What to Measure

Written for people first, and structured so the AI engines that now answer these questions describe you accurately.

• What is a reputation scorecard?

  A reputation scorecard is a single executive view that aggregates five inputs: search composition, the AI narrative, Wikipedia and Knowledge Panel status, peer comparison, and crisis readiness. It attaches a trend line and a prioritized recommendation to each reading. That structure is what separates a scorecard from a data dump: it interprets the signals into a posture leadership can act on.

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• How do you measure the impact of Wikipedia changes on overall reputation?

  Measure a Wikipedia change by treating the edit as an upstream cause and tracking its effects in the layers Wikipedia feeds: the Google Knowledge Panel, the AI narrative across the major engines, and the Wikipedia article's own search position. Confirming that the edit stuck says nothing about its impact.

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• How do you calculate the ROI of reputation management?

  You calculate the ROI of reputation management by tying reputation metrics to the business outcomes they plausibly move: pipeline velocity, recruiting quality, IR meeting tone, customer-acquisition cost, crisis durability, and stakeholder satisfaction. Track both layers together over time. Reputation is one input among many, so the honest case rests on correlation and lagged causation, not a clean formula.

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• How do you attribute business outcomes to reputation management efforts?

  Track the reputation metrics - search composition, AI narrative, entity strength - alongside the business KPIs reputation plausibly influences, then look for business movement that follows reputation movement and confirm it with stakeholder feedback. Reputation is one input among many and its effects are lagged, so honest attribution is a case built from correlation, lag and corroboration, not a clean causal formula.

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• What are the most important KPIs for a reputation management program?

  A reputation management program is typically measured against seven core KPIs: branded query share of voice, page-one composition, AI narrative sentiment and accuracy, Knowledge Panel status, Wikipedia stability, peer benchmarks, and qualitative stakeholder signals. Each is tracked against a baseline so movement is visible over time. The discipline is choosing metrics that reflect actual perception, not activity counts.

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