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C7 - Contingent Validity

C7. Contingent Validity (PMF can change)​

Construct: fit is valid under current market conditions (competition, channel, regulation, budgets, technology) and can change; PMF is not a permanent seal.

Application​

Fit is valid only under current conditions (competition, channel, regulation, budgets, technology). When those conditions change, you do not “lose PMF” in the abstract — you reopen the unit (C1) and retest C2–C6 in that slice.

Examples​

Example 1 — Platform rule change (Apple ATT) Unit (C1 summarized): D2C apps scaling via mobile ads → “acquire customers with predictable CAC” → performance/attribution stack → vs other networks/channels.

Current condition: attribution and targeting depended on cross-app identifiers/tracking.

Change: iOS 14.5+ requires permission via AppTrackingTransparency to track/access IDFA, changing measurement viability/quality for many ad operations.

C7 works: you treat this as a condition change and revalidate the unit: dominant channel shifts, CAC rises/volatilizes, and you need to retest C2 (persistence) and C4/C6 (preference/commitment without “channel subsidy”).

C7 does not work: you keep saying “we have PMF” because old retention still appears, ignoring that channel/measurement conditions changed (fit was partly “channel-fit”).

Example 2 — Change in the “channel system” (cookies / web ads) Unit: e-commerce players dependent on web retargeting → “recover cart and repurchase” → segmentation/ads tool → vs email/CRM/marketplaces.

Current condition: third parties could track/attribute via cookies with low friction.

Change (cookies): third-party cookie regime in Chrome shifted to “user choice” and keeps evolving; treat as contingent condition and revalidate C1–C6 whenever relevant change occurs.

C7 works: you assume channel is contingent and build alternatives (first-party, CRM, content, partnerships), retesting C4/C6 when substitution/costs change.

C7 does not work: you model thesis as a “permanent rule” and cannot operate when channel changes (fit depended on previous regime).

Example 3 — Technology change + bundling (LLMs inside suites) Unit: office teams that want to “produce text/insights faster” → writing/assistant tool → vs status quo (Word/Docs) + alternatives.

Current condition: “writing assistant” was a differentiated category, purchased as a separate tool.

Change: ChatGPT (launched Nov 30, 2022) and then copilots embedded in suites (e.g., Microsoft 365 Copilot integrated in Word/Excel/PowerPoint/Outlook) changed viable alternatives and willingness to pay.

C7 works: you reopen the unit: maybe ICP changes (who still pays outside the suite?), your whole offer changes (integrations/security), and you retest C4 (preference under real substitution) and C5 (terms/pricing accepted without concessions).

C7 does not work: you treat “PMF” as a seal and ignore that the alternative set changed radically (customer now “already has something good enough” embedded).

Example 4 — Budget / macro change (demand exists, but buying changes) Unit: collaboration/video conferencing for companies → “reduce remote-work friction” → platform → vs alternatives/suites.

Current condition: demand explodes in pandemic scenario.

Change: as normalization happens, boom cools down and enterprise spending slows; this changes buying environment and price pressure.

C7 works: you revalidate: C2 may differ (cadence changes), C5 may differ (pricing/delivery), and even C1 may differ (new segment where job remains strong).

C7 does not work: insisting on same ICP/offer as if market had not changed, and attributing everything to “poor execution” (when part is exogenous condition).

Checklist​

Treat these as unit “validity conditions” and monitor:

  • Competition/bundling (incumbent embeds feature)
  • Channel (targeting/attribution regime changes)
  • Regulation/platform policy
  • Budgets/buying cycle
  • Technology (new “good enough” changes alternatives)