Heap

What Is Heap?

Heap is an autocapture product-analytics platform that automatically records every user interaction on a website or app, so teams can analyze behavior without having to instrument each event in advance. Founded in 2013, Heap built its reputation on a simple but powerful idea: instead of asking developers to manually tag every button, form, and page they might want to measure later, capture everything automatically and let analysts define the events they care about retroactively. That approach removes one of the biggest bottlenecks in traditional analytics, the slow, error-prone cycle of deciding what to track, writing tracking code, deploying it, and waiting for data to accumulate.

The platform's defining capability is autocapture. From the moment Heap's snippet loads, it records clicks, taps, page views, form submissions, and other interactions across the entire experience. Because the raw interaction data is already captured, an analyst can later define a meaningful event, say, "clicked the upgrade button on the pricing page", and immediately see historical data for it, as if it had been tracked all along. This retroactive analysis is the core differentiator that separates Heap from event-based tools where you only have data for events you defined before they happened.

Heap is a hosted SaaS product-analytics platform, not a browser extension and not a plugin you bolt onto a CMS. You add its JavaScript snippet to your site or embed its SDK in your app, and Heap streams interaction data to its cloud, where it builds funnels, retention reports, user journeys, and segments. It sits in the product-analytics category alongside tools like Mixpanel and Amplitude, but its autocapture-first philosophy gives it a distinct posture: comprehensive data collection up front, flexible definition of events afterward.

It helps to frame who Heap is for. The platform targets product managers, growth and marketing analysts, and data teams at companies that want to understand and improve how users move through their product. A product manager uses Heap to discover which features drive retention; a growth analyst uses it to find where a conversion funnel leaks; a data team uses its richer plans to pipe captured behavior into a warehouse for deeper modeling. That focus on product and growth analysis, rather than lightweight traffic counting or session-by-session replay, shapes the entire product and explains why it appeals to teams that iterate quickly and do not want analytics to be the thing slowing them down.

How Heap Works

Heap works by loading a JavaScript snippet (served from Heap's CDN) on each page of your site, or an equivalent SDK in a native app. Once loaded, the script begins autocapturing interactions: it records page views, clicks, taps, form submissions, and the elements involved, then transmits that data to Heap's servers. Crucially, this happens without you predefining events, the snippet captures the full stream of interactions automatically, which is the foundation of everything else Heap does.

On top of this raw data, Heap introduces the concept of defined events (sometimes called virtual events). An analyst uses Heap's visual interface to label a particular interaction, for example, a click on a specific button or a submission of a specific form, as a named event. Because the underlying interaction was already captured, the new event is immediately populated with historical data. This means a team can ask a brand-new question, "how many people clicked our new pricing toggle last month?", and get an answer instantly, even though no one wrote tracking code for that toggle.

Heap then provides the analysis tools that product teams expect. Funnels show conversion and drop-off across a sequence of steps, and because events are defined retroactively, funnels can be built and revised at any time using historical data. Retention reports reveal how many users return over time, segments group users by behavior or properties, and user journeys map the paths people actually take through the product. Heap can also enrich data with user and account properties so analysts can slice behavior by plan, cohort, or other dimensions.

For data teams, Heap offers ways to connect captured behavior to the broader stack. Higher-tier plans support exporting or syncing data to a data warehouse, so analysts can join behavioral data with other business data and model it in tools they already use. Heap also provides integrations with common product, marketing, and data platforms, and APIs for sending server-side events or pulling data out. This makes it usable both as a standalone analytics app and as a behavioral data source feeding a larger analytics pipeline.

A useful way to picture the workflow is to follow a single analysis end to end. Suppose a growth team wants to improve trial-to-paid conversion. With Heap already autocapturing interactions, an analyst defines the relevant events, "started trial", "visited pricing", "clicked upgrade", "completed purchase", without touching the codebase, and builds a funnel across them. They immediately see historical conversion rates and where users fall out. They then segment the funnel by acquisition source or plan to find which cohorts convert best, form a hypothesis, ship a change, and watch the funnel update. Because no new instrumentation was required, the loop from question to insight is fast, which is exactly the advantage autocapture is meant to deliver.

How to Tell if a Website Uses Heap

Heap leaves several reliable fingerprints. Because StackOptic analyzes a URL from the server side, it inspects the same signals you can check manually with browser tools, View Source, or a detection extension. As a product-analytics tool with a clear collection footprint, Heap is generally straightforward to detect.

The Heap CDN domain. The strongest signal is a script request to cdn.heapanalytics.com (historically also heapanalytics.com and heap.io domains), typically loading Heap's tracking library. A <script> tag pointing at cdn.heapanalytics.com is strong evidence of Heap.

The heap JavaScript global and app ID. Heap's install snippet initializes a global heap object and calls heap.load("APP_ID") with your environment's numeric application ID. In the DevTools Console, typing window.heap and getting an object back, often with a visible appid, is a clear confirmation that Heap is running.

The initialization snippet. Heap's standard snippet is a recognizable inline script that sets up the heap object and queues method calls before the library finishes loading. Spotting this initialization block in the page source is another dependable tell.

Network beacons to Heap. As the page is used, the library sends captured interaction data to Heap's ingestion endpoints. In the DevTools Network tab you can watch these requests to Heap domains fire as you click and navigate, confirming active collection rather than a stale script.

Here is how to check each signal yourself:

Method	What to do	What Heap reveals
View Source	Right-click, "View Page Source" and search for "heap"	The cdn.heapanalytics.com script and the heap.load("APP_ID") snippet
Browser DevTools	Open the Network tab and interact with the page	Requests to Heap domains streaming captured events
DevTools Console	Type window.heap and press Enter	An object, often exposing the app ID, confirming Heap is present
Wappalyzer	Run the extension on the live page	Identifies "Heap" under analytics
BuiltWith	Look up the domain	Current and historical Heap detection

A fast command-line check is curl -s https://example.com | grep -i "heapanalytics". If that returns a match, you are almost certainly looking at Heap. For the broader methodology, see our guides on how to find out what analytics a website uses and how to find out what technology a website uses.

A practical note on accuracy: like many analytics tools, Heap is sometimes deployed through a tag manager rather than hard-coded into the HTML. When that happens, the page source may show a Google Tag Manager container while the Heap script and its beacons appear only after the tag fires, so the DevTools Network tab and the window.heap Console check become the most reliable confirmations. Our guide on how to check if a website uses Google Tag Manager covers spotting that layer. Server-side analysis is valuable because it fetches the raw HTML and directly referenced scripts without browser interference, but for tag-managed setups the surest confirmation comes from observing the live heap global and the streaming beacons. Combining several signals, the CDN reference, the global object with its app ID, and the network requests, yields a confident verdict even on customized sites.

Key Features

• Autocapture. Automatic recording of clicks, taps, page views, and form submissions across the entire experience, with no manual event tagging required.
• Retroactive event definition. Label interactions as named events at any time and instantly see historical data, because the raw interactions were already captured.
• Funnels. Build and revise conversion funnels on the fly using historical data to find drop-off points.
• Retention analysis. Measure how many users return over time and which behaviors drive stickiness.
• Segmentation. Group users by behavior, properties, plan, or cohort to compare how different audiences engage.
• Warehouse and integrations. Sync captured behavior to a data warehouse and connect with product, marketing, and data tools.
• APIs. Send server-side events and pull data out for custom analysis and pipelines.

Pros and Cons

Pros

• Autocapture eliminates the slow, error-prone cycle of manually instrumenting every event.
• Retroactive analysis lets you answer new questions with historical data you did not plan to collect.
• Fast time-to-insight for product and growth teams that iterate quickly.
• Strong funnel, retention, and segmentation tooling on top of comprehensive data.

Cons

• Capturing everything can produce noisy data that requires governance and clear definitions to stay useful.
• Priced for businesses and growth-stage teams rather than hobbyists, scaling with volume and features.
• Less focused on session-by-session replay than dedicated experience-analytics tools.
• Heavier and more involved than a lightweight, privacy-first page-view counter.

Heap vs Alternatives

Heap sits in the product-analytics category with an autocapture-first philosophy. The table below compares it with common alternatives.

Platform	Data collection	Strength	Best for
Heap	Autocapture (everything)	Retroactive event definition	Teams wanting analysis without pre-instrumentation
Mixpanel	Event-based (defined first)	Funnels and retention	Product teams comfortable instrumenting events
Amplitude	Event-based (defined first)	Deep behavioral and cohort analysis	Data-mature product orgs
FullStory	Autocapture + session replay	Watching real sessions	UX and support teams needing qualitative insight
Google Analytics 4	Event-based	Free, broad traffic analytics	Acquisition and marketing analysis

If you suspect a site uses a different product-analytics tool, the closest comparison is Amplitude, which offers deep behavioral analysis but follows an event-based, define-first model rather than autocapture. For event-based product analytics with a focus on funnels and retention, see Mixpanel.

Use Cases

Heap is most at home where product and growth teams need fast, flexible answers about user behavior. Product managers use it to discover which features correlate with retention and which onboarding steps lose users, defining the relevant events retroactively and getting historical context immediately. Growth analysts use its funnels and segments to find and fix leaks in acquisition and conversion flows.

It also serves data teams that pipe autocaptured behavior into a warehouse for deeper modeling, SaaS and e-commerce companies optimizing multi-step conversion paths, and any team that has been burned by discovering, too late, that it never instrumented an interaction it now needs to analyze. For competitive and market research, detecting Heap on a site signals an organization that invests in product analytics and likely has a product or growth function driving decisions with data.

Consider a few concrete scenarios. A subscription business wanting to improve trial conversion defines its funnel events in Heap without engineering help, spots the step where users stall, and ships a targeted fix, all in days rather than weeks. A product team launching a new feature uses autocaptured data to measure adoption immediately, even for interactions no one thought to tag, and segments adoption by plan to see which customers benefit most. A data-driven marketplace syncs Heap data into its warehouse to combine behavioral signals with revenue data and model lifetime value. In each case the common thread is removing instrumentation as a bottleneck so the team can ask and answer questions quickly.

From a sales-intelligence perspective, spotting Heap on a prospect's site is a meaningful data point. It indicates an organization with a product-analytics practice and, often, a growth or data team making decisions with behavioral data, which correlates with product maturity and budget for tooling. For vendors selling to product, growth, or data teams, that is a strong qualifying signal. To understand how detecting a site's stack feeds lead qualification more broadly, see what is technographics and using tech-stack data to qualify leads.

Frequently Asked Questions

What makes Heap different from Mixpanel or Amplitude?

Heap's defining difference is autocapture. Mixpanel and Amplitude are event-based: you define and instrument the events you want before they can be measured, so you only have data for what you anticipated. Heap captures interactions automatically and lets you define events retroactively, instantly populating them with historical data. That trade favors speed and flexibility, at the cost of more data to govern, while event-based tools favor deliberate, curated tracking.

How can I tell if a website uses Heap?

Search the page source for heap and look for a script from cdn.heapanalytics.com plus the heap.load("APP_ID") initialization snippet. In DevTools, type window.heap in the Console, an object (often exposing the app ID) confirms it, and watch the Network tab for beacons to Heap domains as you interact. Wappalyzer and BuiltWith also detect it. Note that some sites load Heap through Google Tag Manager, so the script may appear only after the tag fires.

Does Heap really capture everything automatically?

Yes, that is the core of its design. Heap's snippet autocaptures interactions such as clicks, taps, page views, and form submissions from the moment it loads, without requiring you to tag each one. You then define named events on top of that captured data whenever you need them, and Heap fills them in with history. Teams still apply governance, naming conventions, and definitions, so that comprehensive capture turns into clean, trustworthy analysis rather than noise.

Is Heap a privacy concern like session replay tools?

Heap focuses on capturing interaction events for product analytics rather than reconstructing full visual session replays, so its data profile differs from dedicated replay tools. That said, any platform that captures user behavior should be configured responsibly, with attention to sensitive fields and compliance obligations such as GDPR and CCPA. Heap provides controls for handling data appropriately, and as with any analytics deployment, clear privacy disclosures and sensible configuration are essential.

Can Heap send data to a data warehouse?

Yes. Higher-tier Heap plans support exporting or syncing captured behavioral data to a data warehouse, where analysts can join it with other business data and model it using their existing tools. This makes Heap usable both as a self-contained analytics application and as a behavioral data source within a larger data stack, which is attractive to data-mature organizations that want to centralize analysis rather than keep behavioral data siloed.

Want to identify Heap and the rest of a site's stack automatically? Run any URL through StackOptic at https://stackoptic.com.