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Autumn’s analytics dashboard provides real-time insights into how customers are using your application. Track feature usage, analyze trends, and understand customer behavior patterns.

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Accessing Analytics

There are two ways to access analytics:
  1. Global Analytics: Navigate to the Analytics tab in the main sidebar to see organization-wide usage
  2. Customer Analytics: View customer-specific usage from any customer detail page
Analytics requires ClickHouse to be enabled in your organization. Usage events are tracked via the Autumn SDK or API.

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Understanding the Analytics View

The analytics page is divided into two main sections:

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Usage Chart

Visual representation of events over time:
  • Bar chart showing event volume by date
  • Customizable time intervals (day, week, month)
  • Group by properties for segmented analysis
  • Filter by event name or feature

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Events Table

Raw event data with detailed information:
  • Event names and timestamps
  • Customer IDs and properties
  • Custom event metadata
  • Pagination for large datasets

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Filtering Analytics Data

1

Select Time Range

Use the interval dropdown to choose your analysis period:
  • Last 7 days
  • Last 30 days
  • Last 90 days
  • Custom date range
Start with a 30-day view to identify overall trends, then narrow down to specific periods for detailed analysis.
2

Choose Events to Display

Click the event dropdown to select which events to analyze:
  • Select specific events by name
  • Choose feature-related events
  • View all events (may be limited for performance)
If no events are selected, the chart will be empty. Select at least one event to see data.
3

Set Bin Size

Control how data is grouped over time:
  • Day: Show daily usage patterns
  • Week: Identify weekly trends
  • Month: Track monthly growth
  • Hour: Analyze intraday patterns
Smaller bin sizes provide more granular detail but may show more noise.
4

Apply Grouping (Optional)

Group events by custom properties to segment your analysis:
  • Customer ID: See per-customer usage
  • Custom properties: Analyze by user role, plan type, region, etc.
  • Feature IDs: Compare usage across features
Grouping creates separate bars/lines for each unique value, making it easy to compare segments.

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Using Group By for Segmentation

Grouping reveals insights by breaking down events by dimensions:
1

Select Group By Property

Click the Group By dropdown to choose a property:
  • Properties are extracted from your event data
  • Common properties include: customer_id, plan, region, device_type
  • Only properties that exist in your events are available
2

View Grouped Chart

The usage chart now shows separate bars for each group:
  • Different colors represent different values
  • Legend shows all groups
  • Hover over bars to see specific values
If there are too many unique values (more than 10), the chart shows only the top 10 by volume, and a warning message appears.
3

Filter to Specific Group

Use the group filter dropdown to focus on a single value:
  • Only shows data for the selected group
  • Useful for drilling down into specific segments
  • Clear the filter to see all groups again

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Understanding Event Properties

Events can include custom properties that provide context:
  • Standard properties: customer_id, timestamp, event_name
  • Custom properties: Any additional data you send with events
  • Nested properties: Support for complex object structures
Send consistent property names across events to make grouping and filtering more powerful. For example, always use plan_id instead of mixing plan_id, plan, and subscription.

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Working with the Events Table

The raw events table shows individual event records:

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Table Features

  • Pagination: Navigate large datasets with page controls
  • Sorting: Click column headers to sort (where enabled)
  • Property columns: All event properties displayed as columns
  • Row details: Click rows for more information

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Adjusting Table View

1

Change Page Size

Use the page size dropdown to show more or fewer events per page:
  • 100, 500, or 1000 events
  • Larger page sizes load more slowly but reduce pagination
2

Navigate Pages

Use the pagination controls to browse through events:
  • First/Last page buttons
  • Previous/Next page arrows
  • Current page indicator shows your position
The events table shows total event count at the top. Use this to understand the scope of your data.

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Customer-Specific Analytics

View analytics for individual customers:
1

Open Customer Page

Navigate to Customers and select a customer.
2

Scroll to Analytics Section

The customer detail page includes a dedicated analytics section showing only that customer’s events.
3

Analyze Customer Usage

Use the same filtering and grouping tools, but scoped to the customer:
  • See which features they use most
  • Identify usage trends over time
  • Understand their engagement patterns
Customer analytics are helpful for:
  • Identifying power users
  • Understanding why customers churn
  • Finding expansion opportunities
  • Debugging customer-reported issues

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Common Analytics Workflows

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Tracking Feature Adoption

1

Filter to Feature Events

Select events related to a specific feature (e.g., feature_used, api_call).
2

Group by Customer

Set Group By to customer_id to see which customers use the feature.
3

Analyze Over Time

Use a 30 or 90-day interval to see adoption trends.

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Comparing Plan Usage

1

Set Up Grouping

Group events by plan or plan_id property (requires sending this with events).
2

Select Relevant Events

Choose events that indicate product usage.
3

Identify Patterns

Look for differences in usage between plan types to inform pricing strategy.

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Finding Inactive Customers

1

Set Long Time Range

Use a 30 or 90-day interval.
2

Review Customer List

In the events table, note which customer IDs are absent or have low event counts.
3

Take Action

Reach out to inactive customers or review their subscription status.

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Performance Considerations

Analytics queries can be resource-intensive. The dashboard implements several optimizations:
  • Event data is cached for faster repeat queries
  • Large result sets are paginated
  • Charts are limited to prevent performance issues
Query Optimization: Start with shorter time ranges and fewer events, then expand as needed. This keeps the dashboard responsive.

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Understanding Data Freshness

Analytics data updates in near real-time:
  • Events appear within seconds of being tracked
  • Charts refresh when you change filters
  • No manual refresh required
If you don’t see recent events, check that your application is correctly sending events to Autumn via the SDK or API.

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Empty States

If you see “No events found”:
  1. No events tracked yet: Start sending events from your application
  2. Filters too restrictive: Widen your date range or select different events
  3. ClickHouse disabled: Contact support to enable analytics
The dashboard shows an empty state with a link to documentation when no analytics events exist.

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Advanced Analytics Features

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Property Extraction

The dashboard automatically detects custom properties in your events and makes them available for grouping and filtering.

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Top Events

When you open the event selector, events are sorted by frequency, showing your most common events first.

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Data Truncation Warning

If a grouping has too many unique values (>10), you’ll see a toast notification. The chart shows only the top 10 by volume to maintain performance.

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Best Practices

Consistent Event Names: Use clear, consistent naming conventions for events (e.g., feature_accessed, api_call_made).
Meaningful Properties: Send useful context with events like plan type, user role, or feature ID to enable rich segmentation.
Regular Monitoring: Check analytics weekly to catch trends early and identify issues before they impact many customers.
Analytics data is stored in ClickHouse, a high-performance analytics database designed for fast queries on large datasets.

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Exporting Data

While the dashboard doesn’t have a direct export button, you can:
  • Use the API to fetch raw event data
  • Query ClickHouse directly if you have access
  • Take screenshots of charts for reports
  • Copy event data from the table view

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Next Steps

  • Learn how to send events from your application using the Autumn SDK
  • Set up custom properties for richer analytics
  • Create automated reports using the API
  • Monitor feature usage to inform product development
Combine analytics insights with invoice data to understand the relationship between usage and revenue.

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