Insights: Visualize Trends and Compositions
Insights is a powerful and flexible tool designed to visualize trends and compositions within your data. Analyze events, cohorts, and user profiles, and display the data in a wide variety of chart types.
Use Cases
Insights helps you answer critical questions about your product and users:Product Analytics
- How is my WAU changing over time?
- How often are users getting value from my product?
- What is the distribution of users across regions or devices?
- How do power users behave differently from other users?
B2B Analytics
- How many messages were sent in the US in the past 30 days?
- How many users had a mobile app session yesterday?
- How many messages are sent per session?
- How much revenue was generated from plans purchased this year?
- How has the power users cohort grown over the past 6 months?
Marketing Analytics
- Which advertising campaigns generate the most checkouts?
- What channels drive the highest engagement?
- How do different user segments respond to campaigns?
Frequency Analysis: Understanding user engagement frequency is crucial. The majority of your users might use your product daily, weekly, or monthly. Learn about the Power User Curve to analyze engagement patterns.
Quick Start
Building an Insights report takes just a few steps. Let’s build a report to answer:How many users signed up from different cities on iOS in the last 30 days?
Step 1: Select Events
Events are the basic building blocks of analysis. Click Select Metrics and choose the events you want to measure.
For this example, select the “Sign Up” event.
You can save behaviors you build and reuse them in other reports. Learn more about Saved Metrics and Behaviors.
Step 2: Choose Measurement
Decide how to measure your selected events. By default, Insights measures unique users who performed the event.
Common Measurements:
- Total Events - Count all event occurrences
- Unique Users - Count unique users who did the event
- DAU/WAU/MAU - Daily, weekly, or monthly active users
- Event Property Sum - Total of a numeric property
- Event Property Average - Average of a numeric property
Step 3: Add Filters
Filters exclude unwanted data. For this example, add an “Operating System” filter where OS equals “iOS”.
Filter Types:
- Event properties (e.g., Platform = “iOS”)
- User properties (e.g., Country = “United States”)
- Cohorts (e.g., “Power Users”)
Step 4: Apply Breakdowns
Breakdowns segment data into groups. Add a “City” breakdown to see signups by city.
Breakdown Options:
- Event properties
- User profile properties
- Cohorts
- Custom properties
Step 5: Choose Visualization
Select the chart type that best displays your data:
Available Charts:
- Line Chart - Trends over time
- Bar Chart - Compare values across segments
- Pie Chart - Show composition percentages
- Table - View precise values
- Metric - Display a single key number
Chart Types
Insights offers multiple visualizations optimized for different analysis needs:Time-Segmented Charts
These charts show data broken down by time intervals:- Line Chart - Best for trending data over time
- Stacked Line Chart - Compare multiple metrics or segments
- Column Chart - View discrete time periods
- Stacked Column Chart - See composition changes over time
Period-Aggregate Charts
These charts show totals across the entire selected period:- Bar Chart - Compare segments or metrics
- Stacked Bar Chart - Show composition by segment
- Pie Chart - Visualize percentage distribution
- Metric Chart - Highlight a single key number
- Table Chart - View precise values and comparisons
Key Features
Formulas
Create calculated metrics using simple arithmetic operators:
Supported Operators:
+Addition-Subtraction*Multiplication/Division()Parentheses for order of operations
Save Formulas: Enterprise and Growth plan users can save formulas for reuse across reports. This ensures consistent metric definitions across your organization.
Time Period Comparisons
Compare current data to previous periods to track growth and trends:
Compare To:
- Previous period (e.g., last week vs this week)
- Previous year (year-over-year growth)
- Custom date range
When comparing to previous years, data points falling on weekends are automatically moved to the next Monday for clearer comparison.
Custom Bucketing
Group high-cardinality segments into meaningful ranges:
Bucket Types:
- Even Buckets - Uniform size ranges
- Varied Buckets - Custom ranges for detailed analysis
Profile Analysis
Analyze user profiles based on their properties rather than events: Example Queries:- What’s the total revenue across all users?
- What’s the average age of our user base?
- How many users are in each country?
- What’s the distribution of subscription plans?
View Users
Click any data point to see the actual users behind the numbers:- View a list of users contributing to that segment
- Save user lists as cohorts
- Export for further analysis
- Understand individual user journeys
Measurements Reference
Events
| Measurement | Description | Example |
|---|---|---|
| Total Events | Count of event occurrences | How many videos were watched? |
| Frequency per User | Events per user | How many videos per user? |
Users
| Measurement | Description | Example |
|---|---|---|
| Unique Users | Count of users who did event | How many users watched a video? |
| DAU | Daily active users (last 24 hours) | Daily video watchers |
| WAU | Weekly active users (last 7 days) | Weekly video watchers |
| MAU | Monthly active users (last 30 days) | Monthly video watchers |
Property Aggregations
| Measurement | Description | Example |
|---|---|---|
| Sum | Total of property values | Total watch time (minutes) |
| Average | Mean of property values | Average video length |
| Median | Middle value | Median session duration |
| Minimum | Lowest value | Shortest video watched |
| Maximum | Highest value | Longest video watched |
| Distinct Count | Unique property values | Number of unique videos |
Advanced Features
Analysis Settings
- Rolling Average - Smooth out data noise by averaging over time windows
- Cumulative - Show running totals that increase over time
Dynamic vs Manual Segments
Control which segments appear in your report:- Dynamic Segments - Automatically show top N segments based on current data
- Manual Segments - Pin specific segments to always display
Annotations
Add notes to time-series charts to mark important events:- Product launches
- Marketing campaigns
- System changes
- External events
View Sample Events
Hover over any event to preview recent samples, helping you:- Verify you’re using the correct event
- Check which properties are available
- Understand event structure
Date Range Guardrails
To ensure fast query performance:- Hourly granularity - Maximum 31 days
- Daily granularity - Maximum 12 months
- All Events queries - Maximum 93 days
- Cohort queries - Maximum 93 time intervals
Real-World Examples
Example 1: Weekly Active Users by Platform
Query:- Event: Any Event
- Measurement: Weekly Active Users (WAU)
- Breakdown: Platform
- Date Range: Last 3 months
- Visualization: Line chart
Example 2: Average Session Duration
Query:- Event: Session End
- Measurement: Average of “Session Duration” property
- Filter: Country = “United States”
- Date Range: Last 30 days
- Visualization: Line chart
Example 3: Revenue by Marketing Channel
Query:- Event: Purchase
- Measurement: Sum of “Amount” property
- Breakdown: UTM Source
- Date Range: This month
- Visualization: Bar chart
Example 4: Product Stickiness
Query:- Metric A: DAU
- Metric B: MAU
- Formula: A / B
- Date Range: Last 6 months
- Visualization: Line chart
Tips for Effective Analysis
Start Simple: Begin with a basic query and add complexity incrementally. This helps you understand how each element affects your results.
Use Saved Metrics: Create saved metrics for KPIs used across multiple reports. This ensures consistency and saves time.
Explore Breakdowns: When you see unexpected trends, add breakdowns to understand which segments are driving the change.
Check Sample Data: Use “View Sample Events” to verify you’re analyzing the right events and properties.
Next Steps
- Learn about Saved Metrics and Behaviors
- Explore Funnels for conversion analysis
- Create Cohorts for user segmentation
- Build Boards to monitor key metrics