Analyze Demand

For a defined industry, produce a structural demand-side analysis. Output: demand.md that names the JOB the industry's customers are hiring solutions to perform, segments by that job (not demographics), and surfaces substitution risk before it shows in share data.

The discipline: Demand-side analysis is the early-warning system for disruption. Five Forces tells you the structure; profit pools tell you where the money sits today; competitive arena tells you who is winning. Demand analysis tells you whether the question being asked is about to change. JTBD originated in product design; at industry-analysis level it aggregates outcomes across the buyer population to spot cross-category substitution before market-share data moves.

Iron rules:

• Every fact-claim carries a V/C/A/I tag — see ../_shared/provenance-tagging.md.
• ≥1 JTBD identified with ALL THREE components (functional / emotional / social) named — even if a component is "minimal" or "absent," state it explicitly. Do not omit.
• ≥2 customer segments defined by the job they hire the product to do, not by demographic or firmographic attributes. "Young urban professionals" or "mid-market SaaS companies" fail this test; "buyers hiring the product to reduce time-to-decision in regulatory submissions" passes.
• ≥1 substitution risk with named substitute candidate (cross-category preferred), explicit switching cost, and stated likelihood. Naming "general competition" or "other vendors" fails.
• Substitution analysis section MUST use the standard heading ## Substitution Risk (exact wording, level-2 heading). Downstream consumers parse by heading; variants fail.
• WTP drivers stated per segment — NOT a single price. Drivers explain WHY this segment will or won't pay.
• ≥1 named demand signal with a measurable leading indicator (search trend, channel check, expert-interview language shift, regulatory filing shift, etc.). Lagging metrics like revenue fail.

Process

1. Intake — lock the analysis frame

Confirm: industry slug, geographic scope, B2B / B2C / hybrid, focal value-chain layer (must match the layer used in map-five-forces if running in orchestrator mode), buying-unit definition (individual / household / SMB / enterprise procurement committee). Read references/jtbd-methodology.md and references/customer-segmentation.md. Note any substitution threats already flagged in working/five-forces.md (orchestrator mode) — they are the priority candidates to chase in step 4.

2. Identify the Job(s)-to-be-Done

Read references/jtbd-methodology.md. For this industry, name the primary JOB customers are hiring solutions to perform. Express as job-as-process, not job-as-attribute (Ulwick): "[verb] [object] [contextual qualifier]" — e.g., "minimize time-to-decision for a regulatory submission under FDA Q-Sub review." For each identified JTBD, name all three components:

• Functional job — the task being done (always present; the easiest to articulate)
• Emotional job — the feeling the buyer wants to achieve or avoid (career-risk minimization, confidence, control). In B2B, this is real and usually under-stated.
• Social job — how the buyer wants to be perceived (innovative, prudent, cost-conscious, modernizer)

If a component is genuinely minimal, state "Emotional job: minimal — purchase is routinized procurement with no career exposure" rather than omitting. Each JTBD carries ≥1 tagged evidence claim.

For B2B industries, additionally map jobs across the buying committee — read references/jtbd-methodology.md "B2B multi-stakeholder JTBD" section. Different stakeholders (economic buyer, technical evaluator, user, procurement) often have DIFFERENT jobs for the same purchase.

3. Segment by JTBD, not demographics

Read references/customer-segmentation.md. Define ≥2 customer segments grounded in the job they are hiring the product to do. Each segment needs:

• Segment name — describes the job-context, not the buyer demographic
• Distinguishing JTBD or outcome-priority pattern — what makes this segment hire the product differently
• Approximate size or weight in the market (V/C/A/I-tagged)
• Why this segment is structurally distinct — what would cause it to switch differently than other segments

Anti-pattern (REJECTED): "Mid-market enterprises in financial services," "Gen-Z consumers," "manufacturers with >$500M revenue." These are demographic/firmographic boxes, not jobs. Correct pattern (ACCEPTED): "Buyers hiring the product to compress a 6-week manual reconciliation cycle into a single audit-ready report," "Buyers hiring the product as career insurance against a known regulator escalation."

The validator scans for demographic-only segment names and fails outputs that show segmentation by attribute rather than job. If a segment is named demographically but its definition is genuinely job-based, restate the name to lead with the job.

4. Substitution risk per segment

Read references/substitution-risk.md. The section heading must be exactly `## Substitution Risk` (verbatim wording, level-2 heading). Downstream consumers (Five Forces reconciliation, analyze-trajectory cross-category-substitute scan) parse this section by exact heading match. Variants like "Threat from Adjacent Categories", "Substitutes", or "Cross-Category Risk" fail validation.

For each segment, name the leading substitute candidates — cross-category preferred. A substitute is anything else the buyer could hire to perform the same JOB, including:

• In-category competitors (weakest substitute analysis — usually already in Five Forces)
• Cross-category substitutes (Zoom for travel, Airbnb for hotels, GLP-1 for snack food + diet programs, ChatGPT for Google search + entry-level analyst work, AI coding assistants for offshore dev labor)
• DIY / in-house build
• Do-nothing (the most common substitute; explicitly assess)

For each named substitute, state:

• Switching cost — financial + workflow + skill + psychological (cite anchor)
• Likelihood over 3-yr horizon — Low / Moderate / High with reasoning
• Trigger event that would accelerate substitution — what would have to be true

At least ONE substitution risk must name a specific candidate with these three fields filled. "Generic competitor pressure" fails.

5. Willingness-to-pay drivers per segment

Read references/wtp-drivers.md. For each segment, identify the DRIVERS of willingness to pay — not a single number. Drivers explain why this segment's price ceiling sits where it sits. Examples:

• "Regulated buyers in segment A will pay 3-5x premium for documented compliance proofs because non-compliance carries seven-figure fines [V: FDA 483 history]"
• "Self-serve developer-tooling buyers in segment B will not pay until usage exceeds free tier ~2x because the procurement friction is higher than the rational threshold [C: PriceBeam B2B WTP study 2024]"
• "Consumer segment C exhibits steep WTP cliff at $X where category framing shifts from impulse to considered [A: vendor pricing test, single data point — confirm]"

Distinguish B2B vs B2C explicitly: B2B WTP is dominated by ROI quantification + procurement-committee risk aversion; B2C WTP is dominated by perceived value at point-of-purchase + reference pricing. State your method anchor (Van Westendorp / conjoint / value-theory / expert-elicit) when available.

6. Name ≥1 leading demand signal

Read references/demand-signals.md. Identify at least one MEASURABLE LEADING INDICATOR that would surface a demand shift before it appears in share data. Required format:

• Signal name — what to watch
• Measurement source — where the indicator lives (Google Trends, app-store rank, GitHub stars, distributor reorder cadence, regulatory filing keyword frequency, expert-interview language shift, job-posting taxonomy)
• Threshold — what level of change constitutes a meaningful shift
• What it would mean — the structural shift the signal would imply

Lagging indicators (revenue, share, NPS) fail this check. A demand signal is something you could observe BEFORE the market noticed.

7. Cross-reference Five Forces (orchestrator mode)

If working/five-forces.md exists in the same industry folder, reconcile: every substitution threat flagged in Five Forces "Threat of Substitutes" must appear here with deeper treatment. If Five Forces flagged a threat that this analysis cannot find a JTBD basis for, flag for Gate 2 — one of the two is wrong. If standalone mode, add note: "Five Forces cross-reference deferred — five-forces.md not present."

8. Append structured next_skills YAML block

End the output file with:

---
next_skills:
  - map-competitive-arena    # demand-side findings inform supply-side competitive mapping
  - analyze-trajectory    # cross-category substitution candidates often signal trajectory shifts
  - assess-moat-sources    # WTP drivers reveal which moat types matter most in this industry
---

At least one skill must be listed.

9. Validate + write output

Run python scripts/validate_demand.py --output-path <path> — checks: ≥1 JTBD with all 3 components, ≥2 JTBD-based segments (no demographic-only names), ≥1 named substitution risk with switching cost + likelihood, WTP drivers per segment, ≥1 named demand signal with measurement source, V/C/A/I tag coverage, next_skills: YAML block. Write to working/demand.md (orchestrator) or standalone/analyze-demand-YYYY-MM-DD.md (standalone).

HTML on request (standalone only): markdown is the default and the only format the validator and the orchestrator consume. If the user explicitly asks for an HTML version of a standalone run, then after validation passes, also render the output via the html-output skill and review it per ../_shared/output-conventions.md § "HTML deliverables and quality review". Never produce HTML automatically.

Gotchas

• Symptom: segments named "Enterprise buyers," "SMBs," "Gen-Z consumers." Cause: demographic/firmographic segmentation imported from marketing. Fix: validator flags demographic-only segment names and fails. Restate segments by the JOB the buyer is hiring the product to do.
• Symptom: B2B JTBD lists only functional job; emotional and social marked "N/A." Cause: drafter believes B2B is purely rational. Fix: validator requires all three components named. Career-risk minimization is an emotional job; "modernizer / cost-conscious procurement" is a social job. State explicitly even when modest.
• Symptom: substitution section lists only direct in-category competitors. Cause: substitute defined too narrowly. Fix: at least one cross-category substitute or "do-nothing" candidate is expected. The validator requires named substitute candidates (not "general competition") with switching cost AND likelihood.
• Symptom: WTP stated as a single price ($X per seat per month). Cause: confused product pricing with industry WTP-driver analysis. Fix: state DRIVERS that explain why the segment's price ceiling sits where it sits — regulation, ROI, reference pricing, procurement friction, etc.
• Symptom: demand signal listed as "revenue growth" or "market share." Cause: lagging indicator confused with leading. Fix: signal must be observable BEFORE the shift hits financial results — search trends, channel checks, expert-interview language, job-posting taxonomy, regulatory filings.
• Symptom: product-design-flavor JTBD ("user wants the button to be blue"). Cause: Ulwick/Christensen applied at wrong altitude. Fix: at industry-analysis level the JOB aggregates across the buyer population — it is the question the industry exists to answer, not a feature spec.

Rules

• Never accept demographic/firmographic segmentation as a substitute for JTBD-based segmentation.
• Never omit emotional or social jobs from B2B analyses — state them explicitly, even if modest.
• Never list substitutes as "general competition" or "other vendors" — name candidates with switching cost and likelihood.
• Never rename the substitution section heading. The exact wording ## Substitution Risk is required for downstream consumer consistency.
• Never state WTP as a single number without driver decomposition.
• Never present lagging indicators (revenue, share) as demand signals.
• Every fact-claim carries a V/C/A/I tag.
• All file reads use encoding='utf-8'.

Old patterns

None yet — v1 (2026-05-18 initial build, Phase 2 of industry-analysis collection).

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