AB Tasty vs Optimizely vs Explore (2026): Web Testing vs Store Revenue
AB Tasty is a marketing-friendly A/B testing and personalisation platform, now part of the VWO group after their 2025 merger. Optimizely Web Experimentation is the enterprise A/B testing standard, built for engineering teams with full-stack rigor. Omniconvert Explore is the Shopify-native eCommerce CRO platform: it runs product, cart, and checkout experiments measured in revenue per visitor.
- AB Tasty is a marketing-friendly A/B testing and personalisation platform, now inside the VWO group after their 2025 merger, and holds a 4.5 out of 5 G2 rating. [G2, 2026]
- Optimizely Web Experimentation is the enterprise A/B testing standard with full-stack rigor and feature flags, and holds a 4.2 out of 5 G2 rating. [G2, 2026]
- Both are real testing platforms but sit at different scales: AB Tasty fits marketing teams, Optimizely fits enterprise engineering programmes.
- Neither has native Shopify integration, native checkout experiment templates, or revenue per visitor as a native metric, which is where a store's revenue is actually decided.
- Omniconvert Explore runs A/B, multivariate, and personalisation experiments natively on Shopify product, cart, and checkout, measured in revenue per visitor: pick it when the goal is store revenue, not generic web testing.
Teams comparing AB Tasty vs Optimizely are usually choosing between two credible testing platforms with different centres of gravity: a marketing-friendly no-code suite on one side, an enterprise engineering standard on the other. AB Tasty leads with a visual editor tuned for marketers and, after merging with VWO in 2025, sits inside the wider VWO group. Optimizely leads with feature flags, full-stack testing, and enterprise scale. Both are real testing tools, but neither is built around the surfaces where a Shopify store wins or loses revenue: the product page, the cart, and the checkout, which is what Omniconvert Explore is built for.
What is AB Tasty, and what is it actually good at?
AB Tasty is a web experimentation and personalisation platform that runs A/B tests, multivariate tests, and on-site personalisation from a no-code visual editor. It combines testing with feature flags in one product and is popular with marketing teams that do not want to depend on engineering to launch an experiment. It holds a 4.5 out of 5 rating on G2 across 185 reviews. [G2, 2026]
AB Tasty is a testing tool built around marketing workflows. Its visual editor makes changing a hero, a headline, or a CTA a click-and-drag task, and its personalisation module lets a marketer target segments without a developer. In 2025 it merged with VWO, and the two products now sit inside the same group; the roadmap and pricing have been reorganised since. [AB Tasty, 2026]
Server-side testing is available through a separate paid add-on module rather than in the base product. Native Shopify integration is limited, and there are no dedicated eCommerce templates for cart or checkout experiments. AB Tasty fits a marketing website with a landing-page or hero-test cadence better than a store optimising the product-to-checkout path.
No-code A/B testing lets a marketer create, launch, and measure a variant of a page from a visual editor, without writing HTML or CSS or opening a ticket with engineering. AB Tasty does this well for marketing sites and landing pages. It is an execution layer for page-level tests, distinct from running a controlled revenue experiment on the Shopify product, cart, and checkout surfaces.
Where AB Tasty is genuinely strong
- No-code visual editor: a mature drag-and-drop experience marketers use without engineering help.
- Testing plus feature flags in one platform: experiments and flag rollouts sit next to each other, not in separate tools.
- Personalisation built in: segment-based content changes ship alongside the testing product.
- Wider VWO group backing: the 2025 merger expanded support resources and the joint product footprint.
Where AB Tasty hits its ceiling for an eCommerce store
- Server-side is a paid add-on: a separate module is required for full server-side experimentation.
- No native Shopify integration: installs via script or tag, with no checkout-level testing built in.
- No eCommerce templates: product, cart, and checkout experiments have to be built from scratch.
- Marketing-site orientation: no native concept of revenue per visitor as a tested outcome.
What is Optimizely, and what is it actually good at?
Optimizely Web Experimentation is the enterprise A/B testing standard. It runs visual and full-stack experiments, ships with feature flags and server-side rigor, and integrates with the wider enterprise data stack. It is the largest platform in the category by customer base and holds a 4.2 out of 5 rating on G2 across 401 reviews. [G2, 2026]
Optimizely is a testing platform first and everything else second. Its statistical engine, audience targeting, and full-stack capability let engineers experiment on server logic and not only page markup, which is why the largest enterprise experimentation programmes run on it. [G2, 2026] Feature flags and web tests live in the same product.
The trade-off is scope and cost. Optimizely is priced for enterprise contracts sold through sales, needs technical staff to operate fully, and has no free trial. It is not built around Shopify or checkout revenue: those experiments require custom integration work and a developer.
Full-stack experimentation extends testing beyond page markup to the server, so an engineer can experiment on a pricing rule, a recommendation, or a rollout of a new feature behind a flag. Optimizely does this well for engineering-led product organisations. It is an execution layer for complex product tests, distinct from running a controlled revenue experiment on the Shopify product, cart, and checkout surfaces.
Where Optimizely is genuinely strong
- Enterprise scale and rigor: a proven statistical engine and audience targeting trusted at the largest programmes.
- Server-side and full-stack testing: experiments reach beyond markup, into pricing, search, and back-end logic.
- Feature flags in the same product: web experiments and controlled feature rollouts run together.
- Enterprise data stack integrations: connects to warehouses, CDPs, and analytics platforms out of the box.
Where Optimizely hits its ceiling for an eCommerce store
- Enterprise pricing and procurement: custom contracts and no free trial, priced well above mid-market testing tools.
- Developer dependency: full-stack tests need engineers, and even visual tests reward technical staff.
- No native Shopify integration: checkout experiments require custom work and glue code.
- Low eCommerce focus: no product, cart, or checkout templates, and no revenue per visitor as a native metric.
What AB Tasty and Optimizely cannot do for an eCommerce store
AB Tasty and Optimizely are both real testing platforms, and they share the same gap for a store. Both run credible A/B tests, but neither is built around the surfaces where eCommerce revenue is won or lost, product pages, cart, and checkout, or around the metric that actually matters to a store: revenue per visitor, not a generic click or a top-of-funnel conversion.
AB Tasty is oriented towards marketing website experimentation and feature management. It has no native Shopify integration and no eCommerce-specific templates, so a team testing a Shopify store has to build the checkout integration by hand and cannot run revenue-focused experiments natively on product and cart flows. The post-merger reshuffle has also moved parts of the offering, including server-side testing, into paid modules.
Optimizely is built for enterprise engineering and product teams managing large experiment programmes across many services. It is not designed for eCommerce revenue workflows and has no native Shopify integration or checkout templates either. Operating it for Shopify CRO means substantial developer involvement, custom integration work, and an enterprise contract before the first test ships.
The two ceilings are different in tone but the same in shape. AB Tasty stops at a no-code marketing test that never reaches the Shopify checkout. Optimizely stops at an enterprise experiment that needs a developer sprint before it touches the cart. Neither is built around the Customer Value Optimization question: whether the result holds for repeat, high-value buyers rather than a first-session visitor. For the wider debate on how to interpret behavioural data before choosing a testing platform, see Has personalization replaced A/B testing?
The deeper issue is that both tools optimise the execution of a generic web test. They can prove a click moved, but they cannot say whether the store actually made more money. Omniconvert Explore is built on the other side of that gap: experiments run natively on the Shopify product, cart, and checkout, and outcomes are measured in revenue per visitor and order rate. The insight, the experiment, and the revenue metric live in one platform, on the surfaces that carry the store's revenue.
eCommerce conversion rate optimization (CRO) is the practice of running controlled experiments on the revenue surfaces of an online store, product pages, cart, and checkout, and measuring the result in revenue per visitor and order rate rather than generic conversion rate. Omniconvert Explore is defined as an eCommerce conversion rate optimization platform for product, cart, and checkout experiments, native to Shopify and priced for store traffic.
What neither tool can tell an eCommerce team
- Did the win move revenue and margin. Whether a change raised revenue per visitor and order rate, and held margin once discounts and returns are counted, not just moved a click or a micro-conversion.
- Which surface to test first. Which pages in the funnel (product, cart, checkout) carry the highest revenue impact if tested next.
- How it behaves in checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without engineering glue work.
- Whether it holds for valuable customers. Whether the result holds for repeat, high-CLV buyers, the Customer Value Optimization question, not just first-session visitors.
Omniconvert benchmarks more than 7,000 eCommerce websites in its CROBenchmark Report 2026, across 248+ audit criteria. The data shows where stores actually lose orders: 99.6% fail to make guest checkout visible and prominent, 94.2% never show checkout progress, and 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
A generic web test in AB Tasty or Optimizely can prove a hero image moved a click, but it cannot reach that checkout step, price the loss, or read the fix in revenue per visitor. Explore runs the experiment on the store's real revenue surfaces and reports the outcome in the metric a store actually cares about.
This is what web-testing platforms leave on the table. A variant that lifts a hero-image click can leave the bank balance flat; what moves it is order rate and average order value along the product-to-checkout path, read as revenue per visitor. Explore optimises for that number directly, and because Customer Value Optimization ties each result back to repeat, high-CLV buyers, the lift it confirms is margin the store keeps rather than traffic it rents. A variant that wins on revenue per visitor and holds for high-CLV customers protects profit; a variant that only lifts a landing-page click often does not. Explore also reaches Shopify-specific levers most testing tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
AB Tasty vs Optimizely vs Explore: the capability comparison
Side by side, the three tools sit at different points on the testing spectrum. AB Tasty is a marketing-friendly visual testing suite. Optimizely is an enterprise A/B testing platform with full-stack rigor. Explore adds native Shopify experiments on product, cart, and checkout, and measures the outcome in revenue per visitor. See A/B testing with Explore for how those experiments run natively on the Shopify funnel.
| Capability | AB Tasty | Optimizely | Omniconvert Explore |
|---|---|---|---|
| Primary function | Web A/B testing and personalisation for marketers | Enterprise A/B testing and feature management | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor and feature flags | Yes visual editor and full-stack | Yes visual plus code editor |
| Multivariate testing | Yes | Yes | Yes |
| Server-side testing | Partial via a paid add-on module | Yes full-stack native | Yes |
| Visual editor | Yes mature no-code editor | Yes less intuitive, technical staff help | Yes built for marketers |
| On-site surveys and overlays | Partial personalisation widgets, no dedicated surveys | No testing platform only | Yes surveys and overlays built in |
| Shopify integration | Medium installs, no checkout testing | Low no native, custom build required | Yes native |
| eCommerce focus | Medium works for stores, not built for them | Low enterprise-generic, not eCommerce | High built for store revenue workflows |
| Revenue per visitor measurement | No generic conversion metrics only | No generic conversion metrics only | Yes revenue per visitor and order rate native |
| Pricing model | Custom, contact sales, free trial available | Custom enterprise, contact sales, no free trial | Session-based, built for store traffic, free trial |
| Best for | Marketing teams wanting testing plus feature flags | Enterprise engineering and product programmes | Shopify and eCommerce teams optimising for revenue |
AliveCor used Omniconvert Explore to run a structured A/B testing program and achieved +21% conversion rate, +5% revenue per visitor, and 94% statistical relevance across their experiments. [Omniconvert, AliveCor case study]
Competitor ratings, pricing, and plan details reflect publicly listed figures as of 2026 and can change; AB Tasty pricing and packaging has been reorganised since the 2025 VWO merger. Explore uses session-based pricing; see the Omniconvert pricing page for current plans.
Get the full CROBenchmark data behind these stats: 7,000+ websites, 15+ industries, 248+ audit criteria, 100+ CRO experts. See exactly where eCommerce growth teams are losing margin in 2026.
Get the CROBenchmark ReportFrequently Asked Questions
Should you choose Explore over AB Tasty or Optimizely?
Decide by shape and scale. If a marketing team wants no-code testing plus feature flags for a website, AB Tasty fits. If an enterprise engineering programme runs hundreds of concurrent tests across web and server, Optimizely fits. For a Shopify store, run your next test on the product-to-checkout path in Explore, measured in revenue per visitor. That is the surface neither web-testing platform is built to touch.
AB Tasty and Optimizely are both credible testing platforms with real strengths. AB Tasty is the marketer's no-code suite, now bundled with the VWO group. Optimizely is the enterprise engineering standard, deep on full-stack testing and feature flags.
The question for a store is narrower: once the visual test is designed, can it run natively on the Shopify product, cart, and checkout, and can it read the outcome in revenue per visitor rather than a generic click. That is the surface Explore is built for.
Stop guessing.
Start testing what moves revenue.
Explore runs A/B, multivariate, and personalization experiments on your product pages, cart, and checkout, then measures the outcome in revenue per visitor, not just clicks.