Most indie hackers still pick ideas the same way:

• Scroll Reddit or X
• See a few spicy posts
• Declare “there’s clearly demand”
• Spend months building
• Discover that nobody actually wants it

The information you needed was there the whole time, buried in noisy threads and timelines. The problem isn’t lack of data; it’s lack of a clear, repeatable way to mine it.

This guide gives you a practical demand discovery workflow for indie hackers and lean teams. It’s built so you can:

• Find real problems and strong demand before you write any code
• Use Reddit, X, and other public conversations without drowning in noise
• Rank and compare opportunities instead of chasing whatever you saw this morning

You can run a first pass of this workflow in a weekend, then tighten it into a weekly habit.

1. Define a Sharp Audience and Problem Space

If you start with “SaaS ideas from Reddit,” you’ve already lost. Your input is too broad; every thread looks interesting.

Your demand discovery workflow needs a clear “searchlight”:

1.1 Choose a specific audience

Think “people in this job, in this context, with this maturity,” not “developers” or “marketers”.

Examples:

• “Solo Shopify store owners doing $2–10k MRR”
• “B2B founders running outbound themselves (no SDRs yet)”
• “Freelance designers who hate admin and billing”
• “Ops managers at small logistics companies (10–100 trucks)”

A quick way to sharpen your audience:

• Who do you already understand (past jobs, side projects, friends)?
• Who do you already have access to (Slack groups, Discords, communities)?
• Whose world do you actually enjoy thinking about?

Pick one audience for a single pass of this workflow. You can always expand later.

1.2 Define a problem space, not an idea

Instead of “I want to build a better CRM,” define the jobs or moments you care about.

Examples of problem spaces:

• “How solo store owners keep inventory accurate without hiring”
• “How small teams coordinate customer support across email, chat, and social”
• “How indie devs launch and get their first 50 users”

Write down 1–2 problem spaces that:

• Touch money (revenue, cost, risk, time)
• You can visualize clearly
• You could explain to a stranger in 2–3 sentences

You’ll use these to decide whether a conversation is relevant or not.

2. Source Real Conversations Without Drowning

Now you know who and what you care about. The goal is to surface real conversations, not just polished content or “building in public” flex posts.

We’ll focus on Reddit and X, but you can add others later.

2.1 Reddit: where pain hides in plain sight

Start with 3–5 subreddits where your audience hangs out.

Examples:

• Solo Shopify owner → r/shopify, r/dropship, r/Entrepreneur
• B2B founders → r/startups, r/SaaS, r/b2b
• Freelance designers → r/freelance, r/design, r/indiehackers

Search for pain-flavored keywords inside those subs:

• “how do you”
• “stuck with”
• “is anyone else”
• “I hate”
• “this is killing me”
• “need help with”
• “burned out”
• “spend hours”

Example search:

• In r/shopify: search "I hate" OR "so annoying" OR "spend hours", sort by “Top” and “This month”.

Skim thread titles first. You are looking for problems, not opinions:

• Good: “I spend 3 hours every day reconciling orders with inventory — how do you automate this?”
• Weak: “Shopify vs WooCommerce — which is better?”

Open promising threads and scan for detailed comments, not hot takes.

2.2 X (Twitter): where urgency and money show up

On X, use search filters to find concrete problems:

• ("how do I" OR "any tools for" OR "is there a way to") ("invoices" OR "inventory" OR "outreach")
• ("tool for" OR "SaaS for" OR "software that") ("[your problem space keywords]")

You’re looking for tweets like:

• “Any software that automatically chases unpaid invoices for freelancers? I’m spending 5–10 hours/month just sending reminders.”
• “Is there a simple way to see which leads replied across email + LinkedIn? My CRM is overkill for 1-person outbound.”

Replies often contain more detail (and alternatives people already tried). Open the thread, not just the original tweet.

2.3 Automate scanning when you can

Manually searching and scanning threads works for a weekend sprint, but it gets tiring fast as a weekly habit.

This is where a tool like Miner can help: it continuously scans Reddit and X, clusters related conversations, and surfaces high-signal opportunities (real pain, buyer intent, weak signals) in a daily email. Instead of manually searching 10 subreddits and a dozen X queries, you jump straight into ranked, pre-filtered conversations.

You can still run the workflow manually; Miner just compresses the discovery phase into minutes.

3. Spot Strong Demand Signals (Not Just Noise)

Not every complaint means “build a product”. You’re hunting for a specific pattern: pain + urgency + willingness to change.

Here’s a simple scoring lens you can apply as you scan.

3.1 Pain: how bad is it?

Look for language that shows emotional or operational pain:

• “This is killing me”
• “I’m burning so much time on this”
• “I dread doing this every week”
• “I lost $$$ because of this”

Example Reddit comment (strong):

I lose at least 1–2 hours EVERY DAY just manually copying Stripe data into my stupid spreadsheet. If I skip a day, reconciliation becomes a nightmare. There has to be a better way.

Example tweet (weak):

I wish sending invoices was more fun lol

3.2 Frequency and repetition

One-off pain can be annoying; repeated pain is opportunity.

Signals of frequency:

• “Every day / every week / every month”
• “For every new client…”
• “For each campaign / for every launch”

Even better: multiple people in the thread saying “same” or “I thought it was just me”.

Example:

I spend 2–3 hours after every launch just piecing data from Stripe, Gumroad, and my landing page to see what worked.

…and two replies:

Same, I have like 4 spreadsheets for this.

I gave up tracking this because it’s too much work.

Now you’re seeing a pattern, not an anecdote.

3.3 Buyer intent: are they searching or paying?

The clearest demand signals are when people:

• Ask explicitly for tools
• Mention trying multiple tools and still being unhappy
• Say they’d pay to solve it

Examples:

• “Is there a tool that automatically emails customers when their card fails? I’d happily pay just to not think about this.”
• “We tried [Tool A], [Tool B], and still end up exporting CSVs and hacking Excel formulas.”

Weak signals:

• “Someone should build X”
• “If only there was a tool for Y” (with no specifics, no context)

3.4 Constraints and workarounds

Finally, look for workarounds — people duct-taping solutions together.

• “Right now I have a zap that sends X to Google Sheets, then I manually…”
• “I run this Python script every Friday to…”
• “I export from Tool A, clean the file, then import into Tool B.”

Workarounds are powerful because:

• They prove the problem is real (people are investing time)
• They tell you how your product needs to integrate and behave

4. Log and Structure Findings in a Lightweight Way

You don’t need a fancy research repo. You just need a consistent way to log and compare opportunities.

Use whatever you’ll actually maintain: Notion, Airtable, Google Sheets, Obsidian.

4.1 Use a simple, repeatable schema

Create a table with columns like:

• ID – simple increment or short label like INV-01
• Audience – “solo Shopify”, “freelance devs”, etc.
• Problem summary – 1–2 line description of the pain
• Source – Reddit/X + link or identifier
• Signal type – Pain, frequency, workaround, buyer intent
• Example quote – copy/paste the strongest snippet
• Current workaround/tools – what they use now
• Impact – time/money/risk affected
• Your notes – quick thoughts or hypotheses
• Score – a rough 1–5 opportunity score (we’ll refine next)

Log conversations, not “ideas”. For example:

• Problem summary: “Manual revenue reconciliation across Stripe, PayPal, and Gumroad after every launch”
• Example quote: “I spend 2–3 hours after every launch just piecing data from Stripe, Gumroad, and my landing page…”

The goal is to preserve context so you can revisit it later with fresh eyes.

4.2 Capture raw quotes, not paraphrases

Copy exact phrases people use. They’ll become:

• Later search queries
• Landing page copy
• Questions for customer interviews

If you use a tool like Miner, you can often save or tag interesting opportunities directly as they appear in your daily brief, then copy key ones into your own research doc.

5. Rank and Compare Opportunities

Now you have a small backlog of raw demand signals. The next step in your demand discovery workflow is to compare them side by side, instead of chasing whatever feels hottest in the moment.

You don’t need a PhD in scoring. Keep it simple and consistent.

5.1 A practical 5-factor score

For each logged problem, score 1–5 (low–high) on:

1. Pain intensity – How painful is this, in their own words?
2. Frequency – How often does this happen?
3. Monetary impact – Does this clearly tie to revenue, cost, or risk?
4. Buyer intent – Are they actively searching or paying for solutions?
5. Founder fit – Do you understand this world and want to work in it?

Example scale:

• 1 = weak / vague
• 3 = solid, but not burning
• 5 = “keeps them up at night”

Then compute a simple Total score = Pain + Frequency + Monetary + Intent + Fit (max 25).

You’re not trying to be precise; you’re trying to rank relative opportunities.

5.2 Anchor each score with evidence

Instead of scoring by gut feeling, use concrete evidence:

• Pain 5? Show the quote.
• Frequency 4? Multiple people say “every week” or “every launch”.
• Intent 5? They mention trying tools, or say they’d pay.

Add a quick note:

• Pain: 4 — “I lose ~2 hrs/day to this”
• Intent: 3 — asking for tools, but no mention of paying

This forces you to stay honest.

5.3 Choose 1–3 opportunities to explore

Sort by Total score and mark the top 3. Then apply one more sanity check:

• Which of these can you reach and talk to in the next 7–14 days?
• Which are you willing to work on for 6–12 months if it hits?

Pick one primary opportunity to explore, plus one backup if the first turns out to be weaker than it looked.

6. Turn Insights Into Testable Product Directions

“People have this problem” is not enough. You need to turn each high-scoring opportunity into a testable product direction, and validate demand before you write serious code.

6.1 Write a simple problem thesis

Start with a short paragraph that combines what you learned:

• Who has the problem
• What the problem is
• When it happens
• How they handle it today

Example:

Solo Shopify store owners doing $2–10k MRR struggle to keep their inventory accurate across Shopify and a separate warehouse app. Every time they run a promotion or get a spike in orders, they spend 1–2 hours manually reconciling stock. They currently export CSVs and manually adjust quantities, and worry about overselling and cancellations.

This becomes your anchor for tests.

6.2 Define a “minimum successful outcome” for your first test

Before building, define what success looks like for your first validation step.

Examples:

• 10 people in your target audience book a call after reading a short problem-focused page
• 5 people pre-pay or commit to a paid pilot
• 10–15 qualitative interviews that confirm the pain and willingness to change

If you can’t imagine even that level of interest, the opportunity is probably weaker than it looked.

6.3 Design a no-code / low-code experiment

Pick an experiment you can run in 1–2 weeks:

• A problem-focused landing page with:
  • A clear description of the pain (in their words)
  • Your hypothesis of a solution
  • A strong CTA: “Book a 15-min call” or “Apply for early access”

• A manual “concierge” version:
  • Offer to perform the job manually: reconciliation, report generation, outreach
  • Charge a small fee to see if people will pay for the outcome, even without software

• A structured outreach:
  • DM or email people who made the original Reddit posts or tweets
  • Reference their own words, offer a short call to discuss if they still have the problem

Examples of outreach based on your logs:

You mentioned on Reddit that you spend 2–3 hours after every launch reconciling Stripe and Gumroad to see what worked. I’m exploring this problem in-depth — are you still dealing with it? If yes, could we do a 20-min call? Happy to share findings and anonymized benchmarks.

If you consistently get ignored or told “I solved this / it’s not a big deal,” that’s data; move to the next opportunity in your ranked list.

7. Make It a Weekly Demand Discovery Habit

The real power of a demand discovery workflow for indie hackers isn’t a one-off sprint; it’s a habit that keeps you close to demand.

Here’s a simple weekly loop:

7.1 Weekly rhythm

• 60–90 minutes: scan Reddit/X for new conversations in your chosen audience/problem spaces
• 30 minutes: log 3–10 new high-signal problems in your table
• 30–60 minutes: score and update your top opportunities
• 60–90 minutes: move one test forward (landing, outreach, calls)

If you use Miner, the first step shrinks a lot: you open your daily brief, review pre-ranked opportunities, and only dive into the ones that fit your audience and problem spaces. Over time, saved and archived briefs become a searchable history of how pain and buyer intent evolve.

7.2 When to stop researching and start building

You don’t need infinite validation. Look for:

• 10–20 people independently describing a similar problem
• 5–10 people willing to talk about it in detail
• Clear, repeated patterns in workarounds and desired outcomes
• At least a handful of people who say some version of “I’d pay for this if it worked”

Then:

• Build a focused v0 solution that solves one narrow job well
• Keep talking to users; continue running the discovery loop for adjacent problems and expansion paths

8. A Weekend Demand Discovery Checklist

If you only have a weekend, here’s a condensed checklist you can run:

• Define audience:
  • Pick one specific audience you understand and can reach
• Define problem spaces:
  • Write 1–2 clear problem spaces tied to time, money, or risk
• Find conversations:
  • Choose 3–5 relevant subreddits and 2–3 X search queries
  • Search for pain keywords (“I hate”, “stuck with”, “how do you”, “tool for”)
• Log 10–20 opportunities:
  • For each, capture audience, problem summary, source, quotes, workaround
• Score and rank:
  • Rate each on Pain, Frequency, Monetary, Intent, Founder fit (1–5)
  • Pick your top 1–3 opportunities
• Draft a thesis:
  • Write a short problem thesis for your #1 opportunity
• Design a test:
  • Either a problem-focused landing page or a manual “concierge” offer
  • Define a minimum successful outcome (e.g., 5 calls booked)
• Do outreach:
  • Contact people from the original threads
  • Share the page or invite them to a short call

On Monday, you’ll have a prioritized list of real problems, not just a list of “cool ideas”.

9. Why This Workflow Beats Building First

This demand discovery process for indie hackers is intentionally low-tech:

• No complex frameworks
• No months-long research cycles
• No waiting for magical inspiration

It forces you to:

• Start from real, detailed conversations
• Distinguish between noise and strong demand signals
• Log and compare opportunities instead of chasing every shiny thread
• Turn insights into small, testable bets before investing months of build time

Reddit and X are noisy, but that’s where people complain, hack workarounds, and ask for help in real-time. A workflow like this — whether you run it manually, or speed it up with a tool like Miner — keeps you anchored to that reality.

If you’re tired of shipping things that never find traction, don’t look for a “better idea.” Build a better demand discovery workflow, and run it every week.

The ideas will follow.