Evidence-first methodology

How ProblemSeekr Identifies Problems Worth Solving

ProblemSeekr is not an idea generator. It is a structured system for extracting, validating, and prioritizing real problems that people repeatedly complain about in public - before you invest time or money building solutions.

1. Data sources

We analyze large volumes of public, permissionless conversations where people naturally describe friction, workarounds, and unmet needs.

  • Public discussion forums and communities
  • Product feedback threads and complaints
  • Workflow, ops, and “how do you handle X?” conversations

We intentionally avoid surveys, prompts, or hypothetical questions. Everything starts from unsolicited, real-world pain.

2. Noise filtering

Not every complaint is a business opportunity. Before anything becomes a “problem brief,” it passes multiple exclusion filters.

  • One-off rants with no repetition
  • Pure feature requests for existing products
  • Problems that are vague, unserious, or non-actionable
  • Complaints with no clear user or context

What remains are problems that show repeated structure, intent, and frustration - not just emotion.

3. Problem clustering

Individual complaints are not useful on their own. We group similar expressions of pain into clusters that represent a shared underlying problem.

  • Different wording → same underlying workflow failure
  • Different tools → same structural bottleneck
  • Different roles → same unmet job-to-be-done

Each cluster becomes a single problem brief with supporting evidence.

4. Severity scoring

Severity is a directional score that helps you prioritize which problems are more likely to support a business.

Scores consider factors such as:

  • Frequency and repetition of the problem
  • How much time, money, or risk the problem creates
  • Whether users actively seek workarounds or alternatives
  • How emotionally charged or urgent the pain appears

A higher score does not guarantee success - but it signals stronger willingness to pay if solved well.

5. Expert reviewed problems

Some problem briefs receive an additional expert review layer.

Expert review evaluates:

  • Business model viability
  • Market maturity and saturation risk
  • Implementation complexity
  • Common failure modes

Expert review does not replace validation - it reduces blind spots.

What this is not

  • An AI idea generator
  • A list of guaranteed startup ideas
  • A replacement for customer interviews

ProblemSeekr helps you choose what to investigate - not skip validation.

How to use this methodology

  1. Start with a public problem brief or Explore.
  2. Run the guided flow to score and shape the opportunity.
  3. Validate with real users using the evidence as a starting point.