Hey Thijs! Thanks for sharing✨. There are two options to approach this:
Option 1: Using Two/Three Phantoms
* Use the first Phantom to extract your posts. This will include the post snippet, post URL, post date, and other associated fields.
* Use the second Phantom to extract comments and likes. This will capture the post URL, comment text, full name, LinkedIn URL, reaction type, and comment date.
Once both tables are configured, add a Lookup integration in the second table to pull post text and date from the first table if needed. The Lookup will match based on the post URL and retrieve the associated data if a match is found. Here's a quick guide on using Lookup: https://www.loom.com/share/ad767e3be9914d19a2f6647efe4dfa85?sid=c8b78c32-9bc1-4501-8124-d6c70d2218cf
Option 2: Using an Apify Scraper
* Use an Apify scraper that combines all the data fields mentioned in a single export action. This eliminates the need for multiple tables.
Here's an example: https://apify.com/curious_coder/linkedin-post-search-scraper
This scraper can retrieve post content, date, comments, likes, profile URLs, full names, and the comment date. The engagement date (for comments) will be in Unix format, but you can normalize it with a formula in your Clay table.
Here's a quick guide on using Apify: https://www.clay.com/university/lesson/deep-dive-apify-actors-limitless-research
Let me know if you have any questions about setting up either option! 😊
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