AB Tasty vs Conductrics vs Explore (2026): Marketing vs API
AB Tasty is a no-code experimentation and personalisation platform, reorganised inside the VWO group after its 2025 merger. Conductrics is an API-first experimentation and adaptive optimisation tool for engineering and data science teams, with no visual editor. Neither is Shopify-native. Omniconvert Explore is the eCommerce CRO platform for product, cart, and checkout, measured in revenue per visitor.
- AB Tasty is a no-code web experimentation and personalisation platform, reorganised inside the VWO group after its 2025 merger, with a 4.5 out of 5 G2 rating. [G2, 2026]
- Conductrics is an API-first experimentation and adaptive optimisation tool for engineering and data science teams, with no visual editor and a 4.3 out of 5 G2 rating. [G2, 2026]
- The two sit at opposite ends of the same shelf: a marketer's no-code visual tool versus an engineer's programmatic optimisation engine.
- Neither has native Shopify integration, store-tuned checkout templates, or revenue per visitor as a first-class outcome metric.
- Omniconvert Explore is the Shopify-native eCommerce CRO platform: visual editor and native checkout, measured in revenue per visitor, owned by the store team.
Teams comparing AB Tasty vs Conductrics are weighing two very different experimentation approaches: a no-code visual tool built for marketers against an API-first engine built for engineers. AB Tasty, now inside the VWO group after its 2025 merger, lets a growth lead build and ship variants without a developer. Conductrics is the opposite: no visual editor, programmatic control, and multi-armed bandit optimisation embedded through code. This page covers what each does well, the Shopify gap they both leave, and when Omniconvert Explore is the right layer for a mid-market store.
What is AB Tasty, and what is it actually good at?
AB Tasty is a web experimentation and personalisation platform. It combines A/B testing, feature flags, and personalisation in one interface, built around a no-code visual editor. Since merging into the VWO group in 2025 it has expanded its feature set and support resources, and remains a popular pick for marketing teams that want to run tests without developer involvement. [AB Tasty, 2026]
AB Tasty is a marketing-team platform first and an engineering tool second. It holds a 4.5 out of 5 rating on G2 across 185 reviews. [G2, 2026] Its strength is breadth for a growth team: a no-code editor for building variants on marketing pages, feature flags for gradual rollouts, and a personalisation layer for audience-based experiences, all in the same product.
Server-side testing is available through a separate paid add-on tier rather than the core plan. Since the VWO merger, the roadmap and pricing have been reorganised, and the combined platform now leans on VWO's wider testing and behaviour analytics stack for depth.
No-code experimentation lets a marketer build and ship experiment variants through a visual editor rather than through code, with variant assignment handled by the platform. AB Tasty does this well for marketing-site testing and feature-flagged releases. It is a generic web experimentation layer, distinct from running a controlled revenue experiment on Shopify product, cart, and checkout pages against native store data.
Where AB Tasty is genuinely strong
- No-code visual editor: marketers build variants without waiting on engineering.
- Feature flags in the same platform: combines A/B testing and gradual feature rollouts in one interface.
- Personalisation layer: audience-based experiences alongside A/B and multivariate tests.
- Post-merger depth: access to the wider VWO testing and analytics stack after the 2025 merger.
Where AB Tasty hits its ceiling for an eCommerce store
- Limited native Shopify integration: no first-class connector to product pages, cart, or checkout out of the box.
- No eCommerce-specific templates: checkout flow experiments must be built manually rather than from a store-tuned starting point.
- Server-side is an add-on: gated behind a separate paid tier, not part of the core plan.
- Post-merger uncertainty: pricing and roadmap have been reorganised since the VWO merger, and buyers report a moving target.
- Generic outcome model: no concept of revenue per visitor as a first-class metric on the store funnel.
What is Conductrics, and what is it actually good at?
Conductrics is an API-first experimentation and adaptive optimisation platform. It is built for data science and engineering teams who want programmatic control over tests, with multi-armed bandit optimisation and adaptive targeting at its core. There is no visual editor: variants, traffic rules, and outcomes are defined through code and APIs. [Conductrics, 2026]
Conductrics is an engineer's tool through and through. It holds a 4.3 out of 5 rating on G2 across 12 reviews. [G2, 2026] Its strength is embedded optimisation: a team integrates the API into its own application and gets bandit-driven, adaptive variant selection without buying a marketer-oriented testing suite.
Multi-armed bandits and adaptive targeting are the headline capability, which means Conductrics is less about discrete A/B tests with a confidence calculation and more about continuous optimisation that shifts traffic toward the best-performing variant over time. That model suits product teams building in-app experiences, not marketing teams shipping landing-page variants.
API-first experimentation means every test is defined, delivered, and read through a programmatic interface, with no visual editor on top of a webpage. Conductrics does this well for engineering teams embedding adaptive optimisation inside their own applications. It is an application-layer optimisation tool, distinct from running a self-serve revenue experiment on Shopify product, cart, and checkout pages from a marketer-accessible interface.
Where Conductrics is genuinely strong
- Multi-armed bandit optimisation: traffic shifts automatically toward the best-performing variant without a manual winner call.
- Adaptive targeting: the engine learns which audience responds to which variant and routes accordingly.
- API-first integration: fits teams that want experimentation inside their own application, not a bolt-on tool.
- Server-side native: every test runs server-side by design, which suits product and infrastructure experiments.
Where Conductrics hits its ceiling for an eCommerce store
- No visual editor: a marketer cannot build a variant on a Shopify product page without a developer.
- Developer implementation required: every test needs engineering work to define, deliver, and read.
- No native Shopify integration: product, cart, and checkout have to be wired as custom API calls, not a store connector.
- Low brand recognition: minimal public documentation and a small G2 footprint make vendor evaluation harder than for mainstream tools.
- No eCommerce metrics native: revenue per visitor and order rate must be constructed from custom events, not read as first-class outcomes.
What AB Tasty and Conductrics cannot do for an eCommerce store
AB Tasty and Conductrics sit at opposite ends of the same shelf. One is the marketer's no-code tool, now inside the VWO group; the other is the engineer's API-first optimisation engine. Neither is built around Shopify product, cart, and checkout, and neither reports the result in revenue per visitor. For a store team that owns the growth number, the two tools leave the same gap at different ends.
AB Tasty is oriented towards marketing-website experimentation and feature management. A growth lead can build a variant in the visual editor without a developer, which is a real advantage. The gap opens when the test reaches the Shopify catalog and checkout: there is no native connector, no eCommerce-specific templates for cart or checkout, and revenue-focused experiments have to be built manually against custom events rather than a native store data model. Post-merger, buyers also report a moving target on pricing and roadmap while VWO reshuffles the combined suite.
Conductrics takes the opposite route. It is designed for technical teams embedding optimisation into their own applications, with no visual editor and no marketer-accessible interface. A Shopify store that wants a bandit-driven test on a product page has to pay for engineering time to integrate the API, define events, and read outcomes. That is a very different buyer from the marketer who was going to pick AB Tasty for no-code variants, and it stalls on development capacity rather than on roadmap.
The gap the two share is the eCommerce one. One is marketing-priced and no-code but Shopify-blind; the other is engineer-priced and programmatic but Shopify-blind in a different way. 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 never lands on the person who owns the revenue number for the store. In AB Tasty the marketer owns the variant but the checkout integration still requires custom work; in Conductrics the engineer owns the integration but the marketer who runs the growth programme cannot self-serve. 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 bandit's allocation or a feature-flagged click.
- 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 checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without a custom connector or a custom API integration.
- 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 visitors or a bandit-selected cohort.
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: 94.2% never show checkout progress steps to the shopper, and 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
Those are fixes a CRO lead can hypothesise, mock up, and want to test today. In AB Tasty a marketer can build the variant, but wiring the outcome back to Shopify checkout revenue is custom work, and post-merger the module map for that work keeps shifting. In Conductrics the engineer can wire the API, but the marketer who owns the growth number has no way in and the hypothesis stalls on engineering capacity. Explore runs the experiment on the real revenue surfaces and reports the outcome in revenue per visitor, without a custom connector or an engineering ticket between the hypothesis and the result.
This is what the title means by marketing versus API. Two capable testing tools at opposite ends of the market, and both looking past the surface where a Shopify store's revenue is actually decided. 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 generic testing tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
AB Tasty vs Conductrics vs Explore: the capability comparison
Side by side, the three tools sit at different points on the experiment lifecycle. AB Tasty is the no-code marketing layer for feature-flagged web experimentation, now inside the VWO group. Conductrics is the API-first optimisation engine for engineering teams embedding bandits into their own applications. 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 Tasty | Conductrics | Omniconvert Explore |
|---|---|---|---|
| Primary function | No-code web testing and feature management | API-first experimentation and adaptive optimisation | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor and feature flags | Yes API-first, no visual editor | Yes visual editor plus code |
| Multivariate testing | Yes | No | Yes |
| Server-side testing | Partial via a separate paid server-side add-on | Yes server-side native by design | Yes |
| Visual editor | Yes strong no-code editor | No API-first only, developer required | Yes WYSIWYG for marketers |
| On-site surveys and overlays | Partial personalisation, no native survey tool | No API-first, no native overlay or survey layer | Yes surveys and overlays built in |
| Shopify integration | Medium limited, no native checkout connector | Low no native connector, API work required | Yes native |
| eCommerce focus | Medium marketing-site oriented, not store-native | Low engineer-oriented, not store-native | High built for store revenue workflows |
| Pricing model | Custom, contact sales, free trial available | Custom, contact sales, no free trial | Session-based, built for store traffic, free trial |
| Best for | Marketing teams wanting no-code testing and feature flags | Data science and engineering teams wanting API-first bandits | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.5 out of 5 (G2, 185 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. AB Tasty is a marketing-team platform now inside the VWO group after the 2025 merger; Conductrics is an API-first engineering tool with no visual editor. 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 Tasty or Conductrics?
Decide by who owns the test. If a marketing team runs variants on broad web pages and wants feature flags in the same place, AB Tasty inside VWO fits. If an engineering team wants programmatic experimentation with adaptive bandits, Conductrics fits. For a Shopify store judged on revenue per visitor, run the next product, cart, and checkout experiment in Explore, where the test ships natively against store data and reports back in revenue per visitor.
AB Tasty and Conductrics are both capable experimentation tools, built for opposite ends of the market. AB Tasty is the marketer's no-code pick, reorganised inside the VWO group after the 2025 merger. Conductrics is the engineer's API-first pick, built for teams embedding bandit optimisation into their own applications.
The question for a Shopify store is narrower: can the person who owns the growth number run a controlled experiment on product, cart, and checkout today, and read the result in revenue per visitor. That is the surface Explore is built for, and the reason most eCommerce teams land on it rather than on a marketing-site tool or an API-first engine.
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