Release Status Released Availability Premium
Status Page Intercom Status Page Default Historical Sync 1 year
Whitelist Tables/Columns Unsupported/Unsupported Default Replication Frequency 30 minutes
Full Table Endpoints 4 Incremental Endpoints 4
Destination Incompatibilities None

Connecting Intercom

Connecting your Intercom data to Stitch is a four-step process:

  1. Add Intercom as a Stitch data source
  2. Define the Historical Sync
  3. Define the Replication Frequency
  4. Authorize Stitch to access Intercom

Add Intercom as a Stitch Data Source

  1. On the Stitch Dashboard page, click the Add an Integration button.

  2. Click the Intercom icon.

  3. Enter a name for the integration. This is the name that will display on the for the integration; it’ll also be used to create the schema in your data warehouse.

    For example, the name “Stitch Intercom” would create a schema called stitch_intercom in the data warehouse. This schema is where all the tables for this integration will be stored.

Defining the Historical Sync

The Sync Historical Data setting will define the starting date for your Intercom integration. This means that data equal to or newer than this date will be replicated to your data warehouse.

Change this setting if you want to sync data beyond Intercom’s default setting of 1 year. For a detailed look at historical syncs, check out the Syncing Historical SaaS Data article.

Define the Replication Frequency

The Replication Frequency controls how often Stitch will attempt to replicate data from your Intercom integration. By default the frequency is set to 30 minutes, but you can change it to better suit your needs.

Before setting the Replication Frequency, note that:

  • The more often Intercom is set to replicate, the higher the number of replicated rows.

  • The number of rows in the source may not equal the number of rows replicated by Stitch. Tables that use Full Table Replication will result in a higher number of replicated rows.

  • Some or all of the tables in Intercom have an attribution window. This means that during every replication job, the past 30 days’ worth of data will be replicated. See the Replication section below for more details.

  • If you’re using a data warehouses that doesn’t natively support nested structures, you’ll see a higher number of replicated rows due to the de-nesting Stitch performs.

To help prevent overages, we recommend setting the Replication Frequency to something less frequent - like 6 hours instead of 30 minutes. For tips on reducing your row count, check out the Reducing Your Row Count section of our Billing Guide.

After selecting a Replication Frequency, click Save Integration.

Authorizing Stitch to Access Intercom

Lastly, you’ll be directed to Intercom’s website to complete the setup.

  1. Enter your Intercom credentials and click Login.
  2. A screen asking for authorization to Intercom will display. Note that Stitch will only ever read your data.
  3. Click Connect.
  4. After the authorization process successfully completes, you’ll be redirected back to Stitch.
  5. Click All Done.

Intercom’s Intial Sync

After you finish setting up Intercom, you might see its Sync Status show as Pending on either the Stitch Dashboard or in the Integration Details page.

For a new integration, a Pending status indicates that Stitch is in the process of scheduling the initial sync for the integration. This may take some time to complete.

Replicating Intercom Data

Every time Stitch runs a replication job for Intercom, the last 30 days’ worth of data will be replicated for these tables:

  • companies

  • company_segments

  • conversations

  • users

Stitch replicates data in this way to account for updates made to existing records within the default attribution window of 30 days, thus ensuring you won’t make decisions based on stale (or false) data. As a result, you may see a higher number of replicated rows than what’s being generated in Intercom.

Setting the Replication Frequency to a higher frequency - like 30 minutes - can result in re-replicating recent data and contribute to high row counts. Syncing fewer tables or selecting a lower frequency can help prevent overages.

Intercom Schema

Stitch's Intercom integration includes these tables:


admins

Replication Method: Full Table
Primary Key: id
Contains Nested Structures?: No

The admins table contains about the admin users in your Intercom account.

Table Info & Attributes

admins Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Admin ID (id)

  • type

  • name

  • email

companies

Replication Method: Incremental
Primary Key: id
Contains Nested Structures?: No

The companies table contains info about the companies that use your Intercom product.

Table Info & Attributes

Replication & Attribution Windows

Every time a replication job runs for Intercom, the past 30 days' worth of data will be replicated for this table. As a result, you may see a higher number of replicated rows than what's being generated in Intercom.

Stitch replicates data in this way to account for updates made to existing records within Intercom's default attribution window, thus ensuring you won't make decisions based on stale (or false) data.

companies Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Company ID (id) - This is the Intercom-defined ID.

  • type

  • created_at

  • remote_created_at

  • updated_at

  • company_id - This is the ID you’ve defined.

  • name

  • custom_attributes

  • session_count

  • monthly_spend

  • user_count

  • plan

company_segments

Replication Method: Full Table
Primary Key: id
Contains Nested Structures?: No

The company_segments table contains info about company segments.

Table Info & Attributes

Replication & Attribution Windows

Every time a replication job runs for Intercom, the past 30 days' worth of data will be replicated for this table. As a result, you may see a higher number of replicated rows than what's being generated in Intercom.

Stitch replicates data in this way to account for updates made to existing records within Intercom's default attribution window, thus ensuring you won't make decisions based on stale (or false) data.

company_segments Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Company Segment ID (id)

  • created_at

  • name

  • person_type

  • type

  • updated_at

conversations

Replication Method: Incremental
Primary Key: id
Contains Nested Structures?: Yes

The conversations table contains info about user conversations, or conversations initiated by your end-users.

Table Info & Attributes

conversations & Nested Structures

This table contains nested structures. If you use a data warehouse that doesn't natively support nested structures, some of the attributes listed below may be in a subtable.

These items are marked with a *

Conversation Parts

If the above applies to you, you may also see a conversations__parts subtable. This subtable contains the individual elements that make up a conversation.

To connect the conversation parts to the top-level table, use the composite key made up of the conversation ID and the row ID: _sdc_source_key_id:_sdc_level_0_id

Replication & Attribution Windows

Every time a replication job runs for Intercom, the past 30 days' worth of data will be replicated for this table. As a result, you may see a higher number of replicated rows than what's being generated in Intercom.

Stitch replicates data in this way to account for updates made to existing records within Intercom's default attribution window, thus ensuring you won't make decisions based on stale (or false) data.

conversations Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Conversation ID (id)

  • type

  • created_at

  • updated_at

  • conversation_message

  • conversation_parts*

  • user

  • assignee

  • open

  • read

  • tags*

leads

Replication Method: Incremental
Primary Key: id
Contains Nested Structures?: Yes

The leads table contains info about the logged-out users of your Intercom app. This was formerly the contacts/contact object.

Table Info & Attributes

leads & Nested Structures

This table contains nested structures. If you use a data warehouse that doesn't natively support nested structures, some of the attributes listed below may be in a subtable.

These items are marked with a *

leads Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Lead ID (id)

  • created_at

  • updated_at

  • user_id

  • email

  • email

  • phone

  • name

  • custom_attributes

  • last_request_at

  • avatar

  • unsubscribed_from_emails

  • location_data

  • user_agent_data

  • last_seen_ip

  • companies

  • social profiles

  • segments*

  • tags*

segments

Replication Method: Full Table
Primary Key: id
Contains Nested Structures?: No

The segments table contains info about the segments - or groups of users defined by a set of rules - in your Intercom account.

Table Info & Attributes

segments Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Segment ID (id)

  • type

  • name

  • created_at

  • updated_at

tags

Replication Method: Full Table
Primary Key: id
Contains Nested Structures?: No

The tags table contains info about the tags in your Intercom account.

Table Info & Attributes

tags Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • Tag ID (id)

  • type

  • name

users

Replication Method: Incremental
Primary Key: id
Contains Nested Structures?: Yes

The users table contains info about the users in your Intercom account.

Table Info & Attributes

users & Nested Structures

This table contains nested structures. If you use a data warehouse that doesn't natively support nested structures, some of the attributes listed below may be in a subtable.

These items are marked with a *

Replication & Attribution Windows

Every time a replication job runs for Intercom, the past 30 days' worth of data will be replicated for this table. As a result, you may see a higher number of replicated rows than what's being generated in Intercom.

Stitch replicates data in this way to account for updates made to existing records within Intercom's default attribution window, thus ensuring you won't make decisions based on stale (or false) data.

users Attributes

While we try to include everything Intercom has here, this may not be a full list of attributes. Refer to Intercom's documentation for a full list and description of each attribute.

  • User ID (id)

  • type

  • created_at

  • updated_at

  • signed_up_at

  • email

  • name

  • phone

  • custom_attributes

  • last_request_at

  • session_count

  • avatar

  • unsubscribed_from_emails

  • location_data

  • user_agent_data

  • last_seen_ip

  • pseudonym

  • anonymous

  • companies*

  • social_profiles*

  • segments*

  • tags*

Related Troubleshooting
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Tags: saas integrations