Conductrics vs Croct vs Explore (2026): Two Developer Tools, One Gap
Conductrics is an API-first experimentation platform for engineering teams that embed testing into their own applications. 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 an API-first experimentation platform for engineering and data science teams, with adaptive multi-armed bandit optimization and a 4.3 out of 5 G2 rating. [G2, 2026]
- 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]
- Both tools are developer-only: neither ships a visual editor, and neither is usable by a marketing team on a standard Shopify Liquid theme.
- Neither is built around the Shopify checkout or measures results in revenue per visitor, so the surfaces where store orders close sit outside their reach.
- 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 deciding how to embed experimentation inside a developer workflow: an API-first platform for internal apps, or a React component library for a headless storefront. Both solve real problems for engineering teams. Neither is built for a marketing lead running tests on a standard Shopify checkout without writing code. 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 API-first A/B testing and adaptive optimization platform for engineering and data science teams. It ships an SDK, a REST API, and multi-armed bandit optimization, and it is designed to be embedded inside a team's own application rather than sit on top of a website as a standalone tool. [Conductrics, 2026]
Conductrics holds a 4.3 out of 5 rating on G2 across 12 reviews, a small but consistent sample from technical teams. [G2, 2026] It is used where experimentation needs to live inside a custom application, and where the team wants programmatic control over how variants are assigned and how the algorithm learns.
The category Conductrics sits in is developer-owned experimentation. It runs tests through code, with bandit and contextual bandit algorithms that adapt allocation as data comes in. That focus is the point of the product, not an oversight.
API-first experimentation means every test is configured and served through code, controlled by developers, without a visual interface for editing pages. Conductrics ships an SDK, a REST API, and adaptive bandit optimization for teams embedding tests into their own applications. It is a delivery mechanism for engineering-owned experiments, distinct from running a controlled revenue experiment on a store's checkout.
Where Conductrics is genuinely strong
- Multi-armed bandit optimization: adaptive allocation that shifts traffic to winning variants as results come in.
- API-first control: full programmatic access, suited to teams embedding experimentation inside a custom application.
- Server-side testing: variants assigned on the server, useful for logged-in flows and non-browser surfaces.
- Data science friendly: a real fit for teams that want to model contextual bandits, not just click through a UI.
Where Conductrics hits its ceiling for an eCommerce store
- No visual editor: every experiment needs a developer, so marketing-led CRO stalls on engineering time.
- No native Shopify integration: Shopify storefronts need custom API glue to run any test at all.
- Low eCommerce focus: no product-page, cart, or checkout templates, and no revenue per visitor metric out of the box.
- Minimal public documentation: small user community, so knowledge transfer inside the store is slow.
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 cannot do for an eCommerce store
Conductrics and Croct sit in different developer niches, but they share one gap for a store. Neither is built for a marketing team running experiments on a standard Shopify storefront, and neither measures the outcome in revenue per visitor on the surfaces where an order actually closes: product page, cart, and checkout.
Conductrics is an API-first tool designed for teams embedding optimization inside their own applications. It has no visual editor and cannot run experiments on a Shopify storefront through a marketer-accessible interface. Every test lives behind a developer ticket, and revenue per visitor is not a native experiment outcome.
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. Both tools optimize the execution of an experiment for an engineering audience. 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 gap underneath the first: the data insights layer that tells the team what to test and whether it worked. Conductrics reports experiment outputs through an API, so heatmaps, session recordings, and on-site surveys have to be added from third-party tools and reconciled by hand. 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 neither tool can tell an eCommerce team
- 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, 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 94.2% never show checkout progress steps. [CROBenchmark Report 2026, Omniconvert]
These are checkout-surface problems, the exact surfaces a developer-only tester is not built to experiment on without weeks of custom integration. 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 developer tools, one gap. Conductrics and Croct both give engineering teams real, capable primitives; neither gives a store's CRO lead a way to ship a checkout test tomorrow morning. 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 data teams an API and bandits. Croct gives React engineers component-level testing on Next.js. Explore adds 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 | API-first experimentation for developer teams | React and Next.js component-level testing | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes API-first, no visual editor | Yes component-level in React and Next.js | Yes visual plus code editor |
| Multivariate testing | No | No | Yes |
| Server-side testing | Yes | Yes | Yes |
| Visual editor | No code only | No code only | Yes visual editor built in |
| On-site surveys and overlays | No needs third-party tools | No component-level only | Yes surveys and overlays built in |
| Shopify integration | Low custom API integration required | Medium headless Next.js only, not standard Liquid | Yes native |
| eCommerce focus | Low general experimentation | Low headless commerce only | High built for store revenue workflows |
| Revenue per visitor measurement | No event-based outcomes | No component-level events | Yes revenue per visitor and order rate native |
| Pricing model | Custom, contact sales, no free trial | Usage-based with a free tier, free trial available | Session-based, built for store traffic, free trial |
| Best for | Data science teams building bandits into custom apps | Frontend engineers on headless Next.js storefronts | 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. 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 who runs the test. If your data team wants API-driven experimentation 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 API-first bandit optimization for engineering teams. 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 code-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.