Crazy Egg vs Hotjar vs Explore (2026): Where Shopify Revenue Is Won
Crazy Egg is a heatmap and session recording tool with basic two-variant A/B testing. Hotjar is a behavior analytics tool for heatmaps, recordings, and surveys, with no built-in A/B testing. 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.
- Crazy Egg is a heatmap and session recording tool with basic two-variant A/B testing, and a 4.2 out of 5 G2 rating. [G2, 2026]
- Hotjar is a behavior analytics tool for heatmaps, recordings, and surveys with no built-in A/B testing, and a 4.3 out of 5 G2 rating. [G2, 2026]
- Both are diagnosis tools: they show where users struggle but stop short of running real experiments on the store funnel.
- Neither runs multivariate or checkout experiments or measures results in revenue per visitor, the surfaces where store revenue is decided.
- Omniconvert Explore pairs those diagnostics with a full experimentation engine on product, cart, and checkout, measured in revenue per visitor: pick it for Shopify revenue surfaces.
Teams comparing Crazy Egg vs Hotjar are usually choosing a behavior analytics tool: something to show where visitors click, scroll, and drop off. Crazy Egg leads with heatmaps and adds a light two-variant test. Hotjar leads with recordings and surveys. Both are strong at diagnosis, but neither is built around the surfaces where a Shopify store actually wins or loses revenue: the product page, the cart, and the checkout. This page covers what each does well, the gap they share, and when Omniconvert Explore is the right layer.
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 users click, scroll, and engage on a page, and includes a basic two-variant test in every plan at a low price point. It is accessible to non-technical marketers. [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 easy to see for teams without an analyst, at an entry price that starts around $49 per month.
The A/B testing it includes is deliberately simple: single-page, two-variant tests. That suits a marketer who wants to try one headline against another, not a program of experiments across a 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 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.
- Low entry price: accessible plans that small businesses can start on quickly.
- 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, server-side testing, or 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 is Hotjar, and what is it actually good at?
Hotjar is a behavior analytics tool. It shows how visitors actually use a page through heatmaps, session recordings, funnels, on-site surveys, and feedback widgets. It makes qualitative behavior easy to see for non-technical teams, and it installs on almost any site with a script or app. [G2, 2026]
Hotjar is a diagnostics tool with a deeper feedback layer than Crazy Egg. It holds a 4.3 out of 5 rating on G2 across 342 reviews. [G2, 2026] Its strength is answering where and why: where users struggle, and what they say when a survey asks them directly.
What Hotjar does not do is run any A/B test at all. It cannot create variants, split traffic, or calculate significance, so it observes and describes behavior rather than proving a fix. Many teams pair it with a separate testing tool for that reason.
Behavior analytics captures how visitors interact with a page, through heatmaps, recordings, and surveys, so a team can see friction and hear feedback. Hotjar does this well for general websites. It is a diagnosis layer, distinct from running a controlled revenue experiment on product, cart, and checkout pages.
Where Hotjar is genuinely strong
- Rich recordings and heatmaps: a mature, widely adopted view of on-page behavior.
- On-site surveys and feedback: collect the why directly from visitors on the page.
- Funnels and drop-off views: see where users leave a multi-step flow.
- Easy install, approachable UI: quick to deploy and usable by non-technical teams.
Where Hotjar hits its ceiling for an eCommerce store
- No A/B testing: it cannot create variants, split traffic, or measure statistical significance.
- Diagnosis, not validation: it shows a problem but cannot prove that a change fixed it.
- No native Shopify experimentation: installs via script or app, with no checkout-level testing.
- No revenue experiments: it has no concept of revenue per visitor as a tested outcome.
What Crazy Egg and Hotjar cannot do for an eCommerce store
Crazy Egg and Hotjar are both behavior analytics tools, and they share the same gap for a store. Both show where visitors struggle, but 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.
Crazy Egg shows clicks and scrolls and adds a simple two-variant test, but that test cannot reach the Shopify cart or checkout, and it has no multivariate or server-side capability. It diagnoses on the surface and experiments only at the edges. Revenue per visitor is not a metric it reports.
Hotjar goes deeper on recordings and surveys but runs no A/B test at all. It is pure diagnosis: it can show you a shopper abandoning the cart and let them tell you why, but it cannot test the fix or measure order rate. Both tools stop at the point where a store needs to act.
The two gaps are the same gap at different depths, and both stop short of the store's revenue. These are analytics tools; they see the friction but cannot run the controlled experiment that proves a fix. Neither is built around the Customer Value Optimization question: whether a result holds for high-value, repeat buyers. For the wider debate behind acting on behavior data, see Has personalization replaced A/B testing?
The deeper issue is that seeing a problem and proving a fix live in separate tools. A team reads a heatmap or a recording, forms a hunch, then needs a real testing platform to validate it on the surface that matters. Omniconvert Explore collapses that loop: heatmaps, session recordings, and surveys sit next to a full experimentation engine, and the same behavioral and customer data defines the segments you test against. The insight and the test live in one place, on the store's real revenue surfaces, which is the difference between watching a problem 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 revealed a click or a drop-off.
- 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 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
A heatmap can show shoppers stalling on that checkout step, but it cannot test the fix or price the loss. 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 where Shopify revenue is won. A recorded rage-click or a lifted micro-conversion 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 Crazy Egg and Hotjar 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.
Crazy Egg vs Hotjar vs Explore: the capability comparison
Side by side, the three tools sit at different points from diagnosis to action. Crazy Egg shows behavior and runs a light test. Hotjar shows behavior in more depth with surveys. Explore adds native Shopify experiments, heatmaps, recordings, 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 | Crazy Egg | Hotjar | Omniconvert Explore |
|---|---|---|---|
| Primary function | Heatmaps with basic A/B testing | Behavior analytics and surveys | eCommerce CRO on product, cart, and checkout |
| A/B testing | Partial basic two-variant, single page | No analytics only, no variants | Yes visual plus code editor |
| Multivariate testing | No | No | Yes |
| Server-side testing | No | No | Yes |
| Heatmaps and session recordings | Yes its core strength | Yes its core strength | Yes built in beside the experiment |
| On-site surveys and overlays | No heatmaps and recordings only | Partial surveys yes, no test overlays | Yes surveys and overlays built in |
| Shopify integration | Medium installs but no checkout testing | Medium installs but no experimentation | Yes native |
| eCommerce focus | Low small-business diagnostics | Medium UX diagnostics on stores | High built for store revenue workflows |
| Revenue per visitor measurement | No behavioral metrics only | No behavioral metrics only | Yes revenue per visitor and order rate native |
| Pricing model | Session-based, from $49/mo, free trial | Freemium, paid from about $32/mo | Session-based, built for store traffic, free trial |
| Best for | Small teams wanting heatmaps and light tests | Teams diagnosing where users struggle | Shopify and eCommerce teams optimizing 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. Both Crazy Egg and Hotjar are behavior analytics tools rather than full experimentation platforms. 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 Crazy Egg or Hotjar?
Decide by whether you need to act on what you see. If you only want low-cost heatmaps and recordings, Crazy Egg or Hotjar will do the diagnosis. But diagnosis alone does not move revenue. For a Shopify store, run your next test on the product-to-checkout path in Explore, with heatmaps and surveys beside it, measured in revenue per visitor. Explore turns the behavior you observe into a proven, revenue-measured change.
Crazy Egg and Hotjar are both capable behavior analytics tools. Crazy Egg is a low-cost heatmap tool with a light test. Hotjar is a deeper recording and survey suite used across many websites.
The question for a store is narrower: once you can see where shoppers struggle, can you run a controlled experiment on the Shopify product, cart, and checkout and read the result in revenue per visitor. 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, with heatmaps and surveys beside them, then measures the outcome in revenue per visitor, not just clicks.