This visual analysis capability provides five distinct types of heatmaps, including the unique Confetti map, offering deep visual insights into click behavior.
Heatmap generation is the foundational feature that made this platform famous. It tracks mouse clicks and scrolling behavior, offering five distinct visual reports: standard Heatmaps (showing hot/cold click zones), Scrollmaps (showing how far users scroll), an Overlay report (showing the exact percentage of clicks on specific elements), a List report, and its signature "Confetti" map. The Confetti map is highly unique; it visualizes individual clicks as distinct colored dots on the page and allows analysts to segment those specific clicks by traffic source, search term, or time of day. This is incredibly powerful for seeing exactly how users from a specific ad campaign interact with a landing page.
Session recording offers basic session recording capabilities to watch individual user journeys, though it lacks the advanced filtering of dedicated replay tools.
To complement its core heatmap functionality, the platform includes a straightforward session recording module. It captures continuous video playbacks of individual user sessions, tracking mouse movements, scrolling, and clicks. The playback timeline highlights when specific interactions occur, helping analysts quickly skip to relevant moments. While highly useful for gaining qualitative context alongside the heatmaps, the recording feature is relatively basic compared to enterprise dedicated replay tools. It lacks highly advanced, DOM-indexed search capabilities or automated, AI-driven friction detection (like automatically flagging rage clicks), meaning analysts must spend more time manually filtering and watching videos to find UX issues.
The vendor acts as a data processor and provides basic tools for data deletion, but relies heavily on the user for full compliance.
The platform provides foundational support for compliance with privacy frameworks like GDPR and CCPA. The vendor operates as a Data Processor, ensuring the client retains control of their data. It offers basic tools to handle Data Subject Access Requests (DSARs), allowing administrators to search for and delete specific user profiles upon request. It also supports IP address anonymization. However, unlike highly specialized privacy platforms, it lacks complex, client-side PII masking rules out of the box. To ensure full legal compliance, the business must rigorously manage exactly what data is sent to the platform and correctly implement a Consent Management Platform (CMP) before tracking begins.
The platform does not natively stream raw, user-level event data to data warehouses, limiting its utility for enterprise data engineering teams.
While the tool is effective for visual UX diagnostics, it is highly restrictive regarding raw data portability. It does not provide automated pipelines or direct integrations (like Google BigQuery or Snowflake) to stream continuous, unsampled, user-level behavioral data. Export capabilities are strictly limited to downloading CSV or Excel files containing pre-aggregated metrics, such as a list of snapshots, basic page view totals, or summarized click coordinates from specific heatmaps. This means data science teams cannot extract the underlying raw behavioral data to build proprietary attribution models or combine UX metrics with external financial databases.
Data retention policies are strictly limited based on the subscription tier, typically holding snapshot data for up to one year on standard plans.
The platform enforces strict data retention limits to manage the high storage costs associated with visual snapshots and recordings. On standard premium plans, heatmap snapshots, A/B test results, and session recordings are typically retained for 1 year before being permanently deleted. Entry-level or older legacy plans may have even shorter retention periods (e.g., 3 to 6 months). Once the retention limit is reached, the visual data is permanently purged and cannot be recovered. Organizations that require long-term archival of specific heatmaps for historical UX comparisons must manually export and save screenshots of those reports before they expire.
Secure corporate access via SAML-based Single Sign-On is supported, but strictly limited to custom enterprise-level plans.
To support larger organizations with stringent IT security protocols, the platform offers SAML-based Single Sign-On (SSO) integration. This allows enterprise administrators to connect the analytics workspace with centralized identity providers such as Okta, Microsoft Entra ID (Azure AD), or Google Workspace. Implementing SSO enables the enforcement of multi-factor authentication and allows IT to manage user access directly from the corporate directory. However, this critical security feature is not available on standard, self-serve premium plans; it requires negotiating a custom Enterprise contract, making it inaccessible for smaller businesses that still require strict access control.
The feature features a native surveys module, allowing marketers to trigger contextual pop-up questions based on specific user behaviors.
Beyond heatmaps, the platform includes active Voice of Customer (VoC) tools to gather qualitative insights. Marketers can easily build interactive polls and surveys and trigger them to appear dynamically on the website. The triggering logic is behavior-based; a survey can be set to pop up only when a user shows exit intent, visits a specific pricing page, or scrolls halfway down an article. This allows teams to ask highly contextual questions exactly when users might be experiencing friction (e.g., "What is missing from this page?"). The responses are collected directly within the dashboard, providing immediate qualitative context to the quantitative heatmap data.
This capability does not feature advanced, AI-driven friction scoring, requiring analysts to manually identify UX issues through heatmaps and recordings.
Unlike some newer behavioral analytics platforms, this tool does not currently feature an automated, machine-learning-driven friction detection engine. It does not automatically calculate a unified "Frustration Score" or flag explicit UX errors like "dead clicks" or "rage clicks" on a dedicated timeline. To identify areas of friction, analysts must manually review the heatmaps (e.g., looking for concentrated clicks on non-clickable elements) or manually watch session recordings to spot where users hesitate or abandon a flow. This requires a significantly higher degree of manual analysis from the UX team compared to tools that automatically highlight struggling users.