August 27, 2026
4 min read
Pain Point Research: Find What Users Struggle With
Pain point research that works: find what people actually struggle with by reading their own words, then turn repeated friction into a real product.
Pain point discovery
4 sources
Find SaaS pain points people already complain about
The best product ideas are not invented, they are found. This tool reads Reddit, Hacker News, Stack Overflow and GitHub for the complaints people write when nobody is asking them a question, clusters the repeats and returns the problems worth solving — each with a verbatim quote checked against the source text.
What counts as a pain point
Not every complaint is an opportunity. A pain point worth building on has all four of these:
- ◎ A specific task. "I export a CSV every Friday and reconcile 200 rows by hand", not "accounting is hard".
- ↻ Repetition. The same friction from different people, in different threads, months apart.
- £ A cost today. Hours, money or a paid workaround they resent. Free annoyance is weak evidence.
- ⌁ Movement. People searching for a tool, switching away or building their own.
Reddit
Niche professional subreddits where people describe their workflow in detail, late at night, without performing for you.
Hacker News
Technical buyers arguing about tools, pricing and what their current stack fails to do.
Stack Overflow & GitHub
A public backlog of unmet needs: workarounds, feature requests and issues nobody has fixed.
How the research runs
| Step | What happens | Source |
|---|---|---|
| Fetch | Reddit (several sort orders, pain-phrased queries, subreddit deep dive) plus Hacker News, Stack Overflow and GitHub, in parallel 4 data sources | 4 APIs |
| Rank | Every post is compared to your topic semantically; unrelated posts are dropped semantic ranking | embeddings |
| Triage | Each post is validated: real problem, pain intensity, buying signal and the verbatim quote quote verified against the source | verified |
| Cluster | Duplicate complaints are merged, so frequency means distinct users, not posts deduplicated | clusters |
| Report | One report built from the validated signals, including counter evidence and willingness to pay evidence only | markdown |
Do it by hand
You can run the same loop yourself in an afternoon. Pick one community, search for friction phrases such as "I still do this manually" or "is there a tool that", copy the quote and the URL, then group the quotes by the underlying problem. It works, and it is slow.
The manual method, in full: customer pain point research, Reddit search operators and how to score pain intensity.
Field notes
September 5, 2026
4 min read
Reddit Search Operators That Actually Surface Complaints
Reddit search operators that surface real complaints instead of promo threads, with the exact queries and a five-minute walkthrough you can run today.
August 13, 2026
5 min read
Pain Intensity Score: How to Rate Customer Pain
Build a pain intensity score from real discussion posts: a repeatable way to rank customer problems and decide which one deserves your next build.
Questions
What is a SaaS pain point?
A recurring, specific complaint that real people post in public, describing a problem they already work around or pay to avoid. It names a task, a cost and a current workaround, not a vague frustration.
Where do SaaS pain points come from?
Public discussions on Reddit, Hacker News, Stack Overflow and GitHub, plus review sites and support threads. Every signal on this site links back to the thread it came from.
How do you know a quote is real?
Each quote is checked against the source text of the post it claims to come from. A quote that cannot be found in the source is dropped, so a hallucinated quote never reaches a report.
How many complaints make a pain point worth building on?
The same problem in several independent threads from different people, ideally with a cost attached. One thread is an anecdote; a pattern across communities is an opportunity.
Run your own
Name a problem you keep hearing about — or the market people are stuck in. The report comes back with the problems they described, the quotes behind them and what they already tried.