AB Tasty vs Croct vs Explore (2026): The Shopify Testing Gap
AB Tasty is a no-code web experimentation and personalization platform, now part of VWO after the 2025 merger. Croct is a developer-first testing platform built for React and Next.js apps. Omniconvert Explore is the Shopify-native eCommerce CRO platform: it runs experiments on product pages, cart, and checkout, and measures the result in revenue per visitor.
- AB Tasty is a no-code web experimentation and personalization platform, now part of VWO after the 2025 merger, with a 4.5 out of 5 G2 rating. [G2, 2026]
- Croct is a developer-first A/B testing and personalization platform built for React and Next.js apps, with a 4.7 out of 5 G2 rating. [G2, 2026]
- AB Tasty serves marketing teams; Croct serves frontend engineers, so they rarely compete for the same buyer.
- Neither is native to a standard Shopify Liquid theme, neither runs out-of-box checkout experiments, and neither reports results in revenue per visitor.
- Omniconvert Explore runs native Shopify experiments on product, cart, and checkout and measures them in revenue per visitor: pick it for store revenue surfaces.
Teams comparing AB Tasty vs Croct are usually choosing between a no-code web testing suite for marketing teams and a code-first testing platform for engineers. AB Tasty leads with a visual editor and feature flags inside the VWO group. Croct leads with React and Next.js component-level testing for headless storefronts. Neither is built around the surfaces where a Shopify store wins or loses revenue: the product page, the cart, and the checkout, which is where Omniconvert Explore sits.
What is AB Tasty, and what is it actually good at?
AB Tasty is a no-code web experimentation and personalization platform popular with marketing teams. It bundles A/B testing with feature flags and a mature visual editor, and merged with VWO in 2025, which expanded features and support. [AB Tasty, 2026]
AB Tasty holds a 4.4 out of 5 rating on G2 across 424 reviews. [G2, 2026] Its strength is that a marketing team can build a visual test, segment an audience, and roll out a feature flag without filing an engineering ticket, which is why it has a loyal following in mid-market marketing teams.
The category it sits in is marketing-team experimentation. It is designed to make A/B testing and feature releases accessible to non-developers on a general website. That is the point of the product.
No-code experimentation lets a non-developer build, launch, and measure a test through a visual editor and audience rules, rather than through code. AB Tasty is built around this model. It is a separate concern from whether a test runs natively on a Shopify store's checkout surface.
Where AB Tasty is genuinely strong
- Mature no-code visual editor: a marketing team can build and ship a test without engineering time.
- Feature flags beside tests: experiments and releases share one platform, useful for coordinated rollouts.
- VWO backing since 2025: wider customer-support resources and roadmap scale after the merger.
- Multivariate and advanced targeting: capable experimentation with granular audience rules.
Where AB Tasty hits its ceiling for an eCommerce store
- Roadmap reshuffled post-merger: direction and pricing are less predictable since the move into VWO.
- Server-side testing is a paid add-on: it lives in a separate enterprise module, not the base plan.
- No native Shopify integration: no checkout-level experiment templates for the Shopify funnel.
- Marketing-site shaped: designed around general web pages, not the product-to-checkout path.
- Generic conversion focus: no built-in revenue per visitor metric.
What is Croct, and what is it actually good at?
Croct is a personalization and A/B testing platform built specifically for React and Next.js applications. It integrates at the component level, so experiments and personalization live inside frontend code. It is popular with headless eCommerce engineering teams. [G2, 2026]
Croct holds a 4.7 out of 5 rating on G2 across 47 reviews, one of the highest-rated tools in its niche. [G2, 2026] Its strength is a developer-first API: frontend engineers wire experiments directly into React components, with feature flags and personalization in the same place.
The category it sits in is component-level experimentation for modern JavaScript frameworks. It is built for teams who own a React or Next.js codebase and want testing inside it, not for marketing operators or standard Shopify Liquid themes.
Component-level testing means an experiment or personalization variant is configured in frontend code at the boundary of a UI component, rather than by overlaying JavaScript on top of a rendered page. Croct is built around this model. It is a separate concern from whether a non-developer can configure the same test, and from whether the test reaches the Shopify checkout.
Where Croct is genuinely strong
- Native React and Next.js integration: experiments live inside the component tree, not in a tag on top of it.
- Developer-first API: feature flags, personalization, and testing in code, with clean typing and tooling.
- Server-side testing supported: results do not depend on client-side flicker or late-loading scripts.
- Strong fit for headless eCommerce: natural for Next.js storefronts built on commerce APIs.
Where Croct hits its ceiling for an eCommerce store
- React or Next.js only: cannot run on a standard Shopify Liquid theme without a headless migration.
- No visual editor: every experiment is a code change and a pull request.
- Not usable by marketing teams independently: each test needs frontend-engineering time.
- No multivariate testing: A/B variants only, no multi-factor designs.
- No native checkout experiment flow: the Shopify checkout stays out of reach without custom work.
What AB Tasty and Croct cannot do for an eCommerce store
AB Tasty and Croct target different buyers, marketing teams and frontend engineers, but they share one gap for a Shopify store. Neither is built around the surfaces where eCommerce revenue is won or lost, product pages, cart, and checkout, or around the metrics that matter there: revenue per visitor, order rate, and the margin a store actually keeps.
AB Tasty is oriented towards marketing-site experimentation and feature management. There is no native Shopify integration, so a store team builds its own checkout connections by hand, and revenue-focused experiments on product pages and cart flows are not a native capability. The platform is primarily marketing-site shaped, not store shaped.
Croct is built for React and Next.js developers, and does not run on a standard Shopify Liquid theme without a headless rebuild. There is no visual editor, so every experiment is a code change. A team on a standard Shopify store simply cannot pick it up as a day-to-day testing layer.
The two gaps are different in nature but point to the same missing layer. Most experimentation tools optimize the execution of a test on a generic page or inside a specific framework. They are not built around the Shopify funnel where orders are actually placed, or around the Customer Value Optimization question: whether a result holds for high-value, repeat buyers. For the wider debate behind acting on test data, see Has personalization replaced A/B testing?
There is a second gap underneath the first: the data insights layer that tells a store what to test and whether it moved revenue. AB Tasty has strong experimentation and feature-flag workflows but no native heatmaps or session recordings; Croct's output is a tested React variant, not an answer to where to point the next experiment on the Shopify funnel. Omniconvert Explore builds that insight layer in: heatmaps, session recordings, and on-site surveys sit next to the experiment, and the same behavioral and customer data defines the audiences you test against. The insight and the test live in one place, on the store's real revenue surfaces, which is the difference between running a test and proving the fix moved revenue per visitor.
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 its margin once discounts and returns are counted, not just lifted a click or a feature-flag release metric.
- 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-value customers, 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, and 94.2% never show checkout progress steps in the flow. [CROBenchmark Report 2026, Omniconvert]
These are checkout-surface problems. A marketing-team visual editor or a React component test cannot reach them without an integration layer the tool does not provide. Explore runs the experiment on the store's real revenue surfaces and reports the outcome in revenue per visitor.
This is what the title means by the Shopify testing gap. A lifted click or a successful feature-flag rollout 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 optimizes for that number directly, and because Customer Value Optimization ties each result back to repeat, high-value 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 top-of-funnel click often does not. That is the revenue question AB Tasty and Croct are not built to answer, and the one Omniconvert Explore is. 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 Croct vs Explore: the capability comparison
Side by side, the three tools serve different buyers. AB Tasty gives marketing teams a no-code suite for web tests and feature flags. Croct gives engineers a React and Next.js layer for component-level tests. Explore adds native Shopify experiments, built-in surveys and overlays, and revenue-per-visitor measurement on the product-to-checkout path. See A/B testing with Explore for how those experiments run natively on the Shopify funnel.
| Capability | AB Tasty | Croct | Omniconvert Explore |
|---|---|---|---|
| Primary function | No-code web A/B testing and feature flags | React and Next.js component-level testing | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor and feature flags | Partial React and Next.js only, no visual editor | Yes visual plus code editor |
| Multivariate testing | Yes | No | Yes |
| Server-side testing | Partial separate paid add-on | Yes | Yes |
| Visual editor | Yes mature no-code editor | No code only | Yes visual plus code |
| On-site surveys and overlays | Partial widget library, limited survey engine | No personalization in code, no survey layer | Yes surveys and overlays built in |
| Shopify integration | Medium installs but no native checkout | Low requires React or Next.js, not Liquid | Yes native |
| eCommerce focus | Medium marketing-first, store-second | Low framework-first, headless only | High built for store revenue workflows |
| Revenue per visitor measurement | No generic conversion metrics | No component-level metrics | Yes revenue per visitor and order rate native |
| Pricing model | Custom, contact sales, free trial | Usage-based, free tier available | Session-based, built for store traffic, free trial |
| Best for | Marketing teams wanting testing and feature flags | Engineering teams on React or Next.js headless builds | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.4 out of 5 (G2, 424 reviews, as of 2026) | 4.7 out of 5 (G2, 47 reviews, as of 2026) | 4.6 out of 5 (G2, 197 reviews, as of 2026) |
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 is now part of the VWO group. 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 Croct?
Decide by stack and team. If a React or Next.js engineering team runs everything in code, keep Croct. If marketing-team no-code testing with feature flags is the core requirement, AB Tasty remains an option. For a Shopify store that needs product, cart, and checkout experiments measured in revenue per visitor, run the next test in Explore. The three solve different jobs, but only Explore is built for the Shopify revenue path.
AB Tasty and Croct are both capable within their lanes. AB Tasty gives marketing teams a mature no-code visual editor with feature management, now backed by the wider VWO organization. Croct gives frontend engineers component-level control inside React and Next.js, which is a genuine advantage on a headless storefront.
The question for a Shopify store is narrower: can your team run a controlled experiment on the product, cart, and checkout, and read the result in revenue per visitor rather than a click. Neither tool is built around that answer. Explore is.
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.
4.6 out of 5 across 197 reviews, G2 , as of 2026