Connect Intercom to Scoop to analyze your customer messaging data, track conversation trends, monitor response times, and understand customer engagement patterns.

AI-Assisted Setup

When connecting Intercom to Scoop, choose "Guide me with AI" for an intelligent, guided setup experience.

Available Analysis Templates

Template	Object	Data Mode	Best For	What You'll Analyze
Conversation Volume & Response (Default)	conversations	Snapshot	Support operations	Volume trends, response times, team assignments
Customer Engagement	contacts	Sync	User tracking	Activity patterns, engagement metrics
Company Revenue & Users	companies	Sync	Account analysis	MRR, user counts, company health
Support Team	admins	Sync	Team management	Team directory, availability
Tag Categories	tags	Sync	Organization	Tag inventory for categorization

Example Questions You Can Answer

Conversation Analysis:

"How many conversations were opened this week?"
"What's our average response time?"
"How many conversations are currently open vs closed?"
"Which channels generate the most conversations (chat, email, social)?"
"What's our conversation volume trend over time?"

Response Performance:

"How long are customers waiting for a response?"
"Which team has the best response times?"
"How many conversations are priority vs non-priority?"
"What's our median time to first response?"
"How does response time vary by channel?"

Customer Engagement:

"When were customers last active in our product?"
"How many users vs leads do we have?"
"Which customers haven't been contacted recently?"
"What's our email unsubscribe rate?"
"How does engagement vary by customer segment?"

Company Metrics:

"What's our total MRR across companies?"
"Which companies have the most users?"
"How does support volume correlate with company plan?"
"Which industries have the highest engagement?"
"What's our company growth trend?"

Need Something Different?

If the templates above don't match your needs, select "Something else" and describe what you want to analyze. For example:

"I want to track conversation tags to identify common issues"
"I need to see team workload by admin"
"I want to analyze response times by company plan"

Scoop's AI will recommend the right configuration for your specific use case.

Snapshotting for Conversation Analysis

Conversations change over time - they get assigned, snoozed, closed, and reopened. Configure your Conversations extract as a Snapshot dataset to:

Track conversation queue size over time
Monitor response time trends
Analyze how conversations flow through states
Compare support metrics day-over-day

Pro Tip: Enable snapshotting on day one for conversations. Customer success teams need historical data to identify trends in support volume and response times.

Connecting Intercom to Scoop

Create a new dataset in Scoop
Select Intercom from the application list
Select your data region (US, EU, or AU) if prompted
Authorize Scoop to access your Intercom workspace
Choose your analysis template or customize
Save and extract data

What Data You Get

Conversations (14 fields)

Customer support interactions and chats.

Field	Description
Conversation ID	Unique identifier (prefixed with IC)
Title	Conversation subject
State	open, closed, or snoozed
Is Open	Whether conversation is currently open
Is Read	Whether conversation has been read
Priority	priority or not_priority
Created Date	When conversation started
Updated Date	Last activity time
Waiting Since	Time since last customer response
Snoozed Until	When snoozed conversation will reopen
Source Type	Channel: conversation, email, twitter, facebook
Author Type	Type of user who started the conversation
Assignee ID	Admin assigned to conversation
Team ID	Team assigned to conversation
Tags	Conversation labels

Contacts (16 fields)

Customers and leads who interact with your product.

Field	Description
Contact ID	Unique identifier
External ID	Your system's user ID
Email	Contact email
Phone	Phone number
Name	Contact name
Role	user or lead
Created Date	When contact was created
Updated Date	When contact was last modified
Signed Up Date	When they signed up for your product
Last Seen Date	Last product activity
Last Contacted Date	When you last messaged them
Last Replied Date	When they last responded
Owner ID	Assigned admin
Hard Bounced	Whether emails to this contact have bounced
Unsubscribed	Email opt-out status
Tags	Contact labels

Companies (14 fields)

Customer organizations with revenue data.

Field	Description
Company ID	Unique internal identifier
External Company ID	Your system's company ID
Name	Company name
Plan	Subscription plan name
Monthly Spend	Monthly revenue from this company
User Count	Number of users at company
Session Count	Total sessions
Created Date	When company was created
Updated Date	When company was last modified
Last Request Date	Last activity date
Size	Company employee count
Industry	Business industry
Website	Company website
Tags	Company labels

Admins (7 fields)

Team members who handle conversations.

Field	Description
Admin ID	Unique identifier
Name	Team member name
Email	Email address
Job Title	Role/title
Away Mode	Whether admin is away
Away Reassign	Whether to reassign conversations when away
Team IDs	Teams admin belongs to

Tags (2 fields)

Labels for organizing conversations, contacts, and companies.

Field	Description
Tag ID	Unique identifier
Name	Tag name

Analysis Examples

Conversation Trends

Track conversation volume and performance:

Daily/weekly/monthly conversation volume
Open vs closed ratio over time
Response time trends
Channel distribution (chat, email, social)

Response Time Analysis

Monitor support speed:

Average/median response time
Time to first response
Waiting time distribution
Response performance by team

Customer Engagement

Understand user activity:

Active vs inactive users
Last seen distribution
Engagement by company segment
Lead vs user ratio

Revenue Insights

Analyze company metrics:

MRR by company
Users per company
Revenue concentration
Plan distribution

Best Practices

Start with Conversations: Core support metrics live here
Enable Snapshotting: Track support queue and response times over time
Combine with Companies: Blend conversations + companies for revenue-correlated analysis
Use Tags: Intercom tags help categorize conversations and customers

Intercom