Conductrics vs Eppo vs Explore (2026): Testing for Store Revenue

What is Conductrics, and what is it actually good at?

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 and corrections for multiple comparisons.
• Contextual bandits you can read: predictive agents built on Thompson Sampling learn in a Listen mode or adapt in an Adaptive mode, and decision trees show which visitor traits drove each choice.
• 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 Eppo, and what is it actually good at?

Where Eppo is genuinely strong

• Direct warehouse connection: analysis runs on Snowflake, BigQuery, or Redshift, with no duplicate metric pipeline.
• Rigorous statistical methods: sequential testing, CUPED variance reduction, and other advanced methods for mature programs.
• Metrics as code: experiment metrics reuse the data team's existing definitions, keeping company-wide numbers consistent.
• High-velocity support: built for teams running dozens of experiments at once with strong data governance.

Where Eppo hits its ceiling for an eCommerce store

• No visual editor: every variant needs engineering, so a marketing team cannot ship a test without a developer.
• Requires a data warehouse: without Snowflake or an equivalent, most of its advantage disappears.
• Enterprise pricing and setup: priced for data organizations, not for a single mid-market Shopify store.
• No native Shopify checkout: no templates, no app, no marketer-accessible checkout experiment surface.

What Conductrics and Eppo leave open for an eCommerce store

What Eppo cannot tell an eCommerce team

1. 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 warehouse metric.
2. Which surface to test first. Which pages in the funnel (product, cart, checkout) carry the highest revenue impact if tested next.
3. How it behaves in checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without engineering glue work.
4. 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, 94.2% never show checkout progress steps, and 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]

These are checkout-surface problems. A warehouse-native analysis platform 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.

That is what the title means by store revenue. A warehouse-rigorous lift 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-value buyers, the lift it confirms is margin the store keeps rather than traffic it rents. A variant that wins on revenue per visitor and holds for high-CLV customers protects profit; a variant that only lifts a top-of-funnel metric often does not. That is the revenue question Eppo is not built to answer, and the one Explore is. Explore also reaches Shopify-specific levers most testing tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.

Conductrics vs Eppo vs Explore: the capability comparison

Competitor ratings, pricing, and plan details reflect publicly listed figures as of 2026 and can change. Conductrics does not publish prices and quotes through sales; Eppo uses custom pricing and requires technical implementation. Explore uses session-based pricing; see the Omniconvert pricing page for current plans.