Convert.com vs Optimizely vs Explore (2026): Two Testers, One Blind Spot
Convert.com is a privacy-first A/B testing tool for CRO agencies and mid-market sites. Optimizely is the enterprise experimentation standard for product and engineering teams. Neither is built around Shopify revenue surfaces. Omniconvert Explore runs product, cart, and checkout experiments natively on Shopify and measures results in revenue per visitor, not clicks.
- Convert.com is the mid-market, privacy-first pick for CRO agencies wanting transparent session-based pricing from $299 per month.
- Optimizely Web Experimentation is the enterprise standard for teams running feature flags and hundreds of concurrent web and server-side tests.
- Neither Convert nor Optimizely is Shopify-native: both need developer work to run product, cart, and checkout experiments on a store.
- Omniconvert Explore runs A/B, multivariate, and personalization experiments on the product, cart, and checkout surfaces of a Shopify store, measured in revenue per visitor.
- The three tools can coexist: keep an enterprise tester for feature flags and use Explore for the storefront revenue tests.
Convert.com vs Optimizely is a common shortlist for teams evaluating serious A/B testing tools in 2026. Convert sits in the mid-market with transparent session-based pricing and a strong privacy stance. Optimizely is the enterprise experimentation standard, built for product and engineering programmes running hundreds of tests. Neither is Shopify-native, and that gap is the reason many DTC teams end up looking at Omniconvert Explore.
What is Convert.com, and what is it actually good at?
Convert.com is a privacy-first A/B testing platform popular with CRO agencies and mid-market teams. It runs A/B, multivariate, and server-side tests with transparent session-based pricing and no third-party data sharing. Its main constraint for a store is the lack of Shopify-native flows.
Convert has built its reputation on being the tool agencies pick when they need transparent pricing, straightforward implementation, and a strong privacy stance. It runs on session-based pricing starting at $299 per month, includes a visual editor, and gives client teams the multivariate testing and advanced targeting they need for structured programmes.
Its statistical engine supports frequentist and Bayesian methods. It integrates cleanly with Google Analytics, GA4, Amplitude, and the analytics stack most CRO agencies already run. Customer support is one of the most cited reasons teams stay on the platform.
Privacy-first testing is a class of A/B testing tool that avoids sharing visitor data with third parties and defaults to first-party cookies and minimal tracking. It is a delivery layer for experiments, distinct from running a controlled revenue experiment on product, cart, and checkout.
Where Convert.com is strong
- Transparent session-based pricing: published tiers starting at $299 per month, no forced enterprise contract.
- Agency-friendly features: multiple client workspaces, role-based access, and white-label reporting fit CRO consultancies.
- Privacy stance: no data sharing with third parties, a GDPR posture that legal teams sign off on quickly.
- Full test suite: A/B, multivariate, split URL, and server-side testing in one platform.
- Support quality: reviewers consistently rate onboarding and account management above category average.
Where Convert.com hits its ceiling for a store
- No native Shopify integration: checkout tests need manual implementation and developer time.
- No eCommerce experiment templates: product page, cart, and checkout patterns are built from scratch.
- Visual editor is functional, not polished: less refined than VWO or Optimizely for complex page edits.
- No built-in heatmaps or session recordings: teams pair Convert with Hotjar, Clarity, or another qualitative tool.
- Revenue per visitor is not a native experiment metric: teams calculate store revenue impact outside the tool.
Convert holds a 4.7/5 rating on G2 across 139+ reviews, one of the highest scores in the mid-market A/B testing category. [G2, 2026]
What is Optimizely Web Experimentation, and what is it actually good at?
Optimizely Web Experimentation is the enterprise standard for A/B testing and full-stack experimentation. It runs web tests, server-side tests, feature flags, and personalization at the scale product and engineering organisations need. Its constraint for a store is that eCommerce is not the design centre.
Optimizely serves the enterprise. Its customer base is heavy with SaaS platforms, media companies, and large marketplaces that run hundreds of concurrent experiments across web pages and back-end services. It has the deepest statistical rigor in the category, with stats-engine features such as sequential testing built for teams that ship results into product decisions.
The platform ties web experimentation to feature flags and full-stack testing. It integrates with the full enterprise data stack (Snowflake, Segment, Amplitude, and the usual BI tools). It is the tool a technical experimentation team will pick if the primary constraint is scale and governance.
Enterprise experimentation is a class of testing platform designed for engineering teams running feature flags, server-side tests, and web experiments across many surfaces at once. It is an execution and governance layer, distinct from running a controlled revenue experiment on product, cart, and checkout.
Where Optimizely is strong
- Full-stack coverage: web, server-side, feature flags, and personalization under one contract.
- Statistical rigor: sequential testing, a stats engine tuned for scale, guardrail metrics that hold under high volume.
- Enterprise integrations: deep hooks into Snowflake, Segment, Amplitude, and the BI stack.
- Programme governance: role-based permissions, environments, and audit trails built for regulated industries.
- Scale: handles hundreds of concurrent experiments without visible performance impact.
Where Optimizely hits its ceiling for a store
- Enterprise pricing and contracts: custom quotes only, out of reach for most sub-$50M ARR stores.
- No native Shopify integration: checkout and catalog experiments need custom development work.
- No eCommerce experiment templates: the platform is category-agnostic, with no product or cart patterns to reuse.
- Steep operational overhead: a dedicated experimentation engineer is effectively required.
- Visual editor less intuitive: reviewers rate the WYSIWYG below mid-market alternatives.
Optimizely holds a 4.2/5 rating on G2 across 401+ reviews, and remains the reference name enterprise buyers evaluate first. [G2, 2026]
What Convert.com and Optimizely cannot do for an eCommerce store
Convert and Optimizely both run controlled experiments. Neither is built around the surfaces where Shopify revenue is actually won or lost: the product page, the cart, and the checkout. Omniconvert Explore is built for that layer, and measures the outcome in revenue per visitor.
Convert is built for CRO practitioners running tests on general websites. It does not have native Shopify integration or purpose-built eCommerce experiment flows. A team using Convert on a Shopify store handles checkout tests through manual implementation and calculates revenue per visitor outside the tool.
Optimizely is built for enterprise engineering and product teams managing complex experiment programmes. It is not designed for eCommerce revenue workflows: there is no native Shopify integration and no checkout experiment templates. Operating it on a Shopify store needs substantial developer involvement.
Both tools optimise the execution of a test. Neither is built around the metric that matters to a store owner: revenue per visitor, not a click. That is the shared gap.
eCommerce 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 Convert nor Optimizely can tell a store owner
- Whether a winning test actually moved revenue per visitor. Both tools report on click or micro-conversion; neither treats revenue per visitor as a first-class experiment metric.
- Which surface in the eCommerce funnel to test first. Neither knows the difference between a product-page test and a checkout test in revenue terms.
- How an experiment interacts with the Shopify catalog and checkout. Variants, discount codes, and Shopify Plus checkout extensibility need engineering glue in both tools.
- Whether the result holds for high-value, repeat customers. The Customer Value Optimization question, not just first-session visitors, sits outside their model.
Across the 7,000+ eCommerce websites Omniconvert benchmarks in the CROBenchmark Report 2026, checkout friction is the single largest source of untested revenue: 99.6% of stores fail to make guest checkout prominent, and 94.2% do not show checkout progress. [CROBenchmark Report 2026, Omniconvert]
AliveCor used 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]
Convert.com vs Optimizely vs Explore: the capability comparison
All three tools run A/B tests. What differs is where they are built to run them: Convert on general websites, Optimizely across an enterprise stack, Explore on a Shopify store's revenue surfaces. Read the table by store profile, not feature count.
| Capability | Convert.com | Optimizely Web Experimentation | Omniconvert Explore |
|---|---|---|---|
| Primary function | Privacy-first A/B testing for CRO agencies | Enterprise A/B testing and full-stack experimentation | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes, visual editor with strong statistical engine | Yes, visual editor plus full-stack SDK | Yes, purpose-built for store surfaces |
| Multivariate testing | Yes | Yes | Yes |
| Server-side testing | Yes | Yes, category-defining | Yes |
| Visual editor | Yes, functional | Yes, less intuitive than mid-market rivals | Yes, tuned for store templates |
| On-site surveys and overlays | No, requires third-party tools | Partial, personalization module priced separately | Yes, on-site surveys and overlays built in |
| Shopify integration | Partial, JS snippet, no native app | No, custom development required | Yes, native Shopify integration |
| eCommerce focus | Partial, general-website design centre | No, enterprise-general design centre | Yes, eCommerce is the design centre |
| Pricing model | Session-based, from $299/mo | Custom enterprise, contact sales | Session-based, sized to store traffic |
| Best for | CRO agencies and mid-market teams testing general sites | Enterprise product and engineering teams at scale | Shopify and DTC stores measuring in revenue per visitor |
Cells describe the design centre and native support, not what a determined team can force with custom code.
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.com or Optimizely Web Experimentation?
Choose Convert.com if your team runs CRO across many client sites and wants transparent, privacy-first pricing. Choose Optimizely if you already run hundreds of experiments across web and full-stack surfaces. Choose Explore if you run a Shopify store and need product, cart, and checkout experiments tied to revenue per visitor. Explore complements the other two: you can keep an enterprise tester for feature flags and run store experiments in Explore.
Convert and Optimizely are honest picks for what they were designed to do. Convert is the mid-market, privacy-first A/B tester of choice for CRO agencies serving many clients on session-based pricing. Optimizely is the enterprise experimentation standard for engineering-heavy programmes that need feature flags and full-stack tests under one contract.
Explore is the eCommerce specialist. If your revenue lives on Shopify product pages, cart, and checkout, and the metric that matters to your CFO is revenue per visitor rather than click rate, this is the tool built around that job. Book a demo and we will map your top three test candidates against your actual store data.
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.