing tools compared by type, price and statistics Page: https://alidemirbas.com.tr/en/blog/best-ab-testing-tools 2026-11-01 · A/B Testing · Ali Demirbaş Compare the best A/B testing tools by type, free plan, price and statistics engine, including 2026 changes such as Wingify and Datadog Experiments. There is no single best A/B testing tool. The right one depends on where your test runs (a web page, product code or a mobile app) and how much traffic you have. It also depends on who will build the variations and how much you can spend. This guide to the best A/B testing tools sorts the main options into four types. It compares their free options, prices and statistics engines using each vendor's own pages, and gives you a short way to decide. Facts were checked on November 1, 2026. Vendors change plans often, so confirm prices before you sign. ## Which A/B testing tool is best? The best A/B testing tool is the one that runs your test in the place where the change happens. It also reports the metric you decide on. A marketing team changing headlines and forms on a website needs a visual editor. A product team testing a new onboarding step in code needs feature flags and SDKs. A team whose metrics already live in a data warehouse may want warehouse-native analysis. A mobile team may already have a free option in its app stack. The ranking lists reviewed for this guide mostly skip this step and order tools by features. As a result, two lists can name a different winner for the same reader. Start from the type of test, then compare tools within that type. ## Four types of A/B testing tools A/B testing tools differ mainly in where the variation is built and served. ### Visual editors for marketing and CRO teams A visual editor lets you change a live page in the browser and launch the change as a variation. You add the vendor's script to your site once, then build tests without editing the site's code. Wingify (the merged VWO and AB Tasty), Optimizely, Convert, Kameleoon and Adobe Target all document a visual or graphic editor. These tools suit landing pages, product pages, [checkout steps](https://alidemirbas.com.tr/en/lab/ab-test-library/tests/one-page-vs-multi-step-checkout-ab-test) and forms. ### Feature flag platforms for product and engineering Feature flag platforms run the test inside your application, which is why product teams and engineers use them. Developers wrap a change in a flag, and the platform decides which users see it. This works for anything you can put behind a flag: pricing logic, recommendation rules, onboarding flows, server responses. GrowthBook, PostHog, Statsig, Amplitude Experiment and Optimizely's feature experimentation product work this way. Several of these also offer a lighter visual editor for web pages. ### Warehouse-native analysis A warehouse-native tool reads exposure and event data from your own warehouse, such as BigQuery or Snowflake, and runs the statistics there. You keep one source of truth for metrics instead of sending events to a vendor. GrowthBook describes itself as warehouse-native. Datadog Experiments, the product Eppo became after Datadog acquired it in 2025, is built on this model. Optimizely offers warehouse-native analytics, and Statsig lists a warehouse-native deployment on its Enterprise plan. ### Testing inside mobile apps Mobile apps need an SDK in the app build. Firebase A/B Testing runs experiments through Remote Config, Cloud Messaging and In-App Messaging and is free to use. Wingify, Kameleoon, Convert and Adobe Target also document iOS and Android SDKs. ## The tools compared The table compares the tools on the points that change a buying decision. These are what type of tool it is, whether you can start free, how pricing works and which statistics it uses. Every cell comes from the vendor's own pricing page or documentation. *Source: each vendor’s pricing page and documentation, checked November 1, 2026.* | Tool | Type | Free option | Pricing | Statistics | | --- | --- | --- | --- | --- | | Wingify (VWO, AB Tasty) | Visual editor, server-side, mobile | 30-day trial, no free plan | Custom quote by monthly active users | Bayesian by default, frequentist optional | | Optimizely | Visual editor, feature flags, warehouse | Free feature flagging, one experiment at a time | Custom quote | Sequential Stats Engine, CUPED | | Convert | Visual editor, full-stack | 15-day trial | From $299/month billed yearly | Frequentist, sequential, Bayesian | | Kameleoon | Visual editor, feature flags | 30-day trial | From $495/month (PBX Starter) | Frequentist, sequential, Bayesian | | Adobe Target | Visual editor, server-side, mobile | No public trial found | Sold through Adobe sales | Welch's t-test, Bayesian for conversion goals | | GrowthBook | Feature flags, warehouse-native, open source | Free cloud plan and free self-hosting | Pro $40 per seat/month | Bayesian by default, frequentist, CUPED | | PostHog | Feature flags, no-code web editor | 1M flag requests/month free | Usage-based after that | Bayesian by default, frequentist, CUPED | | Statsig | Feature flags, analytics, warehouse | 2M events/month free | Pro $150/month | Frequentist, sequential, Bayesian, CUPED | | Amplitude Experiment | Visual web editor, feature flags | Free plan, A/B/n testing not included | Custom on Growth and Enterprise | Sequential (mSPRT) and t-tests | | Firebase A/B Testing | Mobile apps | No cost | Remote Config above the free quota | Frequentist, one-tailed | | Datadog Experiments (Eppo) | Warehouse-native, feature flags | None shown | $450 per experiment/month billed yearly | Frequentist, sequential, Bayesian, CUPED | Two patterns stand out. Tools built for marketing teams rarely publish prices, while tools built for developers usually do and start free. And almost every tool now offers [more than one statistics method](https://alidemirbas.com.tr/en/blog/statistical-significance-ab-testing), so the engine alone rarely decides between two shortlisted tools. Three changes in 2026 make many older lists out of date. VWO and AB Tasty merged and now operate under the [Wingify brand](https://wingify.com/blog/inside-wingify-digital-experience-optimization/), with both old domains forwarding to wingify.com. Statsig agreed to join OpenAI in September 2025, and its blog states that since May 5, 2026 the product and customers are part of Amplitude. Eppo's homepage now reads "Eppo is now Datadog Experiments". ## A/B testing tools reviewed Here is what each tool offers, what it costs and which statistics it uses, based on its own website and documentation. ### Wingify (VWO and AB Tasty) ![Wingify logo above an A/B test report from wingify.com comparing a control and two checkout flows](https://cdn.sanity.io/images/ghdm9112/production/9b65b085eea80a7fdab627c9ea44fe55231054c4-2400x1400.avif) *Image: wingify.com* Wingify is the brand VWO and AB Tasty share since their 2026 merger. It covers visual web testing, server-side tests and mobile SDKs. There is no free plan, only a 30-day trial, and prices are quoted by monthly active users. Reports use Bayesian statistics by default with frequentist analysis as an option, and a GA4 integration is documented. ### Optimizely ![Optimizely logo above a feature flag rollout screen from optimizely.com with per-channel percentages](https://cdn.sanity.io/images/ghdm9112/production/2f452600210a08e553509d32ef2918fbf4afaaf6-2400x1542.avif) *Image: optimizely.com* Optimizely offers a visual editor for web experiments, Feature Experimentation with SDKs for product teams, and warehouse-native analytics. Its free feature flagging runs one experiment at a time, and paid plans are quoted by sales. The Stats Engine uses sequential testing, and CUPED (Controlled-experiment Using Pre-Experiment Data) is available for variance reduction. ### Convert ![Convert logo above an A/B test report from convert.com with the segment filter open](https://cdn.sanity.io/images/ghdm9112/production/c83bd2c58686fcde7032002830997d208fb6bb87-2400x1025.avif) *Image: convert.com* Convert Experiences combines a visual editor with full-stack SDKs, including Android and iOS. The Growth plan is $299 a month billed yearly ($399 month to month) for 100,000 tested users, and there is a 15-day trial. You can choose frequentist, sequential or Bayesian statistics. ### Kameleoon ![Kameleoon logo above its visual editor from kameleoon.com comparing the original and a variation](https://cdn.sanity.io/images/ghdm9112/production/1176cebc99b2861db4be7571603755bee82e5064-2400x1530.avif) *Image: kameleoon.com* Kameleoon pairs a graphic editor with feature flags and more than 12 SDKs. PBX Starter starts at $495 a month for up to 10 experiments and 50,000 visitors, and there is a 30-day trial. Frequentist, sequential and Bayesian methods are available, and CUPED works only with the frequentist method. ### Adobe Target ![Adobe logo and Adobe Target Visual Experience Composer with four experiences, from Experience League](https://cdn.sanity.io/images/ghdm9112/production/5da929e75de407478e2b0f3e5eda88b5c0ab3c91-2400x1572.avif) *Image: experienceleague.adobe.com* Adobe Target offers the Visual Experience Composer, server-side SDKs and a mobile extension. It is sold through Adobe's sales team, and no public trial was found. A/B results use Welch's t-test, with a Bayesian option for conversion goals. ### GrowthBook ![GrowthBook logo above an experiment results screen with goal, secondary and guardrail metrics](https://cdn.sanity.io/images/ghdm9112/production/dac6ae136da58b0890990ad0548928a7a7a11b8f-2400x1449.avif) *Image: growthbook.io* GrowthBook is open source and warehouse-native, so it reads results from your own warehouse. Self-hosting is free, the cloud Starter plan is free for three users, and Pro costs $40 per seat each month. Statistics are Bayesian by default, with frequentist, sequential and CUPED options. GA4 data can be analyzed through the BigQuery export. ### PostHog ![PostHog logo above an experiment results table from posthog.com with control and two test variants](https://cdn.sanity.io/images/ghdm9112/production/1c9f3e49bf1bd732b8d85e8306731232e7dc7b9f-2400x1391.avif) *Image: posthog.com* PostHog runs experiments on its feature flags and adds a no-code toolbar for web changes. The first 1 million flag requests each month are free, then pricing starts at $0.0001 per request. Bayesian is the default, with frequentist, sequential and CUPED options. ### Statsig ![Statsig logo above an experiment scorecard from the Statsig docs with metric deltas and a p-value](https://cdn.sanity.io/images/ghdm9112/production/ee18c16ab75e30585bc48428a26a71cc825a15e0-2400x1376.avif) *Image: statsig.com* Statsig combines feature flags, experiments and product analytics. The free Developer plan covers 2 million events a month, and Pro is $150 a month with 5 million events. It offers frequentist, sequential and Bayesian methods and applies CUPED automatically. Statsig agreed to join OpenAI in 2025, and its blog says the product has been part of Amplitude since May 5, 2026. ### Amplitude Experiment ![Amplitude logo above a website experiment card comparing the current experience and a variant](https://cdn.sanity.io/images/ghdm9112/production/ac5fb219193655ceaadb114e56537e2e028939cb-2400x1665.avif) *Image: amplitude.com* Amplitude Experiment adds feature flags and a visual web editor to Amplitude's analytics. The free plan includes flags but not A/B/n testing, and allows one active web experiment. Growth and Enterprise plans are quoted. Analysis uses sequential testing (mSPRT) and t-tests. ### Firebase A/B Testing ![Firebase logo above an A/B test results screen in the Firebase console, from the Firebase blog](https://cdn.sanity.io/images/ghdm9112/production/6e7c6aaed980e01091468854258eccd8629436f5-2400x1515.avif) *Image: firebase.blog* Firebase A/B Testing runs experiments in mobile apps through Remote Config, Cloud Messaging and In-App Messaging. It costs nothing to use. Results are frequentist and one-tailed, and Google Analytics events serve as experiment goals. ### Datadog Experiments (formerly Eppo) ![Datadog logo above an Experiments results page from datadoghq.com with control and treatment metrics](https://cdn.sanity.io/images/ghdm9112/production/80fcabb6c6b03c7f1af1c373dceca087c92f492f-2400x1665.avif) *Image: datadoghq.com* Datadog acquired Eppo in 2025, and the product is now Datadog Experiments. It is warehouse-native and includes feature flags. Datadog's price list shows $450 per experiment each month on yearly billing, and no free tier is shown. It supports frequentist, sequential and Bayesian analysis with CUPED. ## Free plans and pricing ### What is the best free A/B testing tool? The best free A/B testing tool for a website is usually GrowthBook or PostHog, and for a mobile app it is Firebase A/B Testing. GrowthBook's open-source version is free to self-host with unlimited traffic, and its cloud Starter plan is free for up to three users. PostHog includes the first 1 million feature flag requests each month, and experiments are billed as flag requests. Firebase lists A/B Testing as no-cost on both of its plans. Free plans have limits that matter for testing. Amplitude's free plan includes feature flags but not A/B/n testing, and allows one active web experiment. Optimizely's free feature flagging runs one concurrent experiment. Statsig's free Developer plan covers 2 million events a month. Marketing-focused tools such as Wingify, Convert and Kameleoon offer a time-limited trial instead of a free plan. ### How much do A/B testing tools cost? A/B testing tool pricing ranges from free plans to custom enterprise contracts, and the pricing unit differs by tool. Compare the unit first, because a cheap plan on one unit can be expensive on another. Some tools charge by tested users or visitors. Convert's Growth plan is $299 a month billed yearly ($399 month to month) for 100,000 tested users a month. Kameleoon's PBX Starter starts at $495 a month for up to 10 experiments and 50,000 visitors. Wingify prices each quote on monthly active users and publishes no fixed plans. Developer-focused tools usually charge by usage or seat. Statsig's Pro plan is $150 a month with 5 million events, then $0.05 per 1,000 events. PostHog charges from $0.0001 per flag request above the free million. GrowthBook Pro costs $40 per seat each month. Datadog's price list shows Experiments at $450 per experiment launched each month on yearly billing. Optimizely and Adobe Target sell through their sales teams and publish no list price. Ask any vendor what happens when your traffic grows past the plan, because that is where the price changes most. ## How do I choose an A/B testing tool? If you are working out how to choose an A/B testing tool, answer a few questions in order. Each answer removes part of the market. 1. **Where the change happens:** Website layout and copy point to a visual editor. Product logic points to feature flags. App screens point to a mobile SDK. 2. **Who builds the variations:** Marketers working alone need a visual editor. Teams with developers can use SDKs and flags. 3. **Where your metrics live:** If revenue and retention already sit in a warehouse, a warehouse-native tool avoids a second copy of the numbers. 4. **Traffic on the test page:** Estimate the sample you need with an [A/B test sample size calculator](https://alidemirbas.com.tr/en/calculators/sample-size-calculator) before you pay for capacity. 5. **What the plan includes:** Check which statistics methods, integrations and experiment limits come with the tier you can afford. ### Can I run A/B tests without a developer? Yes, with a visual editor, after a one-time setup. A developer or your site platform has to add the vendor's script to the site once. After that, marketers can change text, images and layout and launch tests themselves. Tests that change prices, logins or server logic still need code. ### Which tool suits a low-traffic site? No tool can lower the traffic a test needs to detect a given effect. That number depends on your conversion rate and [the smallest lift you want to detect](https://alidemirbas.com.tr/en/blog/calculate-ab-test-sample-size), which you can estimate with the calculator above. What a tool can do is help you use traffic well. Variance reduction methods such as CUPED can make a test more sensitive when you have pre-experiment data. Statsig applies CUPED automatically, and GrowthBook, PostHog, Optimizely and Kameleoon offer it. Microsoft's experimentation team explains how [variance reduction works like extra traffic](https://www.microsoft.com/en-us/research/articles/deep-dive-into-variance-reduction/). A low-traffic site also benefits from a free or low-cost plan, since it will run fewer tests. ### Client-side testing, flicker and page speed A client-side tool changes the page in the visitor's browser after it starts loading. Optimizely's own documentation describes the risk: flashing, or flickering, "is when a page loads the original content for a short time" before the variation appears. Its advice is to place the snippet "as high in the head tag as possible". Server-side and feature flag tools decide the variation before the page is sent, so the visitor sees only one version. Flicker matters because visitors who see the original first are not getting a clean variation, which can weaken the test. Check how a vendor handles it before you choose a client-side tool, and test the snippet on your slowest pages. ### What replaced Google Optimize? Nothing from Google replaced it directly. Google Optimize and Optimize 360 stopped working on September 30, 2023, and active experiments ended on that date. In its [sunset notice](https://support.google.com/analytics/answer/12979939?hl=en), Google said it was collaborating on integrations with AB Tasty, Optimizely and VWO. Two of those three now operate as Wingify. #### Can GA4 run A/B tests? No. Google's help center says that to run an A/B test in Google Analytics, you must integrate with a third-party A/B test tool. The tool runs and manages the test, and GA4 is where you can read the results. Wingify, Optimizely, AB Tasty, Convert, Kameleoon and Statsig all document a GA4 integration. GrowthBook reads GA4 data through the BigQuery export. Firebase A/B Testing uses Google Analytics events as experiment goals. ### Questions to ask before you sign A short call with each shortlisted vendor answers what the pricing page does not. These points tend to separate tools that look the same on paper: - **Overage:** what you pay when traffic or events pass the plan limit. - **Statistics:** which method is the default, whether you can change it, and whether sequential testing is included in your tier. - **Data access:** whether you can export raw exposure data or analyze it in your own warehouse. - **Integrations:** whether the GA4 or analytics integration sends exposures, imports audiences or both. - **Consent:** how the tool behaves when a visitor declines cookies. A tool only runs the experiment. The test still needs a clear hypothesis, a primary metric and enough sample, which the [A/B testing guide](https://alidemirbas.com.tr/en/blog/what-is-ab-testing-complete-guide) covers step by step. When results come in, check them with the [A/B test significance calculator](https://alidemirbas.com.tr/en/calculators/ab-test). For ideas worth testing on each page type, browse the [A/B test library](https://alidemirbas.com.tr/en/lab/ab-test-library).