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.
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.
| Platform | Best for | Testing type |
|---|---|---|
| Optimizely | Enterprise experimentation programmes across web, product and content | Web and server-side, plus feature flags |
| Wingify (formerly VWO and AB Tasty) | Marketing-led and mid-sized teams wanting testing, personalisation, heatmaps and session recordings | Web, plus server-side and feature management |
| Kameleoon | Teams wanting AI-driven targeting and both web and feature experimentation | Web and server-side |
| Adobe Target | Organisations already invested in Adobe Experience Cloud | Web and app, with AI personalisation |
| LaunchDarkly | Engineering teams focused on feature flags and safe releases | Server-side and feature experimentation |
| Dynamic Yield | Ecommerce personalisation and recommendations | Personalisation-led testing |
| CMS-native testing, e.g. Contentful Personalization | Content teams testing within their CMS | Content 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.
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.
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.
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.
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.
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.
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.