# Proof Authenticity Rubric ## Source: Influence: The Psychology of Persuasion, Chapter 4 Use this rubric when running Step 5 (Check for Manufactured Proof Risks) or Step 7 (Defense — Evaluate Incoming Social Proof) in the social-proof-optimizer skill. --- ## Authenticity Scoring Rubric Score each proof element on 5 dimensions. Total score determines classification. | Dimension | 2 — Authentic | 1 — Uncertain | 0 — Suspect | |---|---|---|---| | **Identification** | Full name, photo, role, company visible | Partial ID (first name only, or role without company) | No identifying details; anonymous | | **Specificity** | Concrete outcome, timeframe, or before/after detail | General positive sentiment with some context | Pure vague praise ("amazing," "best ever") | | **Source verifiability** | Verifiable via third-party platform (LinkedIn, G2, Capterra, App Store) | Partially verifiable (name exists, company exists, not directly linked) | Cannot be independently verified | | **Temporal distribution** | Reviews/testimonials accumulated over time, organic distribution | Some clustering, mostly organic | Large batch appearing suddenly (50+ in 30 days) | | **Consistency range** | Mix of strong positive, moderate positive, and constructive negative | Mostly positive with rare negative | 100% uniformly glowing; no specifics; no negatives | **Scoring:** - 9–10: High authenticity — use with confidence - 6–8: Moderate authenticity — use with transparency (add "typical results" note if needed) - 3–5: Low authenticity — risk flag; verify independently before using - 0–2: Manufactured proof — do not use; high credibility risk if exposed --- ## Manufactured Proof Taxonomy ### Level 1 — Direct fabrication (highest risk) Definition: Proof that does not correspond to any real customer experience. Examples: - Actors playing customers in "unrehearsed" interview ads - Purchased review packages (Fiverr, Trustpilot manipulation services) - AI-generated testimonials placed on the site - Planted converts at events (Billy Graham model) Risk: Criminal fraud exposure (FTC regulations), complete brand destruction if exposed. Do not use. ### Level 2 — Coerced or incentivized proof (high risk) Definition: Proof from real customers, but obtained under conditions that compromise honest representation. Examples: - Reviews obtained via "leave a 5-star review for a discount" programs without disclosure - Testimonials from customers who were threatened with loss of account if they didn't provide positive feedback - Reviews from employees or founders' personal networks without disclosure Risk: FTC violation (undisclosed material connection), legal exposure, audience trust destruction when exposed. Requires mandatory disclosure to be legal; still ethically problematic. ### Level 3 — Cherry-picked outlier results (medium risk) Definition: Proof from real customers reporting real outcomes, but the outcomes are not representative. Examples: - "Made $47,000 in 30 days" testimonial when the median customer makes $200 - Case study featuring 300% growth company when typical customer sees 15% growth - Highlighting only 5-star reviews while suppressing 1-star reviews that contain valid complaints Risk: FTC "typical results" requirement, audience trust erosion when customers compare promised vs. actual outcomes. Requires "results not typical" or "average customer sees X%" disclosure. ### Level 4 — Selective presentation (low risk) Definition: Proof from real customers reporting real representative outcomes, but only positive cases are featured. Examples: - Testimonial page showing all happy customers (no unhappy customers appear) - Case studies featuring only successful implementations - User counts that include churned users Risk: Confirmation bias in presentation, not fraud. Acceptable marketing practice. Mitigate by ensuring featured cases are representative, not extreme outliers. ### Level 5 — Seeded initial proof (context-dependent) Definition: Artificially initializing social proof to trigger authentic cascades. Examples: - Salting tip jars or collection baskets - Inviting friends/family to be first buyers or reviewers - Using waitlist count as launch-day proof (if the waitlist is real) - Giving product to influencers for genuine usage-based reviews (disclosed) Risk: Low if transparent about the source; high if the seeding is misrepresented as organic behavior. --- ## Defense Detection Checklist When evaluating social proof used by a competitor, partner, or product you are considering: ### Signs of deliberate falsification - [ ] No name, photo, or identifying detail on any testimonial - [ ] All reviews appeared within a short window (30 days or less for large volume) - [ ] 100% positive ratings with no constructive feedback on any platform - [ ] "Testimonial" subjects use stock photography or generic avatars - [ ] User count is unverifiable and has no third-party corroboration - [ ] Staged or scripted quality to quoted language - [ ] No presence of these customers on professional networks (LinkedIn) ### Signs of innocent cascade (pluralistic ignorance) - [ ] Everyone in a group is doing the same thing with no clear information advantage - [ ] The behavior started with an ambiguous trigger (one person switched, one person sold) - [ ] Asking participants why they are doing it produces "everyone else is" answers - [ ] Direct investigation of the underlying facts shows no actual signal ### Response protocol - Deliberate falsification confirmed → disengage automatic pilot; evaluate underlying product via independent channels; do not factor the social proof into your decision - Innocent cascade identified → check the objective facts directly; introduce independent information; do not join the cascade until you have verified the underlying basis - Uncertain → weight social proof at 50% of normal; prioritize independent verification --- ## FTC Compliance Notes (US Context) The Federal Trade Commission requires disclosure of material connections in testimonials: - Employees and contractors must disclose their relationship - Compensated testimonials require disclosure ("Paid partnership," "#ad") - Free products given in exchange for reviews require disclosure - Results testimonials must reflect typical customer outcomes, or provide a "typical results" disclosure Source: FTC Guides Concerning Use of Endorsements and Testimonials in Advertising (16 CFR Part 255). These rules apply to online testimonials, social media posts, and influencer content. Non-US contexts have similar or stricter requirements (EU, UK ASA). When operating internationally, confirm local disclosure requirements before using any incentivized testimonial.