Crazy Egg vs Eppo vs Explore (2026): Two Testing Tools, One Blind Spot
Crazy Egg is a heatmap and session recording tool with a light two-variant A/B test. Eppo is a warehouse-native experimentation platform for data teams with Snowflake or BigQuery. 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 a light two-variant A/B test, and a 4.2 out of 5 G2 rating. [G2, 2026]
- Eppo is a warehouse-native experimentation platform for data teams with Snowflake or BigQuery, and a 4.7 out of 5 G2 rating. [G2, 2026]
- The two tools sit at opposite ends: Crazy Egg is marketer-first diagnosis with a light test; Eppo is data-team-only warehouse analysis.
- Neither runs marketer-accessible experiments on Shopify product, cart, or checkout, and neither reports outcomes in revenue per visitor.
- Omniconvert Explore runs A/B, multivariate, and server-side experiments on Shopify with heatmaps and surveys beside them, measured in revenue per visitor: pick it for store revenue surfaces.
Teams comparing Crazy Egg vs Eppo are usually caught between two very different problems. Crazy Egg is a heatmap-first analytics tool with a light two-variant test, aimed at marketers. Eppo is a warehouse-native experimentation platform built for a data engineering team. Neither is built around the Shopify surfaces where store revenue is actually decided, and that is where Omniconvert Explore fits.
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 suits 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 wanting to try one headline against another, 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.
- 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 Eppo, and what is it actually good at?
Eppo is a warehouse-native experimentation platform. It connects directly to Snowflake, BigQuery, Redshift, and similar warehouses for experiment analysis using your existing metric definitions. It is built for data and engineering teams running high-velocity programs with strong data governance. [Eppo, 2026]
Eppo is an experimentation tool built for organizations with mature data infrastructure. It holds a 4.7 out of 5 rating on G2 across 80 reviews. [G2, 2026] Its strength is rigor: it applies advanced statistical methods to experiments defined in a data warehouse, and it fits teams shipping tens or hundreds of tests a year with strong governance.
Where Crazy Egg leads with visual behavior, Eppo leads with rigorous analysis of experiment results connected to warehouse data. Pricing is custom and quoted through sales, so it slots into enterprise budgets rather than small-team plans.
Warehouse-native experimentation runs experiment analysis directly against a data warehouse like Snowflake or BigQuery, using the metrics a data team already trusts. Eppo does this well for a mature data organization. It is a delivery and analysis layer, distinct from running a controlled experiment on the visual surfaces of a store: product, cart, and checkout.
Where Eppo is genuinely strong
- Warehouse-native connections: direct integration with Snowflake, BigQuery, Redshift, and similar warehouses.
- Rigorous statistics: advanced methods for teams running high-velocity experimentation programs.
- Metric reuse: experiments run against the metric definitions the data team already curates.
- Strong governance: built for organizations managing experimentation across many product teams.
Where Eppo hits its ceiling for an eCommerce store
- No visual editor: variants require code changes, not a marketer-accessible UI.
- Requires warehouse infrastructure: needs Snowflake or a similar warehouse most stores do not run.
- Enterprise pricing: custom, contact-sales pricing that is out of reach for small and mid-market stores.
- No native Shopify experiments: cannot run marketer-accessible tests on Shopify product pages, cart, or checkout.
What Crazy Egg and Eppo cannot do for an eCommerce store
Crazy Egg and Eppo sit at opposite ends of the experimentation spectrum but share the same gap for a store. One is a marketer-friendly heatmap with a light test; the other is a data-team-only warehouse tool. Neither runs revenue-per-visitor tests on Shopify product, cart, and checkout.
Crazy Egg's angle is behavior first. Heatmaps and recordings show where visitors click, scroll, and hesitate, and a light two-variant test in every plan lets a marketer swap a headline. That test cannot reach the Shopify cart or checkout, run multivariate tests, or run server-side experiments.
Eppo's angle is analysis first. It demands warehouse data and technical implementation, then applies rigorous statistics to experiments already defined by engineers. There is no visual editor and no path to a Shopify storefront experiment for a growth or CRO lead.
The two blind spots meet at the same missing layer. Crazy Egg cannot run the storefront experiment that matters. Eppo can, but only if a data team stands between the merchant and the change.
Neither is built around the Customer Value Optimization question of whether a result holds for high-value, repeat buyers. Neither reports outcomes in revenue per visitor on the Shopify funnel. For the wider debate on acting on behavior data, see Has personalization replaced A/B testing?
Omniconvert Explore closes the gap from a different angle. It runs A/B, multivariate, and server-side experiments on Shopify product, cart, and checkout, with heatmaps, session recordings, and surveys beside them. The same platform hosts the observation, the variant, and the result, measured in revenue per visitor rather than a click or a warehouse metric detached from the storefront.
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. 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 warehouse delta detached from the store.
- 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: 94.2% never show checkout progress steps, and 85.1% do not show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
A heatmap can show shoppers stalling on that checkout step, and a warehouse experiment can confirm a delta after the fact. Neither runs the fix on the Shopify page or prices the loss in revenue per visitor. 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 two testing tools, one blind spot. A recorded rage-click, a warehouse-only lift, or a click uplift can each 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. 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 Eppo vs Explore: the capability comparison
Side by side, the three tools sit at different points. Crazy Egg is marketer-friendly heatmaps with a light test. Eppo is a warehouse-connected analysis engine. Explore adds native Shopify experiments and revenue-per-visitor measurement on the product-to-checkout path. See A/B testing with Explore.
| Capability | Crazy Egg | Eppo | Omniconvert Explore |
|---|---|---|---|
| Primary function | Heatmaps with basic A/B testing | Warehouse-native experimentation | eCommerce CRO on product, cart, and checkout |
| A/B testing | Partial basic two-variant, single page | Yes warehouse-native, no visual editor | Yes visual plus code editor |
| Multivariate testing | No | No | Yes |
| Server-side testing | No | Yes | Yes |
| Visual editor | No | No code-only workflow | Yes visual plus code editor |
| On-site surveys and overlays | No heatmaps and recordings only | No warehouse analysis only | Yes surveys and overlays built in |
| Shopify integration | Low installs but no checkout testing | Low requires warehouse infrastructure | Yes native |
| eCommerce focus | Low small-business diagnostics | Low data-team analysis | High built for store revenue workflows |
| Pricing model | Session-based, from $49/mo, free trial | Custom, contact sales, no free trial | Session-based, built for store traffic, free trial |
| Best for | Small teams wanting heatmaps and light tests | Data teams with a mature warehouse and rigorous programs | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.2 out of 5 (G2, 144 reviews, as of 2026) | 4.7 out of 5 (G2, 80 reviews, as of 2026) | 4.6 out of 5 (G2, 191 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. Crazy Egg is a behavior analytics tool with light testing; Eppo is a warehouse-native experimentation platform for data teams. 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 Eppo?
Decide by where the experiment needs to live. If you want cheap heatmaps and a light headline test, Crazy Egg is a fine starting point. If you have a mature data warehouse and a data team running the program, Eppo fits that workflow. For a Shopify store, run your next test in Explore on the product-to-checkout path, with heatmaps and surveys beside it, measured in revenue per visitor.
Crazy Egg and Eppo are both capable tools for their intended audience. Crazy Egg is a low-cost heatmap tool with a light test for marketers. Eppo is a warehouse-native analysis platform for data teams. Neither is a Shopify eCommerce CRO platform.
The question for a store is narrower: can you run a controlled experiment on the Shopify product, cart, and checkout and read the result in revenue per visitor without waiting on a data warehouse. 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.
4.6 out of 5 across 191 reviews, G2 , as of 2026