Surveys lie. Not because people are dishonest — but because being asked "what do you struggle with?" puts people in a different headspace than when they're venting to strangers online at 11pm.
Social media, especially Reddit and Quora, is where people say what they actually think. No brand filter, no politeness tax. Someone just spent three hours trying to fix something that should have taken ten minutes, and now they're typing about it. That's the data you want.
Here's how to find it systematically.
Start with Reddit — It's the Closest Thing to a Pain Point Database
Reddit has over 100,000 active communities, and a large chunk of posts in those communities are some form of "why does X suck / break / not work / cost so much." It's a goldmine for this kind of research.
The search queries that tend to work best:
"anyone else" [topic]— finds shared frustrations"frustrated with" [topic]"hate that" [topic]"why is [tool/process] so""vent" OR "rant" [topic]"switched from" [competitor name]
That last one is particularly useful. When someone says "I switched from X because...", they're giving you an exact description of a pain point with zero ambiguity.
What to Look at Once You're in a Thread
Don't just read the original post — the comments are where the real signal is. A post with 3 upvotes that has 40 comments is telling you something interesting is happening. Look for:
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Reply patterns. When multiple people say "same" or "this is exactly my experience," that's frequency. One person complaining is noise. Ten people saying "yes, this" is a pattern worth noting.
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The specific language. Not just what they're frustrated with, but how they describe it. The words people use when talking to each other (not to brands) are often the words you should use in your product copy. If five people independently call something "a nightmare to set up," that phrase belongs in your marketing.
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The workarounds. People who've been dealing with a problem long enough develop unofficial fixes. "I just export to CSV and paste it into a Google Sheet every time" is someone telling you exactly what your product should make unnecessary.
What Not to Do on Reddit
Don't search only in the obvious subreddit. If you're researching pain points around hiring, r/recruiting is the obvious move — but a lot of the rawest complaints are in r/smallbusiness, r/Entrepreneur, and r/startups, where people who aren't professional recruiters talk about what's broken in the process. If you haven't mapped which communities your audience actually uses, the subreddit finder tool can surface adjacent communities you'd otherwise miss.
Also, don't rely on upvotes as a proxy for importance. A post complaining about a niche but serious problem in your space might have 12 upvotes. A meme about the same topic has 4,000. Upvotes measure what entertains a community, not what matters to your customers.
Quora for Longer, More Structured Problem Descriptions
Reddit is raw and fast. Quora skews toward people who write more carefully and who are often trying to explain their situation to get help.
This makes it valuable for a different reason: people on Quora tend to describe their problem with more context. Instead of "why is X so bad," you get "I've been trying to do Y in X for two months, and the issue I keep running into is Z because of A and B." That's a full use case.
Search Quora for questions like:
- "What are the biggest problems with [category]?"
- "Why do people leave [competitor]?"
- "What's wrong with [tool/process]?"
- "What would you change about [industry]?"
Look at both the answers and the comments on answers. Disagreements in Quora comments often reveal that a pain point affects different people differently — which matters when you're deciding what to prioritize.
X (Twitter) for Real-Time Frustration
Twitter/X isn't great for deep research, but it's good for one thing: catching people in the immediate moment of hitting a problem.
Use X search for:
"[topic] is so frustrating""[tool name] broken""[tool name] hate"- Replies to your competitors' official accounts (complaints often land there)
The signal is thinner on X — people are less likely to get into detail in 280 characters — but the emotional temperature is higher. If you see the same complaint appearing in multiple recent tweets from different accounts, that's a problem that's actively bothering people right now, not just a historical grievance.
X is also useful for spotting the language of frustration in your space. What words do people reach for when they're upset about this category? Those words matter.
The Frequency Signal Is Everything
One person complaining about something is interesting. Ten people describing the same friction in different words across different communities is a real problem worth building or writing about.
The pattern to look for:
- You see a complaint in r/smallbusiness
- You see a similar complaint phrased differently in a Quora answer
- Someone on Twitter mentions the same thing in passing
- There's a Reddit thread from 18 months ago where 30 people agreed
That's the frequency signal. None of those individual posts looks like much on its own. Together, they're telling you something.
When you find that pattern, take note of:
- The common thread across descriptions (what's the actual underlying problem?)
- The specific words that keep appearing
- Whether the problem is getting worse or has been around forever
Organizing What You Find
Raw social media posts aren't insights — they're inputs. What you do with them matters.
At minimum, keep a running doc with:
Direct quotes. Copy the actual text. Don't paraphrase. The original wording is the asset.
The source. Link to the original thread so you can go back and read context later.
Frequency count. How many times have you seen this specific frustration come up? Even an informal tally helps you prioritize.
The implied need. What would make this pain go away? Write one sentence.
You're looking to get to a shortlist of 5-10 pain points that appear often, are described with specific language, and point toward something actionable.
Common Mistakes to Avoid
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Cherry-picking posts that confirm what you already believe. This is easy to do and almost impossible to notice in yourself. If you go looking for evidence that people hate [specific thing], you'll find it. Set a minimum threshold: "I need to find at least 10 independent examples before I count this as a real pattern."
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Reading only recent posts. Some of the best threads are from 2-3 years ago. Pain points that have been around for years and haven't been solved are often the ones worth focusing on.
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Ignoring the people who aren't complaining. Threads where people say "I don't actually have a problem with this" or "you just need to do X" are also valuable. They tell you the problem might be real but not universal — which affects how you prioritize it.
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Missing adjacent communities. Your audience doesn't just exist in communities named after your problem space. They're in communities organized around their identity (r/freelance), their context (r/remotework), or their life stage (r/Entrepreneur). Those adjacent communities often have the most unfiltered conversations.
What Comes Next
Once you have a shortlist of pain points with real quotes and frequency signals behind them, you have something you can actually use: messaging to test, features to spec, content to write, ads to run. If you're still at the product stage, matching those pain points to buying signals on Reddit is the logical next step.
The whole point of this kind of research is to stop guessing what your audience cares about and start reflecting back what they've already said. When your marketing uses the same words people use to describe their own frustration, it doesn't sound like marketing — it sounds like you understand them. Pain point research from social media works best alongside other customer research methods — win/loss interviews, review mining, and user calls can triangulate what the social data is telling you.
That's the goal.
If you want to do this at scale without doing every search manually, Reddinbox pulls real conversations from Reddit, Quora, and X, filters out noise, and surfaces the most relevant pain points with original quotes and source links.