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Best A/B Testing Platforms in 2026: How to Choose

4 September 2026

By: Remarkable

Categories: Channel Optimisation, Content & Experience, Optimizely

The leading A/B testing platforms in 2026 are Optimizely, Wingify (formerly VWO and AB Tasty), Kameleoon and Adobe Target for web experimentation, with LaunchDarkly and Optimizely Feature Experimentation for server-side and feature testing, and personalisation-led tools such as Dynamic Yield. The best choice depends on who runs your tests, whether you test in the browser, on the server or both, how much traffic you have, and which analytics and content platforms you need to connect to. If you are replacing Google Optimize, which closed in 2023, read our guide to Google Optimize alternatives.

What is an A/B testing platform?

An A/B testing platform lets you show different versions of a web page, app screen, feature or message to randomly split groups of users and measure which performs better against a goal, such as conversions, sign-ups or revenue. Modern platforms go well beyond simple A/B tests. They support multivariate and multi-page tests, server-side experiments, feature flags and personalisation, and they use statistical methods designed to give reliable answers without waiting for a fixed sample size.

The leading A/B testing platforms compared

PlatformBest forTesting type
OptimizelyEnterprise experimentation programmes across web, product and contentWeb and server-side, plus feature flags
Wingify (formerly VWO and AB Tasty)Marketing-led and mid-sized teams wanting testing, personalisation, heatmaps and session recordingsWeb, plus server-side and feature management
KameleoonTeams wanting AI-driven targeting and both web and feature experimentationWeb and server-side
Adobe TargetOrganisations already invested in Adobe Experience CloudWeb and app, with AI personalisation
LaunchDarklyEngineering teams focused on feature flags and safe releasesServer-side and feature experimentation
Dynamic YieldEcommerce personalisation and recommendationsPersonalisation-led testing
CMS-native testing, e.g. Contentful PersonalizationContent teams testing within their CMSContent experiments

We have compared several of these in more depth: VWO vs Optimizely, LaunchDarkly vs Optimizely, Optimizely vs Dynamic Yield, Monetate vs Optimizely and Contentful Personalization vs Optimizely.

What to look for in an A/B testing platform

  • The right testing types. Client-side (browser) tests suit marketing teams changing pages. Server-side tests and feature flags suit product and engineering teams testing features, pricing logic and apps. Many organisations need both.
  • Trustworthy statistics. Look for methods such as sequential testing or Bayesian analysis that let you check results as a test runs without inflating false positives, and clear guidance on when a result is reliable.
  • Page speed and no flicker. Client-side tools should load without delaying the page or briefly showing the original version before the variation.
  • Targeting and personalisation by audience, behaviour, location, device and first-party data.
  • Integrations with Google Analytics 4 and your analytics, CDP, CMS and data warehouse, so results connect to revenue and customer data.
  • Privacy and consent. Testing should respect your consent management and data protection obligations, including UK GDPR.
  • AI assistance for generating test ideas and variations and for summarising results, which most platforms now offer in some form.
  • Ease of use for marketers through a visual editor, with developer tools for more complex tests.

How to choose

  • Marketing team testing web pages, moderate traffic: Wingify (VWO and AB Tasty) or Kameleoon are strong options, and Optimizely Web Experimentation if you expect to scale.
  • Organisation-wide experimentation across web, product and apps: Optimizely, which combines web and feature experimentation in one programme.
  • Engineering-led feature releases: LaunchDarkly or Optimizely Feature Experimentation.
  • Already on Adobe Experience Cloud: Adobe Target integrates most closely.
  • Ecommerce personalisation first: Dynamic Yield, or Optimizely with Optimizely Data Platform.
  • Mainly testing content: consider testing built into your CMS before adding another tool.

Whichever tool you choose, the platform matters less than the programme around it: clear hypotheses, enough traffic to reach reliable results, joined-up analytics and a regular rhythm of testing and rolling out winners.

Why Optimizely leads for enterprise experimentation

As an Optimizely partner we are not neutral, so here are the specific reasons enterprise teams choose it. Optimizely’s Stats Engine uses sequential testing, so you can monitor results as they come in. Web and Feature Experimentation share one programme, so marketing and product teams test in the same place with the same metrics. It integrates with Google Analytics 4, Optimizely Data Platform and the rest of Optimizely One, and its AI, the Optimizely Agent Platform (formerly Opal), can suggest test ideas and summarise results, paid for in usage credits. The trade-off is cost: Optimizely is priced for enterprise programmes, so our Optimizely pricing guide is worth reading before you shortlist. A free Feature Experimentation plan is available for feature flags.

Work with an Optimizely Platinum Solution Partner. Remarkable became the UK’s first Optimizely (Episerver) partner in 1995, and our team has won more than 10 OMVP awards over the years. Find out how we help on our Optimizely partner page, or get an Optimizely quote.

A/B testing platform FAQs

What is the best A/B testing platform?

There is no single best platform. Optimizely leads for enterprise experimentation across web and product, Wingify (formerly VWO and AB Tasty) suits marketing-led testing, LaunchDarkly suits engineering-led feature releases, and Adobe Target fits organisations on Adobe Experience Cloud.

What is the difference between client-side and server-side testing?

Client-side tests change the page in the visitor’s browser and suit marketing teams testing content and layout. Server-side tests run in your application code and suit testing features, pricing logic, search and apps, without any page flicker.

Is there a free A/B testing platform?

Google Optimize, the best-known free tool, closed in 2023. Several platforms offer free tiers or trials, and Optimizely has a free Feature Experimentation plan for feature flags, but full web experimentation tools are generally paid.

How much traffic do you need for A/B testing?

It depends on your conversion rate and the size of change you want to detect. Low-traffic pages need longer tests or bigger changes to reach a reliable result, which is why prioritising high-traffic, high-value pages matters.

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