This guide walks through how to use Product Adoption Insights to answer common product questions. It assumes you've already set up No-code Event Tracking and have events firing. If you haven't done that yet, start there.
Common questions PAI can answer
Where are users dropping off in my onboarding flow?
Which plan tier has the highest feature activation rate?
How many users completed [key action] in the last 30 days?
Which users haven't activated a core feature yet?
How did my product change affect engagement?
Which tool to use
Question type | Use this |
|---|---|
"How many users did X over time?" | Chart Builder — Usage Analysis |
"Where do users drop off in a process?" | Chart Builder — Funnel Analysis |
"How does behavior differ between segments?" | Chart Builder + Group By |
"I want to monitor several metrics at once" | Dashboards |
"I want to target users who did/didn't do X" | No-code Event Tracking → Flow conditions |
Answering "where do users drop off?"
Use Funnel Analysis for drop-off questions.
Go to Charts and click Create chart.
Select Funnel analysis.
Add each step in the user journey as a separate step in the funnel. Example: Step 1 = "Signed up" event, Step 2 = "Created project" event, Step 3 = "Invited teammate" event.
Set your time range using the global filter.
Read the % Step Drop-off column to see where the largest loss happens.
What to do with drop-off data:
A high drop-off at Step 1→2 suggests friction immediately after sign-up. Check whether your onboarding flow is targeting the right users.
A high drop-off mid-funnel often points to a specific feature or step that's confusing. Use Userflow Flows to add guidance at that point.
Export the users who dropped off at a specific step (hover right of the step → export icon → Export users as CSV) to follow up directly.
Answering "which segment performs best?"
Use Usage Analysis with Group By.
Create a Usage Analysis chart for the event you want to analyze.
In the chart configuration panel, click Group By.
Select the attribute to segment by — for example, Plan Type, Company Size, or Region.
The chart splits into separate lines/bars for each attribute value.
Tips:
Group By shows up to the top 10 values by volume. Remaining values appear as "Other."
Combine Group By with a global filter to narrow your dataset first.
Building a monitoring dashboard
Go to Dashboards and click Create dashboard.
Give your dashboard a name (e.g., "Onboarding Health" or "Feature Adoption — May 2026").
Click Add chart and select existing charts to add.
Arrange and resize charts by dragging.
Share the dashboard URL with teammates who need visibility.
Troubleshooting: why is my chart empty?
No data is appearing:
Check that the event you're tracking is actually firing. Go to a user's profile and check their event history to confirm the event name matches exactly (case-sensitive).
Verify the time range — charts default to the last 30 days.
Confirm your No-code Event Tracker is published in Production (not just Staging).
Group By shows only one segment:
The user profiles in your dataset may not have the attribute you're grouping by.
Funnel shows 0% completion at step 2+:
Verify the event names for each step are correct and distinct.
Common ways customers use Product Adoption Insights
Beyond answering one-off questions, most teams settle into a handful of recurring patterns that compound in value over time. Each follows the same loop: Capture the right events, Visualize the data in a chart or dashboard, and Act on what you find with a Userflow Tour, Checklist, or targeted Flow.
Activation funnel for new signups
Capture: Set up no-code event trackers on each milestone in your activation path — for example, Account Created → Profile Completed → First Project → First Invite. Use the same event names across the funnel so segments stay comparable.
Visualize: Build a Funnel Analysis chart in Chart Builder using those events as the steps. Pay closest attention to the step with the largest drop-off — that's where most signups stall.
Act: Target a Tour or Checklist at users who reach a step but don't complete the next one. The goal isn't to nudge everyone — it's to surface the next action only for the segment that needs it.
Feature adoption rate by plan tier
Capture: Add a no-code event tracker on the primary action of the feature you want to measure (the action that proves real use — not just a page view).
Visualize: In Chart Builder, create a Usage Analysis chart and apply Group By on company_plan (or whichever attribute holds the plan tier). You'll see adoption broken out by tier, which often reveals that lower tiers either don't know the feature exists or don't have the use case.
Act: Build plan-specific guidance for the tiers with low adoption — an announcement, a Tour scoped to that segment, or a Resource Center item conditional on the plan attribute.
Engagement decay detection
Capture: Track routine actions that signal a healthy active user — a dashboard visit, a core report opened, a record created. Pick actions that real users perform regularly, not edge-case clicks.
Visualize: Create a usage trend chart on that event over a 30-day rolling window. Use Group By on a cohort attribute (signup month, plan, or company size) to spot which segments are decaying fastest.
Act: Set up a re-engagement Tour or in-app message targeting users whose activity has dropped below a healthy threshold. Catching decay early is far cheaper than win-back after churn.
Each of these patterns uses Capture → Understand → Find Friction → Action — the same workflow described in the "Product Adoption Insights" overview. Start with one pattern, prove the loop, then add others.