Best A/B Testing Software in 2026

A/B testing software decides which version of a page, feature or price your visitors see, records what they do next, and tells you whether the difference is real or noise. Three things separate the tools: how you build a test (a visual editor on the live page, or code behind a feature flag), how the statistics are calculated, and what you pay for (traffic, events, tested users or seats).

The market also changed a lot in the last twelve months. VWO and AB Tasty merged and now operate as Wingify; both old domains redirect to wingify.com. Statsig agreed to join OpenAI in September 2025, and Statsig's own blog now notes that it was acquired by Amplitude on May 5, 2026, with the product and customer base moving to Amplitude while it keeps selling the same plans. Any comparison written before 2026 is out of date on these points.

This guide compares seven tools that are on sale today for teams that want to run A/B tests on websites and products. Every price and feature below comes from the vendor's own pricing page, product pages or documentation, read in October 2026.

Why the Choice of A/B Testing Tool Matters

An A/B test is only as good as three things: the change you ship, the data you measure and the statistics you apply. The tool controls all three.

How you build tests. A visual editor lets a marketer change a headline or button on the live page without a developer. That is fast, but the change is applied by a script in the browser after the page loads, which can cause a brief flash of the original version (flicker) if the script is not set up carefully. Server-side or feature-flag testing puts the variation in your code, so there is nothing to flash, but every test needs an engineer. Most teams that test both marketing pages and product features need both methods.

How results are calculated. Vendors use different statistical approaches. Frequentist fixed-horizon tests assume you pick a sample size and look once. Sequential tests are designed so you can check results continuously without inflating false positives. Bayesian engines report the probability that one variant beats another. CUPED uses pre-experiment data to reduce noise, which can shorten tests. None of these is wrong, but a tool that only supports a fixed-horizon test punishes teams that peek at dashboards every day.

What you pay for. Pricing bases differ widely: events (Statsig, PostHog), seats (GrowthBook), tested users (Convert), service connections plus monthly active users (LaunchDarkly), or a custom quote (Optimizely, Wingify). The same traffic can be cheap on one model and expensive on another, so you need your own numbers before comparing.

Where the data lives. Warehouse-native tools run the analysis on data in your Snowflake, BigQuery, Databricks or Redshift account, so experiment metrics match the rest of your reporting. Hosted tools collect their own events. Warehouse-native is better for data teams; hosted is simpler for everyone else.

Statsig review

Statsig combines feature flags, experimentation, product analytics, web analytics and session replay in one platform. For A/B testing it covers both sides of the use case: a no-code visual web editor for page tests (documented as Sidecar) and SDK-based experiments for product features.

Key features

• No-code experiments with a visual web editor, available on all three plans according to the plan comparison table.
• Feature flags, dynamic configs, parameter stores and scheduled percentage rollouts.
• Bayesian and frequentist analysis, CUPED, sequential testing, Bonferroni and Benjamini-Hochberg corrections, winsorization, switchback tests and non-inferiority tests, all listed for every plan.
• Holdouts, multi-arm bandits (Autotune) and custom queries on Pro and Enterprise.
• Warehouse Native deployment, which runs the analysis inside your own data warehouse, on Enterprise.

Pricing

• Developer: free with no credit card; 2M events a month, unlimited flag and config checks, 50,000 session replays, 1-year analytics retention, unlimited seats.
• Pro: $150 a month with 5M events included, then $0.05 per 1,000 events; 100,000 session replays and unlimited retention.
• Enterprise: custom contracts based on events or experiments, with warehouse native deployment, SSO, role-based access, EU hosting and HIPAA eligibility with a BAA.

Ownership. Statsig announced in September 2025 that it would join OpenAI. A note now added to that announcement says Statsig was acquired by Amplitude on May 5, 2026: the original team stayed at OpenAI, while the product, brand and customer base are part of Amplitude, which "continues to develop Statsig." Plans are still sold on statsig.com.

Pros

• The free plan is unusually complete for experimentation: visual editor, sequential testing and CUPED are not held back for paid tiers.
• Unlimited seats on every plan, so the whole team can see results.
• Published Pro pricing makes budgeting straightforward once you know your event volume.
• Flags, experiments, analytics and replays share one data set, so you can see why a variant won.

Cons

• An announced OpenAI deal in 2025 followed by the Amplitude acquisition in May 2026 means the long-term roadmap is less certain than at a stable independent vendor.
• Warehouse native deployment requires Enterprise.
• Event pricing requires a realistic estimate of how many events your site and app send.

Who should use it: teams that want to test marketing pages and product features in one place, and startups that want serious statistics before they have budget.

Who should avoid it: organizations that need warehouse-native analysis on a self-serve plan, or that want to avoid any vendor in the middle of an ownership transition.

GrowthBook review

GrowthBook is an open-source feature flagging and experimentation platform built around your data warehouse. Instead of collecting its own events, it can read exposure and metric data from the warehouse you already use, and it can be self-hosted.

Key features

• Bring your own warehouse on every Cloud and self-hosted plan; a managed warehouse is also available if you do not have one.
• Bayesian and frequentist engines, sample ratio mismatch detection and multiple testing corrections on all plans.
• Sequential testing, CUPED, sticky bucketing, multi-arm bandits, safe rollouts, split URL tests and the AI Visual Editor on Pro.
• An HTML script tag for low-code sites, plus edge apps for Cloudflare Workers, Fastly and Lambda@Edge that GrowthBook documents as a way to "cut flicker before HTML ships."
• 24+ SDKs, a REST API and an MCP server.

Pricing

• Cloud Starter: free, up to 3 users and 1 project, unlimited flags, experiments and traffic; managed warehouse up to 1M events a month; 1M CDN requests a month.
• Cloud Pro: $40 per seat per month, up to 30 users and 3 projects; managed warehouse 2M events a month then $30 per million; CDN requests 2M a month then $10 per million.
• Enterprise: custom, with SSO and SCIM, approval workflows, holdouts and a 99.99% uptime SLA.
• Self-hosted open source: free, unlimited users, 1 project, bring your own warehouse.

Pros

• Warehouse-native analysis is available on every plan, including the free ones.
• Open source and self-hostable, useful for strict data residency.
• Seat pricing with unlimited traffic is easy to predict for small teams.
• Documented edge delivery options for pages where flicker matters.

Cons

• The Cloud free plan stops at 3 users.
• The visual editor, sequential testing and CUPED require Pro or self-hosted Enterprise.
• Teams without a warehouse or SQL skills will not get the main benefit.

Who should use it: data and product teams with a warehouse, companies that want to self-host, and small teams that prefer per-seat pricing to per-event pricing.

Who should avoid it: marketing teams without engineering or data support, and large teams that would pay for many seats.

Optimizely review

Optimizely is the long-standing enterprise name in experimentation. Its suite covers Web Experimentation (visual editor for websites), Feature Experimentation (server-side tests and flags), personalization and Optimizely Analytics, a warehouse-native analytics product.

Key features

• A visual editor for web testing, with server-side control available for deeper tests.
• Stats Engine, which uses sequential testing combined with false discovery rate control so results can be monitored continuously.
• Feature Experimentation documents three methods: Stats Engine (sequential), plus frequentist fixed horizon and Bayesian, which are in beta.
• Optimizely Analytics connects directly to Snowflake, BigQuery, Databricks and Redshift for warehouse-native experiment analysis.
• Multivariate tests, bandits and personalization.

Pricing

• No public prices. Optimizely says "Every Optimizely plan is individually packaged" and asks you to contact sales.
• A free feature flagging plan exists for Feature Experimentation: no credit card, and one concurrent experiment at a time.

Pros

• One vendor for web testing, server-side testing, personalization and warehouse analytics.
• The sequential Stats Engine is designed for teams that check results often.
• Sequential Stats Engine, with fixed-horizon and Bayesian methods in beta in Feature Experimentation.
• A free entry point for engineering teams through the feature flagging plan.

Cons

• You cannot compare its cost without a sales process.
• The free plan's one-experiment limit is tight for real testing.
• Much of the suite is aimed at large programs and will go unused by small teams.

Who should use it: enterprises with an experimentation team, several brands or sites, and the budget for a custom contract.

Who should avoid it: small and mid-sized teams that want published pricing or a self-serve start.

Wingify (formerly VWO and AB Tasty) review

Wingify is the new name for the combined VWO and AB Tasty business. Wingify's site says "AB Tasty and VWO have united," VWO product names are being renamed to Wingify, the app moved to app.wingify.com on June 13, 2026, and existing contracts, pricing and service levels carry over unchanged. Live campaigns, SDKs and tracking snippets keep working; Wingify says only the dashboard changes.

Key features

• Web Experimentation and Rollout with a visual editor, plus Web Personalization.
• Feature Experimentation, Personalization and Rollout with SDKs for major languages, REST APIs, an MCP server and OpenFeature support.
• Statistics: the feature experimentation page describes "Bayesian and Frequentist methodologies (you choose!) with built-in error and peeking correction" and automatic sample ratio mismatch detection. The help center describes SmartStats as Bayesian and notes that newer campaigns on its Data Platform use an upgraded Campaign Reports engine.
• Behavior Analytics, Journey Analytics and User Feedback in the same suite.
• Data export to analytics tools, CDPs and data warehouses.

Pricing

• Growth, Pro and Enterprise tiers are listed for each product, but no prices are shown; pricing is through a demo.
• 30-day free trial, no credit card required. No free-forever plan is listed on the pages read.

Pros

• Testing, heatmaps, journeys, feedback and personalization in one place, which suits CRO work.
• Both a visual editor and server-side SDKs.
• A choice of Bayesian or frequentist analysis for feature experiments.
• Existing VWO and AB Tasty customers keep their contracts and pricing.

Cons

• No public pricing since the rebrand.
• Two product lines are still converging, so names, dashboards and documentation are changing.
• No free plan, only a trial.

Who should use it: marketing and CRO teams that want qualitative insight next to their tests, and existing VWO or AB Tasty customers.

Who should avoid it: teams that need published prices or want a settled product with no migration ahead.

Convert review

Convert (product name Convert Experiences) is a website testing tool focused on agencies, ecommerce and marketing teams, with an emphasis on privacy and transparent pricing.

Key features

• A/B, split URL, multipage, multivariate, price and multi-arm bandit tests.
• Customizable frequentist and Bayesian stats engines, SRM checks and collision prevention; frequentist tests use two-tailed Z tests.
• SmartInsert, which Convert says has delivered flicker-free tests since 2016.
• Full-stack (server-side) experimentation and feature flags on Pro, with SDKs for Ruby, Python, JavaScript, PHP, Android and iOS.
• First-party cookies; Convert says it does not need to store personal data to operate.

Pricing

• Growth: $399/month billed monthly, or $299/month billed annually ($3,588 a year). 100K tested users a month. Extra tested users cost $399 per 100K.
• Pro: $599/month monthly, or $420/month annually ($5,040 a year). 100K tested users a month; adds multivariate and multipage tests, full-stack and feature flags, multi-arm bandit and sequential testing. Extra tested users cost $699 per 250K.
• Enterprise: price on request, annual only, 1M+ tested users a month.
• 15-day free trial, no credit card. Prices exclude taxes.

Pros

• Published prices and limits, which is rare among visual-editor tools.
• Both frequentist and Bayesian analysis.
• Privacy-first design with first-party cookies.
• Server-side testing without an enterprise contract.

Cons

• No free plan.
• Sequential testing and multivariate tests need Pro.
• Overage charges grow quickly on high-traffic sites.

Who should use it: agencies, ecommerce stores and marketing teams that mainly test websites and want to know the price before a call.

Who should avoid it: product teams that need analytics, replays and flags in one place, or very high-traffic sites that would pay heavy overages.

PostHog review

PostHog is a product platform that bundles analytics, session replay, feature flags, experiments, surveys and more. Experiments are built on feature flags: creating an experiment creates a flag.

Key features

• Bayesian and frequentist engines; the frequentist engine has optional sequential testing that produces confidence sequences valid at any stopping point.
• CUPED variance reduction, holdouts and data warehouse metrics.
• Session replays filtered by variant, so you can see how users behaved in each version.
• No-code web experiments built in the PostHog toolbar, marked beta in PostHog's own comparison table.
• SDKs for web, mobile and backend, plus integrations for Webflow, WordPress, Shopify and other no-code platforms.

Pricing

• Free every month: 1M analytics events, 1M feature flag requests (experiments are billed with feature flags), 5K session replays and more.
• Pay-as-you-go: usage above the free allowance. Feature flag requests start at $0.0001 per request and get cheaper with volume.
• No minimum spend or annual contract; you can set a billing limit for each product.

Flicker note. PostHog's docs say no-code experiments suit simple text and style changes and server-rendered sites, and warn that single-page apps (React, Vue, Angular) may overwrite no-code changes when they re-render.

Pros

• A meaningful free tier for experiments through 1M flag requests a month.
• Experiments use the same events as your product analytics.
• Documented Bayesian, frequentist and sequential options.
• Billing limits stop runaway costs.

Cons

• The visual editor is still beta and has documented limits on single-page apps.
• Not designed around marketing workflows such as campaign QA or personalization.
• Usage pricing across several products takes effort to forecast.

Who should use it: product engineers and startups that use PostHog for analytics, or want one tool for analytics and experiments.

Who should avoid it: marketing teams that need a mature visual editor for frequent page tests.

LaunchDarkly review

LaunchDarkly is a feature management platform that has added experimentation, observability and AI configuration tools. Experiments run on top of feature flags.

Key features

• Feature flags with segments, percentage rollouts and flag history (flag scheduling on Enterprise).
• Full-stack A/B/n experiments with Bayesian and frequentist analysis, CUPED, sequential testing, SRM detection, A/A tests and multi-armed bandits, all listed on the pricing page.
• Warehouse-native experimentation documented for Snowflake, BigQuery, Databricks, Redshift and ClickHouse.
• Multiple comparisons correction for frequentist results.
• Unlimited seats on every plan.

Pricing

• Developer: $0 a month forever, unlimited seats, 5 service connections, 1K client-side MAU, 100K experimentation MAU per month at no charge, 1 project and 3 environments.
• Foundation: pay as you go after a 14-day trial. $10 per service connection per month and $8.33 per 1,000 client-side MAU per month, billed yearly; the first 5 service connections are included. No seat fees.
• Enterprise: custom pricing.

Pros

• A mature flag platform, so experiments fit into existing release processes.
• 100K experimentation MAU a month on the free plan.
• Broad warehouse-native support.
• Strong documented statistics options.

Cons

• No visual editor found in its documentation; every test needs code.
• Service connections plus MAU is harder to estimate than a single meter.
• More platform than you need if you only test landing pages.

Who should use it: engineering teams that already release behind flags and want to measure the impact of each rollout.

Who should avoid it: marketers who want to edit pages visually, and small sites that only need simple page tests.

Head-to-Head Comparison

Visual editor vs server-side. Statsig, Optimizely, Wingify and Convert offer both a visual editor and server-side testing. GrowthBook has both but puts the visual editor on Pro. PostHog's no-code editor is beta. LaunchDarkly is code-only. If marketers will build most tests, Statsig, Convert, Wingify and Optimizely fit best; if engineers will, all seven work.

Statistics. Every tool documents more than one approach. Statsig lists Bayesian, frequentist, CUPED and sequential testing on its free plan. GrowthBook offers Bayesian and frequentist free, with sequential and CUPED on Pro. Optimizely's Stats Engine is sequential with false discovery rate control, and Feature Experimentation adds fixed-horizon and Bayesian methods (in beta). Wingify describes Bayesian or frequentist with peeking correction. Convert offers frequentist and Bayesian, with sequential on Pro. PostHog offers Bayesian and frequentist with optional sequential testing and CUPED. LaunchDarkly lists Bayesian, frequentist, CUPED and sequential.

Pricing basis. Events: Statsig (2M free, 5M in Pro) and PostHog (1M flag requests free). Seats: GrowthBook ($40 per seat on Pro). Tested users: Convert (100K a month per plan). Service connections and MAU: LaunchDarkly. Custom quotes: Optimizely and Wingify.

Free plans. Statsig, GrowthBook, PostHog and LaunchDarkly have free plans that can run real experiments. Optimizely's free plan is limited to one concurrent experiment. Wingify (30 days) and Convert (15 days) offer trials only.

Warehouse-native. GrowthBook on every plan; LaunchDarkly via documented warehouse integrations; Statsig Warehouse Native on Enterprise; Optimizely through Optimizely Analytics; PostHog supports data warehouse metrics. Wingify documents exports to warehouses rather than warehouse-native analysis. Convert does not document a warehouse-native mode on the pages read.

Flicker and performance. Only vendor claims and docs are available here. Convert markets SmartInsert as flicker-free and its snippet as lightweight. Optimizely says Web Experimentation delivers "fast, flicker-free experiences." GrowthBook documents edge apps to cut flicker. PostHog documents limits for single-page apps. Server-side tests on any platform avoid client-side flicker because the variation is in the HTML your server sends.

How to Choose: Decision Framework

Questions to answer first

1. Who will build most tests: marketers in a visual editor, or engineers in code?
2. How much traffic, how many events and how many people will use the tool each month?
3. Do you already have a data warehouse that holds your source-of-truth metrics?
4. Do you need personalization, heatmaps or session replay next to experiments?
5. Will your team check results daily? If so, insist on sequential testing or a Bayesian engine with peeking correction.

Red flags

• A tool whose only statistics option is a fixed-horizon test while your team checks dashboards every morning.
• A visual editor on a single-page app without a documented way to handle re-renders.
• Pricing you cannot estimate from your own traffic numbers before a contract.
• No sample ratio mismatch check. An SRM alert is often the first sign that the setup is broken.

What to test in a trial

• Run an A/A test (two identical versions) and confirm the tool reports no winner.
• Build a simple visual test on your most important page and watch for flicker on a slow mobile connection.
• Ship one server-side test behind a flag and confirm exposures are logged once per user.
• Compare the tool's conversion counts with your analytics or warehouse.
• Check how results look before significance: does the tool discourage early stopping?

Worked cost example

Take a team of three people testing a marketing site and a signup flow, with 80,000 tested visitors a month. Assume each visitor generates about 40 tracked events (page views, flag checks, clicks, conversions), or 3.2M events a month. Prices are from the vendors' pricing pages in October 2026.

• Statsig: 3.2M events is above the free 2M, so Pro applies. Pro includes 5M events: $150 a month, or $150 x 12 = $1,800 a year. Unlimited seats.
• GrowthBook Pro, using your own warehouse: 3 seats x $40 = $120 a month, or $120 x 12 = $1,440 a year. If you used the managed warehouse instead, events above the included 2M cost $30 per million: (3.2M - 2M) = 1.2M x $30 = $36, for $156 a month. CDN requests above 2M a month would add $10 per million. GrowthBook Cloud Starter would cost $0 for these three users with your own warehouse, but it lacks the visual editor, sequential testing and CUPED.
• Convert Growth, annual billing: 80,000 tested users is inside the 100K limit, so $299 a month, billed as $3,588 a year. Monthly billing is $399 x 12 = $4,788 a year. Pro, if you need sequential testing or full-stack, is $420 x 12 = $5,040 a year on annual billing.
• Optimizely and Wingify: custom quotes only, so get written quotes for the same traffic before comparing.

The event assumption matters most. At 20 events per visitor (1.6M events), Statsig's free Developer plan would cover this team at $0, while Convert's price would not change because it charges per tested user.

The Verdict: Final Recommendations

Statsig is our top pick for teams that want to run A/B tests on websites and products. Its free plan includes a visual web editor that is not labelled beta, feature flags, Bayesian and frequentist analysis, CUPED and sequential testing, with unlimited seats; no other tool here offers that whole set for free. When you outgrow the free tier, Pro has a published price. The caveat is ownership: Statsig now belongs to Amplitude after the original team went to OpenAI, so review the contract terms and roadmap commitments before a multi-year deal.

GrowthBook is the pick for data teams. Warehouse-native analysis on every plan and a free self-hosted version set it apart in this list, and seat pricing is easy to forecast.

Optimizely is the choice for large organizations that want one enterprise vendor for web and server-side testing, personalization and warehouse analytics, and can accept a sales-led price.

Wingify suits CRO and marketing teams that want heatmaps, journeys and feedback next to their tests, and existing VWO or AB Tasty customers whose contracts carry over.

Convert is the best visual-editor tool if you want to know the price before you call anyone, and it leans on privacy (first-party cookies, no need to store personal data).

PostHog is the natural choice if you already use PostHog for analytics; experiments come almost for free on top.

LaunchDarkly fits engineering teams that release behind flags and want to measure every rollout, but it is not a tool for marketers.

Conclusion

The A/B testing market in 2026 looks different from two years ago. VWO and AB Tasty are now one company under the Wingify name, and Statsig, which agreed to join OpenAI in 2025, is now part of Amplitude. Meanwhile the statistics have improved across the board: sequential testing, CUPED and the choice of Bayesian or frequentist analysis are now standard rather than premium.

For most teams that test both web pages and product features, Statsig offers the most complete package at the lowest entry cost. GrowthBook is the strongest alternative for warehouse-first teams, and Convert is the clearest paid option for website testing. Whichever you pick, start with an A/A test, check how the tool handles flicker on your own pages, and model the price with your real traffic before you sign.