Fullstory

Overview

Fullstory is a behavioral data platform that bridges the gap between quantitative analytics and qualitative user experience. While traditional analytics tools tell you what is happening on your site or app, Fullstory explains why by capturing the complete user journey. It is best known for its high-fidelity session replay capabilities, but has evolved into a comprehensive intelligence platform that uses AI to surface insights automatically.

The platform is built on “Fullcapture” technology, which logs every cursor move, click, scroll, and page mutation without requiring manual event tagging. This allows teams to retroactively analyze data and answer questions they didn’t know they had when the data was collected. Trusted by product managers, engineers, and support teams, Fullstory places a heavy emphasis on privacy, offering robust tools to mask sensitive data at the source (the client’s browser) before it ever reaches their servers.

Key Features

Fullcapture & Session Replay

Fullstory’s core differentiator is its “tagless” autocapture engine, Fullcapture. Unlike event-based analytics that require engineers to instrument specific buttons or actions manually, Fullcapture records the entire DOM structure and assets of your website or mobile app. This creates a pixel-perfect recreation of the user experience. Because the data is structured (not a video recording), users can search for sessions based on specific behaviors—such as “clicked ‘Add to Cart’ but didn’t checkout”—and watch the exact user journey.

Crucially, this feature is built with a “Private by Default” architecture. The system is designed to exclude sensitive text and inputs automatically, ensuring that Personally Identifiable Information (PII) like credit card numbers or passwords never leaves the user’s device. Teams can further customize these privacy rules using CSS selectors to unmask only the specific non-sensitive data they need for analysis.

StoryAI & Automated Insights

Analyzing thousands of session replays manually is impossible at scale. StoryAI solves this by acting as an always-on analyst that processes behavioral data to find patterns. The “Ask StoryAI” feature allows users to ask natural language questions about their data, such as “Why are users dropping off at the payment screen?” The AI analyzes the underlying sessions and provides a summarized answer, citing specific evidence from the data.

Beyond Q&A, the platform automatically detects “frustration signals” such as Rage Clicks (repeatedly clicking an element), Dead Clicks (clicking elements that do nothing), and Error Clicks (clicks resulting in JavaScript errors). These signals are aggregated to prioritize the most damaging issues affecting the user experience, allowing product teams to focus their roadmap on high-impact fixes rather than hunting for problems.

Quantitative Analytics & Heatmaps

While session replay provides the narrative, Fullstory’s analytics suite provides the aggregate metrics needed for decision-making. The platform offers robust funnel analysis, conversion tracking, and retention charting. Users can create “Segments” based on user attributes or behaviors and visualize how these groups move through the product.

This quantitative data is tightly integrated with visual tools like Heatmaps. Users can view Click Maps and Scroll Maps to see aggregate engagement on any page. Unique to Fullstory, these heatmaps are fully interactive and retroactive; because all data is captured, you can view a heatmap for a popup that launched yesterday without having set up tracking beforehand. If a metric looks off—for example, a sudden dip in conversion—users can click directly into the chart to watch the specific sessions that contributed to that data point.

Pricing

Fullstory offers a transparent and generous entry point via FullstoryFree. This permanent free plan includes 30,000 sessions per month with 1 month of data retention and access for up to 10 teammates. It provides access to core features including Session Replay, basic analytics, and debugging tools, making it highly viable for early-stage startups and indie makers.

For growing teams, paid plans are divided into Business, Advanced, and Enterprise tiers. Pricing is generally custom and based on session volume.

• Business: Adds deeper product analytics and qualitative insights.
• Advanced: Unlocks trend discovery, roadmap planning features, and funnels at scale.
• Enterprise: Designed for data science teams, offering predictive modeling, SQL access, and extended data history.

The platform distinguishes itself by not charging per “seat” (user license), encouraging organization-wide adoption. Specialized pricing and programs are often available for qualifying startups.