The Reddit comments scraper for full discussion threads
Pull the full comment thread for any Reddit post.
Kavex's Reddit comments scraper exports the entire comment thread of any Reddit post into a spreadsheet. The comments under a post are where the real conversation happens, the recommendations, the counterarguments, the verbatim customer language a search result alone never shows. You give a list of Reddit post URLs, and Kavex returns every comment with its author, full text, score, nesting depth and timestamp. It is built for researchers analysing a discussion, content teams pulling quotes, and growth teams reading exactly how people talk about a topic before they reply.
A RUN OF 1,000 COMMENTS ON THIS SOURCE, AT 1 PER COMMENT
Say what you want. Read the price first.
Everything else is a ceiling or a filter. The estimate moves with the numbers you type, so the run never surprises you at the end.
Provide Reddit post URLs, one per line. For each post Kavex walks the comment tree and returns every comment with the author, full comment text, score, the reply depth (so you can see what replies to what) and the timestamp it was posted.
Paste your Reddit post URLs on the configure page, set how many comments to pull per post, and run. Kavex walks each thread for you, including nested replies. Use the Reddit Search scraper first to build the list of posts worth reading.
Charged per delivered row. If the source holds fewer than you asked for, the rest of the credits go back to your balance the second the run ends.
One thousand comments, itemised.
The base run, then every add-on as its own line. Nothing is bundled, so you can read the bill from top to bottom.
| Line | Rate | Units | Credits |
|---|---|---|---|
| Reddit Comments | 1 / comment | 1,000 comments | 1,000 |
| +Review sentiment | 0.5 / review | 1,000 reviews | 500 |
| 1,000 enriched comments | 1.5 / comment | 1,500 credits | $1.50 |
$0.0015 PER FINISHED COMMENT · AN ADD-ON IS BILLED ON THE ROWS IT ACTUALLY ENRICHED, SO A REAL BILL LANDS UNDER THIS
What people point it at.
Four ways this source is used today. Every one of them is the same run, the same export and the same credit pool.
- Discussion analysis, read every reply on a thread in one spreadsheet
- Pulling verbatim customer quotes for research or content
- Sentiment analysis on the conversation under a launch or review post
- Finding the most upvoted answers and recommendations in a thread
The rest of the social stack.
Same credit pool, same export. Chain the output of one run into the next without paying for the list twice.
Asked before the first run.
Short answers, no accordion to click through. If something is still missing, the help pages go deeper.
Does it include nested replies?
Yes, Kavex walks the full comment tree and the depth column tells you how deeply nested each reply is, so you can reconstruct the conversation.
How many comments does it pull per post?
You set a per-post limit on the configure page; Kavex returns the comments up to that limit, prioritising the top of the thread.
How fresh is the data?
Every scrape is live, you get the comments exactly as they stand on the post at run time, not a cached copy.
Where do I get the post URLs?
Paste them directly, or run the Reddit Search scraper first, its post_url column feeds straight into this scraper.