Imagine installing one lightweight script and instantly seeing every click, hover, and text change inside your productwithout begging engineers to “just add one more event.” That’s the promise of autocapture raw events in Userpilot.

If you build or grow SaaS products, you already know the pain of old-school analytics. Someone writes a tracking plan, engineering adds the events (eventually), QA finds bugs, marketing needs a new funnel, and suddenly you’re back to square one. Meanwhile, users are busily clicking away, and all that behavior data is simply… gone.

Autocapture flips that script. Instead of deciding everything in advance, you let the tool automatically collect raw interaction data, then decide later which events actually matter. In Userpilot, these are called raw eventsyour unfiltered stream of user interactions, ready to be labeled, grouped, and turned into insights.

In this guide, we’ll unpack how Autocapture Raw Events in Userpilot work, why they’re a game changer for product analytics, how to implement them responsibly, and what real teams have learned from using them in the wild.

What Are Autocapture Raw Events?

From manual tracking to “track almost everything”

Traditional analytics starts with manual event tracking: you decide the exact actions you want to measure (for example, clicked CTA button or completed onboarding checklist), then add tracking code or configure them through a visual tagger. It’s precise, but slow and fragile. Miss an event today and you can’t analyze it retroactively tomorrow.

Autocapture takes a different approach. The analytics tool automatically records a broad set of user interactionsthings like:

• Clicks on buttons, links, and interactive elements
• Text input changes in forms and fields
• Form submissions and key UI actions
• Page views or screen views in your app

These raw records, before you give them any friendly names or business context, are called raw events. Think of them as the “black box recorder” for your product: they capture what happened, when, and where, even if you didn’t know you’d care about it at the time.

Raw events vs. labeled and tracked events

In Userpilot’s model, raw events are just the start of the journey. Once interactions are collected, you can:

• Label events – attach meaningful, human-readable names to specific raw events (for example, “Clicked Upgrade CTA” instead of “button click on #home-cta-primary”).
• Promote events to tracked events – select the labeled events that truly matter to your growth goals so they appear in dashboards, trend charts, funnels, and goal reports.
• Combine events into custom events – group multiple interactions into higher-level actions (for example, “Completed onboarding” might include invited teammate + created first project + published template).

This layered approach lets you start with “capture everything important by default,” then introduce structure over time so your team isn’t drowning in noise.

How Userpilot’s Autocapture Raw Events Work

Once you’ve installed the Userpilot script in your web app or product, Autocapture Raw Events kicks in automatically. From that point on, Userpilot begins logging user interactions as raw events without requiring extra coding for each one.

Where raw events live in Userpilot

Inside the Userpilot dashboard, autocaptured events are surfaced in a dedicated Raw events area. Each event typically includes:

• The interaction type (e.g., click, text change, form submit)
• Total occurrences across your user base
• The last occurred timestamp so you know whether an action is actively happening

That view becomes your discovery layer: you can scan through what users are actually doing, filter by page or element, and decide which events deserve names and ongoing tracking.

From raw to labeled to “business-ready”

Here’s a simple way to picture the lifecycle of an autocaptured event in Userpilot:

1. An interaction happens. A user clicks a key button in your app.
2. Userpilot autocaptures it. The event appears as a raw event with generic system properties.
3. You label it. You assign a descriptive label like “Upgrade button clicked – pricing page.”
4. You promote it. You mark it as a tracked event so it shows up in funnels, retention charts, and goals.

This workflow lets product managers and growth teams start with a complete data stream and then continuously refine what’s important as the product evolves.

Turning autocapture off (and why you might)

Although autocapture is powerful, not every team wants every interaction. In some casesespecially in highly regulated industries, or if your app has extremely complex DOM structuresyou may want to narrow what you collect. Userpilot gives you the ability to turn off or limit Autocapture Raw Events at the workspace level if needed.

That means you can:

• Run autocapture during discovery and early product stages.
• Turn it off later and rely mostly on curated events.
• Or run a hybrid approach using raw events for exploration and tracked events for reporting.

Why Autocapture Raw Events Matter for Product Teams

1. Faster time to insights

With manual tracking, any missed event means missed history. With autocapture, you don’t need to predict every interaction you’ll care about six months from now. You can simply say, “What were people doing on that new settings page last quarter?” and pull it from previously captured raw data.

That’s particularly useful when:

• You launch a new feature and realize later which interactions actually predict retention.
• Your leadership asks ad-hoc questions about user behavior you didn’t spec ahead of time.
• You need to troubleshoot adoption issues retroactively (e.g., “Did users even see the tooltip we added?”).

2. Reduced engineering dependency

One of the biggest selling points of tools like Userpilot is that product teams can own their analytics setup without having to constantly file tickets. Autocapture amplifies that: you no longer need a developer to wire up every new eventyour job becomes curation and naming, not implementation.

This is especially valuable if:

• Your engineering team is already overloaded with core product work.
• You iterate rapidly on UI and don’t want tracking to break with every design change.
• Non-technical stakeholders (PMs, UX, marketing) want freedom to explore behavior patterns on their own.

3. Better context for product-led growth

Product-led growth (PLG) strategies rely heavily on understanding real in-app behavior: which features drive “aha” moments, which patterns predict upgrades, and which workflows correlate with churn. Autocapture raw events give your PLG motion a richer data foundation.

When you combine raw events with Userpilot’s in-app experiences (like onboarding flows, checklists, and resource centers), you can:

• Trigger guides or tooltips based on actual behaviors, not just assumptions.
• Measure whether users who see certain flows go on to activate or convert.
• Segment users based on interaction depth with key features, not just logins.

4. A safety net for your tracking plan

Even the best tracking plans miss things. Autocapture is your safety net. If you forget to explicitly track an important button or workflow, chances are it’s still captured as a raw event, waiting to be identified and promoted.

Designing a Clean Event Taxonomy on Top of Raw Events

Autocapture doesn’t mean “give up on structure.” In fact, the more data you collect, the more you need a clear taxonomy so your dashboards don’t turn into alphabet soup.

Start with business questions, not every possible click

Before you label and promote events, get crisp on what you’re trying to answer:

• “How do users progress from sign-up to first value?”
• “Which features are most correlated with expansion revenue?”
• “Where do trial users drop off in onboarding?”

Work backwards from those questions to identify a core set of eventsmaybe 20–50that you absolutely need to track. These usually include:

• Key feature usage events (for example, “Created report,” “Shared dashboard”)
• Milestones in onboarding (for example, “Connected data source,” “Invited teammate”)
• Conversion and upgrade events (for example, “Started trial,” “Upgraded to Pro”)

Define clear naming conventions

Once you choose which interactions matter, give them consistent names. A simple pattern might be:

• <Entity> – <Action> – <Context>

Examples:

• Project – Created – From template
• Billing – Updated – Payment method
• Dashboard – Shared – External link

That way, when new PMs or analysts join, they don’t have to decipher cryptic event names like btn_23_click.

Use raw events as a discovery tool

A healthy workflow with Userpilot’s autocapture looks like this:

1. Explore the Raw events tab to see what users are actually doing.
2. Filter by high-volume interactions or pages tied to important flows (like onboarding, billing, or core features).
3. Label the events that clearly connect to your growth metrics.
4. Promote those labeled events to tracked events and build reports around them.

Over time, you’ll refine your taxonomy as you learn which events are predictive and which were just “nice to know.”

Implementing Autocapture Raw Events in Userpilot: A Practical Walkthrough

Let’s walk through a practical, high-level setup for a SaaS product that wants to use Autocapture Raw Events – Userpilot to power product analytics.

Step 1: Install Userpilot everywhere your users live

First, add the Userpilot snippet or SDK to your app (typically in the main layout or global template). Make sure it’s:

• Loaded for all authenticated users (and guests, if you track them)
• Configured with user IDs and company IDs so you can segment by account
• Consistent across environments (for example, staging vs. production)

Step 2: Confirm autocapture is running

Log into Userpilot and visit the Raw events section. Interact with your app (click buttons, fill out forms, test key flows), then refresh the events list. You should begin to see:

• Click events on navigation and CTAs
• Form submissions on login, signup, and billing pages
• Text changes in key input fields

Step 3: Identify your “must-have” events

With data flowing, sit down with your product and growth stakeholders and answer:

• What does “activation” mean for us?
• Which actions correlate with long-term retention?
• What are the top 3–5 flows that users must complete for the product to deliver value?

Use the raw events view to find the underlying interactions that map to those milestones. These are your first candidates to label and track.

Step 4: Label and promote events

For each important raw event:

1. Open it in the Raw events view.
2. Assign a descriptive label that follows your naming convention.
3. Mark it as a tracked event so it appears in dashboards, trends, funnels, and goals.

Over time, your library of tracked events becomes the backbone of your reporting.

Step 5: Build dashboards and experiments

Once your core events are tracked, use Userpilot’s analytics features to:

• Track activation funnels from sign-up to first value.
• Measure feature adoption across different user segments.
• Analyze retention by usage patterns (for example, weekly active use of a flagship feature).
• Trigger in-app experiences based on specific behaviors (for example, show a “Pro tips” guide after users use a feature three times).

Common Pitfalls (and How to Avoid Them)

Too much noise, not enough signal

Autocapture can generate a lot of datagreat for discovery, dangerous for reporting. If you promote every raw event, your reports quickly become unmanageable. The solution:

• Limit tracked events to those tied directly to business outcomes.
• Use prefixes or categories in naming to group similar events.
• Regularly archive or deprecate events that no one uses anymore.

Ignoring performance and privacy

Any analytics collection must respect performance and user privacy. Best practices include:

• Mask or avoid capturing sensitive fields (like passwords, credit card numbers, or highly personal data).
• Ensure your privacy policy clearly explains what you capture and why.
• Work with legal or compliance teams if you operate under strict regimes (GDPR, HIPAA, etc.).

Leaving raw events unloved

Raw events are most valuable when they’re actively reviewed. If you never visit the Raw events tab, you’ll miss emerging behaviorslike new navigation patterns or unexpected feature usage. Make it a habit to:

• Review raw events after major releases or UI changes.
• Scan for high-volume interactions you don’t yet track.
• Use those discoveries to refine onboarding and feature education.

Real-World Use Cases for Autocapture Raw Events

1. Diagnosing a failing onboarding experiment

Suppose your team launches a new onboarding checklist, but activation rates barely move. Without autocapture, you might know only that “activation is still low.” With Userpilot’s raw events, you can dig into:

• Which checklist items users click onif they open the checklist at all.
• Where they stall in the onboarding flow.
• Whether they interact with key features before abandoning the app.

Often, you’ll discover simple issues: important buttons hidden below the fold, confusing copy, or users skipping the very feature you assumed was obvious.

2. Finding “power user” behaviors

Your most loyal, high-value customers probably use your product differently than casual users. With raw events, you can:

• Filter for users with high retention or expansion revenue.
• Analyze the events they trigger most often.
• Spot patterns, like frequent use of advanced filters or collaboration features.

Once you’ve labeled and tracked those events, you can encourage similar behaviors in newer users through in-app nudges, tooltips, and checklists.

3. Supporting customer success with real usage data

When a customer success manager jumps on a call with a customer, raw events and tracked events together give them a live picture of what’s happening:

• Has the customer ever clicked the feature they’re confused about?
• Did they complete the setup flow or get stuck halfway?
• Are they using the product in a way your team didn’t expect?

Instead of guessing, CSMs can share targeted tips, custom walkthroughs, or follow-up flows based on what users actually didnot just what they say they did.

Lessons from the Field: of Autocapture Experience

Let’s get a little more practical and talk about what it’s actually like to live with Autocapture Raw Events – Userpilot day to day.

Picture three different teams adopting autocapture.

Team A is a fast-moving startup. They don’t have a data team, and their single PM is also doing half the UX work. When they turned on autocapture in Userpilot, it felt like magic: within a day, they could see which parts of their onboarding flow people touched, which CTAs got all the love, and which “genius” settings page nobody ever opened.

But then the PM did what many people do: they started labeling everything. Every click, every form, every minor UI detail became a labeled event. Dashboards multiplied. Filters stacked up. After a month, nobody knew which charts to trust because there were 17 different versions of “activation” and five dashboards all claiming to be “the” product overview.

The fix wasn’t technicalit was cultural. They paused, defined a small set of core metrics, and archived the noisy events. Raw events stayed on as a discovery tool, but only a curated subset graduated to “official” tracked events. Suddenly, their reports started telling a clear story again.

Team B lives in an enterprise environment. They love data but also love process. When they enabled autocapture, their first reaction was mild panic: “Are we allowed to collect this? What about privacy? Do we need a committee for this?” They were right to ask those questions.

Their approach was to treat autocapture like a temporary discovery mode. For a few weeks, they let Userpilot capture raw events, then sat down with legal, security, and product to decide which event categories were acceptable long-term. They masked or excluded sensitive fields, formalized their naming conventions, and documented how events map to internal metrics. By the time they declared their implementation “production ready,” they had both the richness of autocaptured data and the guardrails their compliance team needed.

Team C thought they didn’t need autocapture at all. They had a carefully crafted tracking plan, all wired through code. Everything was tidyuntil a key PM left, the app UI was redesigned, and suddenly half the tracked events stopped firing correctly. New features went live without analytics coverage because nobody had time to update the plan.

When they introduced Autocapture Raw Events in Userpilot, they didn’t abandon their original approach; they gave it a backup generator. Raw events filled in the gaps while they rebuilt their tracking plan. They could still rely on their core coded events for long-term metrics, but now they had a way to discover broken journeys, unexpected behaviors, and new patterns without waiting for perfect specs.

Across all three teams, a few lessons repeat:

• Autocapture is a force multiplier, not a replacement for thinking. You still need to decide what “success” means and which interactions actually matter.
• Governance matters. A simple naming convention and a shared metrics glossary go a long way toward preventing dashboard chaos.
• Regular reviews pay off. Make time to browse your raw events after releases. You’ll spot both problems and opportunities your spec never predicted.

When used well, Autocapture Raw Events in Userpilot help you spend less time wrestling with tracking code and more time answering the questions that actually move your product forward: Who’s getting value? Who’s stuck? And what can you change in the product experienceright nowto nudge more users into the “this is awesome” camp?

Final Thoughts

Autocapture Raw Events – Userpilot isn’t just a convenience feature. It’s a different way of thinking about analytics: capture rich user behavior by default, then carefully curate the events that matter most for your business.

Used thoughtfullywith governance, privacy, and clear goalsautocapture gives product, growth, and customer success teams the visibility they need to build truly user-centric experiences. Instead of forever guessing what users are doing inside your app, you can finally see it, measure it, and improve it.

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