About

AB Tasty

AB Tasty is an enterprise experimentation and personalization platform built for digital marketing and product teams at mid-market to enterprise companies who want A/B testing, feature flagging, and AI-driven personalization in a single bundled package.

It is primarily used by digital marketing teams, growth managers, and product managers at ecommerce, media, and digital-native companies — particularly European organizations and teams that value a bundled pricing model where personalization and feature flags are included rather than sold as add-ons.

Teams choose AB Tasty for its Evi AI that provides sentiment-based targeting and automated personalization; its feature flag and rollout management for gradual feature releases; its bundled approach that includes server-side testing, personalization, and mobile SDKs without additional fees; and its visual editor that enables marketing teams to build experiments without developer dependency.

Note: AB Tasty and VWO completed a corporate merger under Everstone Capital in late 2025 — they remain separate products with separate teams and pricing, but share a parent company. AB Tasty has no published pricing and no free tier; custom quotes via sales only.

About

Optimizely

Optimizely is an enterprise-grade experimentation and digital experience platform built for large organizations with dedicated experimentation teams who need mature server-side testing, advanced personalization, and a statistical engine capable of handling complex multi-product testing programs.

It is primarily used by enterprise marketing teams, experimentation program managers, and product organizations at companies with $50M+ in revenue and the budget and technical infrastructure to support an enterprise experimentation stack.

Teams choose Optimizely for its Stats Accelerator statistical engine that reduces the time required to reach significance; its advanced audience segmentation and AI-driven personalization across web, mobile, and server-side surfaces; its native integration with Optimizely Content Cloud and Commerce Cloud; and its enterprise compliance certifications including SOC 2 and HIPAA options.

Optimizely has no published pricing and requires a sales process typically taking four to eight weeks. Entry-level Web Experimentation contracts start around $36,000/year; enterprise deployments range from $120,000 to $400,000+/year. No free tier.

Feature

AB Tasty

Optimizely

Lucky Orange

A/B Testing

Yes

Yes

No

Multivariate Testing

Yes

Yes

No

Server-side Testing

Yes

Yes

No

Feature Flags

Yes

Yes

No

Visual Editor (no-code)

Yes

Yes

Yes

Personalization

Yes

Yes

No

Heatmaps & Session Recordings

No

No

Yes

Funnel Analysis

Limited

Limited

Yes

AI-Powered Insights

Yes

Yes

Yes

Free Plan

No

No

Yes

Pricing Transparency

No

No

Yes

Choose AB Tasty if you are a mid-to-enterprise marketing or product team that wants comprehensive experimentation and personalization in a bundled package, particularly if you are in Europe or want a vendor with strong ecommerce and digital-native expertise. Custom pricing via sales; no free tier. Ask about the VWO merger impact on long-term roadmap before signing. Avoid it if you need native behavioral analytics like heatmaps or session recordings without a separate tool.

Choose Optimizely if you have a mature, dedicated experimentation program at an enterprise organization with the budget, technical resources, and team size to justify the investment. Best for companies running 30+ tests per quarter with dedicated CRO headcount. Starts ~$36,000/year (sales required; no published pricing). Avoid it if you are a small or mid-market team — the budget barrier and implementation complexity make it the wrong tool below enterprise scale.

Enterprise testing platforms tell you which variant won. Do you know what to test next?

AB Tasty and Optimizely are both built to run experiments at enterprise scale. They are excellent at telling you which variant performed better, at statistical confidence, across complex audience segments. What neither one does is tell your team where the next experiment opportunity is — that still requires someone to form a hypothesis, often by manually reviewing behavioral data in a separate tool.

Lucky Orange Discovery AI closes that gap by analyzing your session data and answering the question that precedes every experiment: where is the friction, and what is causing it? You get evidence-backed answers in plain language — so your team spends less time deciding what to test and more time validating the experiments that matter.

Ask questions like:

  • Which elements on the homepage are getting the most interaction from users who do not convert?

  • What are users doing on the product detail page before they abandon without adding to cart?

  • Where do users who arrive from paid search drop off compared to those from organic?

See how Discovery AI works