Data Overview
Intercom provides rich customer communication data across multiple entities. Depending on the report type you select, you can access everything from individual contacts and their conversation history to support tickets, company information, and team structures.
Report types and entities
List of conversations
Tracking customer interactions
Conversation ID, participant details, message count, created/updated dates, status
List of tickets
Support team analytics
Ticket ID, status, priority, assigned team/admin, created/updated dates, customer details
List of contacts
Customer segmentation and analysis
Contact ID, email, name, phone, company, custom attributes, created/updated dates
List of companies
Account-based analytics
Company ID, name, industry, employee count, custom attributes
List of articles
Content performance
Article ID, title, status, publish date, content type
List of teams
Team management and assignment tracking
Team ID, name, admin assignments, member count
List of segments
Audience targeting
Segment ID, name, contact count, criteria
Conversations data
Key metrics
Conversation count
Total number of conversations
Average messages per conversation
Message volume per interaction
Conversations by status
Open, closed, or snoozed
Messages from contacts vs admins
Inbound vs outbound message ratio
First response time
Time from customer message to first admin reply
Key dimensions
Conversation status
Open, closed, snoozed
Customer email/name
Identifier of the contact
Team assigned
Which team is handling the conversation
Created date
When the conversation started
Updated date
Last activity timestamp
Participant type
Admin, contact, or system
Tickets data
Key metrics
Ticket count
Total open, closed, or in-progress tickets
Tickets by priority
High, normal, low priority breakdown
Tickets by status
Status distribution (e.g., open, resolved, pending)
Average resolution time
Time from creation to closure
Tickets assigned per admin
Workload distribution
Key dimensions
Ticket status
Open, in-progress, closed, pending
Ticket priority
High, normal, low
Assigned team/admin
Who owns the ticket
Customer email/name
Ticket creator
Created date
When the ticket was opened
Updated date
Last status or comment change
Ticket type
Type classification
Contacts data
Key metrics
Total contacts
All unique contacts in your workspace
Contacts by company
Breakdown by associated company
Contacts by segment
How many contacts in each segment
Contacts with conversations
Contacts who have engaged
Key dimensions
Contact email address
Name
Contact full name
Phone
Contact phone number
Company
Associated company name or ID
Custom attributes
Any custom fields you've defined
Created date
When the contact was added
Updated date
Last profile update
Signed up date
When they became a customer
Common metric combinations
Here are ways to combine Intercom data for powerful insights:
Support efficiency: Join tickets with teams to calculate average resolution time and ticket load per team
Customer engagement: Combine contacts with conversations to identify your most active customers
Help center performance: Link articles to company data to see which knowledge base content is most relevant to your audience
Team workload: Append ticket and conversation data from different teams to compare support volume
Use cases by role
Track team performance and customer satisfaction.
Export your tickets and conversations to Looker Studio to build a real-time dashboard showing:
Ticket volume by status and priority
Average resolution time per team
Admin workload and response times
Conversation trends over time
Use advanced filters to focus on specific teams, time periods, or ticket types. Aggregate your data to calculate metrics like first response time or customer satisfaction trends.
Understand customer feedback and engagement patterns.
Export conversations and contacts to analyze:
Which features customers ask about most
Customer sentiment in conversations (especially with AI analysis via Claude or ChatGPT)
Active segments and their engagement levels
Common support topics by company or industry
Join contact and conversation data to identify your most engaged customers and track their journey.
Use Intercom data to improve messaging and targeting.
Pull contacts and segments into Google Sheets or BigQuery to:
Segment customers by engagement (conversation count, ticket frequency)
Identify upsell or renewal opportunities based on ticket patterns
Track how often key segments contact support
Analyze help center article performance to inform content strategy
Append multi-workspace data to get a unified view of all customer interactions.
Build comprehensive customer communication dashboards.
Stream all Intercom data to BigQuery or your data warehouse:
Combine conversations, tickets, and contacts for 360-degree customer view
Track support metrics (volume, resolution time, team performance)
Analyze help center usage and content performance
Create custom segments based on interaction patterns
Use joins and aggregations to calculate derived metrics like "conversations per contact" or "average tickets per company."
Platform-specific notes
Conversations timeout: Large conversation datasets (especially with full message history) can exceed the 9-minute import limit. Use date filters to pull data in smaller chunks (e.g., weekly or daily) and append them together.
Ticket searching: The "List of tickets" report allows advanced filtering—use it to narrow results by status, priority, or assigned team before importing.
Custom attributes: Both contacts and companies support custom data attributes. These appear as columns in your export and can be used for advanced filtering.
Date macros: For "created after," "created before," "updated after," and "updated before" filters, you can use macros like
{{30daysago}}or{{today}}to automate date ranges.Message history: Conversation exports include full message threads, which increases data size. If imports are timing out, consider using date filters to pull conversations in smaller batches.
Company associations: Contacts can be linked to companies; conversations and tickets may also reference company data depending on your setup.
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