Reddit's 100M+ daily active users generate some of the most authentic, unfiltered consumer feedback on the internet. Unlike Twitter posts or TikTok comments — which are short and performative — Reddit threads run deep, with users discussing products, brands, and tools in detail across nested reply chains.
For market research, brand monitoring, sentiment analysis, or even just preserving a thread before it gets deleted, you need a way to pull every comment out as structured data. This guide covers how to do that in seconds, plus what the alternatives look like.
What you'll get in the CSV
- Comment body (with Markdown preserved or cleaned, your choice)
- Author username
- Upvote score (net of downvotes)
- Award count and gilded status
- Parent comment ID — lets you rebuild the full reply tree in Excel
- Depth (top-level = 0, reply-to-reply = 2, etc.)
- Comment posted timestamp
- Comment permalink (jumps straight to it on reddit.com)
- Edited flag and moderator/OP flags
- Subreddit and original post ID
That's everything visible on the thread itself, captured in a structure that's analysis-ready.
The 60-second method: ZocialComment
The fastest way is a free browser tool. No signup, no developer account, no Python.
Step 1 — Grab the thread URL
Any of these formats work:
https://www.reddit.com/r/{subreddit}/comments/{id}/{slug}/https://old.reddit.com/r/{subreddit}/comments/{id}/...https://www.reddit.com/r/{subreddit}/s/{shortcode}(mobile share links)https://redd.it/{id}(shortened)
The exporter resolves short links automatically to the canonical thread URL before fetching.
Step 2 — Paste and export
Open zocialcomment.com/export/reddit, paste the URL, click Export Comments. The tool walks the thread, including nested replies, and counts what's available.
Step 3 — Download as CSV or JSON
Once processing finishes you can download as CSV (one row per comment, denormalized with parent-id references) or JSON (preserves the nested reply tree natively — better for code).
What about PRAW (the official Python Reddit API)?
PRAW is the official Python wrapper for Reddit's API. It's well-documented and works fine, but:
- You need to register an app with Reddit to get a client ID and secret.
- You need to write code — at minimum 30–50 lines to handle MoreComments expansion (Reddit lazy-loads deep reply chains and PRAW has to "unfold" them with extra requests).
- Since the 2023 API changes, free tier limits are 100 queries per minute per OAuth client — fine for small threads, but big ones with 10k+ comments take a while.
- You still have to write the CSV serialization yourself.
If you're a developer building automation, PRAW is the right answer. For a one-off CSV export, it's overkill.
Why Pushshift is no longer an option
For years, Pushshift was the go-to historical archive for Reddit data. It's gone now — Reddit shut down third-party access during the 2023 API price hike. The remaining mirrors are spotty, often missing recent posts, and not suitable for current research.
If you need historical Reddit data for academic research, academic dumps are available via Academic Torrents, but they require terabytes of disk space.
Apify and other browser-scraper alternatives
Apify offers a Reddit Scraper actor priced at ~$0.50 per 1,000 results. It's flexible (you can write custom JavaScript), but the setup cost is non-trivial for non-developers and the per-run pricing adds up for ongoing monitoring.
For comparison, ZocialComment is $20/month for 20,000 credits (one credit = one comment), so 1,000 comments = $1. Apify is cheaper per-call, ZocialComment is cheaper for sustained use.
Real use cases
1. Product feedback mining
Search reddit.com for "
2. Subreddit trend research
Pick a top thread of the month in r/marketing, r/Entrepreneur, or your niche subreddit. Export the comments. The recurring themes become your content calendar — every concern, question, or recommendation in that thread is a blog-post idea or product-feature idea.
3. Crisis monitoring
When a brand has a moment on Reddit — good or bad — the thread fills up fast. Exporting it within hours gives PR teams a chronological record of what was said, by whom, and when. Comments often get deleted later; the export preserves them.
4. Influencer / AMA analysis
When a creator does an AMA in r/IAmA, the post becomes a structured Q&A. Export it and you have a clean transcript — useful for understanding how the creator talks about their work, what their audience cares about, and which answers got the most engagement.
Handling deleted comments and removed users
Reddit shows [removed] for moderator-removed comments and [deleted] for user-deleted ones. These come through in the export as those literal strings in the body column — you can filter them out with a simple Excel formula (=IF(OR(B2="[removed]",B2="[deleted]"),"","")) or a JSON filter.
For removed-by-moderator comments specifically, the original text isn't recoverable through any public means — Reddit purges it from the API response. If you need to see removed content, you need the Reveddit-style approach which uses cached snapshots, not the API.
FAQ
Can I export private subreddit threads?
No. Private subreddits require you to be an approved member, and even then the content isn't exposed to unauthenticated scrapers. Use PRAW with an authenticated session if you must.
How deep do the reply trees go?
The exporter walks the entire visible thread, including Reddit's "load more" expansions, so deep nested replies are captured.
Why is depth a column?
So you can filter to top-level comments only (depth = 0) or analyze conversational dynamics (e.g., how often replies-to-replies get more upvotes than the top-level comment).
Do I need a Reddit account?
No. The exporter reads public threads directly.
What if I want the raw Markdown?
Use the Raw mode (vs Clean mode) on the download dropdown. Raw preserves Markdown syntax like **bold**, links, and bullet points exactly as posted.
Try it
Paste any public Reddit thread URL into the Reddit Comment Exporter — you'll have a CSV in seconds. Three free exports daily, no signup.