Conductrics vs Evergage vs Explore (2026): Shopify Revenue Focus
Conductrics is an experimentation and optimization platform with A/B and multivariate testing, a visual editor, server-side and mobile SDKs, contextual bandits, and in-experiment surveys. Evergage, now Salesforce Marketing Cloud Personalization, is an enterprise real-time personalization suite. 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 rather than clicks.
- Conductrics is an experimentation and optimization platform with A/B and multivariate testing, a visual editor (Conductrics Express), server-side and mobile SDKs, contextual bandits, and in-experiment surveys.
- Evergage, now Salesforce Marketing Cloud Personalization, is an enterprise real-time personalization suite with a 4.3 out of 5 G2 rating across 94 reviews. [G2, 2026]
- Conductrics and Evergage solve different jobs, general-purpose testing and enterprise personalization, and are rarely direct substitutes for each other.
- Evergage is not built around the Shopify checkout, where store revenue is decided, and does not measure results in revenue per visitor; Conductrics is general-purpose, with no dedicated Shopify app or eCommerce-specific features listed.
- 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 Conductrics vs Evergage are weighing two different trade-offs: a general-purpose experimentation platform against an enterprise personalization suite. Conductrics pairs a visual editor with server-side, edge, and mobile testing, multivariate reporting, and contextual bandits. Evergage delivers real-time one-to-one personalization at scale, inside Salesforce. Evergage is not self-serve for a Shopify store, and Conductrics lists no dedicated Shopify app; neither is built around testing where revenue actually closes, which is the job Omniconvert Explore was built for.
What is Conductrics, and what is it actually good at?
Conductrics is an experimentation and optimization platform for A/B testing and multivariate testing. Non-technical teams can build tests in its visual editor, Conductrics Express, and the same platform runs tests server-side, at the CDN edge, and in mobile apps, with contextual bandits and rule-based targeting on top. [Conductrics, 2026]
Conductrics was founded in 2008 and launched in 2010. It serves teams across industries that want a visual editor for UI changes and, through a REST API and server-side libraries, programmatic control for tests that live on a server, at the edge, or in an app.
The category Conductrics sits in is general-purpose experimentation and optimization. Alongside classic tests, its predictive agents are contextual bandits built on Thompson Sampling: a Listen mode learns without changing the experience, an Adaptive mode acts on what it learns, and readable decision trees show which visitor traits drove each choice.
A contextual bandit is an adaptive algorithm that uses what it knows about each visitor to choose which variant to show, shifting traffic toward what performs best for that kind of visitor as evidence builds. Conductrics' predictive agents work this way, using Thompson Sampling. It is a way of allocating traffic, distinct from choosing which store surface to test and the metric to read it in.
Where Conductrics is genuinely strong
- Visual editor plus server-side, edge, and mobile: Conductrics Express handles on-page changes, custom JavaScript, multi-page changes, and split-URL tests, while a REST API, Conductrics Edge, and iOS, Android, and React Native SDKs cover servers, the CDN, and apps.
- A/B and multivariate testing with statistical rigor: a Main Effects Report shows which variable drives a lift, interaction effects included, backed by error-rate control and corrections for multiple comparisons.
- Contextual bandits you can read: predictive agents learn in a Listen mode or adapt in an Adaptive mode, and decision trees show which visitor traits drove each choice.
- Surveys inside experiments: Conductrics Surveys ask anything from NPS to custom questions, matched to the variation each visitor saw.
Where Conductrics hits its ceiling for an eCommerce store
- No dedicated Shopify app: no Shopify-specific integration is listed; it installs on a store through its script tag, so store tests are set up like any page test rather than from Shopify's catalog.
- General-purpose, not eCommerce-specific: it serves many industries and lists no eCommerce-specific features, while Explore is built around product, cart, and checkout and reports in revenue per visitor.
- Prices through sales: prices are not published, so a store has to ask for a quote before it can compare costs.
- Breadth a store may not need: much of its range, from server-side, edge, and mobile testing to contextual bandits, goes beyond what a team running only storefront tests may use.
What is Evergage, and what is it actually good at?
Evergage, now Salesforce Marketing Cloud Personalization, is an enterprise real-time personalization platform. Its machine learning builds a live profile of each visitor to serve individualized product and content recommendations across web, email, mobile, and in-store, connected to the Salesforce CDP. [G2, 2026]
Evergage is a personalization engine first and a testing tool second. It was named a G2 Leader for personalization engines, holding a 4.3 out of 5 rating across 94 reviews. [G2, 2026] Its strength is delivering the right experience to the right visitor in the moment, at scale.
Its A/B and multivariate testing exists to validate personalization campaigns: which rule, audience, or recommendation performs best. That is a different job from running a standalone conversion experiment program on a Shopify checkout.
Real-time personalization adapts what a visitor sees based on a live behavioral profile, serving individualized content and recommendations as they browse. Evergage does this across channels inside the Salesforce ecosystem. It is an enterprise capability, distinct from running controlled revenue experiments on product, cart, and checkout pages.
Where Evergage is genuinely strong
- Real-time one-to-one personalization: machine learning, not static rules alone, driving individualized experiences.
- Recommendations at scale: machine-learning product and content recommendations across many channels.
- Deep behavioral analytics: rich segmentation connected to the Salesforce CDP and Marketing Cloud.
- Enterprise omnichannel reach: web, email, mobile apps, onsite search, and in-store touchpoints.
Where Evergage hits its ceiling for a single store
- Enterprise implementation: needs technical resources, so it is rarely self-serve for one eCommerce team.
- Custom enterprise pricing: value depends on the broader Salesforce stack, not a standalone store budget.
- Testing serves personalization: A/B testing validates campaigns, not a revenue experiment program.
- No native Shopify checkout: no checkout-level experiment templates for the Shopify funnel.
What Conductrics and Evergage leave open for an eCommerce store
Conductrics and Evergage are built for different jobs, general-purpose testing and enterprise personalization, but they share one gap for a store. Neither is built around the surfaces where eCommerce revenue is won or lost, product pages, cart, and checkout, or around the metric that matters there: revenue per visitor.
Conductrics is a general-purpose optimization platform used across industries. It has a visual editor and installs on any website, a Shopify storefront included, through its script tag, but it lists no dedicated Shopify app and no Shopify-specific integration. Store tests are set up like any page test rather than from Shopify's catalog, and no eCommerce-specific features, such as product, cart, or checkout reporting, are listed.
Evergage is built for enterprise marketing teams running real-time personalization across many channels, usually inside the Salesforce ecosystem. Its testing validates personalization rules rather than revenue-per-visitor experiments on product, cart, and checkout. A Shopify store evaluating it takes on enterprise implementation and custom pricing when what it often needs is a focused eCommerce experimentation platform. For the wider debate behind this testing-versus-personalization split, see Has personalization replaced A/B testing?
The two gaps differ in nature but point to the same missing layer. Most testing and personalization tools optimize the execution of a test or a campaign on a generic page. They are not built around where store revenue is actually decided, or around the Customer Value Optimization question: whether a result holds for high-value, repeat buyers.
There is a second gap underneath the first: the data insights layer that tells a team what to test and whether it actually worked. Conductrics brings surveys into its experiments, matched to the variation each visitor saw, and works with behavior tools such as Contentsquare and Hotjar, which read its experiments without a custom integration. Evergage holds deep behavioral data, but it lives inside an enterprise Salesforce deployment most single Shopify stores will never run. 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, which is the difference between guessing at a hypothesis and reading it off the store's own data.
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 Evergage cannot 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 lifted a click or a micro-conversion.
- Which surface to test first. Which pages in the 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 engineering glue work.
- Whether it holds for valuable customers. Whether the result holds for repeat, high-value customers, the Customer Value Optimization question, not just first-session visitors.
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. A personalization suite is not built to experiment on those surfaces, and a general-purpose testing platform with no Shopify-specific integration tests them like any other page. 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 a Shopify revenue focus. A higher click rate or a lifted micro-conversion can leave the bank balance flat; what moves it 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 top-of-funnel click often does not. That is the revenue question Evergage is 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.
Conductrics vs Evergage vs Explore: the capability comparison
Side by side, the three tools serve different layers. Conductrics runs A/B, multivariate, and bandit tests from a visual editor or in code, on the web, server-side, and in apps. Evergage personalizes experiences for enterprises inside Salesforce. Explore adds native Shopify experiments, built-in surveys and overlays, and revenue-per-visitor measurement on the product-to-checkout path. See A/B testing with Explore for how those experiments run natively on the Shopify funnel.
| Capability | Conductrics | Evergage | Omniconvert Explore |
|---|---|---|---|
| Primary function | Experimentation and adaptive optimization across web, server, and mobile | Enterprise real-time personalization | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes visual editor, server-side, and mobile | Yes within personalization campaigns | Yes visual plus code editor |
| Multivariate testing | Yes with Main Effects reporting | Yes | Yes |
| Server-side testing | Yes REST API, SDKs, and edge | Yes via SDK | Yes |
| Visual editor | Yes Conductrics Express | Yes | Yes |
| On-site surveys and overlays | Yes on-site surveys inside experiments (Conductrics Surveys) | No personalization, not surveys | Yes surveys and overlays built in |
| Shopify integration | Partial no dedicated Shopify app; installs through its script tag | Low enterprise implementation | Yes native |
| eCommerce focus | Low general-purpose, not eCommerce-specific | Medium enterprise personalization | High built for store revenue workflows |
| Pricing model | Prices not published, quote from sales | Custom enterprise, quote on request | Session-based, built for store traffic, free trial |
| Best for | Teams testing across web, server-side, edge, and mobile | Enterprise teams in the Salesforce ecosystem | Shopify and eCommerce teams optimizing for revenue |
| User rating | No public G2 rating | 4.3 out of 5 (G2, 94 reviews, as of 2026) | 4.6 out of 5 (G2, 197 reviews, as of 2026) |
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. Evergage is now Salesforce Marketing Cloud Personalization. Explore uses session-based pricing; see the Explore 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 Evergage?
Decide by the shape of your testing program. If you test across web, server-side, edge, and mobile and want contextual bandits and in-experiment surveys in one platform, keep Conductrics. If you run enterprise personalization inside Salesforce, Evergage earns its place. For a Shopify store that needs a self-serve experiment program on product, cart, and checkout, pick Explore and run the next test on the surface where the money actually moves, measured in revenue per visitor.
Conductrics and Evergage are both capable platforms with real strengths. Conductrics combines a visual editor with server-side, edge, and mobile testing, multivariate reporting, and contextual bandits with readable decision trees. Evergage is a G2 Leader for enterprise personalization inside the Salesforce ecosystem.
The question for a Shopify store is narrower. Can your team launch a checkout experiment, read the result in revenue per visitor, and iterate without an enterprise contract? 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 197 reviews, G2 , as of 2026