Implementation Guide to Build LinkedIn Campaigns

If you’re looking to build your own LinkedIn sequence system, you’re in the right spot. This article is solely dedicated to implementing every required automation to smoothly run a sequence.

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Overall Architecture

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Requirements

• Follow the article Adding & Managing Users.
• Have a clear understanding of your data model.

To build campaigns, you need a combination of three stages, each with its own business logic:

1. Sequence Initialization:
   • Enrich the leads to send a sequence to.
   • Identify the lead’s connection degree with the user sending the sequence.
   • Schedule connection requests.
2. Detect Accepted Connection Requests:
   • This process is scheduled on Captain Data and repeats at a frequency of your choice (recommended: every 3 hours).
   • Detect connection requests that have been accepted.
3. Sequence Running:
   • Logic for sending messages and detecting replies.

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Prerequisites

Before starting, ensure the following:

• The LinkedIn account of the user sending the sequence is connected.
• You have access to the LinkedIn profile URL of the leads for the sequence.

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Schemas Legend

Here's the schemas legend for future explanations.

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Sequence Initialization

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Connection Degree

Determine the connection degree between your user and the leads to interact with. Based on this information:

• Schedule connection requests using Connect LinkedIn Profile.
• Move leads to the next step.

Sequence Init Process

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Extract Your User’s Connections & Detect Accepted Requests

You need to identify when connection requests are accepted using Extract LinkedIn Connections. Regularly extract net new LinkedIn connections of the end-user and compare them with leads to engage.

• Frequency: Every 3 hours.
• Parameter: max_minutes=180 in concordance with your repeat frequency, here 180 minutes for 3 hours, to ensure you only get new connections.

Repeat Logic Process

Use this JSON body payload when launching a Run (Job):

{
  "job_name": "Fetch New Connections",
  "steps": [
    {
      ... "parameters": { "max_minutes": 180 },...
    }
  ],
  "repeat_option": {
    "type": "hour", // minute/hour/day/week/month
    "value": 3  // Must be an integer representing the interval
  }
}

Here is the Launch a Workflow API Reference to help you.

Using the Extract LinkedIn Connections workflow, sync connections every 3 to 6 hours. This approach ensures a balance between efficiency and adhering to LinkedIn’s limits.

Some Key Points:

• Account limits: Each account can add up to 100 new connections per week (default batch is 25/day, sending 5 requests every 30 minutes).
• Pagination: Returns 40 connections per page.
• Timing: Extracting connections multiple times daily optimizes results.

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Sequence Running Process

Sequence Running Process

This process is triggered when a connection request has been accepted. You then:

1. Send a LinkedIn message using Message LinkedIn Profile.
2. Detect replies by setting the check_reply parameter to true, see Message LinkedIn Profile full documentation.

You can easily fetch all conversations and messages to leverage within your product. We recommend using the following automated Action:

• Extract LinkedIn Conversations
• Extract LinkedIn Messages

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Additional Features

Some users add profile visits to their sequences. This can also run as a stand-alone process:

1. Launch Workflow for Profile Visit.
2. Await success webhook.
3. Get results.
4. Update your data model to track the visit action as part of the campaign report.

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Data Models

Light Data Model

In the lighter version above, all attributes are attached to the Leads and everything is managed from this table. This is an ideal implementation:

Ideal Data Model

The following data model is recommended for organizing leads:

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Connections

You should probably centralize connections, as there’s a high probability that User A has similar connections to User B.

• We recommend creating a join between Users and Connections, as described in UsersConnections.
• Not doing this means handling duplicates. Since a user can have up to 30,000 connections, this can quickly become a burden for your database.
• Don’t forget to save and add the connected_at attribute to know when both accounts connected.

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Actions APIs to Use

• Extract LinkedIn People Profile
• Visit LinkedIn Profile (optional)
• Connect LinkedIn Profile
• Message LinkedIn Profile
• Extract LinkedIn Connections
• Extract LinkedIn Conversations
• Extract LinkedIn Messages
• Enrich LinkedIn User Contact Information (optional)
• Withdraw LinkedIn Pending Invitations (optional)
• Like LinkedIn Post (optional) It could be interesting to like posts on behalf of users in an ABM campaign.

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Best Practices

1. Validate LinkedIn URLs:

   • Ensure profile URLs follow the pattern linkedin.com/in/.
   • Ensure company URLs follow the pattern linkedin.com/company/.

2. Differentiate IDs:

   • Track linkedin_profile_id for leads (immutable).
   • Save sales_navigator_profile_id to trigger automations and regenerate URLs.

3. Pending Requests:

   • Track if a request exceeds 20 days.
   • Withdraw pending invitations to unclutter sent invitations.

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Data Attributes for Reporting

To give your users a great experience, we recommend keeping track of the following:

Let us know if you have specific needs or additional features to implement!