Research a Sales Prospect's LinkedIn Engagement

Created by

Unseen User

Actor

LinkedIn User Comments & Reactions Scraper [NO COOKIES] ✅

Before you send a cold email, see what your prospect has actually been engaging with on LinkedIn. This task pulls every comment they wrote and every post they reacted to over the last three months, along with the original post and who published it. Use it to open with something they genuinely care about instead of a guess from their job title.

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LinkedIn User Comments & Reactions Scraper [NO COOKIES] ✅unseenuser/linkedin-user-comments-reactions

Type

Action

Comment

Source Profile

+15 fields

Input

LinkedIn Profiles(required):https://www.linkedin.com/in/justinwelsh

What To Collect:both

Time Period:3months

Output fields

Type

Action

Comment

Source Profile

Post Author

Post Text

Post URL

Reactions

Comments

Posted

Page

Comment URL

Engaged Date

Engaged Age

Post Date

Post Author Title

Post Author Profile

Post URN

Reposts

How it works

Sign up on Apify or log in

The LinkedIn User Comments & Reactions Scraper [NO COOKIES] ✅ Actor is ready to run with the inputs already set for "Research a Sales Prospect's LinkedIn Engagement". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Research a Sales Prospect's LinkedIn Engagement" task

The LinkedIn User Comments & Reactions Scraper [NO COOKIES] ✅ Actor will start running based on the input automatically. You can also change all the input fields, like linkedin profiles, what to collect, and more, to match your specific use case.

Receive the "Research a Sales Prospect's LinkedIn Engagement" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as type, action, comment, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Research a Sales Prospect's LinkedIn Engagement" task via API.