Conductrics vs Statsig vs Explore (2026): Built for Shopify Revenue
Conductrics is an experimentation and optimization platform with A/B and multivariate testing, a visual editor, server-side and mobile SDKs, and contextual bandits. Statsig is a feature flag and experimentation platform for product and engineering teams, with built-in analytics. 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 rather than engineering event counts.
- Conductrics is an experimentation and optimization platform with A/B and multivariate testing, a visual editor (Conductrics Express), server-side and mobile SDKs, contextual bandits, and in-experiment surveys.
- Statsig is a feature flag and experimentation platform for product engineering teams, with a 4.7 out of 5 G2 rating across 346 reviews. [G2, 2026]
- Statsig is engineering-first without a visual editor, so marketing teams cannot ship an experiment without a developer sprint; Conductrics has a visual editor, Conductrics Express, for non-technical teams.
- Neither runs natively on the Shopify catalog or checkout; Statsig does not measure results in revenue per visitor, and Conductrics lists no eCommerce-specific features.
- 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 Statsig are usually deciding how much of their experimentation lives in code. Conductrics covers both sides: a visual editor for on-page changes and server-side, edge, and mobile testing, with multivariate tests and contextual bandits. Statsig answers it with feature flags plus built-in analytics on a generous free tier, for engineering-led teams that want experimentation embedded in their own code. This page covers what each does well, the gap they share for a Shopify store, and when Omniconvert Explore is the right layer.
What is Conductrics, and what is it actually good at?
Conductrics is an experimentation and adaptive optimization platform for A/B and multivariate testing. It pairs a visual editor, Conductrics Express, with server-side, edge, and mobile options, and adds contextual bandits, rule-based targeting, and surveys inside experiments. [Conductrics, 2026]
Conductrics was founded in 2008 and launched in 2010, and it is used across industries. Non-technical teams can make UI changes in its visual editor, while developers can run tests through a REST API and libraries for Node.js, Java, and Swift, at the CDN edge with Conductrics Edge, or in iOS, Android, and React Native apps.
The category Conductrics sits in is general-purpose experimentation and optimization. Targeting can use rules on any data source, custom visitor traits, or predictions from a team's own models passed in through the API, and its predictive agents, contextual bandits built on Thompson Sampling, adapt traffic as they learn, with decision trees that show which traits drove each choice.
A contextual bandit is an adaptive algorithm that uses what it knows about each visitor to choose which variant to show, shifting traffic toward what performs best for that kind of visitor as evidence builds. Conductrics' predictive agents work this way, using Thompson Sampling, with a Listen mode that learns without changing the experience and an Adaptive mode that acts on what it learns. It is a way of allocating traffic, distinct from choosing which store surface to test and the metric to read it in.
Where Conductrics is genuinely strong
- Visual editor plus server-side, edge, and mobile: Conductrics Express handles on-page changes, custom JavaScript, multi-page changes, and split-URL tests, while a REST API, Conductrics Edge, and iOS, Android, and React Native SDKs cover servers, the CDN, and apps.
- A/B and multivariate testing with statistical rigor: a Main Effects Report shows which variable drives a lift, interaction effects included, backed by error-rate control, checks for test interference, and corrections for multiple comparisons.
- Contextual bandits you can read: predictive agents learn in a Listen mode or adapt in an Adaptive mode, decision trees show which visitor traits drove each choice, and an audience report surfaces segments by performance.
- Surveys inside experiments: Conductrics Surveys ask anything from NPS to custom questions, matched to the variation each visitor saw.
Where Conductrics hits its ceiling for an eCommerce store
- No dedicated Shopify app: no Shopify-specific integration is listed; it installs on a store through its script tag, so store tests are set up like any page test rather than from Shopify's catalog.
- General-purpose, not eCommerce-specific: it serves many industries and lists no eCommerce-specific features, while Explore is built around product, cart, and checkout and reports in revenue per visitor.
- Prices through sales: prices are not published, so a store has to ask for a quote before it can compare costs.
- Breadth a store may not need: much of its range, from server-side, edge, and mobile testing to contextual bandits, goes beyond what a team running only storefront tests may use.
What is Statsig, and what is it actually good at?
Statsig is a feature flag and experimentation platform for product and engineering teams. It connects flags to a built-in product analytics layer, supports advanced methods like CUPED and sequential testing, and offers a generous free tier that scales into paid seat-based plans. [Statsig, 2026]
Statsig is one of the highest-rated engineering-facing tools in the category, with a 4.7 out of 5 rating on G2 across 346 reviews. [G2, 2026] It is popular with product engineering teams that want feature releases and their measurement in a single platform, without wiring analytics separately.
The category Statsig sits in is developer-led experimentation. SDKs gate features per user, cohort data flows straight into the analytics layer, and statistical rigor is built into the result view. That focus is the point of the product.
Feature flag experimentation gates a code path behind a toggle that the platform can switch on or off per user, then measures which cohort behaved better. Statsig connects this directly to a product analytics layer, so every feature release comes with automatic measurement. It is an engineering delivery mechanism, distinct from running a controlled revenue experiment on product, cart, and checkout.
Where Statsig is genuinely strong
- Feature flags plus analytics: every release ships with measurement attached, without stitching a separate tool.
- Advanced statistical methods: CUPED, sequential testing, and variance reduction improve power on engineering event data.
- Generous free tier: teams can start without procurement, then scale into seat-based plans as usage grows.
- Scales for engineering programs: multi-SDK support and cohort tools fit large product-development orgs.
Where Statsig hits its ceiling for an eCommerce store
- SDK integration required: every experiment needs developer implementation, so marketing cannot self-serve.
- No visual editor: product-page copy, layout, and overlay tests all become engineering tickets.
- No native Shopify integration: checkout is not a supported surface, and Shopify's own flow is out of reach without custom work.
- Engineering event counts, not revenue: results read in flag exposures and events, not revenue per visitor or order rate.
What Conductrics and Statsig leave open for an eCommerce store
Conductrics and Statsig are built for different jobs, general-purpose experimentation and feature flag delivery, but they share one gap for a store. Neither runs natively on the Shopify catalog or checkout, and neither is built around the metric a store lives on: revenue per visitor. Statsig also has no visual editor, where Conductrics has Conductrics Express.
Conductrics is a general-purpose optimization platform used across industries. It has a visual editor and installs on any website, a Shopify storefront included, through its script tag, but it lists no dedicated Shopify app, no Shopify-specific integration, and no eCommerce-specific features, so store tests are set up like any page test rather than from Shopify's catalog.
Statsig is an engineering-first feature flag and experimentation tool. It has no visual editor and requires SDK implementation for every experiment. It cannot run tests on Shopify product pages or checkout flows without significant developer involvement, and its results read in flag exposures and events rather than revenue per visitor.
The two gaps differ in shape but point to the same missing layer. Engineering-first tools like Statsig optimize the delivery of an experiment or a flag in a codebase, and a general-purpose platform like Conductrics optimizes how a test runs on any site. Neither is built around where store revenue is actually decided (the product page, the cart, the checkout) or around the Customer Value Optimization question: whether a result holds for high-value, repeat buyers.
Statsig has a second gap underneath the first: the marketer-accessible layer that lets a growth team ship a test without a developer sprint, since it assumes the person running the experiment writes code. Conductrics offers that layer through its visual editor, but as a general-purpose tool with no Shopify-specific integration listed. Omniconvert Explore assumes the person running the experiment owns revenue: it ships a visual editor, native Shopify targeting, on-site surveys, and overlays, and reads every result in revenue per visitor on the store's real surfaces.
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 Statsig cannot 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 lifted a flag exposure or an event count.
- Which surface to test first. Which pages in the funnel (product, cart, checkout) carry the highest revenue impact if tested next, ranked by a store-level benchmark rather than a hunch.
- How it behaves in checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without SDK glue work for every touchpoint.
- 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 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. A code-first flag is not built to experiment on those surfaces, and a general-purpose testing platform with no Shopify-specific integration tests them like any other page. Explore runs the experiment on the store's real revenue surfaces and reports the outcome in revenue per visitor, so the team can see whether the fix actually moved the order.
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]
Conductrics vs Statsig vs Explore: the capability comparison
Side by side, the three tools serve different layers. Conductrics gives teams A/B, multivariate, and bandit testing, from a visual editor to server-side and mobile. Statsig gives engineering teams feature flags with analytics. 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 on the Shopify funnel.
| Capability | Conductrics | Statsig | Omniconvert Explore |
|---|---|---|---|
| Primary function | A/B and multivariate testing with contextual bandits | Feature flags with built-in experimentation and analytics | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor, server-side, and mobile | Yes SDK-based, no visual editor | Yes visual plus code editor |
| Multivariate testing | Yes with Main Effects reporting | No | Yes |
| Server-side testing | Yes | Yes | Yes |
| Visual editor | Yes Conductrics Express | No SDK required | Yes visual editor plus code |
| On-site surveys and overlays | Yes on-site surveys inside experiments (Conductrics Surveys) | No not in scope | Yes surveys and overlays built in |
| Shopify integration | Partial no dedicated Shopify app; installs through its script tag | Low SDK work per touchpoint | Yes native |
| eCommerce focus | Low general-purpose, not eCommerce-specific | Low product engineering use | High built for store revenue workflows |
| Pricing model | Prices not published, quote from sales | Seat-based, free tier available, free trial | Session-based, built for store traffic, free trial |
| Best for | Teams testing across web, server-side, edge, and mobile | Product and engineering teams shipping feature-flagged code | Shopify and eCommerce teams optimizing for revenue |
| User rating | No public G2 rating | 4.7 out of 5 (G2, 346 reviews, as of 2026) | 4.6 out of 5 (G2, 197 reviews, as of 2026) |
Competitor ratings, pricing, and plan details reflect publicly listed figures as of 2026 and can change. 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 Statsig?
Decide by who runs the experiments and where. If you want A/B, multivariate, and bandit testing across web, server-side, and mobile, Conductrics fits. If your engineering team wants feature flags and analytics in one platform, Statsig is a strong pick. For a Shopify store where marketing runs the tests and revenue per visitor is the outcome, keep Explore for the product-to-checkout path. The three are complementary; only Explore is built for the store surfaces.
Conductrics and Statsig are both capable within their categories. Conductrics pairs a visual editor with server-side, edge, and mobile testing, multivariate reporting, and contextual bandits. Statsig gives product engineering teams feature flags and analytics in one platform, on a generous free tier.
The question for a Shopify store is narrower: can your marketing team run a controlled experiment on the product-to-checkout path 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, then measures the outcome in revenue per visitor, not just clicks.
4.6 out of 5 across 197 reviews, G2 , as of 2026