Methods, checklists and lessons from turning public discussions into demand evidence. No invented numbers — only how to read what people already wrote.
All articles
Churn reason research from public sources: where cancel threads live, which complaints are usable signals, and how to turn them into a product.
Find untapped B2C SaaS niches by reading consumer complaints: where they are written down, four filters to test them, and what to skip.
Use GitHub issues to find micro SaaS ideas: filter the noise out of issue search, read reactions and wontfix threads, and turn an unmet need into a product.
How to run a SaaS competitive analysis from public complaints: what paying customers say about the alternatives, where rivals fail, and the gap you can take.
Market research for startups, without a research budget: read public complaints for demand, size the market bottom-up, and turn it into a decision.
Learn how to find micro saas ideas from recurring complaints in public communities, and how to tell a small, buildable niche from noise.
Customer discovery interview questions that surface real problems instead of polite agreement, with the follow-ups that keep a call honest.
How to validate a saas idea with public evidence, five customer conversations and a small demand test, so you build only what people want.
How to compare micro saas niches by recurring pain, reachable buyers and weak competition, so a solo founder picks a market they can own.
A practical market analysis for startups: size demand bottom-up, map the alternatives, and find the gap a small product can win.
How to find a saas idea by reading complaints instead of brainstorming, with a one-week routine that ends in a testable problem statement.
A customer discovery interview template you can run this week: the script, the sequencing and how to turn transcripts into product decisions.
App store review mining turns one-star reviews into a feature brief. Learn to read reviews for the gaps competitors keep failing to close.
How to test demand before building with landing pages, waitlists and interviews, and how to tell a real buying signal from polite encouragement.
Finding B2B pain points in public support threads: read for the workaround, group the repeated tasks, and turn scattered threads into a shortlist.
Jobs to be done examples in plain English, and how a solo founder uses the framework to read demand inside public complaints and reviews.
How to write a problem statement from real quotes: the who, the workaround and the cost, tightened until it points at one buildable thing.
Boring business ideas are often the best ones. Here is how to spot dull but profitable problems, test them with real evidence, and know where to look.
Competitor research for indie hackers: read user complaints instead of landing pages, find the gaps that matter, and run a repeatable pass you can keep.
Willingness to pay research from public threads: the signals that show someone will actually pay, the ones that fool you, and how to search for them.
Subreddits vs surveys: why public threads give better evidence for idea research than a questionnaire, and how to read them before you build anything.
Reddit search operators that surface real complaints instead of promo threads, with the exact queries and a five-minute walkthrough you can run today.
Learn how to document research findings so they survive contact with your build: a one-page shape, sources attached, and a review before you commit.
Counter evidence keeps a promising idea honest. Learn where to look, how to record what you find, and when it should stop a build before you start.
How to find problems worth solving: three tests for demand, where to look for evidence, and when to walk away from an idea that only sounds good.
Run a market opportunity assessment in one week with a practical checklist: collect the posts, score the pain, and decide if the problem is real.
Moving from complaint to feature spec is a translation job. This is a one-sitting workflow that turns raw quotes into a spec you can actually build from.
Pain point research that works: find what people actually struggle with by reading their own words, then turn repeated friction into a real product.
Recurring complaints are the strongest signal in a sea of messy threads. Learn to group them, count distinct people, and rank by how often they return.
Pricing research for a micro SaaS does not need surveys. Learn how to read price signals in public discussions and pick a number you can defend today.
Micro SaaS ideas come from complaints, not brainstorms. Learn how to collect, read, and filter real complaints into a small product you can ship fast.
Reddit vs Hacker News vs Stack Overflow for research: what each community is genuinely good for and how to combine them in one focused pass today.
Idea validation red flags are quiet. Learn the signals that look like progress but are not, and run a checklist that tells you when to stop or keep going.
How to validate a startup idea with evidence instead of opinions: what counts as proof, where to look, and when to walk away before you build anything.
Evidence based idea validation means matching every claim to its source text. Here is what counts as proof before you write a single line of code.
AI research hallucinations turn confident summaries into invented quotes. Here is how to check every quote against source text before you trust a report.
Reddit market research, step by step: pick the right communities, read threads for pain, and turn raw quotes into a shortlist of problems worth solving.
Build a pain intensity score from real discussion posts: a repeatable way to rank customer problems and decide which one deserves your next build.
Customer quotes are the raw material of demand evidence. Learn how to read them, sort real signals from curiosity, and decide what to build next.
Learn how to find SaaS ideas on Reddit by reading real complaints instead of brainstorms, then turning raw threads into a shortlist you can test.
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.