Conductrics vs Dynamic Yield vs Explore (2026): Neither Built for Shopify
Conductrics is API-first experimentation for engineering teams that want programmatic control and adaptive optimization. Dynamic Yield is enterprise personalization for retail brands with dedicated implementation teams. Omniconvert Explore is an eCommerce CRO platform for mid-market Shopify stores that need self-serve testing on product, cart, and checkout, measured in revenue per visitor.
- Conductrics is API-first experimentation for engineering teams with a 4.3 out of 5 G2 rating across 12 reviews. [G2, 2026]
- Dynamic Yield is an enterprise personalization suite owned by Mastercard with a 4.5 out of 5 G2 rating across 200 reviews. [G2, 2026]
- The two tools share the same blind spot: neither is built around Shopify revenue surfaces (product, cart, checkout) for marketer-led self-serve testing.
- Explore runs A/B, multivariate, personalization, and on-site surveys natively on Shopify, priced per session, measured in revenue per visitor.
- Choose Explore when a mid-market Shopify team needs self-serve CRO on revenue-critical surfaces without an engineering project or a six-figure contract.
Conductrics vs Dynamic Yield is a comparison between two tools that solve very different problems. Conductrics is an API-first experimentation platform built for data science teams that want programmatic control and machine learning optimization. Dynamic Yield is an enterprise personalization suite for retail organizations running experimentation at scale, now owned by Mastercard. This page compares both to Omniconvert Explore, the eCommerce CRO platform built around Shopify revenue surfaces and revenue per visitor as the outcome metric.
What is Conductrics, and what is it actually good at?
Conductrics is an API-first experimentation and adaptive optimization platform built for engineering and data science teams that want programmatic control over testing. It embeds inside an application through APIs, not a visual editor, and favors multi-armed bandit optimization over classical A/B testing.
Conductrics is used by teams that need experimentation embedded in their own applications rather than a standalone tool. The core design choice is that every optimization decision is an API call the application makes at request time. There is no drag-and-drop editor, no marketer console, and no visual variant builder.
The technical strengths are real. Multi-armed bandit and adaptive targeting are first-class, not add-ons, and the platform can be wired into web, mobile, and back-end services from the same SDK. For a team building a custom stack, that flexibility is the point.
Conductrics carries a 4.3 out of 5 rating on G2 across 12 reviews. [G2, 2026] The small review sample reflects a narrow, technical audience rather than a broad marketing-led user base.
API-first experimentation is a pattern where the platform exposes optimization decisions as endpoints your application calls at request time. Your engineers own the surface, the event tracking, and the rollout. It is a delivery layer for custom applications, distinct from a marketer-owned toolset running experiments on product, cart, and checkout.
Where Conductrics fits
- Programmatic control: experiment logic runs inside your codebase, exposed to your services through an SDK.
- Adaptive optimization: multi-armed bandits and machine learning targeting, not fixed 50/50 splits.
- Embedded in custom applications: designed for products where experimentation is a first-party feature, not a bolt-on.
- Data science and engineering teams: the audience is technical operators who write against an API.
Where Conductrics hits its ceiling for an eCommerce store
- No visual editor: a marketer cannot build a variant on a product or checkout page without engineering help.
- Low brand recognition, minimal public documentation: smaller community and fewer implementation guides than enterprise peers.
- No native Shopify integration: storefront experiments require custom implementation work.
- Not designed for marketing-led CRO: it is a code-level engine, not an eCommerce testing platform.
What is Dynamic Yield, and what is it actually good at?
Dynamic Yield is an enterprise personalization and A/B testing platform owned by Mastercard. It runs product recommendations, experience optimization, and testing across web, mobile, and email for large retail organizations with dedicated personalization teams and implementation resources.
Dynamic Yield is one of the most advanced eCommerce personalization stacks on the market. It combines a recommendation engine, an experience optimization layer, and A/B testing under a single account. Major enterprise retailers use it, including IKEA and McDonald's, and the Mastercard acquisition has added data and enterprise-sales resources on top.
The trade-off is scale and cost. Custom pricing typically starts in the five-figure annual range, and setup is a proper implementation project, not a self-serve install. It is a serious tool that pays back only when the buyer has a dedicated personalization function on the inside.
Dynamic Yield holds a 4.5 out of 5 rating on G2 across 200 reviews. [G2, 2026] It sits as an established category leader in enterprise personalization.
Enterprise personalization is the practice of connecting customer data, product catalog signals, and behavioral triggers to individualize experiences across web, app, and email at scale. It is a large operational stack that pays back only with a dedicated in-house team. That is distinct from a focused revenue experiment on a Shopify product page or checkout that a store's marketing lead can ship this week.
Where Dynamic Yield fits
- Advanced personalization stack: recommendation engines, experience optimization, and A/B testing under one roof.
- Cross-channel coverage: web, mobile, and email in a single platform.
- Enterprise data and support: Mastercard acquisition brings additional data resources and enterprise sales.
- Proven at retailer scale: used by major enterprise retailers including IKEA and McDonald's.
Where Dynamic Yield hits its ceiling for a mid-market store
- Enterprise pricing: custom contracts, typically five figures annually, inaccessible for most mid-market Shopify brands.
- Implementation complexity: high setup effort that assumes a dedicated project and developer time.
- Over-specified for simple A/B testing: the full personalization stack is more platform than most stores need.
- Not built for self-serve marketer workflows: the sweet spot is a dedicated internal team, not a store's marketing lead running experiments this week.
What Conductrics and Dynamic Yield cannot do for an eCommerce store
Conductrics and Dynamic Yield sit at opposite ends of the experimentation market: one is API-first for engineers, the other is enterprise-scale for retail. Neither is designed for a mid-market Shopify team that needs to run self-serve tests on product, cart, and checkout, measured in revenue per visitor.
Conductrics is an API-first experimentation tool designed for technical teams embedding optimization into their own applications. It has no visual editor and cannot run experiments on Shopify storefronts through a marketer-accessible interface. It is not designed for self-serve eCommerce CRO.
Dynamic Yield is an enterprise platform built for large retail organizations with dedicated personalization teams. It is not designed for mid-market Shopify brands running self-serve CRO experiments. Implementation complexity and enterprise pricing put it out of reach for stores that need to test product and checkout without a developer project.
Most experimentation tools optimize the execution of a test, not the economics of it. They are not built around the surfaces where eCommerce revenue is actually won or lost: product pages, cart, and checkout. They also are not built around the metric that matters to a store, revenue per visitor rather than a click.
That is the layer eCommerce CRO is built for.
eCommerce CRO is defined as the practice of running controlled experiments on the revenue surfaces of an online store, product pages, cart, and checkout, measured in revenue per visitor and order rate rather than a 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 store
- Whether a winning variant actually moved revenue per visitor. Neither tool measures the store's real outcome metric by default. They surface conversion rate or micro-conversions, not revenue per visitor and order rate as first-class results.
- Which page in the funnel has the highest revenue impact if tested first. Neither tool ranks product, cart, and checkout by expected revenue lift for the store's specific traffic and catalog.
- How the experiment interacts with the Shopify catalog and checkout. Native Shopify integration, variant handling, and checkout-flow instrumentation are not the design center of an API-first or an enterprise-scale tool.
- Whether the result holds for high-value, repeat customers. The Customer Value Optimization question, whether the winning variant improves outcomes for repeat buyers, is outside the default reporting.
Omniconvert benchmarks more than 7,000 eCommerce websites in its CROBenchmark Report 2026, across 248+ audit criteria. The data shows that 99.6% of stores fail to make guest checkout prominent and 94.2% never show checkout progress. [CROBenchmark Report 2026, Omniconvert] Those are the specific store-level tests neither an API-first engine nor an enterprise personalization suite is set up to prioritize.
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]
Conductrics vs Dynamic Yield vs Explore: the capability comparison
A side-by-side view. Read the Explore column against each competitor: where the same job is done, and where Explore does the job the other tool was not built to do for a Shopify store.
| Capability | Conductrics | Dynamic Yield | Omniconvert Explore |
|---|---|---|---|
| Primary function | API-first experimentation for engineering teams | Enterprise personalization and A/B testing at retail scale | eCommerce CRO for Shopify: product, cart, checkout |
| A/B testing | Yes, API-first, no visual editor | Yes, visual editor plus personalization engine | Yes, self-serve visual editor |
| Multivariate testing | No | Yes | Yes |
| Server-side testing | Yes, first-class | Yes | Yes |
| Visual editor | No, API-only | Yes | Yes |
| On-site surveys and overlays | No | Partial, personalization overlays, not surveys | Yes, both surveys and overlays |
| Shopify integration | Low, custom API implementation required | High, at enterprise implementation cost | Native |
| eCommerce focus | Low, generic experimentation | High, enterprise retail focus | High, purpose-built for stores |
| Pricing model | Custom, contact sales | Custom enterprise, typically five-figure annual | Session-based, built for store traffic |
| Best for | Data science and engineering teams building experimentation into custom applications | Enterprise retail with a dedicated personalization team | Mid-market Shopify brands running marketer-led CRO on product, cart, and checkout |
| User rating | 4.3 out of 5 (G2, 12 reviews, as of 2026) | 4.5 out of 5 (G2, 200 reviews, as of 2026) | 4.6 out of 5 (G2, 191 reviews, as of 2026) |
Competitor ratings, pricing, and plan details reflect publicly listed figures as of 2026 and can change. Conductrics has no public entry price; Dynamic Yield uses custom enterprise contracts. 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 Conductrics or Dynamic Yield?
For a mid-market Shopify store running self-serve CRO on product, cart, and checkout, Explore is the direct fit. Conductrics is the choice for a data science team wiring adaptive experimentation into a custom application. Dynamic Yield is the choice for a large enterprise retailer running a full personalization program with a dedicated team. Decide by scale and by who owns the tests inside the business.
The three products serve different profiles. Conductrics is a delivery layer for engineers who want optimization as an API call. Dynamic Yield is a personalization suite that needs a dedicated team to earn its return.
Explore is the eCommerce CRO platform where a store's marketing lead builds and ships a revenue experiment without a developer queue. If you run a mid-market Shopify brand and ship product, cart, or checkout variants this month, Explore is built for that. Conductrics fits a custom-application engineering group; Dynamic Yield fits an enterprise retail organization with a dedicated personalization function.
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