Amplitude Experiment vs Croct vs Explore (2026): The Code Gap
Amplitude Experiment is a code-based experimentation layer bolted onto Amplitude Analytics; it needs developers and the Amplitude stack. Croct runs React and Next.js tests at the component level, powerful for headless engineering teams. Omniconvert Explore is Shopify-native eCommerce CRO: it runs product, cart, and checkout experiments without code and measures the outcome in revenue per visitor.
- Amplitude Experiment is an SDK-based experimentation layer bolted onto Amplitude Analytics, with no visual editor and a 4.5 out of 5 G2 rating across 2,200 reviews. [G2, 2026]
- Croct is a React and Next.js testing and personalization SDK for frontend engineers on headless stores, with a 4.7 out of 5 G2 rating across 47 reviews. [G2, 2026]
- Both are developer-first; neither has a visual editor, and neither works on a standard Shopify Liquid theme without engineering.
- Amplitude Experiment reports results in product events and cohorts, Croct in component conversions; neither reports in revenue per visitor on the checkout path.
- Omniconvert Explore runs product, cart, and checkout experiments natively on Shopify through a visual editor, measured in revenue per visitor: pick it when marketing and CRO teams need to ship tests without engineering.
Teams comparing Amplitude Experiment vs Croct are usually Amplitude Analytics customers adding experimentation to product data, or React engineers building a headless Shopify app. Amplitude Experiment ships tests as an SDK layer tied to its analytics; Croct ships them as React components inside a Next.js app. Both are developer-first and neither has a visual editor, so marketers on a standard Shopify store cannot run a test without engineering support. This page covers what each does well, the gap they share, and when Omniconvert Explore is the right layer.
What is Amplitude Experiment, and what is it actually good at?
Amplitude Experiment is an experimentation layer that sits on top of Amplitude Analytics. It uses the same event data for targeting cohorts and reads test results next to the rest of a product-analytics stack. Tests ship through SDKs and feature flags, not a visual editor. [Amplitude, 2026]
Amplitude Experiment is a product-analytics tool first and a testing tool second. It holds a 4.5 out of 5 rating on G2 across 2,200 reviews, carried in large part by the Amplitude Analytics platform it extends. [G2, 2026] Its strength is data continuity: a cohort defined for a retention report is the same cohort available for a test, and results read in the same workspace as the rest of the product metrics.
The testing itself is SDK-based: variants ship through code, feature flags gate exposure, and server-side testing is a first-class use case. That suits a product team that already runs Amplitude and wants engineering-grade experimentation; it does not suit a marketer or CRO lead who wants to ship a product-page variant without engineering support.
Product-analytics experimentation layers A/B tests on top of an existing product-analytics platform, using the same event data for targeting and reporting. Amplitude Experiment does this well for teams that already live inside Amplitude Analytics. It is an SDK layer for engineers, distinct from running a visual, no-code revenue experiment on a Shopify product, cart, or checkout page.
Where Amplitude Experiment is genuinely strong
- Data continuity with Amplitude Analytics: experiments inherit the same events, cohorts, and funnels used across the rest of the product.
- Advanced cohort targeting: target variants by behavior defined across millions of product events, not just session attributes.
- Server-side and feature-flag testing: solid support for engineering-grade release experiments.
- Mature analytics workspace: results, metrics, and retention views all sit in one place for the product team.
Where Amplitude Experiment hits its ceiling for an eCommerce store
- No visual editor: every variant ships through code, so marketers cannot run a test without engineering.
- Requires Amplitude Analytics: the value proposition assumes the full Amplitude stack is already in place.
- No native Shopify integration: checkout and catalog experiments need custom engineering glue.
- Product events, not store revenue: outcomes read in product-analytics terms, not in revenue per visitor on the product-to-checkout path.
What is Croct, and what is it actually good at?
Croct is an A/B testing and personalization platform built for React and Next.js applications. Experiments and personalization sit at the component level in code, through a developer API, which makes it a natural fit for frontend engineers on headless stores. [G2, 2026]
Croct is a developer tool first and a marketing tool a distant second. It holds a 4.7 out of 5 rating on G2 across 47 reviews, a strong score on a small but engineering-heavy review base. [G2, 2026] Its strength is natural fit: on a Next.js store, a Croct component drops into the React tree with the same ergonomics as any other library the frontend team already uses.
Testing, personalization, and feature flags all run through code, with a usage-based pricing model that scales with the headless app rather than with store sessions. That suits an engineering team that owns the frontend and wants component-level control; it does not suit a store on a standard Shopify Liquid theme, where every variant needs a React app the store does not have.
Headless React testing runs A/B tests and personalization at the component level inside a React or Next.js application, through a developer API. Croct is a strong fit for engineering teams that have already migrated their store to a headless architecture. It is a code-first testing SDK, distinct from running a visual, no-code revenue experiment on a standard Shopify Liquid theme.
Where Croct is genuinely strong
- React and Next.js native: components drop into the frontend tree with the same ergonomics as any other React library.
- Developer-first API: A/B testing, personalization, and feature flags accessible through a single SDK the engineering team already understands.
- Server-side and component-level testing: clean separation between release flags and visitor-facing experiments.
- Usage-based pricing with a free tier: easy to start on, scales with traffic rather than seats.
Where Croct hits its ceiling for an eCommerce store
- React or Next.js only: cannot be used on standard Shopify Liquid themes without a full headless migration.
- No visual editor: every experiment ships as a code change, so marketing and CRO cannot run tests independently.
- No native checkout experiments: the Shopify checkout sits outside the React tree Croct controls.
- Not an eCommerce-first metric model: no built-in concept of revenue per visitor as a tested outcome.
What Amplitude Experiment and Croct cannot do for an eCommerce store
Amplitude Experiment and Croct are both developer-first tools; neither has a visual editor. For a standard Shopify Liquid store, that means every variant ships through engineering, and results read in product events or component conversions, not in revenue per visitor on the product-to-checkout path.
Amplitude Experiment is an add-on layer for existing Amplitude Analytics customers. It has no visual editor and requires developer implementation. It is not designed for eCommerce checkout flow experiments and cannot run product-page tests through a marketer-accessible interface.
Croct is built for React and Next.js developers and cannot be used on standard Shopify Liquid themes without significant development work. It has no visual editor and all experiments require code. Teams running a standard Shopify store cannot use Croct without migrating to a headless architecture.
The gap is the same gap. Both are built for engineers, neither for the eCommerce funnel. Most experimentation tools optimize the execution of a test; few are built around the surfaces where eCommerce revenue is won or lost.
Omniconvert Explore is built for that layer. It runs experiments on the store's real revenue surfaces, product, cart, and checkout, accessible to marketers through a visual editor. Results read in revenue per visitor and order rate, not in product events or component conversions.
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 product-event lift or a React component conversion raised revenue per visitor and order rate on the store, not just a signal inside the testing SDK.
- Which surface to test first. Which pages in the Shopify funnel (product, cart, checkout) carry the highest revenue impact if tested next, read as revenue, not as application events.
- How it behaves in checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without an engineer wiring an SDK or a React component in place.
- 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 or event-level conversions.
Omniconvert benchmarks more than 7,000 eCommerce websites in its CROBenchmark Report 2026, across 248+ audit criteria. The data shows where stores lose orders: 99.6% fail to make guest checkout prominent, and 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
A product-analytics dashboard or a React component log can show where shoppers stall. Neither can test the fix as a product-cart-checkout experiment inside a standard Shopify theme, and neither reports the result in revenue per visitor.
Explore reaches that layer. It optimizes for revenue per visitor directly, and ties each result back to repeat, high-value buyers through Customer Value Optimization. A variant that wins on revenue per visitor and holds for high-CLV customers protects 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.
Amplitude Experiment vs Croct vs Explore: the capability comparison
Side by side, these tools sit at different points on the engineering spectrum. Amplitude Experiment is an SDK layer on top of a product-analytics suite. Croct is a React component library. Explore is a Shopify-native platform with a visual editor and revenue-per-visitor measurement built in. See A/B testing with Explore for how those experiments run on the Shopify funnel.
| Capability | Amplitude Experiment | Croct | Omniconvert Explore |
|---|---|---|---|
| Primary function | Experimentation on a product-analytics stack | React and Next.js testing and personalization | eCommerce CRO on product, cart, and checkout |
| A/B testing | Partial SDK-based, requires Amplitude Analytics | Partial React and Next.js only, code-first | Yes visual plus code editor |
| Multivariate testing | No | No | Yes |
| Server-side testing | Yes SDK-based | Yes through its API | Yes |
| Visual editor | No SDK and code only | No components only | Yes no-code and code paths |
| On-site surveys and overlays | No | No | Yes surveys and overlays built in |
| Shopify integration | Low requires engineering glue | Medium headless Next.js only | Yes native |
| eCommerce focus | Low product-analytics first | Low any React site, not store-specific | High built for store revenue workflows |
| Revenue per visitor measurement | Partial via custom revenue events | No component conversions only | Yes revenue per visitor and order rate native |
| Pricing model | Seat-based, free tier, paid plans by quote | Usage-based, free tier available | Session-based, built for store traffic, free trial |
| Best for | Product teams on Amplitude Analytics | Frontend engineers on headless Next.js stores | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.5 out of 5 (G2, 2200 reviews, as of 2026) | 4.7 out of 5 (G2, 47 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. Amplitude Experiment requires Amplitude Analytics as a prerequisite; Croct requires a React or Next.js application. 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 Amplitude Experiment or Croct?
Decide by the surface and by who runs the test. If your product team lives in Amplitude Analytics and tests inside the product stack, keep Amplitude Experiment. If your store is a React or Next.js build and engineers want component-level testing, keep Croct. For a standard Shopify store where marketers ship product, cart, and checkout tests, run them on Explore, measured in revenue per visitor.
Amplitude Experiment and Croct are both capable developer tools. Amplitude Experiment pairs testing with product analytics and is strong when experiments need the same cohorts and events used across the product stack. Croct is well suited to React and Next.js stores where the engineering team already owns the frontend and wants component-level control.
The question for a standard Shopify store is narrower: who ships the test and what the test is measured in. Once a marketer runs a product-page or checkout test, a visual editor and session-based pricing matter more than a product-analytics data model. 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