AB Smartly vs Apptimize vs Explore (2026): Two SDK Testers, One Blind Spot
AB Smartly is a real-time experimentation platform from former Booking.com engineers, with SDK-based assignment. Apptimize is a mobile-first testing tool that runs experiments across iOS, Android, and web through one SDK. Both need developer work. Omniconvert Explore is the Shopify-native eCommerce CRO platform: it runs product, cart, and checkout experiments and measures results in revenue per visitor.
- AB Smartly is a real-time experimentation platform built by former Booking.com engineers, with a 4.8 out of 5 G2 rating across 45 reviews. [G2, 2026]
- Apptimize is a mobile-first cross-platform A/B testing tool that runs experiments across iOS, Android, React Native, and web through one SDK, with a 4.3 out of 5 G2 rating across 35 reviews. [G2, 2026]
- Both are SDK-first: neither has a visual editor, neither integrates natively with Shopify, and every web experiment starts as a developer ticket.
- Neither runs experiments natively on the Shopify product page, cart, or checkout, and neither reports the outcome in revenue per visitor.
- Omniconvert Explore is a Shopify-native eCommerce CRO platform: it runs A/B, multivariate, and checkout experiments through a visual editor and measures the result in revenue per visitor.
Teams comparing AB Smartly vs Apptimize are usually choosing an SDK-based experimentation platform for a product engineering group. AB Smartly leads with real-time server-side results shaped by the Booking.com programme. Apptimize leads with true cross-platform A/B testing across iOS, Android, React Native, and web in one SDK. Both are strong for engineering-driven testing, but neither is designed for a Shopify marketing team to ship product page or checkout experiments. This page covers what each does well, the gap they share for eCommerce, and when Omniconvert Explore is the right layer.
What is AB Smartly, and what is it actually good at?
AB Smartly is a real-time experimentation platform built by former Booking.com engineers. It uses SDK-based assignment, exposes results as they arrive rather than in a nightly batch, and connects directly to a data warehouse for downstream analysis. It is built for high-velocity engineering programmes that treat testing as continuous infrastructure. [AB Smartly, 2026]
AB Smartly is an engineering platform built by practitioners of one of the largest experimentation programmes in the industry. It holds a 4.8 out of 5 rating on G2 across 45 reviews. [G2, 2026] Its strength is speed and rigour together: results update in real time rather than in a scheduled job, and the platform is designed for teams that run hundreds of parallel experiments without waiting on a batch pipeline.
Assignment happens through SDKs, with server-side splits and advanced statistical methods. The warehouse connector lets a data team join experiment exposure to any downstream metric that already lives in Snowflake, BigQuery, or Redshift.
Real-time experimentation streams experiment assignment and outcome events as they happen, so exposures and metrics update continuously instead of running as a scheduled batch. AB Smartly does this well for engineering teams shipping many parallel tests. It is an execution and analysis layer for developer-owned code, distinct from running a controlled revenue experiment on Shopify product, cart, and checkout pages through a marketer-accessible interface.
Where AB Smartly is genuinely strong
- Real-time results: exposures and metrics update continuously, not in a nightly batch.
- Booking.com heritage: statistical methods and program design shaped by one of the largest testing programmes in the industry.
- Warehouse connector: joins experiment exposure to metrics already defined in Snowflake, BigQuery, or Redshift.
- Server-side and SDK based: scales for high-velocity engineering programmes running many parallel tests.
Where AB Smartly hits its ceiling for an eCommerce store
- No visual editor: variants ship through code and SDKs, not a WYSIWYG a marketer can use.
- No native Shopify integration: nothing wired to product pages, cart, or checkout out of the box.
- Engineering-priced: custom pricing designed for engineering-led organisations, not for a self-serve CRO budget.
- No multivariate testing: the platform does not run MVT natively.
- Generic outcome model: no concept of revenue per visitor as a first-class metric on the store funnel.
What is Apptimize, and what is it actually good at?
Apptimize is a mobile-first cross-platform A/B testing and feature management platform. One SDK covers iOS, Android, React Native, and the web, so a single experiment can run with consistent logic across every surface. It is built for mobile product teams shipping a native app alongside a web experience. [Apptimize, 2026]
Apptimize is one of the few platforms that runs a single experiment across iOS, Android, React Native, and web with the same assignment logic. It holds a 4.3 out of 5 rating on G2 across 35 reviews. [G2, 2026] Its strength is consistency across surfaces: a mobile product team can define a variant once and see how it behaves on every client without a separate testing tool per platform.
The platform pairs experimentation with feature flag management, so shipping and rolling back a variant sit in the same workflow as running the test. Assignment happens through SDKs; there is no visual editor for web pages.
Cross-platform A/B testing runs one experiment with shared assignment and metric logic across native iOS, Android, and web clients, using an SDK on each surface. Apptimize does this well for mobile product teams. It is a mobile-first delivery and feature-flag layer, distinct from running a controlled revenue experiment on Shopify product, cart, and checkout pages through a marketer-accessible interface.
Where Apptimize is genuinely strong
- True cross-platform testing: one experiment across iOS, Android, React Native, and web with shared logic.
- Feature flag management: shipping and rollback of variants sits inside the same workflow as the test.
- Mobile product focus: built for teams whose primary revenue surface is a native app, not a website.
- SDK-based server and client testing: covers both native and server-side experiment logic.
Where Apptimize hits its ceiling for an eCommerce store
- No visual editor: every web variant needs SDK implementation, not a WYSIWYG a marketer can use.
- No native Shopify integration: nothing wired to product pages, cart, or checkout out of the box.
- Mobile-first, not store-first: the product is designed around a native app funnel, not a Shopify storefront.
- No multivariate testing: the platform does not run MVT natively.
- Generic outcome model: no concept of revenue per visitor or repeat-customer value on the store funnel.
What AB Smartly and Apptimize cannot do for an eCommerce store
AB Smartly and Apptimize sit on different edges of the same shape: both are SDK-first tools that ask engineering to own the test. Neither has a visual editor for web, neither integrates natively with Shopify, and neither is built around the surfaces where store revenue is won or lost (product pages, cart, and checkout) or the metric that matters there: revenue per visitor.
AB Smartly is built for engineering teams running high-velocity, real-time server-side tests, and the Booking.com pedigree shows in how the platform treats experimentation as continuous infrastructure. On a Shopify store the same shape becomes a problem. Every product page, cart, and checkout experiment starts as an SDK ticket, and the queue is set by engineering. The A/B test the CRO lead wanted this week ships when engineering ships it.
Apptimize is mobile-first and designed for teams running iOS and Android apps alongside a web experience. On a store storefront, that focus flips into a gap: web experiments require the same manual SDK implementation as the mobile clients, without any native Shopify connector, and there is no marketer-accessible interface for a cart or checkout test. The winning variant on the mobile app rarely reaches the Shopify checkout without a separate build.
The gap the two share is the eCommerce one. These are experimentation platforms, but they are not eCommerce CRO platforms. Neither treats the product-to-checkout path as the primary surface, and neither reports the result in revenue per visitor. For the wider context on how testing programmes actually move revenue, see Has personalization replaced A/B testing?
The deeper issue is that ownership of the test sits far from the person who owns the revenue number. A CRO lead has a hypothesis about the cart page and, in either tool, needs a developer to write assignment code, ship the variant behind a flag, and later stitch results back to order rate. Omniconvert Explore collapses that loop: a visual editor for product page and checkout variants, native Shopify integration, on-site surveys and overlays in the same platform, and the outcome measured in revenue per visitor. The person who owns the store's growth number owns the test.
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 variant raised revenue per visitor and order rate, and held its margin once discounts and returns are counted, not just moved an engineering event or a mobile-app conversion.
- Which surface to test first. Which pages in the store funnel (product, cart, checkout) carry the highest revenue impact if tested next.
- How it behaves in Shopify checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without a manual SDK build for the storefront.
- Whether it holds for valuable customers. Whether the result holds for repeat, high-value customers, the Customer Value Optimization question, not just for first-session or first-install visitors.
Omniconvert benchmarks more than 7,000 eCommerce websites in its CROBenchmark Report 2026, across 248+ audit criteria. The findings show where stores actually lose orders: 99.6% fail to make guest checkout visible and prominent, and 94.2% never show checkout progress steps to the shopper. [CROBenchmark Report 2026, Omniconvert]
Those are fixes a CRO lead can hypothesise, mock up, and want to test today. In AB Smartly or Apptimize, the same fix is an engineering ticket, sitting in a queue set by another team, and in Apptimize's case a queue mostly shaped by the mobile release train. Explore runs the experiment on the real revenue surfaces and reports the outcome in revenue per visitor, without an SDK integration between the hypothesis and the result.
This is what the title means by two SDK testers, one blind spot. Real-time engineering rigour and true cross-platform mobile testing are both real capabilities, but they sit on top of the metric another team owns. Explore optimizes for revenue per visitor 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 SDK-first tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
AB Smartly vs Apptimize vs Explore: the capability comparison
Side by side, the three tools sit at different points on the experiment map. AB Smartly is the real-time server-side platform for engineering teams shipping many parallel tests. Apptimize is the cross-platform mobile-first tester for product teams running iOS and Android alongside web. Explore is the eCommerce CRO layer for the store team that owns product, cart, and checkout, and is judged on revenue per visitor. See A/B testing with Explore for how those experiments run natively on the Shopify funnel.
| Capability | AB Smartly | Apptimize | Omniconvert Explore |
|---|---|---|---|
| Primary function | Real-time engineering-led experimentation | Cross-platform mobile A/B testing and feature flags | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes SDK-based, no visual editor | Yes SDK-based across iOS, Android, and web | Yes visual editor plus code |
| Multivariate testing | No | No | Yes |
| Server-side testing | Yes core capability | Yes supported alongside client SDKs | Yes |
| Visual editor | No code and SDKs only | No code and SDKs only | Yes WYSIWYG for marketers |
| On-site surveys and overlays | No | No | Yes surveys and overlays built in |
| Shopify integration | Low no native connector | Low no native connector | Yes native |
| eCommerce focus | Low built for engineering teams | Low built for mobile product teams | High built for store revenue workflows |
| Pricing model | Custom, contact sales, enterprise | Custom, contact sales, enterprise | Session-based, built for store traffic, free trial |
| Best for | Engineering teams wanting real-time server-side experimentation | Mobile product teams testing across iOS, Android, and web | Shopify and eCommerce teams optimizing for revenue |
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]
Competitor ratings, pricing, and plan details reflect publicly listed figures as of 2026 and can change. AB Smartly is engineering-owned real-time experimentation; Apptimize is mobile-first cross-platform testing. Neither is a marketer-accessible eCommerce CRO tool. 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 Apptimize?
Decide by who runs your tests. If your engineering team wants real-time experiments with Booking.com-grade statistics, AB Smartly serves them. If your mobile team wants A/B testing across iOS, Android, and web in one SDK, Apptimize serves them. But a Shopify marketing or CRO team cannot ship page or checkout variants in either tool without developer work. For a store, run your next test on the product-to-checkout path in Explore, self-serve, and read the result in revenue per visitor.
AB Smartly and Apptimize are both strong at what they do. AB Smartly brings real-time engineering rigour shaped by the Booking.com programme. Apptimize brings true cross-platform testing to teams running a mobile app alongside a web experience.
The question for a store is narrower: once you have a hypothesis about the cart or checkout, can a CRO lead ship the variant, measure the result in revenue per visitor, and answer whether the win holds for high-value repeat customers, without waiting on an engineering or mobile-release ticket. 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.