Product analytics · Heap (a Contentsquare company)

Heap

Product analytics built on autocapture, recording every user interaction so events can be defined retroactively instead of pre-instrumented.

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Heap is a product analytics platform built around autocapture: instead of requiring engineers to instrument every click and page view in advance, Heap's SDK records all user interactions automatically and lets analysts define events retroactively from that captured data. This means historical questions can be answered without waiting weeks for new instrumentation to accumulate data. The platform covers funnels, retention curves, user paths, and session replay (as an add-on), and layers Sense AI on top to surface anomalies and generate reports in plain language. Heap ships as a pure cloud SaaS product and, since being acquired by Contentsquare in 2023, sits alongside Contentsquare's digital experience analytics suite while continuing to operate under its own brand. It connects to data warehouses for exporting captured events and is aimed at product and growth teams who want to explore behavior they didn't think to track ahead of time.

At a glance

Vendor Heap (a Contentsquare company)
Pricing model Free tier + paid plans
Free tier Yes
Deployment Cloud
Open source No
Best for Teams that want to mine historical user behavior for insights they didn't think to instrument in advance.

Pricing

Free plan covers up to 10K monthly sessions; paid Growth, Pro and Premier tiers use custom session-based pricing set after a sales conversation.

Plan Price Notes
Free Free Up to 10,000 monthly sessions; 6 months of data history
Growth Custom, session-based Unlimited users and reports; 12 months of data history
Pro Custom, session-based Adds account analytics, engagement matrix, session replay add-on
Premier Custom, session-based Adds data warehouse integration, unlimited projects, dedicated CSM

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • Autocapture of every user interaction without manual event tagging
  • Retroactive event definition against historical data
  • Funnel, retention, and path analysis
  • Session replay (add-on)
  • Sense AI for automated insights and anomaly detection
  • Data warehouse sync (Snowflake, BigQuery, Redshift)
  • Account-level (B2B) analytics
  • SSO and role-based permissions

Integrations

Profile last reviewed September 21, 2026

Alternatives

Pendo Product analytics paired with no-code in-app guides, surveys and onboarding flows built from the same usage data. Mixpanel Cloud-based product analytics platform for event tracking, funnels, retention, session replay, and experimentation. Amplitude Cloud-based digital analytics platform for event tracking, behavioral cohorts, session replay, and feature experimentation. PostHog Open-source product analytics suite combining event analytics, session replay, feature flags, experiments and error tracking.

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Terms to know

Event tracking Capturing specific user actions, such as clicks or purchases, as discrete, named pieces of data. Funnel analysis A method for tracking how users move through an ordered sequence of steps toward a goal, and where they drop off. Retention analysis The study of how many users keep returning to and engaging with a product after their first use. Cohort analysis Grouping customers by a shared starting point, such as signup month, and tracking how their behavior diverges over time. Anomaly detection Identifying data points or patterns that deviate significantly from expected or normal behavior. Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions.

Related guides

Behavioral event data, explained How product and marketing teams turn raw clicks and actions into events, and what separates a usable event stream from a noisy one. How to choose a product analytics tool Product analytics tools split by how events get captured, who reads them, and whether in-app engagement is bundled in — decide those first. How to run a cohort retention analysis How to build a retention cohort table in SQL, read the curve it produces, and avoid the comparisons that quietly mislead.