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Guide

Scraping and Lead Gen

Guides for scraping leads and building outreach lists.

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Public platforms like LinkedIn hold a large amount of intent signal in comments, posts, and profiles, but pulling that into a usable list takes a specific, careful approach. These guides cover practical scraping methods for lead generation, including where the line is on what is reasonable and sustainable to do.

Comments as an underused signal

People commenting on a post about a specific problem are telling you, in public, that the problem matters to them. That is a stronger signal than most cold lists you could buy.

Turning raw data into a usable list

Scraped data is only useful once it is cleaned and organized: names matched to profiles, duplicates removed, and irrelevant entries filtered out before outreach even starts.

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Frequently asked questions

Is scraping LinkedIn comments allowed?

Scraping public data carries platform risk and should be done carefully and at a reasonable pace. These guides focus on practical, lower risk approaches rather than aggressive automation.

What should I do with a list right after scraping it?

Clean it first: remove duplicates and irrelevant entries, then match names to context like their comment or post, which makes personalized outreach far easier.

Best practices

Filter before you outreach

Spend time removing obviously irrelevant entries from a scraped list before sending a single message. A smaller, clean list beats a larger, messy one.

Respect rate limits and platform rules

Scraping aggressively or too quickly risks account restrictions. A slower, steadier approach is more sustainable for ongoing lead generation.

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