Before we dip our feet into the nitty-gritties of each platform, let’s look at all of them at a glance

1. Fibr

Via Fibr

If you are coming from AB Tasty and you want something that feels much more modern and automated, Fibr is the one to look at first. 

Fibr is an AI-powered CRO platform that focuses on website personalization, experimentation, and performance optimization. Instead of treating A/B testing as a one-off project, Fibr uses a set of AI agents to keep running experiments, personalizing content, and tuning your pages in real time. 

Via Fibr

Fibr sits in a sweet spot for teams that want strong A/B testing without the usual cost and complexity. You can create, run, and analyze tests on any webpage with no hard caps on campaigns or sessions, which is a relief if you are used to traffic-based pricing. There is a dedicated AI A/B testing experience that helps you set up experiments quickly, generate multiple variants for headlines, CTAs, and layout elements, and then auto-analyze performance. 

Fibr can plug into GA4 so you can keep all your attribution, revenue metrics, and experiment results in one place. The platform leans on different statistical models like Bayesian methods and classic Z tests, and selects an appropriate model based on your data, so non-technical teams do not need to obsess over stats settings.

Standout features

• AI A/B testing agent (Max): An AI agent that helps with hypothesis ideas, variant creation, test setup, and basic analysis so marketers can launch experiments with very little manual work.

• Lifetime free A/B testing tier: Ability to create, run, and analyze A/B tests on any webpage with no hard limit on campaigns or sessions, making it easy to scale experimentation without watching traffic meters.

• No-code visual editing for landing pages: Marketers can tweak headlines, images, CTAs, and sections directly on the page without developer involvement, which keeps experimentation moving.

• Powerful AI variant generation: You pick the elements you want to improve and Fibr generates multiple high-converting alternatives that you can immediately test.

• Deep GA4 integration: Experiments can be tracked inside Google Analytics 4, including attributed revenue and behavior, so you do not need an extra reporting layer just for A/B tests.

• Always on optimization and personalization: Fibr’s agents continuously learn from traffic and results, then adjust experiences and recommendations to keep squeezing more performance from your funnels.

• Landing page and ad alignment: The platform can generate or adapt landing pages to match your ad campaigns and messaging, which helps close the gap between ad clicks and conversions.

• Broader AI toolkit for CRO: Beyond testing, you get AI tools for landing page analysis, copy generation, hooks, and on-page personalization, so experimentation sits in a bigger optimization workflow.

Pros of Fibr

• Serious value for money for heavy testing: Lifetime free A/B testing combined with AI assistance makes it far more cost-effective than many legacy testing suites that charge per traffic band or experiment volume. 

• Automation friendly for lean teams: AI agents reduce the manual work of coming up with ideas, building variants, and watching dashboards, which is ideal for teams without a dedicated experimentation squad.

• Built for modern marketing stacks: Integrations with GA4 and ad platforms, plus a focus on landing pages and campaigns, mean it slots in nicely for performance marketing and growth teams. 

Cons of Fibr

• While testing volume is effectively unlimited, the free A/B testing product allows only one active campaign per unique URL, which is limiting for more advanced experimentation setups. 

• The AI layer makes setup easier, but you still need solid hypotheses, guardrails, and a simple experimentation process internally, especially if you plan to run many tests in parallel.

Fibr pricing

• Free A/B testing tier: Lifetime free access to the A/B testing tool with unlimited campaigns and sessions, capped at one campaign per unique URL.

• Paid Fibr AI suite: A standard edition listed around $479 per month for the full AI CRO platform, with enterprise and agency style plans on top.

• Usage-based variables: Pricing is customized based on the number of seats, creatives, workflows, AI credits, and page visits, so larger teams and high traffic sites will sit at the higher end of the range.

Compared to AB Tasty, Fibr comes across as a more AI native and pricing-friendly option, more so if your main focus is high velocity landing page and campaign experimentation rather than a heavy, all-purpose personalization suite.

2. Optimizely

Via Optimizely

Optimizely is one of the older, enterprise-focused experimentation platforms. It covers web A/B testing, full-stack feature experimentation, and personalization across websites, apps, and backend services. 

On the web side, Optimizely Web Experimentation lets you run A/B and multivariate tests by adding a JavaScript snippet to your site, then creating experiments through a visual editor or code. It is built to work across any channel or device that can load that snippet. 

For product and engineering teams, Optimizely Feature Experimentation adds SDK-based feature flags and experiments across web, mobile, and server-side environments. This is where you handle things like algorithm tests, backend logic changes, or gradual rollouts with flags. 

Both products use Optimizely’s Stats Engine, a proprietary statistics framework based on sequential testing and false discovery rate control, so teams can peek at results while maintaining valid decisions. 

Standout features

• Full-stack experimentation across channels: Web snippet for front-end tests plus SDKs for server-side and mobile, so you can treat experimentation as a product capability rather than just a marketing tool. 

• Visual editor plus code-driven setup: Marketers can use a visual editor for UI changes, while developers work directly in code and SDKs for more complex tests. 

• Stats Engine with sequential testing: Built-in statistical engine designed for real-time decision making with protections around peeking and multiple comparisons. 

• Audience targeting and personalization: Ability to target experiments and personalized experiences to specific segments based on behavior, attributes, or events. 

• Enterprise ecosystem and integrations: Connectors into analytics and data tools plus a broader Optimizely product suite for content and commerce, aimed at larger digital teams.

Pros of Optimizely

• Designed with high traffic sites and enterprise governance in mind, with role-based access, auditability, and structured workflows. 

• One vendor for front-end tests, backend experiments, and feature flags, which simplifies procurement and internal alignment.

• Strong developer docs and SDK support, which matters if engineering is heavily involved in experimentation.

Cons of Optimizely

• Official site uses “request pricing”, and third-party benchmarks put typical contracts starting around $36k per year, with many enterprise deals significantly higher. 

• The combination of cost, implementation effort, and breadth of features tends to make it overkill for smaller teams or those just getting started with testing. 

Optimizely pricing

No transparent self-serve plans. Pricing is available only via sales, even for Web Experimentation.

3. VWO
   
   

Via VWO

VWO, formerly “Visual Website Optimizer”, is a SaaS platform focused on experimentation and digital experience optimization. It combines web A/B testing, feature management, behavioral analytics, and personalization into a single environment. 

VWO Testing lets you set up A/B, multivariate, and split URL tests on your site using either a visual editor or a code-based editor. The visual editor is aimed at marketers who want to change copy, layouts, or UI elements without touching code, while developers can work directly in HTML, CSS, and JavaScript where needed. 

VWO’s reporting is powered by a Bayesian stats engine called SmartStats. It is designed to handle peeking and multiple comparisons, and gives probability-based outputs so teams can see how likely a variation is to win, lose, or be equivalent to control. Recent updates added more control over statistical parameters and sequential style monitoring of experiments. 

For more complex scenarios, VWO Feature Experimentation extends testing to the server side and mobile via SDKs, so you can run flags and experiments beyond just the website. 

Standout features

• Visual and code-based test creation: Marketers can use a point-and-click editor, while developers take over for more advanced changes or performance-sensitive tests. 

• Broad test types in one tool: Support for standard A/B, multivariate, and split URL tests, plus feature-level experiments and bandit-style methods in the wider platform.

• Bayesian SmartStats reporting: Probability-based reports that help you understand how confident you can be in a winner and how an experiment is trending over time. 

• Behavior analytics alongside testing: Built in heatmaps, session recordings, and funnels so you can pair qualitative behavior with experiment results. 

• Client-side and server-side coverage: Web snippet for quick experiments and SDKs for backend or app-level tests, similar in scope to other full platform offerings.

Pros of VWO

• Testing, feature flags, behavioral analytics, and personalization sit under one roof, which simplifies tool sprawl for many teams. 

• Visual editor and experiment templates make it approachable for marketing 

• There is a free tier with limited A/B testing

Cons of VWO

• While the entry point can be more approachable than legacy enterprise tools, costs climb with monthly visitors and enabled products

• The all-in-one approach is useful, but smaller teams that only need basic A/B tests may find the interface and options more complex than they truly need. 

VWO pricing

• Free plan available with basic A/B testing and limited features for low traffic sites.

• Enterprise and higher traffic pricing is custom, based on monthly tracked users and the mix of testing, feature experimentation, and insights products you enable. 
  
  

4. Adobe Target

Via Adobe Target

Adobe Target sits inside Adobe Experience Cloud as the testing and personalization product. It is aimed squarely at larger digital teams that want one environment to run A/B tests, personalization, recommendations and automation across web and mobile. 

Target supports classic A/B tests, multivariate tests and a couple of AI-assisted flavors. You can build experiments in the Visual Experience Composer for front-end changes or use a form-based composer for more structured setups.

On the A/B testing side, you get three main activity types. Manual A/B tests, Auto Allocate, which automatically shifts more traffic to the better-performing variant over time, and Auto Target, which uses machine learning to personalize experiences to individuals rather than only picking a single global winner. 

Target also plugs into Adobe Analytics and Adobe Advertising, so you can run experiments on landing pages from paid media and measure results inside Analytics with shared dimensions and events. 

Standout features

• Multiple A/B activity types in one place: Manual A/B tests, Auto Allocate and Auto Target, which together cover basic experiments and more automated, personalization-style testing

• Visual and form-based experience composers: Marketers can work visually on pages, while more advanced users rely on the form-based composer for structured setups and integrations

• AI-assisted personalization and recommendations: Adobe Target uses Adobe Sensei to power automated targeting, recommendations and optimization at scale for web and app experiences

• Integration with Adobe Experience Cloud: When used with Analytics, Audience Manager and Adobe Experience Manager, you get shared audiences, reporting and content, which is the main draw for existing Adobe customers

• Enterprise-focused governance and releases: Role-based access, environments and ongoing release cycles tailored to enterprises that need process, auditability and long-term support

Pros of Adobe Target

• If you already use Adobe Analytics or Adobe Experience Manager, Target can sit easily in that stack so data and audiences move more easily between tools

• Manual tests, automated allocation and machine learning based targeting give room to grow beyond simple A/B testing

• The product and implementation approach are designed for large sites, multiple brands and distributed teams rather than a single growth marketer

Cons of Adobe Target

• Target often shows its best side when paired with other Adobe tools. This increases implementation effort and operational overhead

• Pricing is custom, tied to traffic and modules, and third-party benchmarks consistently describe it as a five-figure plus annual spend for most enterprise customers

Adobe Target pricing

Custom quotes only with pricing based on traffic volume, feature set and deployment scale

5. Insider

Via Insider

Insider is a cross-channel customer experience and personalization platform. It brings together customer data, segmentation, automation and messaging so marketing and CX teams can create journeys across web, app, email, SMS, WhatsApp and more from a single interface.

Experimentation in Insider is inside its wider “Individualize” and “Experiment” capabilities. Teams can run A/B tests on web pages, in product experiences and across channels, trying different CTAs, layouts, images or message variants and tracking lift on key goals. 

A big focus is on AI led segmentation. Insider uses predictive algorithms to build ready-to-use segments, such as likely purchasers or churn risks, then lets you split test experiences and campaigns specifically for those groups. Results for experiments roll up into unified reporting so you can see performance across touchpoints rather than only at the page level.

Standout features

• Cross-channel experimentation and messaging: A/B testing and personalization across web, app, email, SMS, WhatsApp and other channels from the same platform.

• AI-driven predictive segmentation: Algorithms mine behavioral and attribute data to build predictive segments that can be targeted and tested without manual rules for every case.

• Journey orchestration and automation: Tools to design and automate multi-step customer journeys, using conditions, triggers and experiments along the way.

• On-site personalization for e-commerce: Capabilities for personalized banners, product recommendations and content blocks on web and mobile, often highlighted for e-commerce use cases. 

• Single platform approach for growth teams: Insider positions itself as a growth management platform that combines customer data, segmentation, campaigns and reporting in one stack.

Pros of Insider

• Designed to run targeted, data-driven experiences rather than only simple global A/B tests, which suits brands with large audiences and multiple channels. 

• Many references and case studies focus on retail, travel and similar verticals where onsite and cross-channel personalization directly tie into revenue.

• A/B testing is not a separate tool, it is embedded into flows, which can help teams continuously test variants as part of daily campaign work

Cons of Insider

• The breadth of features and channels means the platform usually needs a structured rollout and clear internal ownership rather than a quick plug-in experiment tool.

• Public pricing is not listed. Buyer guides position it as a negotiated, custom contract based on scale and modules, which can make it harder for smaller teams to evaluate. 

Insider pricing

• Custom, quote-based pricing, usually tied to traffic or monthly active users, number of channels in use and enabled modules