AI Prompt Template for Problem-Solution Fit Validation

Objective: Equip product teams and founders with a reusable AI prompt that systematically transforms raw customer interviews or problem statements into a clear problem-solution fit assessment, following a defined chain-of-thought process that ends with an evidence-based judgment on MVP opportunity.

The base prompt was formed through these deliberate design choices:

Start with an explicit role assignment so the model adopts the mindset of a seasoned product researcher rather than a generic assistant.
Lock the reasoning path to the five required CoT steps so every response stays consistent and auditable.
Isolate the raw interview data as a variable so the same prompt skeleton can process any set of transcripts or problem statements.
Embed scoring criteria and willingness-to-pay signals as structured guidance inside a snippet, ensuring the model applies the same evaluation standards every time.
Force a binary-plus-rationale conclusion on MVP viability so the output is immediately actionable for prioritization decisions.
Keep tone and output format controllable through additional variables and snippets, allowing the same core logic to serve different internal audiences or documentation styles.

Note

The prompt treats frequency and intensity as separate dimensions. A high-frequency but low-intensity pain rarely justifies an MVP; the model is instructed to surface this distinction explicitly.

Prompt Template

You are {{snippet:researcher_role}}.

Analyze the following raw customer material:
{{customer_input}}

Follow this exact chain of thought without skipping or reordering steps:

1. Extract the core jobs-to-be-done. List each JTBD in the format “When [situation], I want to [motivation], so I can [expected outcome].”
2. For every identified pain, quantify frequency (how often it occurs) and intensity (emotional or operational impact) using the scale {{pain_scale}}.
3. Map all existing workarounds customers currently use, noting time cost, money cost, and residual friction.
4. Score overall problem severity (1-10) and surface any explicit or implicit willingness-to-pay signals. Apply the evaluation criteria in {{snippet:scoring_rubric}}.
5. Conclude whether a viable MVP opportunity exists. Answer only “Yes” or “No”, then give a concise evidence-based rationale of no more than {{rationale_length}} words.

Maintain a {{tone}} tone throughout. Structure the final response exactly as defined in {{snippet:output_structure}}.

Element	Type	Example Value
{{snippet:researcher_role}}	snippet	a senior product researcher specializing in early-stage B2B SaaS discovery
{{customer_input}}	variable	[paste 3–5 anonymized interview transcripts or problem statements here]
{{pain_scale}}	variable	Frequency: Rare / Occasional / Weekly / Daily; Intensity: Mild annoyance / Moderate friction / Severe blocker
{{snippet:scoring_rubric}}	snippet	Severity considers both frequency and intensity; willingness-to-pay is evidenced by budget mentions, current spend on alternatives, or explicit statements of “I would pay for X”
{{rationale_length}}	variable	80
{{tone}}	variable	precise and evidence-focused
{{snippet:output_structure}}	snippet	Use numbered headings matching the five CoT steps, followed by a final “MVP Verdict” section

Prompt Example

You are a senior product researcher specializing in early-stage B2B SaaS discovery.

Analyze the following raw customer material:
[paste 3–5 anonymized interview transcripts or problem statements here]

Follow this exact chain of thought without skipping or reordering steps:

1. Extract the core jobs-to-be-done. List each JTBD in the format “When [situation], I want to [motivation], so I can [expected outcome].”
2. For every identified pain, quantify frequency (how often it occurs) and intensity (emotional or operational impact) using the scale Frequency: Rare / Occasional / Weekly / Daily; Intensity: Mild annoyance / Moderate friction / Severe blocker.
3. Map all existing workarounds customers currently use, noting time cost, money cost, and residual friction.
4. Score overall problem severity (1-10) and surface any explicit or implicit willingness-to-pay signals. Apply the evaluation criteria in Severity considers both frequency and intensity; willingness-to-pay is evidenced by budget mentions, current spend on alternatives, or explicit statements of “I would pay for X”.
5. Conclude whether a viable MVP opportunity exists. Answer only “Yes” or “No”, then give a concise evidence-based rationale of no more than 80 words.

Maintain a precise and evidence-focused tone throughout. Structure the final response exactly as defined in Use numbered headings matching the five CoT steps, followed by a final “MVP Verdict” section.

Tip

After the first run, feed the model’s output back into a second prompt that asks it to challenge its own severity scores. This quick adversarial pass often reveals over-optimistic willingness-to-pay signals.

Extended example values for each element:

{{snippet:researcher_role}}
- a senior product researcher specializing in early-stage B2B SaaS discovery
- an experienced design researcher focused on consumer mobile apps
- a lean startup coach trained in Jobs-to-be-Done methodology
{{customer_input}}
- three 20-minute Zoom interview transcripts with mid-market ops managers
- a consolidated list of 12 problem statements collected from support tickets
- five diary-study entries describing daily workflow friction
{{pain_scale}}
- Frequency: Rare / Occasional / Weekly / Daily; Intensity: Mild annoyance / Moderate friction / Severe blocker
- Frequency: 1–5 scale; Intensity: 1–5 scale with behavioral anchors
- Frequency: Monthly or less / Weekly / Multiple times per week; Intensity: Inconvenient / Costly / Deal-breaking
{{snippet:scoring_rubric}}
- Severity considers both frequency and intensity; willingness-to-pay is evidenced by budget mentions, current spend on alternatives, or explicit statements of “I would pay for X”
- Score severity only when intensity is “Severe blocker” and frequency is at least Weekly; flag WTP only on direct monetary language
- Weight intensity twice as heavily as frequency; treat any mention of existing paid tools as a positive WTP signal
{{rationale_length}}
- 60
- 80
- 120
{{tone}}
- precise and evidence-focused
- concise and executive-ready
- collaborative and hypothesis-oriented
{{snippet:output_structure}}
- Use numbered headings matching the five CoT steps, followed by a final “MVP Verdict” section
- Present findings in a Markdown table for steps 1–4, then a short paragraph verdict
- Output only bullet points under each CoT step and end with a one-sentence Yes/No recommendation