Evergage vs Personyze vs Explore (2026): Personalize or Test Revenue
Evergage, now Salesforce Marketing Cloud Personalization, is an enterprise real-time personalization platform with built-in A/B testing. Personyze bundles website personalization, product recommendations, and basic A/B testing for mid-market teams. 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.
- Evergage, now Salesforce Marketing Cloud Personalization, is an enterprise real-time personalization suite with a 4.3 out of 5 G2 rating. [G2, 2026]
- Personyze is a mid-market platform that bundles website personalization, product recommendations, and basic A/B testing, rated 4.6 out of 5 on G2. [G2, 2026]
- Evergage and Personyze sit at opposite ends of the same category: enterprise and mid-market personalization, with testing as a supporting feature.
- Neither is built around the Shopify checkout or measures results in revenue per visitor, the surfaces where store revenue is decided.
- 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 Evergage vs Personyze are usually weighing enterprise personalization against a mid-market personalization-plus-testing bundle. Evergage answers the personalization question for enterprises inside Salesforce. Personyze offers similar behavioral targeting and recommendations at a fraction of the price, with basic A/B testing on top. Neither is built around the surfaces where a Shopify store actually wins or loses revenue: the product page, the cart, and the checkout. This page covers what each does well, the gap they share, and when Omniconvert Explore is the right layer.
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 store's 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 an eCommerce 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 is Personyze, and what is it actually good at?
Personyze is a mid-market website personalization platform that bundles behavioral targeting, product recommendations, and basic A/B testing in one tool. It is priced session-based from $250 per month with a free trial, and is accessible to non-technical marketing teams. [G2, 2026]
Personyze holds a 4.6 out of 5 rating on G2 across 48 reviews. [G2, 2026] Its appeal is the bundle: teams that want on-site personalization and product recommendations, but do not want to buy a dedicated testing tool alongside, get both in one subscription.
The category Personyze sits in is mid-market personalization with testing as a supporting feature. Its behavioral targeting reads user actions and profile data to trigger content changes, and its A/B testing validates which of those variations performs better on a chosen metric.
Behavioral targeting delivers different content to different visitors based on what they have done on the site: pages viewed, products browsed, cart actions, referral source. Personyze uses it to drive on-site personalization and product recommendations. It is a delivery layer, distinct from running a controlled revenue experiment on product, cart, and checkout.
Where Personyze is genuinely strong
- Bundled personalization and testing: one platform for on-site personalization, recommendations, and basic A/B tests.
- Accessible to non-technical teams: marketing users can build variations without engineering support.
- Mid-market pricing: session-based from $250 per month with a free trial, planable on a store budget.
- Behavioral targeting: triggers content changes on user actions and profile data.
Where Personyze hits its ceiling for an eCommerce store
- Testing is secondary: A/B testing exists to validate personalization variants, not to run a rigorous experiment program.
- No server-side testing: checkout and back-end experiments cannot run at the server layer.
- Limited multivariate: multivariate testing exists but is thin next to dedicated experimentation tools.
- Limited Shopify integration: not natively built for Shopify checkout flow experiments.
What Evergage and Personyze cannot do for an eCommerce store
Evergage and Personyze sit at opposite ends of the same category, enterprise and mid-market 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 metrics that matter there: revenue per visitor, order rate, and the margin a store actually keeps.
Evergage is built for enterprise marketing teams running real-time personalization across many channels, usually inside the Salesforce ecosystem. Its testing validates personalization rules, not revenue 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 that measures revenue per visitor natively.
Personyze is a personalization platform with basic A/B testing bolted on. It does not have native Shopify checkout flow testing or the statistical rigor of dedicated experimentation platforms. Teams using it for eCommerce CRO can personalize on-site experiences but cannot run controlled, revenue-connected experiments on the checkout flow where the order actually closes.
The two gaps differ in scale but point to the same missing layer. Both tools optimize the delivery of a personalized experience on a generic page. Neither is built around where store revenue is actually decided, or around the Customer Value Optimization question: whether a result holds for high-value, repeat buyers. For the wider debate behind this testing-versus-personalization split, see Has personalization replaced A/B testing?
There is a second gap underneath the first: rigorous experiment methodology on the store's revenue path. Personyze runs personalization variants but does not offer server-side testing or the statistical depth that separates a real experiment from an A/B/n rotation. Evergage runs its testing inside personalization campaigns, tied to Salesforce infrastructure most single Shopify stores will never deploy. Omniconvert Explore puts a controlled A/B and multivariate program on the product-to-checkout path, with heatmaps, session recordings, and on-site surveys living next to the experiment. 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. 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 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 personalized impression.
- 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, the exact surfaces a personalization suite is not built to experiment on. 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 testing revenue. A more personalized product recommendation 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. That is the revenue question Evergage and Personyze are not built to answer, and the one Explore is. Explore also reaches Shopify-specific levers most personalization tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
Evergage vs Personyze vs Explore: the capability comparison
Side by side, the three tools serve different layers. Evergage personalizes experiences for enterprises. Personyze bundles personalization and basic testing for mid-market teams. 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 | Evergage | Personyze | Omniconvert Explore |
|---|---|---|---|
| Primary function | Enterprise real-time personalization | Mid-market personalization with basic A/B testing | eCommerce CRO on product, cart, and checkout |
| A/B testing | Yes within personalization campaigns | Yes basic, personalization-first | Yes visual plus code editor |
| Multivariate testing | Yes | Limited | Yes |
| Server-side testing | Yes via SDK | No | Yes |
| Visual editor | Yes | Yes | Yes |
| On-site surveys and overlays | Yes personalization overlays, no surveys | Yes personalization overlays, no surveys | Yes surveys and overlays built in |
| Shopify integration | Low enterprise implementation | Medium limited native support | Yes native |
| eCommerce focus | Medium enterprise personalization | Medium mid-market personalization | High built for store revenue workflows |
| Revenue per visitor measurement | No personalization KPIs | No generic conversion metrics | Yes revenue per visitor and order rate native |
| Pricing model | Custom enterprise, quote on request | Session-based, from $250/mo, free trial | Session-based, built for store traffic, free trial |
| Best for | Enterprise teams in the Salesforce ecosystem | Mid-market teams wanting personalization plus testing | Shopify and eCommerce teams optimizing for revenue |
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 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 Evergage or Personyze?
Start with the surface where your revenue is decided. If you need enterprise real-time personalization inside Salesforce, Evergage earns its place. If you want a bundled personalization-plus-testing tool on a mid-market budget, Personyze covers that ground. For a Shopify store, run your next test on the product-to-checkout path in Explore, measured in revenue per visitor. The three are complementary, but only Explore is built for the checkout where the order closes.
Evergage and Personyze are both capable personalization tools within their categories. Evergage is a G2 Leader for enterprise personalization inside the Salesforce ecosystem. Personyze is a well-rated mid-market bundle for teams that want personalization and testing in one place.
The question for a store is narrower: can your team run a controlled experiment on the Shopify product, cart, and checkout, and read the result in revenue per visitor rather than a click or a personalized impression. 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.