No True Scotsman
Reframe objections by redefining criteria to align prospects with ideal customer traits
Introduction
No True Scotsman is a logical fallacy where a broad claim is protected from counterexamples by arbitrarily redefining the category after the fact. When evidence contradicts the claim, the speaker says the counterexample does not belong to the “true” group. This misleads reasoners by changing definitions midstream, insulating beliefs from disconfirmation, and confusing audiences about standards.
This article explains the structure of the fallacy, why it persuades despite being invalid, and how to identify, avoid, and counter it across media, business, and sales contexts.
Sales connection: In sales conversations, No True Scotsman appears when reps or buyers dismiss inconvenient cases as outliers or “not real customers,” when ROI misses are blamed on “non-ideal implementations,” or when churn is excused as “not our ICP.” These moves erode trust, distort qualification, and harm close rates and retention.
Formal Definition & Taxonomy
Definition
No True Scotsman occurs when someone asserts a universal claim about a group, encounters a counterexample, and then redefines the group to exclude that counterexample without a principled rule. Pattern:
1.All X are Y.
2.Counterexample: here is an X that is not Y.
3.Response: No true X is not Y, so that X does not count.
Taxonomy
•Category: Informal fallacy
•Type: Fallacy of presumption and ambiguity
•Family: Ad hoc redefinition to evade falsification; a relevance error because the reply does not address the evidence but changes terms
Commonly confused fallacies
•Ad hoc rescue: Any improvised fix to save a hypothesis. No True Scotsman is a specific ad hoc fix via category redefinition.
•Straw man: Misrepresents an opponent’s view to make it easier to attack. No True Scotsman redefines the proponent’s own claim to dodge a counterexample.
Sales lens - where it shows up
•Inbound qualification: “Our leads are high intent.” When shown low-intent leads: “Those were not true inbound.”
•Discovery: “Our ICP always buys.” When a qualified prospect does not buy: “They were not a true ICP.”
•Demo: “Adopters see quick time to value.” When a slow adoption appears: “That was not a true deployment.”
•Proposal: “Our 5x ROI is universal.” Missed ROI becomes “not a true use case.”
•Negotiation or renewal: “Happy customers never churn.” A churned customer becomes “not a true customer.”
Mechanism: Why It Persuades Despite Being Invalid
The reasoning error
The fallacy protects a universal claim by shifting definitions after confronting evidence. Instead of revising the claim or the confidence in it, the speaker narrows the category to keep the statement unfalsified. This is logically invalid because the conclusion is maintained not by reasons but by changing the meaning of terms. It also risks unsoundness because the premises become vague or false under the new, ad hoc definition.
Cognitive principles that fuel it
•Confirmation bias: We seek and preserve belief-consistent evidence, dismissing disconfirming cases as exceptions.
•Motivated reasoning: Identity and incentives make it emotionally costly to concede counterexamples.
•Fluency effect: Simple, clean narratives like “our ICP always succeeds” feel true and are easier to defend than nuanced ones.
•Reactance and face-saving: When challenged, people resist conceding and instead adjust definitions to avoid status loss.
Sales mapping
•Confirmation bias → cherry-picked case studies; outliers labeled “not real customers.”
•Motivated reasoning → pipeline optimism is preserved by redefining ICP post hoc.
•Fluency effect → polished ROI slides oversimplify reality, and exceptions get excluded linguistically.
•Face-saving → in renewal conversations, churn is reclassified to avoid responsibility.
Language and structure cues
•“No real X would do that.”
•“Those are not true users/customers/enterprise accounts.”
•“Real use cases do not have that problem.”
•“A genuine implementation never fails.”
•Sudden addition of qualifiers: “true,” “real,” “proper,” “authentic,” “serious,” “enterprise-grade.”
Triggers in everyday contexts
•Metrics reviews where failing data points get labeled “not representative.”
•Social or media debates that dismiss counterexamples as “not real members of the group.”
•Postmortems that retroactively narrow scope definitions to explain away defects.
Sales-specific cues
•Slide patterns where the “addressable market” shrinks after losses to preserve a universal success claim.
•ROI calculators that exclude negative cases with vague criteria like “improper configuration.”
•Competitive traps: “No real enterprise chooses Vendor B.”
Examples Across Contexts
Each example shows the claim, the fallacy, and a stronger alternative.
Public discourse or speech
•Claim: “No true environmentalist would support nuclear energy.”
•Why fallacious: Redefines “environmentalist” to exclude those who do, evading debate about tradeoffs.
•Stronger version: “Some environmentalists support nuclear for low-carbon baseload. Let’s compare lifecycle emissions, cost, and risk.”
Marketing, product, or UX
•Claim: “No real power user needs onboarding.”
•Why fallacious: Excludes power users who do need onboarding, protecting a design assumption.
•Stronger version: “Segmented research shows 42 percent of advanced users still need expert onboarding for feature discovery.”
Workplace or analytics
•Claim: “No true data-driven team would ship without an A/B test.”
•Why fallacious: Redefines “data-driven” to exclude valid exception handling under constraints.
•Stronger version: “We prefer A/B testing, but under time constraints we use quasi-experiments with explicit risk documentation.”
Sales - discovery, demo, proposal, or objection
•Claim: “No true ICP churns.”
•Why fallacious: Excludes churned accounts to preserve the ICP claim.
•Stronger version: “Churn within ICP segments is 6.8 percent vs 11.4 percent overall. Here are drivers and mitigations.”
How to Counter the Fallacy (Respectfully)
Step-by-step rebuttal playbook
1.Surface the structure
2.Clarify burden of proof
3.Request the missing premise or evidence
4.Offer a charitable reconstruction
5.Present a valid alternative
Reusable counter-moves or phrases
•“Let’s pre-register the definition before viewing results.”
•“Can we specify necessary and sufficient criteria for ‘true’ membership?”
•“If exceptions exist, the statement should be probabilistic, not universal.”
•“Let’s measure outcomes by clearly defined segments rather than exclude cases post hoc.”
•“What evidence would count against our claim under the current definition?”
Sales scripts that de-escalate
•Discovery: “You mentioned ‘true ICP always buys.’ Could we list objective ICP criteria and review recent losses that met them?”
•Demo: “Rather than say every ‘real deployment’ sees 5x ROI, we’ll show median ROI and variance by segment.”
•Proposal: “To avoid redefining success later, let’s agree on inclusion criteria and KPIs now.”
•Negotiation: “If an edge case underperforms, we'll analyze it as part of the defined cohort, not exclude it.”
•Renewal: “We will treat your account as in-scope under the agreed ICP and review outcomes accordingly.”
Avoid Committing It Yourself
Drafting checklist
•Claim scope: Avoid universal quantifiers like “all,” “never,” “every.”
•Evidence type: Report distributions and variance, not only medians.
•Warrant: Make definitions explicit and stable across the analysis.
•Counter-case: Acknowledge and quantify exceptions.
•Uncertainty language: Use ranges and conditions where the claim applies.
Sales guardrails
•Define ICP, inclusion criteria, and success metrics before pilots.
•Publish ROI methodology and do not retroactively exclude misses.
•Report segment-level outcomes and confidence intervals.
•Document when a case is out-of-scope in advance, not after results.
•When in doubt, run a bounded pilot instead of asserting universals.
Before and after - sales argument
•Weak (No True Scotsman): “No true enterprise customer fails to realize value with our platform.”
•Strong (valid and sound): “Among enterprises meeting pre-defined criteria A, B, and C, 84 percent reach target KPI within 90 days. Here is the full distribution and the exceptions with causes.”
Table: Quick Reference
| Pattern/Template | Typical language cues | Root bias/mechanism | Counter-move | Better alternative |
|---|---|---|---|---|
| Post hoc purity test | “No real X would do Y.” | Confirmation bias | Ask for pre-registered definitions | Specify criteria upfront and test |
| Excluding misses | “That churned logo was not our true ICP.” | Motivated reasoning | Freeze scope before results | Report segment outcomes including misses |
| Universal success claim - sales | “All proper deployments hit 5x ROI.” | Fluency effect | Replace universal with conditional probability | Publish median, variance, and conditions |
| Competitive framing | “No serious company picks Vendor B.” | Face-saving, status dynamics | Request market share and objective comparisons | Head-to-head criteria and transparent benchmarks |
| Dashboard hygiene | “Those incidents are not from real users.” | Self-serving bias | Keep user definitions constant | Count all users that meet predefined rules |
(Contains at least 2 sales rows.)
Measurement & Review
Lightweight audits for No True Scotsman
•Peer review prompts: “Are definitions changing after results are seen?” “Would this account have been considered in-scope if it had succeeded?”
•Logic linting checklist: Flag words like “true,” “real,” “proper,” “authentic,” “serious,” “genuine.”
•Comprehension checks: Ask a colleague to restate the inclusion criteria. If they cannot, the category is too vague.
Sales metrics tie-in
•Win rate vs deal health: Watch for inflated win rates that depend on redefining ICP after losses.
•Objection trends: Buyers pushing back on universal claims signal definition drift.
•Pilot-to-contract conversion: Require pre-specified inclusion and success metrics to avoid post hoc exclusions.
•Churn analytics: Track whether churn is systematically reclassified as “out of scope” after the fact.
Guardrails for analytics and causal claims
•Pre-register definitions, success metrics, and stop rules.
•Use holdouts or matched cohorts to compare segments fairly.
•Document confounds and edge-case policies before data collection.
•Not legal advice.
Adjacent & Nested Patterns
•Shifting goalposts: Raising the standard after evidence appears is often paired with No True Scotsman.
•Ad hominem or straw man in competitive take-downs: Redefining “real customers” while attacking competitor users.
•Boundary conditions in sales: A legitimate scope statement is not fallacious if defined before results. Example: “This pilot excludes teams without data integration due to API limits.” That is a principled exclusion, not an ad hoc rescue.
Conclusion
No True Scotsman is tempting because it protects identity, brand narratives, and simple stories. But moving the goalposts dissolves credibility, blocks learning, and misguides decisions. The disciplined alternative is to define terms beforehand, welcome counterexamples, and update beliefs when reality speaks.
Sales closer: Stable definitions and transparent evidence build buyer trust, sharpen forecasts, and support durable retention.
End matter
Checklist - Do and Avoid
Do
•Pre-register category definitions and inclusion criteria.
•Use conditional claims with clear boundary conditions.
•Show full distributions, not only highlights.
•Treat counterexamples as data, not disqualifications.
•In sales, tie ICP to objective traits and publish them.
•Record reasons for exceptions before outcomes are known.
•Share methodology appendices with buyers for trust.
•Review claims quarterly against observed variance.
Avoid
•Adding “true,” “real,” or “proper” to exclude inconvenient cases.
•Universal claims that admit no exceptions.
•Redefining ICP after a loss or churn.
•ROI universals like “everyone gets 5x.”
•Filtering dashboards to hide negative cohorts.
•Using purity language in competitive framing.
•Treating definition changes as harmless admin updates.
Mini-quiz
Which statement contains No True Scotsman?
1.“Any customer meeting criteria A, B, and C usually reaches the KPI within 90 days.”
2.“That customer failed, but no true ICP fails, so they were not a true ICP.” ✅
3.“Some ICP segments need longer onboarding, so we model staggered value capture.”
References
•Flew, A. (1975). Thinking About Thinking. Fontana. [Origin of the label commonly attributed to Flew; if edition details vary by source, provenance may be imprecise.]**
•Walton, D. (2015). Informal Logic: A Pragmatic Approach (2nd ed.). Cambridge University Press.
•Copi, I. M., Cohen, C., & McMahon, K. (2016). Introduction to Logic (14th ed.). Pearson.
•Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
This article distinguishes logical invalidity - changing definitions to avoid refutation - from unsoundness, where even a neatly defined argument may rest on false or incomplete premises.
Last updated: 2025-11-13