LinkedIn Lead Generation & Data Enrichment with Make.com

# Features of this Lead Generation Workflow

In this guide, we'll show you a Make.com workflow that gathers leads from LinkedIn Groups and builds your database by extracting information from user profiles. Alternatively, you can extract Company Employees or profiles from LinkedIn Search results.

The final result is a Google Sheet containing all the collected data.

Having a large list of leads from a relevant field empowers you to:

• Enhance CRM Data Quality: Enrich existing LinkedIn profiles in your CRM with detailed user data, optimizing marketing strategies and maximizing ROI.

• Generate Personalized Outreach DMs: Target decision-makers to significantly enhance engagement rates and conversion potential for B2B companies.

• Conduct Market Research: Gain insights into market trends and customer preferences, enabling data-driven decisions that boost sales.

• Engage in Recruitment: Identify top talent in niche LinkedIn Groups, speeding up hiring processes and reducing costs.

• Perform Sales Prospecting: Create targeted prospect lists that align with your ideal customer profiles, improving deal closure rates.

Personalizing this HARPA GRID + Make.com automated workflow streamlines your processes and delivers measurable returns by optimizing lead generation, recruitment, and data management.

# Requirements:

1. LinkedIn account and membership in the group you want to scrape user data from.

2. Import these two commands from the Command Library:

   • LinkedIn Group Members Export - Exports up to 2,000 members from any LinkedIn group you belong to.

   • LinkedIn Profile Scraper - Scrapes all available data from LinkedIn profiles, including contacts, education, experience etc.

   Alternatively, replace the LinkedIn Group Members Export command with one of these:

   • LinkedIn Company Employees Export.

   • LinkedIn Search Results Export.

3. Complete the basic HARPA & Make.com setup:

   • Sign up for Make.com and install the official HARPA AI Web Browser Agent app.

   • Set up an active HARPA GRID Node.

   • Configure the HARPA API Connection in Make.com.

# Creating and Running a Scenario

1. Create a new scenario in Make.com

2. Click "+" and add a HARPA: Run AI Command module to your scenario

3. Configure your module:

• Select your connection and paste the command name LinkedIn Group Members Export. If you haven't downloaded it yet, you can get it here.

• Enter the command inputs, e.g.: enter "150" for the number of users and "DONE" to complete the command. You can test the command first to understand which inputs you need.

• Open your LinkedIn group's member list and copy the URL into the module. Group URLs usually look like: https://www.linkedin.com/groups/123456/members/

• Enter the parameter name that will store the user list. In our example, it's 'json'.

The default command timeout is set to 5 min or 3000000 ms. If you plan to extract a large number of profiles, increase this time based on your needs.

4. Run the module to check it.

   Tip: You can set "5" as the first input - this will make the command run faster while you continue building the scenario.

Once you get the data array results successfully, move on to the next step.

5. Let's add the next module - Iterator. This will help process each profile in the data array one by one.

6. In the Iterator settings, drag the array element containing our previous parsing results.

   Note: You need the full array containing all the data, not specific fields like link or name.

7. Add the HARPA: Run AI Command module to your scenario and configure it:

• Select your connection and paste the command name LinkedIn Profile Scraper. If you haven't downloaded it yet, get it here.

• Drag the "link" element from the previous module into the "URL" field. This means the Iterator will go through the data array, sending each Link to be processed by the HARPA AI Command.

• Enter the parameter name that will store user data. Use 'profile'.

8. Test your scenario to make sure all modules are working.

Once each module runs successfully one time, you can stop - no further testing is needed.

We now have a scenario that collects new LinkedIn leads and gathers data from their profiles. You can send this data to your Database, CRM, Google Sheets or other storage, and add more HARPA AI Commands to generate personalized DMs for each user.

9. Add the Google Sheets: Add a Row module. If you have never used Google Sheets with Make.com before, you need to create a connection.

10. Open your Google Drive and create a spreadsheet in Google Sheets to store the extracted data. Of course, it's possible to set up automatic creation of Google Sheets, but that would only complicate this explanation.

Name the Google Sheets file and add column headers in the first row: Name, URL, Location, Status, About, Experience, Education, Language, Contact.

11. Go back to Make.com and select your file by name in the Google Sheets module. Choose the Sheets page and drag data from the previous HARPA module into the appropriate columns for storage.

Your Lead Generation scenario is ready - you can now save and test it.