Amplitude Experiment vs Evergage vs Explore (2026): Stacks vs Store
Amplitude Experiment is Amplitude's experimentation layer, built on top of Amplitude Analytics and delivered through an SDK. Evergage, now Salesforce Marketing Cloud Personalization, is an enterprise real-time personalization suite tied to Salesforce. 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.
- Amplitude Experiment is Amplitude's SDK-based experimentation layer, requires Amplitude Analytics, and holds a 4.5 out of 5 G2 rating across 2,200 reviews. [G2, 2026]
- 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]
- The two tools sit in different stacks: product-analytics experimentation on one side, enterprise Salesforce personalization on the other, with no native Shopify integration.
- Neither is built around the Shopify checkout, and neither reports experiment results in revenue per visitor or order rate.
- Omniconvert Explore runs experiments on product, cart, and checkout natively and measures outcomes in revenue per visitor: pick it when a Shopify store is the buyer.
Teams comparing Amplitude Experiment vs Evergage are usually choosing between two very different stacks that share a testing label. Amplitude Experiment is an experimentation SDK bolted onto Amplitude Analytics, built for product teams already on that stack. Evergage is a real-time personalization suite built for enterprise marketing teams inside Salesforce. This page covers what each does well for its own audience, the ceiling they share when a Shopify store is the buyer, and where Omniconvert Explore is the right layer.
What is Amplitude Experiment, and what is it actually good at?
Amplitude Experiment is Amplitude's experimentation layer, built on top of Amplitude Analytics. Tests fire through an SDK, feature flags gate the variants, and results are analysed as events inside the same Amplitude environment. It holds a 4.5 out of 5 G2 rating across 2,200 reviews. [G2, 2026]
Amplitude Experiment is a testing layer for teams already running Amplitude Analytics. Its strength is that experiments and product-analytics events live in the same environment, so a team can target Amplitude cohorts and read results next to every other product event without a separate integration.
The trade-off is a hard prerequisite. Amplitude Experiment requires Amplitude Analytics, has no visual editor, and runs experiments through an SDK. Every test needs a developer to ship, and for a Shopify store the analytics stack has to be Amplitude first, not Shopify's own funnel data.
Product-analytics experimentation is a testing layer built on top of a product analytics platform. Experiments run through an SDK, and results are analysed against events already flowing into the analytics tool. Amplitude Experiment does this well for teams already on Amplitude. It is a testing layer inside a product-analytics workflow, distinct from running a controlled revenue experiment on product, cart, and checkout pages.
Where Amplitude Experiment is genuinely strong
- Analytics-native results: experiments and product events sit in one platform, with no separate data integration.
- Cohort targeting: reach segments already defined inside Amplitude Analytics.
- Server-side testing: run experiments on backend flows without client-side flicker.
- Free tier available: start experimenting at no cost once Amplitude Analytics is in place.
Where Amplitude Experiment hits its ceiling for an eCommerce store
- No visual editor: every variant needs developer time, so marketing ideas queue behind engineering capacity.
- Amplitude Analytics required: the value only lands once your stack is already Amplitude-first.
- Not built for Shopify: no native checkout experimentation, and no revenue per visitor metric out of the box.
- Product-team ergonomics: designed around product events, not checkout revenue, so store questions read as event trends rather than order-rate lift.
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 apps, onsite search, 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 enterprise 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 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 personalization 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 drives individualized experiences, not static rules alone.
- 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 Amplitude Experiment and Evergage cannot do for an eCommerce store
Amplitude Experiment is a product-analytics add-on. Evergage is an enterprise personalization suite. The two tools live in different stacks and sell to different buyers, but they share one ceiling for a Shopify store. Neither is built around the checkout, and neither reports outcomes in revenue per visitor.
Amplitude Experiment sits on top of Amplitude Analytics and delivers experiments through an SDK. That works cleanly inside a product team already writing to Amplitude, but it puts every store experiment behind an engineering ticket. A marketer cannot ship a checkout test without a developer, and the win reads as an event trend rather than a revenue lift. It is not a Shopify-native CRO tool, and its reporting speaks the language of product events, not order rate.
Evergage is built for enterprise marketing teams running real-time personalization across many channels, usually inside the Salesforce ecosystem. Its testing is designed to validate personalization rules, not to run revenue-per-visitor experiments on product pages, cart, and checkout. A Shopify store evaluating Evergage takes on enterprise implementation and custom pricing when what it often needs is a focused eCommerce experimentation platform that measures revenue per visitor natively.
The two gaps sit in different stacks but point to the same missing layer. Amplitude Experiment optimizes for a generic product event. Evergage optimizes a personalization campaign. Neither is designed around the surfaces where store revenue is actually won or lost: product pages, cart, and checkout. Neither answers the Customer Value Optimization question: whether a lifted conversion holds for repeat, high-value buyers rather than first-session visitors. For the wider debate behind this testing-versus-personalization split, see Has personalization replaced A/B testing?
Omniconvert Explore is built for this layer. Explore runs A/B, multivariate, personalization, and on-site survey experiments on the Shopify product, cart, and checkout, natively, and reports the outcome in revenue per visitor and order rate. Insight and test live in one place, on the store's real revenue surfaces, and the same behavioral data defines the segments you measure against.
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 product event or a personalization click.
- 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 Shopify checkout. How an experiment interacts with the Shopify catalog, variants, and checkout flow natively, without engineering glue work.
- Whether it holds for high-CLV customers. Whether the result holds for repeat, high-value buyers, 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, 94.2% never show checkout progress, and 85.1% never show the full order cost before the final step. [CROBenchmark Report 2026, Omniconvert]
A product-analytics event stream or a personalization campaign can point at friction. Neither prices the loss on the actual Shopify checkout or proves the fix there. Explore runs the experiment on the store's real revenue surfaces and reports the outcome in revenue per visitor, tied back through Customer Value Optimization to the buyers a store keeps rather than the traffic it rents. Explore also reaches Shopify-specific levers most testing tools cannot touch, including price testing; see Explore 3.0: pricing testing on Shopify.
Amplitude Experiment vs Evergage vs Explore: the capability comparison
Side by side, the three tools sit at different points on the testing-to-revenue spectrum. Amplitude Experiment ties tests to product analytics through an SDK. Evergage drives real-time personalization inside Salesforce. Explore adds native Shopify experiments on product, cart, and checkout, with heatmaps and surveys beside them, measured in revenue per visitor. See A/B testing with Explore for how those experiments run on the Shopify funnel.
| Capability | Amplitude Experiment | Evergage | Omniconvert Explore |
|---|---|---|---|
| Primary function | Product-analytics experimentation via SDK | Enterprise real-time personalization inside Salesforce | eCommerce CRO on product, cart, and checkout |
| A/B testing | Partial SDK-based, requires Amplitude Analytics | Partial within personalization campaigns | Yes visual plus code editor |
| Multivariate testing | No | Yes | Yes |
| Server-side testing | Yes | Yes | Yes |
| Visual editor | No SDK and developer-first | Yes inside personalization campaigns | Yes plus code editor |
| On-site surveys and overlays | No not in scope for the product | No personalization, not surveys | Yes surveys and overlays built in |
| Shopify integration | Low via SDK, developer-implemented | Low enterprise implementation | Yes native |
| eCommerce focus | Low product-team ergonomics | Medium enterprise personalization | High built for store revenue workflows |
| Pricing model | Seat-based, free tier available (Amplitude Analytics required) | Custom enterprise, quote on request | Session-based, built for store traffic, free trial |
| Best for | Product teams already on Amplitude Analytics | Enterprise teams in the Salesforce ecosystem | Shopify and eCommerce teams optimizing for revenue |
| User rating | 4.5 out of 5 (G2, 2200 reviews, as of 2026) | 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. Amplitude Experiment's value assumes an existing Amplitude Analytics investment; 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 Amplitude Experiment or Evergage?
Decide by the stack your team actually runs. If your product team is on Amplitude and experiments need to live inside analytics, keep Amplitude Experiment. If your enterprise runs Salesforce and needs real-time personalization at scale, Evergage earns its place. For a Shopify store, run your next test on the product-to-checkout path in Explore, measured in revenue per visitor. The three tools are complementary, but only Explore is built for the surface where the order closes.
Amplitude Experiment and Evergage are both capable platforms within their categories. Amplitude Experiment delivers experimentation tied directly to Amplitude Analytics, and Evergage is a G2 Leader for personalization engines inside Salesforce.
The question for a store is narrower. Can your team test the Shopify product, cart, and checkout, and read the result in revenue per visitor rather than a product event or a personalization click? 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