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:
- Add Intercom as a Stitch data source
- Define the Historical Sync
- Define the Replication Frequency
- Authorize Stitch to access Intercom
Add Intercom as a Stitch Data Source
- On the Stitch Dashboard page, click the Add an Integration button.
-
Click the Intercom icon.
-
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.
- Enter your Intercom credentials and click Login.
- A screen asking for authorization to Intercom will display. Note that Stitch will only ever read your data.
- Click Connect.
- After the authorization process successfully completes, you’ll be redirected back to Stitch.
- 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
admins
table contains about the admin users in your Intercom account.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
companies
table contains info about the companies that use your Intercom product.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
company_segments
table contains info about company segments.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
conversations
table contains info about user conversations, or conversations initiated by your end-users.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
leads
table contains info about the logged-out users of your Intercom app. This was formerly the contacts/contact
object.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
segments
table contains info about the segments - or groups of users defined by a set of rules - in your Intercom account.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
tags
table contains info about the tags in your Intercom account.users
Replication Method: Incremental
Primary Key: id
Contains Nested Structures?:
Yes
users
table contains info about the users in your Intercom account.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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