Fullstory alternative (2026): Session replay vs Shopify CRO
Fullstory is a digital experience analytics platform built around session replay and autocaptured behavioural data, letting teams investigate friction retroactively without pre-tagging events. Omniconvert Explore is a Shopify-native eCommerce CRO platform that runs A/B, multivariate, and personalization experiments on product, cart, and checkout, measured in revenue per visitor. Different jobs, often complementary.
- Fullstory is a digital experience analytics platform built around session replay and autocaptured behavioural data, rated 4.5 out of 5 on G2 across more than 1,000 reviews. [G2, 2026]
- It autocaptures every interaction, replays individual sessions in detail, and flags friction with rage-click and dead-click detection.
- Fullstory does not run A/B, multivariate, or server-side experiments; it observes friction but cannot validate a fix.
- Omniconvert Explore runs experiments on Shopify product, cart, and checkout pages natively, and measures results in revenue per visitor.
- The two rarely compete: many stores use Fullstory to find friction and Explore to test the fix on the same storefront.
Teams comparing Fullstory vs Omniconvert Explore are usually asking two overlapping questions. Fullstory is a session replay and digital experience analytics platform, well-liked for autocapturing every interaction so teams can investigate friction retroactively without instrumenting events in advance. Omniconvert Explore is a Shopify-native CRO platform that runs experiments on product, cart, and checkout, and measures the outcome in revenue per visitor. This page explains where each fits and where they never really compete.
What is Fullstory, and what does it actually do?
Fullstory autocaptures every click, scroll, and form interaction on your site and stores it as searchable session data. Teams use it to replay individual sessions, surface rage clicks and dead clicks, and investigate friction after the fact without pre-tagging events. [Fullstory, 2026]
Fullstory is highly rated in its category, with a 4.5 out of 5 rating on G2 across more than 1,000 reviews. [G2, 2026] The pitch is that every interaction is captured by default, so a product or CX team can go back to any moment on the site and understand what a visitor actually experienced, without deciding in advance which events to log.
The category Fullstory sits in is digital experience analytics: session replay, autocaptured behavioural data, heatmaps, and friction signals like rage clicks and dead clicks. It is an observation and investigation tool for teams asking "what is happening on our site, and where are people getting stuck?"
The question this page answers is narrower: is session replay analytics the same job as running conversion experiments on a Shopify store? And if not, where is the gap?
Session replay analytics means the platform records every visitor interaction as a replayable session, autocaptures events without prior instrumentation, and layers behavioural signals like rage clicks and dead clicks on top of that stream. It is powerful for finding where friction happens. It is a separate concern from whether a proposed fix actually lifts revenue when tested against the current experience.
Where Fullstory is genuinely strong
- Autocaptured behavioural data: every interaction is recorded by default, so teams can investigate any question retroactively without a tagging plan.
- Detailed session replay: individual visitor sessions are rendered pixel-accurate for deep qualitative investigation.
- Strong search across sessions: finding the exact sessions where a specific pattern occurred is fast, even at scale.
- Rage-click and dead-click detection: automated friction signals surface issues that funnel dashboards routinely miss.
Where Fullstory hits its ceiling for an eCommerce store
- No experimentation: Fullstory does not run A/B tests, multivariate tests, or variant delivery of any kind, so a hypothesis can be documented but never validated inside the tool.
- Quote-based enterprise pricing: pricing sits at the enterprise end and requires a custom quote, which puts it out of reach for most mid-market Shopify teams.
- Analyst-heavy workflow: the volume of captured session data takes significant analyst time to turn into decisions, not a lightweight lift for a small growth team.
- Low Shopify fit: no native Shopify app for product, cart, and checkout experiment surfaces, and no revenue-per-visitor framing out of the box.
None of this makes Fullstory a weak product. It makes it an observation and investigation tool. The friction shows up specifically when the team that watched a hundred rage clicks pile up on the cart page still needs to prove which fix actually recovers the revenue.
What Fullstory cannot do for an eCommerce store
Fullstory is an analytics and session replay platform rather than an optimisation platform. It records what visitors did but offers no mechanism to test an alternative. Teams using Fullstory for eCommerce CRO build a detailed picture of friction and then still need a testing tool to validate which changes actually lift revenue per visitor.
Omniconvert Explore is built for the layer Fullstory leaves open. Fullstory can show you exactly where a visitor abandoned the checkout, replay it frame by frame, and count how many others did the same. It cannot ship an alternative version of that checkout to half your traffic and tell you which one earned more revenue per visitor. Those are not the same task.
Most session replay tools are built around a captured event stream and a qualitative investigation loop. They optimise the discovery of friction. They are not built around the surfaces where eCommerce revenue is actually won or lost, or around the metric a store runs on.
eCommerce 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 Fullstory cannot tell an eCommerce team
- Did the fix move revenue. Whether a proposed fix to the friction you replayed actually raised revenue per visitor and order rate, not just reduced rage clicks in the replay.
- Which surface to test first. Which pages in the Shopify funnel (product, cart, checkout) carry the highest revenue impact if tested next, ranked by expected lift rather than by session count.
- How the change behaves in checkout. How a variant of the cart or checkout interacts with the Shopify catalog, variants, and payment flow natively, without an engineer building a bespoke deployment.
- Whether it holds for valuable customers. Whether the result holds for repeat, high-value customers, the Customer Value Optimization question, not just first-session traffic.
Across the 7,000+ eCommerce websites in Omniconvert's CROBenchmark Report 2026, the stores that lift revenue fastest are the ones that pair a friction-discovery tool with a testing tool: they use replay to see where visitors struggle, and they use experimentation to prove which change actually recovers checkout revenue. The benchmark shows testing cadence drops sharply when a team can find friction but has no self-serve way to test a fix. [CROBenchmark Report 2026, Omniconvert]
Explore runs the experiment on the store's real revenue surfaces and reports the outcome in revenue per visitor. 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]
Fullstory vs Explore: the capability comparison
Side by side, Fullstory and Explore share almost no overlap in daily job. Fullstory captures sessions, replays them, and surfaces friction signals. Explore ships Shopify-native experiments on product, cart, and checkout, adds surveys and overlays, and reports in revenue per visitor. Where they touch is qualitative insight, and even there they solve for different halves of the loop.
| Capability | Fullstory | Omniconvert Explore |
|---|---|---|
| Primary function | Session replay and digital experience analytics for friction investigation | eCommerce CRO on product, cart, and checkout pages |
| A/B testing | No not part of the product | Yes visual editor plus code editor |
| Multivariate testing | No | Yes |
| Server-side testing | No | Yes |
| Visual editor | No Fullstory does not deliver variants | Yes no developer required |
| On-site surveys and overlays | No not part of the product | Yes surveys and overlays built in |
| Shopify integration | Low no native Shopify app for experiment surfaces | Yes native |
| eCommerce focus | Medium used by eCommerce, not built specifically for store revenue | High built for store revenue workflows |
| Pricing model | Quote-based, custom enterprise quote, free trial | Session-based, built for store traffic, free trial |
| Best for | Product and engineering teams investigating user friction at scale | Shopify and eCommerce teams optimizing product, cart, and checkout for revenue |
Competitor pricing and plan details reflect publicly listed figures as of 2026 and can change. 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 Fullstory?
If your team needs deep session replay and autocaptured behavioural data to investigate friction across the storefront, choose Fullstory: rage-click and dead-click detection surface issues analytics dashboards miss. If your revenue depends on validating fixes with controlled Shopify experiments on product, cart, and checkout, choose Explore: it tests hypotheses natively and measures outcomes in revenue per visitor. The two are complementary; many stores use both, Fullstory to find friction, Explore to test the fix.
Fullstory earns its place inside product and CX organizations that need to understand what actually happened on a page. Autocapture, detailed replay, and friction signals give investigators a qualitative depth that a funnel dashboard cannot match, which is exactly what a CX or product team wants when a metric moves and no one can explain why.
The question for a store is narrower: once you have seen the friction, are the fixes running as controlled experiments on the product, cart, and checkout pages, without engineering glue work, and are they measured in revenue per visitor. 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.