Conductrics vs Croct vs Explore (2026): Which Fits a Shopify Store
Conductrics is a general-purpose experimentation platform with A/B and multivariate testing, a visual editor, server-side and mobile SDKs, and contextual bandits. Croct is a component-level A/B testing tool for React and Next.js developers. Omniconvert Explore is the Shopify-native eCommerce CRO platform: it runs experiments on product pages, cart, and checkout, measured in revenue per visitor rather than generic conversion rate.
- Conductrics is a general-purpose experimentation platform with A/B and multivariate testing, a visual editor, server-side and mobile SDKs, and contextual bandit optimization.
- Croct is a React and Next.js component-level A/B testing and personalization platform, with a 4.7 out of 5 G2 rating from a developer audience. [G2, 2026]
- Croct is developer-only: it ships no visual editor and is not usable by a marketing team on a standard Shopify Liquid theme. Conductrics has a visual editor but no dedicated Shopify app.
- Croct is not built around the Shopify checkout and does not measure results in revenue per visitor, so the surfaces where store orders close sit outside its reach; Conductrics is general-purpose, with no eCommerce-specific features listed.
- Omniconvert Explore runs experiments on product, cart, and checkout natively and measures results in revenue per visitor: pick it for Shopify revenue surfaces.
Teams comparing Conductrics vs Croct are usually choosing between two different shapes of experimentation: a general-purpose platform with a visual editor and server-side and mobile SDKs, or a React component library for a headless storefront. Both solve real problems. Croct is not built for a marketing lead running tests on a standard Shopify checkout without writing code, and Conductrics lists no dedicated Shopify app. This page covers what each does well, the gap they share, and where Omniconvert Explore is the right layer.
What is Conductrics, and what is it actually good at?
Conductrics is an A/B testing, multivariate testing, and adaptive optimization platform. It runs tests client-side through a single script tag, with a visual editor called Conductrics Express, and server-side through a REST API and libraries for Node.js, Java, and Swift, at the CDN edge, and in iOS, Android, and React Native apps. [Conductrics, 2026]
Conductrics was founded in 2008 and launched in 2010, and it is used across industries. Teams can build UI changes in Conductrics Express, which Conductrics describes as built for non-technical teams who need to test UI changes, or serve variants from their own code, and they can let contextual bandits learn which experience suits which visitor.
The category Conductrics sits in is general-purpose experimentation across web, server, and mobile. Multivariate tests are composed from existing tests and read through a Main Effects Report, surveys run inside experiments, and statistical controls such as multiple-comparison corrections and test-interference checks guard the results. That breadth is the point of the product.
A contextual bandit is an adaptive algorithm that learns which experience works best for which kind of visitor and, as evidence builds, sends more visitors to the better option instead of holding a fixed split. Conductrics runs them as predictive agents using Thompson Sampling, with a Listen mode that learns without changing the experience, an Adaptive mode, and human-readable decision trees that show which visitor traits drove a choice. It is an allocation method, distinct from a controlled revenue experiment on a store's checkout.
Where Conductrics is genuinely strong
- Visual editor plus code: Conductrics Express for WYSIWYG UI changes, multi-page changes, and redirect tests, with custom JavaScript when a change needs it.
- A/B and multivariate testing: multivariate tests composed from existing tests, with MVT and Main Effects reports that show which variable drives a lift.
- Server-side, edge, and mobile: a REST API, Node.js, Java, and Swift libraries, Conductrics Edge at the CDN, and iOS, Android, and React Native SDKs.
- Contextual bandits with readable decisions: predictive agents with a Listen mode and an Adaptive mode, and decision trees that show which visitor traits drove each choice.
- Surveys and statistical rigor: in-experiment surveys matched to the variation each visitor saw, plus error-rate control and corrections for multiple comparisons.
Where Conductrics hits its ceiling for an eCommerce store
- No dedicated Shopify app: no Shopify-specific integration is listed; Conductrics installs on a store through its script tag, so store tests are set up like any other page test rather than from Shopify's catalog.
- General-purpose, not store-specific: no eCommerce-specific features are listed, such as product-page, cart, or checkout templates; reporting those surfaces in revenue per visitor out of the box is Explore's focus.
- Prices through sales: prices are not published; quotes come from sales.
- Breadth a store-only team may not need: server-side, edge, mobile, and bandit testing reach well past what a team testing only its Shopify storefront may use.
What is Croct, and what is it actually good at?
Croct is an A/B testing, personalization, and feature-flag platform built for React and Next.js applications. It integrates at the component level: a developer wraps a React component, defines variants in code, and Croct's API decides what each visitor sees. It is popular with headless eCommerce teams shipping storefronts on Next.js. [Croct, 2026]
Croct holds a 4.7 out of 5 rating on G2 across 47 reviews, strong for a developer-first platform in a niche category. [G2, 2026] It is well liked by frontend engineers because the SDK, hooks, and personalization API feel native to how Next.js codebases are already structured.
The category Croct sits in is component-level testing for the React ecosystem. It runs A/B tests, personalization, and feature flags on a headless frontend, where the team already writes and deploys frontend code. That is the surface the product is built for.
Component-level testing means an experiment is defined on a specific React or Next.js component in code, changing what that component renders per variant. Croct ships a React SDK, hooks, and a personalization API built around this pattern. It is native to a headless frontend, distinct from running a test on a standard Shopify Liquid theme or a checkout the tool does not touch.
Where Croct is genuinely strong
- Deep React and Next.js fit: SDK, hooks, and typed APIs that map directly onto how frontend engineers already work.
- Component-level personalization: a variant lives on the component, not a page overlay, so it behaves as part of the app.
- A/B tests, personalization, and flags in one: a single SDK covers experimentation and progressive delivery for a headless build.
- Usage-based pricing with a free tier: low friction for engineering teams to start without a procurement cycle.
Where Croct hits its ceiling for a standard Shopify store
- React or Next.js required: standard Shopify Liquid themes cannot use it without a headless rebuild.
- No visual editor: every variant is configured in code, so marketing and CRO teams cannot run tests independently.
- Limited native Shopify surfaces: checkout, order-status, and other non-React surfaces sit outside its reach.
- Generic conversion focus: results are read as component events, not natively as revenue per visitor or order rate.
What Conductrics and Croct leave open for an eCommerce store
Conductrics and Croct sit in different niches, a general-purpose experimentation platform and a React component library, but they share one gap for a store: neither is Shopify-native. Croct is not built for a marketing team running experiments on a standard Shopify storefront, and it does not measure the outcome in revenue per visitor on the surfaces where an order actually closes: product page, cart, and checkout. Conductrics lists no dedicated Shopify app and no eCommerce-specific features.
Conductrics is a general-purpose experimentation platform. A marketer can build a variant in its visual editor, and engineers can serve tests server-side, at the CDN edge, or in mobile apps. On a Shopify storefront it installs through its script tag as it would on any website: no dedicated Shopify app or Shopify-specific integration is listed, and no eCommerce-specific features are, so store tests are set up as general page tests rather than from Shopify's catalog.
Croct is built for React and Next.js developers and cannot be used on a standard Shopify Liquid theme without a significant headless rebuild. Every experiment is configured in code, so a CRO lead running a store on a stock theme has no path to ship a test independently. The product's reach ends where the React app ends.
The two gaps sit in different corners but point to the same missing layer. Croct optimizes the execution of an experiment for an engineering audience, and Conductrics serves every industry rather than the store in particular. Neither is built around where store revenue is decided, or around the Customer Value Optimization question: whether the win holds for repeat, high-value buyers. For the wider debate behind this testing-versus-personalization split, see Has personalization replaced A/B testing?
There is a second question underneath the first: the data insights layer that tells the team what to test and whether it worked. Conductrics runs surveys inside its experiments, matched to the variation each visitor saw, and Contentsquare and Hotjar read its experiments without custom integration. Croct's telemetry lives on the components it wraps, so anything outside the React tree stays invisible. Omniconvert Explore builds that data insights layer in: heatmaps, session recordings, and surveys sit next to the experiment, and the same behavioral and customer data defines the segments you test against. The insight and the test live in one place, which is the difference between guessing at a hypothesis and reading it off the store's own data.
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 an eCommerce team needs a test to tell it
- Did the win move revenue and margin. Whether a winning variant raised revenue per visitor and order rate, and held its margin once discounts and returns are counted, not just fired an event.
- 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, through a Shopify integration.
- 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. [CROBenchmark Report 2026, Omniconvert]
These are checkout-surface problems, the exact surfaces a code-only tester like Croct is not built to experiment on without weeks of custom integration, and that a general-purpose platform like Conductrics approaches as it would any website, without a dedicated Shopify app. 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 fit. Croct gives engineering teams real, capable primitives but gives a store's CRO lead no way to ship a checkout test tomorrow morning; Conductrics gives a broad experimentation platform with no dedicated Shopify app. A higher click event or a lifted component 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-CLV 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.
Conductrics vs Croct vs Explore: the capability comparison
Side by side, the three tools serve different audiences. Conductrics gives teams A/B and multivariate testing from a visual editor or code, with bandits, across web, server, and mobile. Croct gives React engineers component-level testing on Next.js. Explore brings 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 | Conductrics | Croct | Omniconvert Explore |
|---|---|---|---|
| Primary function | General-purpose A/B, multivariate, and adaptive experimentation | React and Next.js component-level testing | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor plus server-side and mobile SDKs | Yes component-level in React and Next.js | Yes visual plus code editor |
| Multivariate testing | Yes with a Main Effects Report | No | Yes |
| Server-side testing | Yes | Yes | Yes |
| Visual editor | Yes Conductrics Express, WYSIWYG plus custom JavaScript | No code only | Yes visual editor built in |
| On-site surveys and overlays | Yes on-site surveys inside experiments (Conductrics Surveys) | No component-level only | Yes surveys and overlays built in |
| Shopify integration | Partial no dedicated Shopify app; installs through its script tag | Medium headless Next.js only, not standard Liquid | Yes native |
| eCommerce focus | Low general-purpose, not eCommerce-specific | Low headless commerce only | High built for store revenue workflows |
| Revenue per visitor measurement | General-purpose; no eCommerce-specific revenue report listed | No component-level events | Yes revenue per visitor and order rate native |
| Pricing model | Prices not published, quote from sales | Usage-based with a free tier, free trial available | Session-based, built for store traffic, free trial |
| Best for | Teams testing across web, server, edge, and mobile, with adaptive bandits | Frontend engineers on headless Next.js storefronts | Shopify and eCommerce teams optimizing for revenue |
| User rating | No public G2 rating | 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. Conductrics quotes pricing on request; Croct offers a free tier with usage-based paid plans. 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 Conductrics or Croct?
Start with where the test runs. If you want one experimentation platform across web, server, edge, and mobile, with adaptive bandits, keep Conductrics. If your engineers are shipping a headless Next.js storefront, Croct earns its place. For a standard Shopify store where marketing owns testing, run your next experiment on the product-to-checkout path in Explore, measured in revenue per visitor. The three are complementary, but only Explore is built for the store.
Conductrics and Croct are both capable tools inside their categories. Conductrics is strong at A/B, multivariate, and adaptive bandit testing across web, server, edge, and mobile, with a visual editor for UI changes. Croct is a natural fit for React and Next.js developers running a headless eCommerce frontend.
The question for a standard 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 component-level event. 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 197 reviews, G2 , as of 2026