Apptimize vs Conductrics vs Explore (2026): SDK vs Storefront
Apptimize is a cross-platform A/B testing tool with a mobile SDK for iOS, Android, and web. Conductrics is an API-first experimentation platform with adaptive optimization for engineering teams. Both require developer implementation. Omniconvert Explore is the Shopify-native eCommerce CRO platform: it runs experiments on product, cart, and checkout, measured in revenue per visitor.
- 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]
- Conductrics is an API-first experimentation and adaptive optimization platform for data science and engineering teams, with a 4.3 out of 5 G2 rating across 12 reviews. [G2, 2026]
- Both are developer-first: neither has a visual editor, neither integrates natively with Shopify, and every web experiment starts as an SDK ticket or an API integration.
- 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 Apptimize vs Conductrics are usually looking at two developer-first testing tools: one mobile-first, one API-first, both handing the actual work to engineering. Apptimize leads with true cross-platform SDK testing across iOS, Android, React Native, and web. Conductrics leads with API-first adaptive optimization built for data science and engineering teams. Both are strong for the audiences they target, 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 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 assignment 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 SDK 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.
- Server-side and client SDK support: covers both native client 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 is Conductrics, and what is it actually good at?
Conductrics is an API-first experimentation and adaptive optimization platform built for technical teams. It supports classic A/B testing plus multi-armed bandits and adaptive targeting, and is designed to be embedded programmatically into a team's own applications rather than run as a standalone marketing tool. [Conductrics, 2026]
Conductrics is an experimentation engine for teams that want programmatic control. It holds a 4.3 out of 5 rating on G2 across 12 reviews. [G2, 2026] Its strength is the shape of the API and the machine-learning layer around it: a data science team can wire adaptive optimization into a checkout, a search ranker, or a pricing engine and let the platform allocate traffic to the arm that is currently winning.
Assignment happens through API calls, with server-side splits and multi-armed bandit optimization. There is no visual editor and no marketer-facing dashboard for building a page variant; every experiment is defined by the team that owns the code.
API-first experimentation exposes assignment, targeting, and outcome tracking as an API that a team calls from its own application code, rather than a WYSIWYG builder or a Shopify app. Conductrics adds multi-armed bandit optimization on top, so traffic shifts to the leading variant while the test runs. It is a developer-owned optimization layer, distinct from running a controlled revenue experiment on Shopify product, cart, and checkout pages through a marketer-accessible interface.
Where Conductrics is genuinely strong
- API-first architecture: assignment and targeting exposed as programmatic calls a technical team can embed anywhere.
- Multi-armed bandit optimization: adaptive allocation shifts traffic to the arm that is currently winning while the test runs.
- Adaptive targeting: machine-learning-driven segmentation useful for personalization inside custom applications.
- Fit for embedded use cases: built for teams that need experimentation inside their own product, not as a standalone tool.
Where Conductrics hits its ceiling for an eCommerce store
- No visual editor: every variant is defined in code and requires developer implementation.
- No native Shopify integration: nothing wired to product pages, cart, or checkout out of the box.
- Not built for self-serve marketing: the product is designed around engineering ownership, not a CRO lead who wants to ship this week.
- Limited public documentation: very low brand presence and thin documentation compared to mainstream tools.
- Generic outcome model: results arrive through custom API-connected events, not native revenue per visitor on the store funnel.
What Apptimize and Conductrics cannot do for an eCommerce store
Apptimize and Conductrics come from different corners (mobile clients and back-end APIs) but land on the same shape for a store. Both are developer-first tools that expect 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.
Apptimize is mobile-first and designed for teams running iOS and Android apps alongside a web experience. On a Shopify 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. A winning variant on the mobile app rarely reaches the Shopify checkout without a separate build.
Conductrics is API-first and designed for data science and engineering teams embedding optimization into their own applications. On a store storefront that shape becomes the same problem from the opposite direction: every experiment is an API integration, event schemas are custom, and there is no self-serve interface for a marketer to launch a product page test. Results come back as data the team has to model against orders, not native revenue per visitor.
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, neither speaks Shopify natively, 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 SDK or API code, ship the variant, 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 a custom 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 or API 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 Apptimize the same fix is a mobile-shaped SDK ticket for the web, sitting behind the mobile release train. In Conductrics it is an API integration and an event-schema conversation with the data team. Explore runs the experiment on the real revenue surfaces and reports the outcome in revenue per visitor, without an SDK or API build between the hypothesis and the result.
This is what the title means by SDK vs storefront. Cross-platform mobile testing and API-first adaptive optimization 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 and API-first tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
Apptimize vs Conductrics vs Explore: the capability comparison
Side by side, the three tools sit at different points on the experiment map. Apptimize is the cross-platform mobile-first tester for product teams running iOS and Android alongside web. Conductrics is the API-first adaptive-optimization engine for data science and engineering teams. 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 | Apptimize | Conductrics | Omniconvert Explore |
|---|---|---|---|
| Primary function | Cross-platform mobile A/B testing and feature flags | API-first experimentation with adaptive optimization | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes SDK-based across iOS, Android, and web | Yes API-first, no visual editor | Yes visual editor plus code |
| Multivariate testing | No | No multi-armed bandits instead | Yes |
| Server-side testing | Yes supported alongside client SDKs | Yes core capability | Yes |
| Visual editor | No code and SDKs only | No code and APIs 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 mobile product teams | Low built for data science and engineering 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 | Mobile product teams testing across iOS, Android, and web | Data science and engineering teams wanting API-first adaptive optimization | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.3 out of 5 (G2, 35 reviews, as of 2026) | 4.3 out of 5 (G2, 12 reviews, as of 2026) | 4.6 out of 5 (G2, 191 reviews, as of 2026) |
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. Apptimize is mobile-first cross-platform SDK testing; Conductrics is API-first adaptive experimentation. 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 Apptimize or Conductrics?
Decide by who runs the tests. If your mobile product team wants cross-platform SDK testing across iOS and Android, keep Apptimize. If your engineering team wants API-first experimentation with multi-armed bandits inside your own app, Conductrics fits. But a Shopify marketing team cannot ship a product page or checkout variant in either tool without engineering time. Run your next test in Explore, self-serve, measured in revenue per visitor. Only Explore is built for the storefront where the order closes.
Apptimize and Conductrics are both strong at what they do. Apptimize brings true cross-platform testing to teams running a mobile app alongside a web experience. Conductrics brings programmatic API-first experimentation and multi-armed bandit optimization to data science and engineering teams.
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.
4.6 out of 5 across 191 reviews, G2 , as of 2026