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Extract Sales Navigator Conversations

Sales Navigator Conversation Extractor extracts conversations from your Sales Navigator inbox.

POST/v1/actions/salesnavigator-extract-conversations/run/live

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Edges is not related to LinkedIn and is not an official LinkedIn product.

Input

Request parameters

FieldTypeRequired

cursorstringno

Cursor value obtained from the `X-Pagination-Next` response header of a previous request, used to continue pagination. Cursors expire after 24 hours. If a cursor has expired or is invalid, pagination must be restarted from the beginning.

page_sizeintegerno

Maximum number of results per page (read-only; defined by the endpoint, actual count may be lower in some cases like throttling or internal limits).

Configuration

FieldTypeRequired

categorystringno

Set category to choose which kind of conversations to extract.

Integration

FieldTypeRequired

identity_idsarrayyes

Array of identity UUIDs to use for the action

identity_modestringyes

Mode for identity handling: direct, auto, or managed.

Description

What Extract Sales Navigator Conversations does

Extract Sales Navigator Conversations pulls the list of conversations from your Sales Navigator inbox — counterpart, last message preview, timestamps, unread status — and returns each thread as a structured record. It mirrors Extract LinkedIn Conversations for the SN inbox.

Use it to treat the Sales Navigator inbox as a first-class data source: CRM sync, reply detection after InMail, or a triage pipeline.

How it works

Edges reads the Sales Navigator inbox through your connected SN session and returns thread records. Pair a thread URL with Extract Sales Navigator Messages when you need the full message history.

The action runs live through Edges infrastructure and is paced against upstream rate guidance. Inbox visibility matches the connected seat.

When to use Extract Sales Navigator Conversations

Use this to snapshot or poll the SN inbox — after InMail sequences, for unread triage, or to keep a CRM in sync with SN threads.

Typical chain: salesnavigator-inmail-profile → Extract Sales Navigator Conversations → webhook on new replies.

Use cases

Reply tracking after InMail: poll conversations and diff against the last snapshot.
CRM inbox sync so SN threads are visible next to email in the opportunity.
Unread triage for SDRs who should not live in the SN UI.
Reporting on conversation volume per seat.

Best practices

Schedule rather than tight live loops. Inbox extracts belong on async or scheduled runs with a callback.
Store thread IDs and only fetch messages for threads that changed.
Keep one SN identity per seat so conversation lists do not mix inboxes.
Use Extract Sales Navigator Messages for the thread body; this action is the inbox index.

Common questions

Does this return every message in each thread?

No. It returns conversation-level records. Use Extract Sales Navigator Messages with a thread URL for the full history.

Is this the same as Extract LinkedIn Conversations?

Same job, different inbox. LinkedIn DMs use linkedin-extract-conversations. Sales Navigator / InMail threads use this action.

Do I need a Sales Navigator seat?

Yes. The action reads the SN inbox on the connected identity.

Get started

Schedule Extract Sales Navigator Conversations against the SN identity that sends InMail, persist thread IDs, and compose with Extract Sales Navigator Messages from the library.

Request

curl -X POST "https://api.edges.run/v1/actions/salesnavigator-extract-conversations/run/live" \
  -H "X-API-KEY: <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
  "identity_ids": [
    "your-identity-uuid"
  ],
  "identity_mode": "direct",
  "parameters": {
    "category": "example_value"
  }
}'

Response

200 OK · application/json

[
  {
    "sales_navigator_thread_id": "example-123",
    "sales_navigator_thread_url": "https://www.linkedin.com/in/example-profile",
    "unread_count": 42,
    "read": true,
    "total_message_count": 42,
    "last_activity_at": "example_value",
    "status": "example_value",
    "participants": [
      1,
      2,
      3
    ],
    "last_message": {
      "key": "value"
    }
  }
]

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