If you’re building a SaaS product and want to know how people are actually using it, you’ve probably been told to “track product adoption.” But most guides throw buzzwords around and leave you with a mess of charts that don’t help you make decisions. Here’s a no-nonsense guide to tracking product adoption in real time using Heap—with a focus on what actually works, what doesn’t, and how to keep your sanity.
Who’s This For?
- Product managers tired of guessing what’s working
- Growth folks who want real answers, not dashboards for their boss
- Engineers or analysts setting up Heap for the first time
- Anyone who doesn’t have a dedicated analytics team (and even if you do, you’ll want to understand this yourself)
What “Product Adoption” Actually Means
Let’s get clear about what you’re really after:
- Are people signing up?
- Are they using key features?
- Are they coming back?
- Are they getting value, or just poking around?
You want to know if users are moving from “new signups” to “regulars” to “power users.” That’s adoption. Don’t let anyone tell you it’s a single metric—it’s a progression.
Step 1: Get Your Heap Basics Right
First things first: if you haven’t already, create a Heap account and install their tracking snippet or SDK. Heap likes to brag that it “captures everything automatically,” and to be fair, it does grab most clicks, page views, and form submissions out of the box. But it won’t magically know what counts as “adoption” for your product.
What you actually need to do:
- Install Heap: Drop their snippet (or use their SDK for mobile). Don’t skip this; no data means no insights.
- Check data is coming in: Open Heap and watch the live data feed. Click around your app. If you see your actions show up, you’re good.
- Name key events: Don’t trust Heap’s auto-naming. Go in and label things clearly (“Clicked Upgrade,” “Completed Onboarding,” etc.). If you ignore this step, your reports will be a nightmare.
Pro tip: If you have anything behind feature flags, make sure those interactions are tracked. Heap can miss these if you’re not careful.
Step 2: Define Your “Adoption” Events
Here’s where most teams go wrong: they try to track everything and end up drowning in useless data. Focus on the core actions that mean someone’s actually using your product.
What to track (and what to ignore):
- Track: Sign up, finish onboarding, use a core feature (whatever your “aha moment” is), upgrade, invite a teammate.
- Ignore: Every single button click, scrolling, adjusting settings, or other trivia—unless those are core to your product.
How to do it in Heap:
- Go to “Events” and create new ones for each key action. Use clear, human names.
- Test each event. Do the action yourself and make sure it shows up.
- Bonus: group related events into “funnels” (like “Signup → Onboard → Use Feature”) to see dropoff.
Common pitfalls:
- Too many events: If you can’t explain why you’re tracking something, don’t.
- Vague event names: “Button Click” tells you nothing in six months.
Step 3: Build Real-Time Dashboards
Heap is pretty good at showing you stuff as it happens. But only if you set up dashboards that reflect real adoption, not just vanity metrics.
What to do:
- Create a dashboard called “Product Adoption (Real Time).”
- Add these widgets:
- New Signups (last hour/day)
- Onboarding Completion Rate
- Core Feature Usage (unique users, last 24h)
- Returning Users (7-day/30-day active)
-
Upgrade/Conversion Rate
-
Set refresh intervals to “real time” or as close as possible (Heap can show within a few minutes, but don’t expect second-by-second updates).
Pro tips:
- Filter by segment: New users vs. long-time users, or by plan type, so you don’t get skewed results.
- Don’t overcomplicate: Five to seven widgets max. More isn’t better.
Step 4: Make Adoption Funnels (and Actually Use Them)
Funnels in Heap let you see where people drop off between key steps. Set up a funnel for your main adoption path.
Example funnel:
- Sign Up
- Complete Onboarding
- Use Key Feature
- Return Within 7 Days
To set up:
- Go to Funnels in Heap.
- Add your named events as steps.
- Let Heap crunch the numbers.
What to look for:
- Big drop-offs: That’s where you’re losing people. Fix those spots first.
- Conversion rates: Don’t obsess over 1% changes; look for big gaps.
What not to do:
- Don’t try to build a funnel for every minor action. Stick to the big stuff that matters for adoption.
Step 5: Set Up Alerts (But Don’t Let Them Drive You Crazy)
Heap lets you set up alerts when metrics spike or drop. This is useful—until you get 20 emails a day and start ignoring them.
How to do it smartly:
- Set alerts for only the critical metrics (e.g., onboarding completion drops by 10%).
- Send alerts to a channel, not your personal inbox.
- Review alert rules every month. If an alert never fires or always fires, adjust it.
Avoid:
- Setting up alerts for vanity metrics (“Page Views Down!” means nothing if adoption is steady).
- Creating so many alerts you start ignoring them all.
Step 6: Don’t Fall for the “Real-Time” Trap
“Real time” is nice, but don’t kid yourself: you’re not going to make product decisions every five minutes. Use real-time data for:
- Spotting bugs or sudden drops
- Checking if a new feature is breaking things
- Getting early signals after a launch
But for meaningful adoption trends, look at daily or weekly data. Chasing minute-by-minute changes is a good way to stress yourself out and make knee-jerk decisions.
What Works, What Doesn’t, and What to Ignore
What Works
- Naming your events and funnels in plain English
- Focusing on 3-5 key adoption actions
- Using real-time data for launches or incident response
What Doesn’t
- Tracking everything “just in case”
- Relying only on out-of-the-box auto-captured events
- Overloading dashboards with noise
What to Ignore
- Vanity metrics (page views, random clicks)
- Micro-optimizing alert thresholds
- Over-customizing reports for every stakeholder
Keep It Simple, Iterate Often
You don’t need a perfect setup on day one. Start with a handful of clear events, build a dashboard you’ll actually check, and use funnels to spot real problems. If you’re not getting useful insights, strip things back. The best analytics setups are the ones you actually use, not the ones with the most bells and whistles.
Heap won’t magically solve adoption for you—but used well, it’ll show you what’s really going on, so you can spend your time fixing real problems, not just watching charts.