Real example · generated by Scoutr
This is what a real report looks like.
We ran one of our own projects, LeadsRadar, through the same pipeline you get. Browse the 12 sections of the report and the MVP the agent modeled, exactly as they were delivered.
Project, as the founder described it
Lead discovery in online forums
A tool called LeadsRadar that searches Reddit and Hacker News conversations (based on defined keywords and embeddings) to find people complaining about a specific problem. That problem is the one the LeadsRadar user is trying to solve, so they want to reach out, through a comment or a DM, and offer their tool. The problem LeadsRadar solves is finding conversations from potential customers in the last 24 hours and making outreach easier by providing AI-written message templates that sound natural, in different tones, focused on providing value and contributing to whoever raised the complaint. Sales-driven, but done intelligently.
Summary
Biggest risk
That the problem is perceived as too small to justify a change in behavior.
Next steps
- 1Step 1: Build and test a landing page focused on the problem. Post it in sales communities. Time: 2 weeks. Success = capture 10 or more emails in 7 days.
- 2Step 2: Run in-depth interviews with 10-15 potential users to validate willingness to pay. Time: 3 weeks. Success = positive feedback from at least 50%.
- 3Step 3: Consolidate what the experiment showed and adjust the MVP based on the feedback. Time: 2 weeks. Success = adjusted product ready for a pilot.
What we know
- The problem of identifying leads from complaints is relevant.
- There are competitors in the space, which signals a recognized need.
What's left to validate
- How willing users really are to change their current process. Validate it with a problem landing page.
Critical points
Problem
Summary
The problem you are trying to solve has some clarity. You are attacking the difficulty companies face in identifying and contacting potential customers who express real needs in forums. However, you could be attacking a symptom if the end user's buying intent is not well identified.
Strengths
- Clear focus on specific conversation niches, such as Reddit and Hacker News.
Red flags
- End-user intent
Conversations
Reddit and Hacker News threads the engine matched to your problem. Each one links to the original discussion.
“r/msp on Reddit: Client doesn’t understand the value of services Wants to lower price we already agreed upon. Any Advice?”
“r/freelance on Reddit: What to do with clients? All of them seem to be a problem”
“r/PublicRelations on Reddit: Rant: I am tired of how ungrateful my clients are.”
“r/freelance on Reddit: Is there a psychology answer to why clients dont know what they want?”
“r/agency on Reddit: How Do You Handle Clients with Unrealistic Expectations?”
“r/freelance on Reddit: How do you turn down a client that isn't willing to pay your asking price?”
“r/smallbusiness on Reddit: Why does it feel like clients who pay the least always require the most?”
“r/CustomerSuccess on Reddit: Tips for difficult conversations with customers”
“r/smallbusiness on Reddit: How do you understand what customers want but can’t find in your store?”
“Launch HN: Thematic (YC S17) Customer Feedback Analysis via NLP”
We analyse customer feedback to tell companies how to increase cust
“Launch HN: ScopeAI (YC W17) – Extract insights from customer conversations”
we’ve built a product that automat
Target user
Summary
Startup founders or sales professionals looking to identify potential customers who express needs in online forums. (Inferred)
Beachhead segment
SaaS sellers looking for leads in tech niches.
User profiles
Innovative seller
Sales representative at a tech startup
Daily pain:Hard to identify quality leads amid the noise of general-purpose platforms.
Workarounds
Summary
Today users rely on manual searches on Reddit and Hacker News, reading and sorting thousands of conversations without specific tooling.
Tools they use
Status quo cost
The time spent on these manual tasks is considerable, with a high chance of missing relevant conversations.
Switching barrier
Inertia toward free tools and familiarity with the current manual search method.
Competitors
Pricing: $70-$100 per month
What they do:Automate sales communication over email.
Gap:They don't focus on specific forums as a lead source.
Differentiate:Focus on personalizing the first touch based on the content of the complaint.
Pricing: $29 per user per month
What they do:Provide personality analysis to improve communication.
Gap:No focus on public conversations in forums.
Differentiate:Provide contextual suggestions based on forums, not only on profiles.
Pricing: From $75 per month
What they do:Make it easy to capture contact data for leads.
Gap:They don't integrate forum insights into prospecting.
Differentiate:Add automatic emotion analysis on forum conversations.
Pricing: N/A — possibly discontinued
What they do:Improve relationship building in sales.
Gap:Real-time collection of conversations on online platforms.
Differentiate:Focus on data freshness, with real-time updates from forums.
Pricing: From $39 per month
What they do:Offer tools for lead generation and email verification.
Gap:They don't cover the early phase of complaints and findings in forums.
Differentiate:Equip your tool to capture needs at the source of the conversation.
Porter
To respond, stand out by building unique integrations or personalization features.
To respond, offer premium features that justify the cost.
To respond, secure multiple API sources to avoid a single dependency.
To respond, build a strong customer base before new entrants do.
To respond, highlight your ability to deliver deeper, more actionable insights.
Market
Total market
Reachable segment
3-year capture
We assumed 3M potential tech users × 10% interested × $100/year = $300M TAM. SAM: focus on predominantly English-speaking markets, 30% = $90M. SOM: target 10% of the SAM = $9M.
Demand
Level
weakReddit posts about client frustrations suggest a related but indirect problem (see the post 'Client doesn't understand the value of services' in r/msp). Without MRR data there is no strong demand validation.
Payment signals
Adjacent tools like Reply.io and Crystal Knows are priced in the $29-$100 per month range.
What's missing
Direct indicators that users are actively looking for tools like LeadsRadar are missing.
Mom Test
“How do you find relevant conversations about your customers' problems today?”
How they are solving this right now
“Have you ever tried to automate this process?”
Previous attempts to find a solution
“What happens to you if you can't find suitable leads quickly?”
Consequences of not solving the problem
“Would you be willing to invest in a tool that improves this process?”
Willingness to pay
+1 more
Experiments
Problem landing page
Hypothesis
If I describe the problem clearly, then I will get measurable interest from sales professionals.
How to run it
Build a landing page that presents the lead identification problem in a clear headline. Include problem testimonials and an email capture form. Post it in sales forums and measure captures.
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A verdict backed by real evidence.
Describe your project and Scoutr cross-references Reddit, Hacker News, search demand and competitor revenue. You get BUILD, VALIDATE or KILL with the receipts attached, not an opinion.
Illustrative example
Every project in one hub.
Each diagnosed project keeps its verdict, fit score and signals. Compare them side by side and decide which one deserves your next sprint.
Illustrative example
Model the MVP with an agent that cuts scope.
The agent drafts your features from the validated report and sorts them into core, nice-to-have and out-of-scope, with a written reason for every call. Its whole job is stopping scope creep.
Illustrative example
Hand off a spec your coding agent can execute.
One click assembles features, acceptance criteria and rationale into a build-ready spec you paste straight into Claude Code, Codex or Cursor.
So, what are we validating?
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What Scoutr would tell you about these ideas.
Three possible verdicts, with the reason attached. Notice the KILLs: Scoutr also tells you when not to build.
AI Rust tutor for senior devs
Real demand and a viable beachhead; validate pricing with 5 conversations first.
AI meeting notetaker
The pain is real but already served: notetakers ship bundled with meeting platforms.
Pet adoption matchmaker
Strong emotional pull, weak willingness to pay; run the next two experiments before building.
CRM for indie therapists
Painful manual billing workflows and no dominant tool in the niche.
Crypto-tax helper for freelancers
Shrinking search demand and a compliance surface one person can't maintain.
Async retro tool for remote teams
Clear complaint threads, crowded space; differentiation hypothesis still unproven.
Illustrative examples
Hey, I'm the founder. I built scoutr by myself after watching two of my own projects die because nobody actually wanted them. This is the discovery work I wish I'd done first. If you ever get stuck or want to argue with a verdict, message me.
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