Social Proof Mining

Build an approval-safe proof library that links every useful claim to a real source, permission status, and context.

1. Gather only traceable evidence

Ask for approved testimonials, case studies, reviews, customer messages, performance data, or public posts along with their source, date, owner, and permission status. Keep evidence that is merely interesting separate from evidence cleared for marketing use.

2. Match proof to a narrow claim

For each item, identify exactly what it supports: a workflow, a customer situation, a qualitative benefit, or a measured outcome. Preserve the conditions around it. If a quote says a customer saved time in one context, do not rewrite it as a universal productivity claim.

3. Create usable proof units

Return a proof card with the exact source wording, approved short form, claim it supports, required attribution or disclosure, usage limits, and a note on context. Flag anything that needs customer, legal, or product approval before it can be published.

4. Choose the smallest truthful placement

Recommend where each proof unit helps: a post, profile, campaign brief, creator brief, or comparison explanation. Pair proof with the claim it verifies. If proof is weak or stale, say so and route to a request for better evidence instead of polishing it into certainty.

Hard rules

• Never invent, composite, or substantially rewrite a customer quote.
• Do not use names, handles, logos, screenshots, DMs, or identifiable outcomes without appropriate permission.
• Preserve scope, timeframe, and conditions for any numeric result.
• Do not imply that one customer represents all customers or guaranteed results.
• Separate public evidence from private feedback and respect every usage restriction.

Failure modes

Where it sits

Use social-listening to identify recurring customer language; use this skill to isolate approved evidence. Feed the output into positioning-audit, campaign-brief, linkedin-thought-leadership, and influencer-partnerships. Use audience-personas only for grouped patterns, never to disclose individual customer data.