AB Smartly vs Varify.io vs Explore (2026): Two Testers, One Checkout Gap
AB Smartly is an engineering-led SDK-based experimentation platform built by former Booking.com engineers. Varify.io is a European GDPR-compliant A/B testing tool with a visual editor and session-based pricing. 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.
- AB Smartly is a real-time SDK-based A/B testing platform built by former Booking.com engineers, with a 4.8 out of 5 G2 rating across 45 reviews. [G2, 2026]
- Varify.io is a European GDPR-compliant visual A/B testing tool with a 4.8 out of 5 G2 rating across 36 reviews and flat session-based pricing. [G2, 2026]
- AB Smartly is engineering-first with no visual editor and no native Shopify; Varify.io is marketer-friendly and GDPR-first but front-end only, with no server-side testing.
- Neither runs A/B tests natively on the Shopify checkout, or reports outcomes in revenue per visitor across the product-to-checkout path.
- 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 AB Smartly vs Varify.io are looking at two very different corners of the testing market: engineering-led SDK experimentation on one side, European GDPR-first visual testing on the other. AB Smartly leads with real-time results and warehouse hooks built for product engineers. Varify.io leads with a clean visual editor and predictable session-based pricing for European mid-market teams. Both are strong for their audiences, but neither is built around the surfaces where a Shopify store actually wins or loses revenue: the product page, the cart, and the checkout, which is where Omniconvert Explore lives.
What is AB Smartly, and what is it actually good at?
AB Smartly is a real-time A/B testing platform built by former Booking.com engineers. It runs SDK-based server-side experiments, streams results live, and connects natively to the customer's own data warehouse. It is built for engineer-led, high-velocity experimentation programmes. [AB Smartly, 2026]
AB Smartly holds a 4.8 out of 5 rating on G2 across 45 reviews. [G2, 2026] Its strength is engineering-first experimentation: real-time result streaming, a native connector into Snowflake, BigQuery, or Redshift, and statistical methods refined at Booking.com scale. That combination fits organizations where the experimentation programme is run by product engineers and data scientists rather than marketers.
The category AB Smartly sits in is high-velocity SDK-based testing. It runs experiments through code rather than a visual editor, which is how it stays honest about server-side behavior and warehouse joins. That focus is the point of the product, not a gap in it.
Real-time experimentation streams results as events arrive, so engineering teams can see effects at low latency and cut, hold, or scale traffic quickly. AB Smartly builds this into its SDK and warehouse connector. It is an engineering delivery layer, distinct from running a controlled revenue experiment natively on Shopify product, cart, and checkout pages.
Where AB Smartly is genuinely strong
- Real-time result streaming: low-latency reads on lift and significance as events arrive.
- Data warehouse integration: native connection into the customer's own Snowflake, BigQuery, or Redshift.
- Statistical rigor from Booking.com: variance reduction and sequential methods refined at scale.
- SDK-based server-side testing: engineering-led velocity for teams that ship changes through code.
Where AB Smartly hits its ceiling for an eCommerce store
- No visual editor: CRO and marketing teams cannot ship a test without engineering time.
- No native Shopify integration: product page and checkout tests need custom code.
- No multivariate testing: rules out combinatorial experiments common in eCommerce.
- Engineering event metrics: results arrive as event data, not revenue per visitor.
What is Varify.io, and what is it actually good at?
Varify.io is a European GDPR-compliant A/B testing platform with a visual editor, advanced targeting, and transparent session-based pricing. It is popular with mid-market teams across the EU that need front-end experimentation without the compliance friction that comes with US-owned tools. [Varify.io, 2026]
Varify.io holds a 4.8 out of 5 rating on G2 across 36 reviews, one of the highest scores in the European A/B testing category. [G2, 2026] Its strength is a clean, marketer-friendly product: a visual editor a growth team can operate without engineering, targeting rules for segmentation, and a flat session-based price that stays predictable when traffic spikes. Support is consistently praised in review threads.
The category Varify.io sits in is European privacy-first front-end testing. It is built to run visual A/B tests on general websites while satisfying EU data-protection expectations out of the box. That focus is the point of the product.
GDPR-first A/B testing means the platform is engineered around EU data-protection rules by default: EU data residency, no third-party data sharing, and minimal cookie footprint. Varify.io builds this into its product and pricing. It is a compliance and delivery choice, distinct from running a controlled revenue experiment natively on Shopify product, cart, and checkout templates.
Where Varify.io is genuinely strong
- GDPR compliance out of the box: EU-friendly data handling that removes a common blocker for European teams.
- Marketer-accessible visual editor: growth teams can ship a front-end test without engineering time.
- Transparent session-based pricing: costs stay predictable through traffic spikes, from $299 per month with a free trial.
- Advanced targeting and highly rated support: granular audience rules and support that reviewers repeatedly single out.
Where Varify.io hits its ceiling for an eCommerce store
- No server-side testing: rules out backend logic tests such as pricing, shipping thresholds, or discount rules.
- Limited Shopify integration: checkout flow experiments are not natively supported and need custom integration work.
- Front-end scope: good for landing and category pages, thin on full-funnel product-to-checkout coverage.
- Generic conversion focus: results are framed around conversion tracking, not revenue per visitor.
What AB Smartly and Varify.io cannot do for an eCommerce store
AB Smartly and Varify.io sit at opposite ends of the testing market: engineering-first server-side SDKs on one side, marketer-first GDPR visual testing on the other. Both leave the same gap for a store. Neither can run a controlled A/B test on the Shopify product page, cart, and checkout surfaces themselves and read the result in revenue per visitor.
AB Smartly is built for engineering teams running high-velocity server-side experiments. It has no native Shopify integration and cannot run product page or checkout experiments through a visual interface accessible to non-technical users. A marketer cannot ship a test without engineering time, and results arrive as engineering event data for the warehouse rather than eCommerce revenue metrics.
Varify.io is a European privacy-first A/B testing platform focused on front-end web optimization. It does not have native Shopify integration or purpose-built eCommerce checkout experiment templates. Teams using it for Shopify CRO get clean front-end testing but cannot run revenue-connected experiments on the cart and checkout flows without custom integration work, and there is no server-side testing to cover the backend logic that shapes an order.
The two gaps look opposite but land in the same missing layer. AB Smartly optimizes the mechanics of a test at engineering scale on a generic page. Varify.io optimizes a front-end variant with EU-friendly data handling on a generic page. Neither is built around where a store's revenue is actually decided: the product page template, the cart page, and the Shopify checkout, read as revenue per visitor and tied back to repeat, high-value buyers through Customer Value Optimization. For the wider debate behind acting on experiment data, see Has personalization replaced A/B testing?
There is also a data insights gap underneath the testing gap. AB Smartly ships engineering event streams, not on-site heatmaps or surveys, so a marketing team stitches those in from third-party tools. Varify.io ships front-end testing but no built-in behavioral analysis, so heatmaps, session recordings, and on-site surveys still come from a second vendor. 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, on the store's real revenue 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 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 moved a click, an engineering event, or a front-end micro-conversion.
- Which surface to test first. Which pages in the funnel (product, cart, checkout) carry the highest revenue impact if tested next, not just which landing page variant had the highest signup rate.
- How it behaves in checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without engineering glue work or template forking.
- Whether it holds for valuable customers. Whether the result holds for repeat, high-value buyers, the Customer Value Optimization question, not just first-session visitors or first-time front-end respondents.
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 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
These are checkout-surface problems, exactly the surfaces a code-first testing SDK or a front-end visual testing tool is not built to experiment on directly. 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 testers and one checkout gap. A server-side experiment won at engineering speed on a generic page can leave the bank balance flat; so can a lifted front-end conversion on a landing page that never reaches the Shopify checkout. What actually moves the store's revenue 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 click or a landing-page conversion often does not. That is the revenue question AB Smartly and Varify.io are 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.
AB Smartly vs Varify.io vs Explore: the capability comparison
Side by side, the three tools cover different jobs. AB Smartly runs code-first server-side tests for engineering teams. Varify.io runs GDPR-first visual A/B tests for European mid-market marketers. Explore adds native Shopify A/B and multivariate experiments across product, cart, and checkout, with built-in surveys and revenue-per-visitor measurement on the full funnel. See A/B testing with Explore for how those experiments run natively on the Shopify funnel.
| Capability | AB Smartly | Varify.io | Omniconvert Explore |
|---|---|---|---|
| Primary function | Real-time SDK-based experimentation | GDPR-first visual A/B testing | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes SDK-based, no visual editor | Yes visual editor, front-end only | Yes visual plus code editor |
| Multivariate testing | No | Limited basic combinations only | Yes across page elements |
| Server-side testing | Yes SDK-native | No | Yes |
| Visual editor | No engineering only | Yes marketer-friendly | Yes |
| On-site surveys and overlays | No engineering event streams only | No needs third-party tools | Yes surveys and overlays built in |
| Shopify integration | Low no native connector | Medium not native, no checkout support | Yes native |
| eCommerce focus | Low engineering-first, category-agnostic | Medium European mid-market web | High built for store revenue workflows |
| Pricing model | Custom, contact sales | Session-based, from $299/mo, free trial | Session-based, built for store traffic, free trial |
| Best for | Engineering teams wanting real-time results with warehouse rigor | European mid-market teams wanting GDPR-compliant flat-rate testing | Shopify and eCommerce teams optimizing for revenue per visitor |
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. AB Smartly uses custom pricing quoted on request. Varify.io starts at $299/month with a free trial. 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 AB Smartly or Varify.io?
Decide by team shape and where your traffic lives. If your programme is engineer-run and needs real-time warehouse-linked results, keep AB Smartly. If you are European mid-market and want visual GDPR-compliant tests with predictable pricing, keep Varify.io. For A/B tests on your Shopify product pages, cart, and checkout, measured in revenue per visitor, run those in Explore. The three cover different jobs, but only Explore tests where the order closes.
AB Smartly and Varify.io are both strong inside their categories. AB Smartly is a real-time engineering-led experimentation platform built by Booking.com veterans, with a 4.8 out of 5 G2 rating. Varify.io is a top-rated European GDPR-first visual testing tool, at 4.8 out of 5 on G2 across 36 reviews.
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 an engineering event or a landing-page conversion. 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.