By Dairon Canel · Founder, Proven · Updated June 2026
Glossary
What is a Pain Score?
A Pain Score is Proven's 0–100 measure of how real and intense a market problem is, based on live evidence from public discussions. It is not a prediction and not an AI opinion — it is a signal derived from what real people actually wrote about the problem.
What goes into the Pain Score
Three things feed into the score: volume, specificity, and emotional charge — the first three items in the startup validation checklist. Volume is how many posts mention the pain across Reddit, Hacker News, and App Store reviews. Specificity is whether posts describe a concrete frustration — lost time, lost money, a broken workflow — or a vague wish for something better. Emotional charge is how strongly the language signals genuine frustration versus mild inconvenience.
A pain that shows up in 40 posts where people describe losing clients or billing hours scores higher than a pain that shows up in 5 posts where people shrug and say it would be nice to have a tool for that. Both are real signals — but they are very different signals in terms of urgency, willingness to pay, and market readiness.
The three inputs are weighted and combined into a single number. No individual input dominates — a high volume of vague posts scores lower than a moderate volume of intensely specific ones. The goal is a score that reflects the strength of the pain signal, not just its size.
How to read the ranges
A score above 70 means strong, consistent evidence of real pain. Multiple sources, specific language, emotional charge — the market is actively expressing this problem and looking for solutions. This is the range where the signal justifies deeper investigation and, if the competitor map confirms a gap, a build decision.
A score between 50 and 70 means the signal is there but not yet urgent. The pain exists publicly, but the posts are fewer, less specific, or lower in emotional intensity. This often means the market is early — the problem is real but founders haven't seen enough pain yet to go looking for a product, or the product category hasn't been defined yet. Worth monitoring; not yet worth building.
Below 50 means the evidence is thin, vague, or absent in the sources Proven searched. This can mean the pain doesn't exist publicly at the scale needed to build a business, or that the description used to search for it needs to be reframed. A brief returning 35 is not a failed brief — it is honest data about what the market is expressing right now.
What a Pain Score is not
The Pain Score is not a market size estimate. A high score means the pain is publicly expressed with intensity — it says nothing about the total addressable market in dollars. A niche B2B pain talked about by 500 specialists on Reddit can score 80. A consumer pain talked about by millions casually might score 45.
It is not an AI opinion on whether your idea is good. The score is calculated from post signals, not from a model evaluating your concept. Two completely different ideas can score identically if the public evidence for their respective pains has the same volume, specificity, and emotional charge.
It is also not directly comparable across very different markets. A Pain Score of 65 in a narrow developer tooling niche means something different from a 65 in a broad consumer wellness category. The score is most useful as a signal within the context of a single brief — not as an absolute threshold that means the same thing for every idea.
Pain Score in practice
Two examples show what the ranges look like in context.
Reddit returns 40+ threads about billing nightmares — agencies describing specific client disputes, hours lost chasing approvals, revenue delayed by 30–60 days. Language is emotionally charged: “lost a client over this,” “billing is destroying my margins.” Multiple posts describe having tried existing tools and abandoned them. Pain Score: 82. Verdict: Build it.
Occasional mentions of async communication, mostly positive curiosity rather than frustration. Existing tools (Loom, Slack clips) are mentioned positively. No posts describe a specific workflow broken by the absence of this. Pain Score: 31. Verdict: Explore more before building.
Frequently asked questions
What's a good Pain Score to build on?
Above 70 is a strong signal, but the score alone is not enough — read the actual evidence posts. A 75 from vague, generic complaints is weaker than a 65 from specific, high-frequency descriptions of a concrete operational problem. The Pain Score tells you how much signal exists. The Pain Evidence section tells you whether that signal is the kind worth building on.
Can a low Pain Score mean the idea is bad?
Not necessarily. A low score can mean several things: the market talks about the pain in different language than you described, the problem is early and hasn't generated visible public discussion yet, or the pain is expressed in communities Proven doesn't search. Try reframing the pain description with different vocabulary and run another brief before drawing conclusions.
Is a Pain Score of 40 worth pursuing?
Depends on what's in the evidence. A 40 with 10 very specific, emotionally charged posts in a niche B2B market might be more actionable than a 70 with 60 vague consumer observations. Always read the actual evidence, not just the number. The score is a summary; the posts are the source of truth.
Does Pain Score affect the verdict?
Yes, it is a primary input. But the verdict also weighs competitor density, willingness-to-pay signals, and red flag patterns. A high Pain Score with a saturated competitor map and no visible gap might still produce an 'Explore more' verdict. A moderate Pain Score with clear competitor weaknesses and strong willingness-to-pay language might still produce 'Build it.'
Can Pain Scores change over time for the same idea?
Yes. Posts are fetched live at submission time, so the same idea submitted months apart can return a different score as the market discussion evolves. A problem gaining media attention, a competitor shutting down, or a shift in industry tooling can all change what's being said publicly about a pain.
See the Pain Score in context inside a Founder's Brief, or learn how Proven calculates it.
Written by Dairon Canel with AI assistance for research and structure.