Convert vs Eppo vs Explore (2026): The Shopify Testing Gap
Convert is a privacy-first A/B testing platform for CRO agencies and mid-market teams on general websites. Eppo is a warehouse-native experimentation platform that connects to Snowflake or BigQuery for a data engineering team. 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.
- Convert is a privacy-first A/B testing platform for CRO agencies and mid-market teams, from $299 per month with a 4.7 out of 5 G2 rating. [G2, 2026]
- Eppo is a warehouse-native experimentation platform for data teams on Snowflake, BigQuery, or Redshift, with a 4.7 out of 5 G2 rating. [G2, 2026]
- Convert runs tests through a visual editor on general websites; Eppo runs them in code against warehouse data. Each wins in its own corner.
- Neither is built around the Shopify checkout or measures results in revenue per visitor, the surfaces where store revenue is decided.
- 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 Convert vs Eppo are usually caught between two very different testing worlds. Convert is a privacy-first A/B testing tool built for CRO agencies and mid-market websites, with a visual editor and session-based pricing. Eppo is a warehouse-native experimentation platform that connects directly to Snowflake or BigQuery for a data engineering team. Neither is built around the Shopify surfaces where store revenue is actually decided, and that is where Omniconvert Explore fits.
What is Convert, and what is it actually good at?
Convert is a privacy-first A/B testing platform for CRO agencies and mid-market teams. It supports multivariate testing, server-side testing, and advanced targeting, integrates with Google Analytics and major analytics platforms, and is known for transparent session-based pricing and a no-data-sharing stance. [Convert, 2026]
Convert is one of the most highly rated tools in the category, with a 4.7 out of 5 rating on G2 across 139 reviews. [G2, 2026] It is a favorite among CRO agencies for transparent, session-based pricing from $299 per month and for agency-friendly account features, and its support is consistently praised.
The category Convert sits in is practitioner-led web testing. It runs A/B and multivariate tests on general websites, with a strong privacy posture that appeals to teams handling sensitive traffic. That focus is the point of the product, and Convert earns its reputation by doing it cleanly.
Privacy-first testing means the platform avoids sharing experiment data with third parties and minimizes what it collects, which matters for teams under strict compliance requirements. Convert builds this into its product and pricing. It is a separate concern from whether a test runs natively on a Shopify checkout.
Where Convert is genuinely strong
- Transparent, session-based pricing: predictable costs from $299 per month that agencies and mid-market teams can plan around.
- Strong privacy stance: no data sharing with third parties, useful for teams with strict compliance needs.
- Multivariate and server-side testing: capable experimentation with granular audience rules.
- Highly rated support and integrations: well-regarded support, with Google Analytics and major analytics connections.
Where Convert hits its ceiling for an eCommerce store
- No native Shopify integration: no eCommerce-specific experiment templates, so store setups are manual.
- Editor is functional, not polished: the visual editor trails VWO and Optimizely for ease of use.
- No built-in behavioral analysis: no native heatmaps or session recordings, so teams add third-party tools.
- Generic conversion focus: results are framed around general conversion, not revenue per visitor.
What is Eppo, and what is it actually good at?
Eppo is a warehouse-native experimentation platform. It connects directly to Snowflake, BigQuery, Redshift, and similar warehouses for experiment analysis using the metric definitions a data team already curates. It is built for organizations with mature data infrastructure running high-velocity programs. [Eppo, 2026]
Eppo is an experimentation tool built for engineering and data organizations, not for marketers. It holds a 4.7 out of 5 rating on G2 across 80 reviews. [G2, 2026] Its strength is statistical rigor: it applies advanced methods to experiments defined in a warehouse, and it fits teams shipping tens or hundreds of tests a year under strong governance.
Where Convert leads with a visual editor and session-based plans, Eppo leads with rigorous analysis of experiment results connected to warehouse data. Pricing is custom and quoted through sales, so it slots into enterprise budgets rather than small-team plans.
Warehouse-native experimentation runs experiment analysis directly against a data warehouse like Snowflake or BigQuery, using the metric definitions a data team already trusts. Eppo does this well for a mature data organization. It is an analysis layer, distinct from running a controlled experiment on the visual surfaces of a store: product, cart, and checkout.
Where Eppo is genuinely strong
- Warehouse-native connections: direct integration with Snowflake, BigQuery, Redshift, and similar warehouses.
- Rigorous statistics: advanced methods for teams running high-velocity experimentation programs.
- Metric reuse: experiments run against the metric definitions the data team already curates.
- Strong governance: built for organizations managing experimentation across many product teams.
Where Eppo hits its ceiling for an eCommerce store
- No visual editor: variants require code changes, not a marketer-accessible UI.
- Requires warehouse infrastructure: needs Snowflake or a similar warehouse most stores do not run.
- Enterprise pricing: custom, contact-sales pricing that is out of reach for small and mid-market stores.
- No native Shopify experiments: cannot run marketer-accessible tests on Shopify product pages, cart, or checkout.
What Convert and Eppo cannot do for an eCommerce store
Convert and Eppo sit at opposite ends of the testing spectrum but share the same gap for a store. One is a practitioner tool for agency CRO; the other is a data-team platform for warehouse-native experiments. Neither runs revenue-per-visitor tests on Shopify product, cart, and checkout.
Convert's angle is practitioner-led. It is built for CRO agencies and mid-market teams running tests on general websites, cleanly and with a strong privacy stance. It has no native Shopify integration and no eCommerce-specific experiment flows. Teams using it for Shopify CRO must handle checkout testing through manual implementation, and revenue per visitor is not a native experiment metric.
Eppo's angle is analysis-led. It is a warehouse-native tool built for organizations with mature data engineering, with no visual editor and a Snowflake-or-similar dependency. It cannot run experiments on Shopify product pages or checkout flows through a marketer-accessible interface, and it is not designed for self-serve eCommerce CRO.
The two gaps differ in nature but point to the same missing layer. Both tools optimize the execution of a test on a generic surface. Neither is built around where store revenue is actually decided, or around the Customer Value Optimization question: whether a result holds for high-value, repeat buyers. For the wider debate behind the testing stack, see Has personalization replaced A/B testing?
There is a second gap underneath the first: the data insights layer that tells a team what to test and whether it actually worked. Convert runs clean experiments but ships no native behavioral analysis, so heatmaps, session recordings, and on-site surveys come from third-party tools the team has to stitch together. Eppo delivers warehouse-grade analysis but demands a data engineering layer most single Shopify stores will never run. Omniconvert Explore builds that 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. 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 lifted a click or a warehouse delta detached from the store.
- 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 general web tester or a warehouse-only experimentation tool is not built to experiment on. 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 the Shopify testing gap. A clean A/B test on a landing page or a warehouse-only lift can each 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. Explore also reaches Shopify-specific levers most testing tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
Convert vs Eppo vs Explore: the capability comparison
Side by side, the three tools sit at different points. Convert runs clean privacy-first tests on general websites. Eppo runs warehouse-native experiments for data teams. 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.
| Capability | Convert | Eppo | Omniconvert Explore |
|---|---|---|---|
| Primary function | Privacy-first general-website A/B testing | Warehouse-native experimentation | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual and code editor | Yes warehouse-native, no visual editor | Yes visual plus code editor |
| Multivariate testing | Yes | No | Yes |
| Server-side testing | Yes | Yes | Yes |
| Visual editor | Yes functional, not polished | No code-only workflow | Yes visual plus code editor |
| On-site surveys and overlays | No needs third-party tools | No warehouse analysis only | Yes surveys and overlays built in |
| Built-in data insights | No heatmaps and recordings via third parties | Partial warehouse analysis, no on-page diagnostics | Yes heatmaps, recordings, and surveys built in |
| Shopify integration | Medium not native, manual setup | Low requires warehouse infrastructure | Yes native |
| eCommerce focus | Medium agency and mid-market web | Low data-team analysis | High built for store revenue workflows |
| Revenue per visitor measurement | No generic conversion metrics | Partial warehouse metrics, not storefront-native | Yes revenue per visitor and order rate native |
| Pricing model | Session-based, from $299/mo, free trial | Custom, contact sales, no free trial | Session-based, built for store traffic, free trial |
| Best for | CRO agencies and mid-market teams wanting privacy-first testing | Data and engineering teams with a mature warehouse | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.7 out of 5 (G2, 139 reviews, as of 2026) | 4.7 out of 5 (G2, 80 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. Convert publishes session-based plans from $299 per month; Eppo is custom contact-sales pricing. 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 Convert or Eppo?
Start with the surface where your revenue is decided. If your CRO work spans many non-Shopify client sites, Convert is a clean, privacy-first fit. If you already run Snowflake and a data team owns experimentation, Eppo earns its place. For a Shopify store, run your next test on the product-to-checkout path in Explore, measured in revenue per visitor. The three are complementary, not competing, but only Explore is built for the checkout where the order closes.
Convert and Eppo are both capable tools inside their categories. Convert is transparent, privacy-first, and agency-friendly for general-website testing. Eppo is a rigorous warehouse-native analysis engine for teams with real data infrastructure.
The question for a store is narrower: can your team run a controlled experiment on the Shopify product, cart, and checkout, and read the result in revenue per visitor rather than a click or a warehouse metric detached from the storefront. 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