KISSmetrics vs FullStory: Revenue Analytics vs Session Replay

FullStory and KISSmetrics both claim to help you understand user behavior, but they approach the problem from opposite directions. FullStory starts with individual sessions and works outward—you watch what one user did, spot patterns, and extrapolate. KISSmetrics starts with aggregate behavioral data and works inward—you identify trends across thousands of users, then drill into the segments and journeys that explain those trends.

This is not a subtle difference. It shapes everything about how you use each tool, what questions you can answer, and which teams get the most value. FullStory is built for product and UX teams who need to see exactly what happened during a session. KISSmetrics is built for growth, marketing, and product teams who need to connect behavior to revenue at scale. This comparison covers the real trade-offs so you can choose the right tool for your actual needs.

Different Philosophies

FullStory was founded on the idea that watching user sessions reveals insights that aggregated data cannot. Its core product is a session replay engine that captures every DOM interaction—clicks, scrolls, form inputs, page transitions—and lets you play them back like a video. The company has expanded into analytics features like frustration signals, journeys, and dashboards, but session replay remains the foundation.

KISSmetrics was founded on the idea that every user action should be tied to an identified person and traced through to revenue. Its core product is an event-based analytics platform that tracks users across sessions, devices, and touchpoints, then provides funnels, cohort analysis, and revenue reporting. The company has always focused on connecting behavior to business outcomes rather than replaying individual sessions.

These philosophies create fundamentally different workflows. With FullStory, a typical investigation starts with a hunch—“users seem confused on the checkout page”—and you watch sessions to confirm or deny it. With KISSmetrics, a typical investigation starts with data—“checkout conversion dropped 5% this week for users from paid search”—and you segment, compare cohorts, and trace funnels to identify the cause.

Neither approach is wrong. But they lead to different types of insights and different types of decisions.

Session Replay vs Revenue Analytics

What FullStory Does Well

FullStory’s session replay is genuinely powerful. You can search for sessions where users experienced “rage clicks” (rapid repeated clicks indicating frustration), dead clicks (clicking elements that do nothing), or error events. You can filter sessions by page, user segment, or custom events, then watch exactly what happened.

This is invaluable for debugging UX problems. If your support team reports that users are having trouble completing a form, you can pull up sessions where that form was visited and watch the struggle in real time. You will see the exact sequence of actions, the hesitation, the errors, and the eventual abandonment or completion. No amount of aggregate data tells you why a form is broken quite like watching someone try to use it.

FullStory has also added journey mapping and conversion funnel features. These let you see how users move between pages and where they drop off. However, these features are built on top of the session replay infrastructure, which means they are strongest when you want to drill down from an aggregate view into a specific recording.

What KISSmetrics Does Well

KISSmetrics excels at questions that require connecting behavior to revenue across the full customer lifecycle. Its reporting suite includes funnel analysis, cohort reports, revenue tracking, and path analysis—all built on person-level data.

For example, you can answer: “Of users who signed up from our webinar campaign in October, what percentage activated within 7 days, and what is their average revenue at 90 days compared to users from paid search?” This requires tracking identified users across multiple sessions, connecting their acquisition source to their activation behavior to their payment events. KISSmetrics handles this natively.

You can also build revenue-weighted funnels that show not just conversion rates but the dollar impact of each step. If improving one funnel step would add $50,000 in monthly revenue while improving another would add $8,000, the priority is obvious. This is the kind of analysis that directly informs business strategy.

Analysis Capabilities

Funnels

Both tools offer funnel analysis, but the depth differs. FullStory funnels show you how users move through a series of pages or events and let you click into a session recording at any step. KISSmetrics funnels let you segment by any user property (acquisition source, plan type, geographic region, custom attributes), compare time periods, and see the revenue impact of conversion rate changes at each step.

If your question is “where do users drop off?” both tools answer it. If your question is “where do users from paid search drop off compared to organic users, and what is the revenue impact of closing that gap?” you need KISSmetrics.

Cohort Analysis

KISSmetrics provides full cohort analysis that lets you group users by sign-up date, acquisition channel, or any custom property, then track their behavior over time. You can see that users who signed up in January have a 60-day retention rate of 45%, while February sign-ups retained at 52%, and investigate what changed between those cohorts.

FullStory does not offer traditional cohort analysis. Its strength is in session-level insights, not longitudinal tracking of user groups. You can segment sessions by date range and user attributes, but you cannot easily track how a group of users behaves over weeks and months.

Revenue Reporting

KISSmetrics natively tracks revenue events and calculates metrics like customer lifetime value, average revenue per user, and revenue by segment. You can see which acquisition channels produce the highest-value customers, not just the most customers. This is critical for allocating marketing spend efficiently.

FullStory does not focus on revenue analytics. While you can set up custom events for purchases, the platform is not designed to calculate LTV, segment revenue, or attribute revenue to acquisition sources. Revenue-oriented teams will need to supplement FullStory with another tool.

Data Model and Identity Resolution

KISSmetrics uses a person-centric data model. Every event is tied to an identified user, and the platform automatically merges anonymous pre-signup activity with the identified user profile once they authenticate. This means you can trace a user’s journey from their very first anonymous visit through to their most recent purchase, even if they used multiple devices along the way.

FullStory also supports user identification and can link sessions to known users. However, its data model is fundamentally session-based. The primary unit of analysis is the session recording, not the user profile. While you can search for sessions by a specific user, the tool is optimized for session-level investigation rather than cross-session journey analysis.

This distinction matters most for businesses with long consideration cycles. If your average customer visits six times over three weeks before purchasing, KISSmetrics shows you the complete journey as a unified timeline. FullStory shows you six separate session recordings that you would need to watch individually to piece together the story.

Implementation and Setup

FullStory is remarkably quick to set up. You add a JavaScript snippet to your site and it immediately begins capturing session recordings. There is minimal configuration required to start getting value—you can watch your first session recording within minutes of installation. Privacy controls, user identification, and custom events can be added incrementally.

KISSmetrics requires more upfront planning. You need to define the events you want to track, implement the tracking code for each event, and set up user properties. A basic implementation might take a day; a comprehensive one might take a week. The trade-off is that once set up, every event is precisely defined and tied to a person, giving you clean, reliable data for analysis.

For teams that want immediate visual insights with minimal setup, FullStory wins on time-to-value. For teams that want structured, queryable behavioral data connected to revenue, the investment in KISSmetrics setup pays dividends over time.

Pricing and Total Cost

FullStory’s pricing is not publicly listed and requires a sales conversation. Based on industry reports and user feedback, FullStory’s plans typically start at several hundred dollars per month and can reach $1,000 or more for higher session volumes and advanced features. Enterprise contracts can be significantly more. The cost is primarily driven by the number of sessions recorded per month.

KISSmetrics starts at $99 per month with transparent, published pricing. Plans scale based on tracked events and features. There are no surprises in the billing, and you can estimate your costs before committing.

Beyond the sticker price, consider the total cost of ownership. FullStory often requires supplemental analytics tools for revenue reporting, cohort analysis, and attribution. If you add KISSmetrics (or a similar tool) alongside FullStory, your total spend increases. KISSmetrics can serve as the primary analytics platform for behavioral and revenue analysis, reducing the need for additional tools.

Also consider the cost of analysis time. Session recordings are engaging but time-consuming. Watching 50 sessions to identify a pattern takes hours. Running a funnel query in KISSmetrics that identifies the same pattern takes minutes. Both approaches have their place, but if your team’s time is limited, the efficiency of structured analytics matters.

Which Teams Benefit Most

FullStory Is Best For

• UX and design teams who need to see exactly how users interact with interfaces and identify usability problems through direct observation.
• Customer support teams who want to see what a user experienced before filing a support ticket, enabling faster and more empathetic resolution.
• QA and engineering teams who need to reproduce bugs by watching the exact sequence of user actions that triggered an error.
• Product managers focused on feature usability who want to watch how users interact with a newly released feature.

KISSmetrics Is Best For

• Growth and marketing teams who need to attribute revenue to acquisition channels and optimize spend based on customer lifetime value, not just conversions.
• Product managers focused on activation, retention, and expansion who need cohort analysis and funnel data to prioritize development work.
• Revenue and operations teams who need to understand which user behaviors drive upgrades, expansions, and long-term retention.
• Founders and executives who need to connect product metrics to business outcomes and make data-informed strategic decisions.

The Verdict

FullStory and KISSmetrics are not competitors in any meaningful sense. They solve different problems for different people at different stages of the analysis workflow.

If you are trying to answer “what is happening on this page and why are users struggling?”, FullStory is the right tool. Its session replay and frustration detection capabilities are best-in-class for identifying and diagnosing UX issues.

If you are trying to answer “which users become valuable customers, what behaviors predict retention, and where should we invest to grow revenue?”, KISSmetrics is the right tool. Its person-level tracking, revenue analytics, and cohort analysis are purpose-built for connecting behavior to business outcomes.

Some organizations use both, and that combination can be powerful. FullStory diagnoses the micro-level problems. KISSmetrics quantifies the macro-level impact. Together, they provide a complete view of user behavior from individual session friction to lifetime revenue contribution.

For teams that must choose one, the deciding factor is your most pressing question. If your product experience is rough and users are visibly struggling, start with FullStory to fix the immediate friction. If your product works but you cannot connect user behavior to revenue growth, start with KISSmetrics to build the analytical foundation that will drive your next stage of growth.