AB Tasty vs Crazy Egg vs Explore (2026): Testing Without Shopify Checkout
AB Tasty is a marketing experimentation and personalization platform that merged with VWO in 2025, with A/B testing, feature flags, and a strong no-code editor. Crazy Egg is a heatmap tool with basic two-variant A/B testing. Omniconvert Explore is the Shopify-native eCommerce CRO platform: it runs product, cart, and checkout experiments measured in revenue per visitor.
- AB Tasty is an enterprise marketing-site experimentation and feature-flag platform (merged with VWO in 2025), with a strong no-code editor and a 4.5 out of 5 G2 rating. [G2, 2026]
- Crazy Egg is a heatmap and session recording tool with basic two-variant A/B testing from around $49 per month, and a 4.2 out of 5 G2 rating. [G2, 2026]
- The two tools sit at opposite ends of the market, but share one gap: neither is built for Shopify product, cart, and checkout experiments.
- Neither reports results in revenue per visitor, and neither offers native Shopify checkout templates, so revenue questions get answered in custom calculated metrics or not at all.
- Omniconvert Explore pairs native Shopify experimentation with heatmaps, recordings, and surveys, measured in revenue per visitor: pick it when the next test has to reach the checkout.
Teams comparing AB Tasty vs Crazy Egg are usually trying to pick a testing tool: one with a full visual editor and feature flags, the other with heatmaps and a light A/B test tacked on. AB Tasty suits marketing teams running experiments across web pages. Crazy Egg suits small teams watching clicks and scrolls on a budget. Neither is built around the Shopify product, cart, and checkout funnel, which is where Omniconvert Explore fits.
What is AB Tasty, and what is it actually good at?
AB Tasty is a web experimentation and personalisation platform that merged with VWO in 2025. It combines A/B testing, feature flags, and personalization in one platform, with a strong no-code visual editor and multivariate testing support. It is popular with marketing teams that want to run experiments without constant developer involvement. [AB Tasty, 2026]
AB Tasty is one of the more established tools in the category, with a 4.4 out of 5 rating on G2 across 424 reviews. [G2, 2026] Its position rests on bundling three jobs that used to live in separate tools: web A/B testing, feature management, and on-site personalization, all behind one editor and one audience model.
The post-merger reality has expanded the roadmap but also reorganized it. Server-side testing now sits in a separate paid module rather than in the core product, and pricing is quote-based rather than listed, which is why many evaluations here are driven by sales conversations rather than a self-service trial.
A feature flag is a runtime switch that controls whether a piece of code or UI is on for a given visitor, so teams can release features gradually and roll them back without a deploy. AB Tasty pairs this with its testing engine, which is a release-management layer. It is distinct from running a controlled revenue experiment on product, cart, and checkout pages.
Where AB Tasty is genuinely strong
- Testing plus feature flags in one platform: ship a feature flagged and measure it as an experiment without a second tool.
- No-code visual editor: marketing teams build and launch variants without developer time.
- Personalization engine: audience segments drive both tests and tailored content on the same site.
- Enterprise support: an account team, implementation help, and a mature customer success program after the VWO merger.
Where AB Tasty hits its ceiling for an eCommerce store
- Server-side testing is modular: advanced server-side experiments require a separate paid add-on, not the core plan.
- Shopify integration is limited: no native checkout experimentation and no store-specific experiment templates.
- Marketing-site orientation: templates and defaults assume a corporate or marketing website, not a product-to-checkout funnel.
- No revenue-per-visitor native metric: no concept of revenue per visitor as a built-in experiment outcome.
What is Crazy Egg, and what is it actually good at?
Crazy Egg is a heatmap and session recording tool with lightweight A/B testing. It shows where visitors click, scroll, and engage on a page, and includes a basic two-variant test on every plan at an entry price around $49 per month. It is accessible to non-technical marketers on small sites. [Crazy Egg, 2026]
Crazy Egg is a behavior analytics tool first and a testing tool second. It holds a 4.2 out of 5 rating on G2 across 144 reviews. [G2, 2026] Its strength is making click, scroll, and engagement data readable for teams that do not have an analyst on staff, at a price point that fits a small business.
The A/B testing that comes with it is deliberately simple: single-page, two-variant tests, no multivariate, no server-side, no advanced audience targeting. That fits a marketer testing a headline, not a program of experiments across a store funnel.
A heatmap aggregates where visitors click, move, and scroll on a page into a visual overlay, so a team can see attention and friction at a glance. Crazy Egg does this well and pairs it with session recordings. It is a diagnosis layer, distinct from running a controlled revenue experiment on product, cart, and checkout pages.
Where Crazy Egg is genuinely strong
- Heatmaps and scroll maps: a clear, visual read on where clicks and attention land.
- Session recordings: watch real sessions to see where users hesitate on a page.
- Low entry price: accessible plans that small teams can start on without a procurement cycle.
- Basic A/B testing included: a simple two-variant test in every plan for light experiments.
Where Crazy Egg hits its ceiling for an eCommerce store
- Testing is basic: no multivariate testing, no server-side testing, no advanced audience targeting.
- No checkout experiments: it cannot run tests on Shopify product, cart, or checkout flows.
- Analytics first: teams serious about CRO outgrow its experiment features quickly.
- Generic conversion focus: no concept of revenue per visitor as a tested outcome.
What AB Tasty and Crazy Egg cannot do for an eCommerce store
AB Tasty and Crazy Egg sit at opposite ends of the testing market, enterprise marketing-site experimentation and small-business heatmaps, 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 website experimentation and feature management. Its templates and defaults assume a corporate or marketing page; its Shopify integration is medium at best, with no native checkout experiment templates. Teams using it for Shopify CRO end up building checkout integrations by hand and running revenue-focused experiments against custom calculated metrics rather than native ones.
Crazy Egg is a heatmap and session recording tool first. Its A/B test is single-page and two-variant, so it cannot reach the Shopify cart or checkout, has no multivariate or server-side option, and reports clicks and scrolls rather than revenue. It diagnoses on the surface and experiments only at the edges. For the wider debate behind acting on behavior data, see Has personalization replaced A/B testing?
The two gaps meet in the same place: neither tool is built around the Shopify revenue funnel. One is a general-purpose experimentation suite that treats a store like any other site; the other is an analytics tool with a light test. Platforms like Omniconvert Explore sit between them: a full experimentation engine with heatmaps, session recordings, and surveys beside it, running natively on product, cart, and checkout, and reading the result in revenue per visitor rather than clicks.
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. 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 micro-conversion.
- Which surface to test first. Which pages in the funnel (product, cart, checkout) carry the highest revenue impact if tested next, read against real benchmarks.
- 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, 94.2% do not show checkout progress steps, and 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
A feature flag on a hero banner, or a heatmap of a landing page, cannot test or price any of those losses. Explore runs the experiment on the store's real revenue surfaces and reports the outcome in revenue per visitor, not clicks. Explore also reaches Shopify-specific levers most testing tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
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]
AB Tasty vs Crazy Egg vs Explore: the capability comparison
Side by side, the three tools sit at different points on the stack. AB Tasty bundles testing, feature flags, and personalization for marketing sites. Crazy Egg bundles heatmaps and recordings with a light test. Explore bundles native Shopify experiments, heatmaps, recordings, surveys, and overlays, and reads results in revenue per visitor 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 | Crazy Egg | Omniconvert Explore |
|---|---|---|---|
| Primary function | Marketing-site experimentation and feature flags | Heatmaps with basic A/B testing | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor and feature flags | Partial basic two-variant, single page | Yes visual plus code editor |
| Multivariate testing | Yes | No | Yes |
| Server-side testing | Partial paid add-on only | No | Yes |
| Visual editor | Yes strong no-code editor | No | Yes |
| On-site surveys and overlays | Partial overlays yes, no native surveys | No heatmaps and recordings only | Yes surveys and overlays built in |
| Shopify integration | Medium installs but no checkout testing | Low installs but no checkout testing | Yes native |
| eCommerce focus | Medium marketing-site orientation | Low small-business diagnostics | High built for store revenue workflows |
| Pricing model | Custom, contact sales, free trial | Session-based, from $49/mo, free trial | Session-based, built for store traffic, free trial |
| Best for | Marketing teams combining testing with feature flags | Small teams wanting heatmaps and light tests | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.4 out of 5 (G2, 424 reviews, as of 2026) | 4.2 out of 5 (G2, 144 reviews, as of 2026) | 4.6 out of 5 (G2, 197 reviews, as of 2026) |
Competitor ratings, pricing, and plan details reflect publicly listed figures as of 2026 and can change. AB Tasty is positioned for marketing-site experimentation; Crazy Egg is a heatmap tool with light testing. 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 Crazy Egg?
Decide by whether your testing has to reach the Shopify checkout. If your scope is marketing websites with lots of feature-flag releases, AB Tasty works well; if you want cheap heatmaps and a headline test, Crazy Egg does the job. For a store that needs to prove a fix on product pages, cart, or checkout and read it in revenue per visitor, run that test in Explore.
AB Tasty is a capable enterprise experimentation and feature-management platform. Crazy Egg is a capable entry-level heatmap tool with light testing. Both are useful inside the scopes they were designed for.
The question for a Shopify store is narrower: can the tool run a controlled experiment on the product, cart, and checkout flow natively, and report the result in revenue per visitor. That is the surface Explore is built for, with heatmaps and surveys beside the experiment rather than in a second tool.
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