Reddit pain points: find what buyers need with Claude

Reddit pain points are the problems people describe in their own words when they ask a community for help. Short of running interviews, they are the best raw material you can get for positioning and ad copy. The workflow has four steps: find the subreddits where your buyers talk, pull their posts and comments through an API, have Claude cluster the pains, desired outcomes and exact phrases, then turn those into headlines, hooks and FAQ answers.

This guide runs that loop on one real thread, where a small B2B team asks r/CRM which CRM to buy. It uses real API calls, a copy-paste prompt and Claude's actual output. It also covers the step most tutorials skip, which is throwing out the vendor comments before you count anything.

Why Reddit pain points beat surveys

Surveys get the answers people think they should give. Reddit gets what they say when they are frustrated and asking strangers for help, which is closer to how they will read your landing page.

Growth marketers have been running versions of this for a while. Cody Schneider's ad pipeline starts with "scrape reddit with the exa api for the pain points and desired outcomes behind your product" and turns those into 15 short scripts (@codyschneider, 2026-10-01). Aaron Shepherd does the same for cold email: "reddit has the language / exact wording your buyer uses." He asks Claude for exactly three findings: the dominant emotion, the biggest objection, and what buyers need to see before they trust a solution (@AaronxShepherd, 2026-10-08). To learn why users leave a product, Ross Simmonds suggests five searches: "[Your SaaS] worth it", "alternatives", "Switching from", "pricing" and "problems" (@TheCoolestCool, 2026-10-02).

None of those posts show the plumbing, so this one does.

Step 1: find where your buyers talk

Search by the problem, not by your product name. Someone shopping for a CRM rarely posts in a CRM vendor's subreddit. They post in r/smallbusiness, r/sales or r/SaaS. GET /v1/reddit/subreddits/search returns communities for a topic:

curl "https://api.chatterapi.com/v1/reddit/subreddits/search?q=saas" \
  -H "Authorization: Bearer $CHATTERAPI_KEY"

{
  "data": [
    { "name": "SaaSMarketing", "subscribers": 37320, "nsfw": false },
    { "name": "B2BSaaS", "subscribers": 30565, "nsfw": false },
    { "name": "SaaS", "subscribers": 820451, "nsfw": false },
    { "name": "microsaas", "subscribers": 219914, "nsfw": false },
    { "name": "SaasSelection", "subscribers": 4033, "nsfw": false }
  ],
  "page": { "nextCursor": "ASezT4MJ…", "hasMore": true },
  "credits": { "charged": 0, "remaining": 719 }
}

Every response in this post was recorded with a test key and trimmed to the useful fields. The test key returns one real sample per endpoint for free. A live call costs 2 credits per page. The free subreddit finder does the same thing in a browser.

Before you do anything else in that community, read its rules. GET /v1/reddit/subreddits/{name} returns them in one call:

curl "https://api.chatterapi.com/v1/reddit/subreddits/SaaS" \
  -H "Authorization: Bearer $CHATTERAPI_KEY"

{
  "data": {
    "name": "SaaS",
    "subscribers": 820451,
    "rules": [
      { "title": "No Vendor Spam on posts or comments" },
      { "title": "No selling, soliciting, or fundraising" },
      { "title": "AMA / Surveys / Polls require approval" },
      { "title": "No Promotional or Advertising SaaS" }
    ],
    "posting": { "restrictPosting": true, "allowPolls": false }
  }
}

In this sample r/SaaS lists 11 rules, and four of them cover promotion. Reading is fine, but a "what's your biggest pain?" survey needs mod approval before you post it. If you know that before you start, your research won't end in a ban.

Step 2: pull posts and comments

Search posts with GET /v1/reddit/search (2 credits per page of up to 25):

curl "https://api.chatterapi.com/v1/reddit/search?q=best+crm+for+small+business&sort=relevance&time=year" \
  -H "Authorization: Bearer $CHATTERAPI_KEY"

{
  "data": [
    {
      "id": "1wdihhj",
      "title": "What CRM should a small business use?",
      "subreddit": "CRM",
      "score": 51,
      "numComments": 186,
      "createdAt": "2026-09-11T14:52:16.000Z"
    },
    {
      "id": "1vmy4xb",
      "title": "If You Had to Pick the Best CRM for Small Business Today, What Would It Be?",
      "subreddit": "CRMSoftware",
      "score": 10,
      "numComments": 56
    }
  ],
  "page": { "nextCursor": "AX-vad04…", "hasMore": true }
}

Pick threads with a high comment count relative to their score. A post with 51 points and 186 comments is a conversation, and the pains are in the comments.

Comment search, GET /v1/reddit/comments/search, finds complaints that never got their own post. One sample result is a r/smallbusiness comment describing this exact method: "I also check subreddits where my target audience would be and search for keywords like pain points, alternative to, best tool, etc." (u/xyzrg).

Then pull the whole thread with GET /v1/reddit/threads/{id} (3 credits per page):

curl "https://api.chatterapi.com/v1/reddit/threads/1wdihhj" \
  -H "Authorization: Bearer $CHATTERAPI_KEY"

{
  "data": {
    "post": { "id": "1wdihhj", "title": "What CRM should a small business use?", "numComments": 186 },
    "comments": [
      {
        "id": "p961pv9",
        "parentId": null,
        "body": "...if every rep has to remember a bunch of fields and manual updates after every interaction you've basically traded the spreadsheet problem for a CRM admin problem.",
        "score": 3
      },
      {
        "id": "p96a4as",
        "parentId": "p969uba",
        "body": "Mainly leads falling through and nobody having a clean view of where every conversation stands once a few people are involved...",
        "score": 1
      }
    ],
    "reportedCommentCount": 186
  },
  "page": { "nextCursor": null, "hasMore": false }
}

This sample loaded 101 of the 186 comments. That is normal for large threads, so compare comments.length with reportedCommentCount to see what you are missing. Comments come back flat with a parentId, and the Reddit API guide shows how to rebuild the tree.

The shortcut: intent-ranked results

To find people asking for recommendations rather than general discussion, use GET /v1/reddit/leads, which ranks posts and comments by intent (4 credits per page):

curl "https://api.chatterapi.com/v1/reddit/leads?q=crm&competitors=hubspot,pipedrive&time=month" \
  -H "Authorization: Bearer $CHATTERAPI_KEY"

{
  "data": [
    {
      "kind": "post",
      "community": "CRMSoftware",
      "text": "Is there a CRM that flags when customers stop buying certain products?...",
      "intent": "asking_for_recommendation",
      "intentScore": 0.82,
      "matchedTerms": ["is there a crm", "looking for"]
    },
    {
      "kind": "post",
      "community": "PakEntrepreneursHub",
      "text": "...Looking for a reliable business partner to bring your ideas to life?...",
      "intentScore": 0.74,
      "matchedTerms": ["looking for a", "looking for", "need a"]
    }
  ]
}

Look hard at the second result. It is a service ad that matched "looking for a," and it scored 0.74. Intent scoring is phrase matching, so put disqualifying words in exclude, raise minScore, and read each item before you trust it. matchedTerms tells you why each item was picked. The free Reddit lead finder runs the same search.

Step 3: have Claude cluster the pains

Claude can't reliably browse Reddit on its own, so you have to give it the text. We flattened the thread to one comment per line, each prefixed with its id, and ran this prompt with the Claude Code CLI:

(cat cluster_prompt.txt; echo '---'; cat thread_corpus.txt) | claude -p

The prompt:

You are doing customer research. Below are Reddit posts and comments from people
shopping for a CRM for a small team. Each comment starts with its id in brackets.

Return four sections:

1. PAINS: the 5 most common problems, ranked by how many separate comments mention
   them. For each: a one-line name, the count, and 2 verbatim quotes with their ids.
2. DESIRED OUTCOMES: what people say they want instead, in their words, with ids.
3. EXACT PHRASES: 10 short phrases (3-10 words) copied verbatim that a buyer would
   recognise as their own words.
4. SKEPTICISM: comments that look like vendor promotion or astroturfing (product
   named repeatedly with similar wording, self-disclosed staff). List ids and why.
   Exclude them from sections 1-3.

Rules: quote only text that appears below, never paraphrase inside quotation marks.
If a pain appears in only one comment, say so. Do not invent counts.

Two rules do most of the work. Because every quote is verbatim and carries an id, you can check any claim with a text search. Section 4 is there because this thread, like most buying threads, was full of vendors.

What came back

The skepticism section was the most useful part of the output. Claude flagged five comments as likely astroturfing: all recommended the same new CRM in near-identical wording ("AI native CRM," agents handling follow-up, no "CRM admin"). It also listed more than a dozen self-disclosed founders and staff, among them a commenter who identified as HubSpot's founder and CTO and opened with "I am biased." It caught undisclosed pitches too, plus one comment posted twice, and excluded all of them before counting. If you skip this step, your "top pain" ends up being whatever the loudest vendor is selling.

After filtering, the ranked pains were:

Among the desired outcomes were "everyone working from the same place," "every active deal has a next action + due date," "make sure exporting your data isn't painful," and "cost should scale with a seat, not a capability." We searched the thread text for each quote above, and every one appears verbatim.

These counts describe one thread. They are not a market statistic. 186 comments from one subreddit show how this group talks. Run the loop across five or ten threads before you call something the top pain.

Step 4: turn Reddit pain points into copy

The phrases are what you came for. The buyer wrote them, so reuse them close to verbatim.

• For positioning: the top pain wasn't missing features. It was upkeep. A line like "A CRM your team keeps updated without five hours of admin a week" answers the thread directly, while "feature-rich" answers nobody.
• For ad hooks, use one pain per hook in the buyer's words: "Traded your spreadsheet problem for a CRM admin problem?" or "Leads falling through once three people are selling?" Schneider describes the same structure: hook, pain point, desired outcome.
• FAQ and objection copy can come straight from the thread, as "Can we export our data if we outgrow it?" and "Does price go up per feature or per seat?" did. Put those on the pricing page.
• In sales notes, treat the overbuying pain as an objection to handle on calls. Sell the next 12 to 18 months, not the five-year vision.

Chris Everest describes going a step further and packaging the answers to repeated questions into info products (@everestchris6, 2026-09-17). Whatever you build, the input is the same: problems people state publicly, in their own words.

The whole loop in one Python script

This collects threads for a query and keeps only comment ids and text, then writes a corpus file for the prompt above. No usernames are stored.

import os, requests

BASE = "https://api.chatterapi.com/v1"
HEADERS = {"Authorization": f"Bearer {os.environ['CHATTERAPI_KEY']}"}

def get(path, **params):
    r = requests.get(f"{BASE}{path}", headers=HEADERS, params=params, timeout=60)
    r.raise_for_status()
    return r.json()

def collect(query, max_threads=5, min_comments=20):
    posts = get("/reddit/search", q=query, sort="relevance", time="year")["data"]
    picked = [p for p in posts if p["numComments"] >= min_comments][:max_threads]
    lines = []
    for p in picked:
        t = get(f"/reddit/threads/{p['id']}")["data"]
        lines.append(f"POST t3_{p['id']} r/{p['subreddit']}: {t['post']['title']}")
        for c in t["comments"]:
            if c["body"].strip():                      # skip deleted or removed comments
                lines.append(f"[{c['id']}] ({c['score']} pts) {c['body']}")
    return lines

lines = collect("best crm for small business")
with open("thread_corpus.txt", "w") as f:
    f.write("\n\n".join(lines))
print(len(lines), "lines written")

Five threads cost about 2 credits for the search plus 3 per thread page, so roughly 17 credits for one pass. Then run the claude -p command from Step 3. If you'd rather Claude made the calls itself, add the MCP server and ask it to run the same steps with reddit_search and reddit_thread. Our comparison of the best MCP servers for Reddit and X covers setup, and giving an AI agent Reddit and X data goes further into agent loops.

Is Reddit even representative?

The fair objection is that Reddit users are not your market, and the loud ones are not even typical Reddit users.

Some evidence backs the worry. Peter Vijeh analysed 51,129 comments across six knife subreddits and found that a small group of brand-loyal accounts wrote "11.3%" of brand mentions in buying threads, against about 7.9% expected by chance (study). He thinks enthusiastic fans explain it better than paid posting, and he says his labels are unvalidated. Whatever the cause, a few accounts can tilt what a thread appears to say. Our CRM thread had the same shape.

So use Reddit for hypotheses and language, not as proof of demand. Filter out vendors first and count across several threads. Then test the top pains somewhere that measures behaviour: ad click-through, landing page conversion, or five customer calls. Reddit shows how buyers phrase the problem, and your own data shows how many of them there are.

Ethics: research, don't harvest

Reading public threads to understand a market is one thing. Using them as a contact list is another, and that gets accounts banned and domains filtered.

• Don't spam the threads you studied. Most buyer subreddits ban vendor promotion, so check the rules you pulled in Step 1. If you do reply, answer the question and say who you are.
• Never DM people in bulk. Someone who posted about a pain did not opt in to your sequence. One viral recipe suggests clicking through commenters' profiles to find their companies. Skip it, because that turns research into tracking individuals.
• Store as little as you can. The script above keeps comment ids and text, not usernames. Reddit's Data API Wiki asks developers to remove content that has been deleted from Reddit (checked 2026-10-14), so delete raw dumps once the analysis is done.
• Don't infer sensitive traits. Cluster problems, not people.

If you want Reddit as a marketing channel rather than a research source, that's a different job, closer to done-for-you Reddit marketing than to scraping.

Start with one thread

Pick a buying thread in your category with 100+ comments, pull it, and run the prompt above. That gets you your buyers' phrasing in about ten minutes. Sign up with Google for 100 free credits with no card, enough for about 30 thread pulls. ChatterAPI gives your code and your agents Reddit and X data through one key, over REST or MCP, and you don't have to apply for a developer account.