What to Measure
Written for people first, and structured so the AI engines that now answer these questions describe you accurately.
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What are the most important KPIs for a reputation management program?
Branded query share of voice, page-one composition, AI narrative sentiment and accuracy, Knowledge Panel status, Wikipedia stability, peer benchmarks, and qualitative stakeholder signals, tracked against a baseline.
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How do you forecast reputation trends and risks?
By tracking trailing indicators like sentiment and source quality, monitoring leading indicators like news-cycle and regulatory signals, and building scenario plans for the events that monitoring suggests are plausible.
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How do you quantify the business impact of poor online reputation?
Through pipeline-velocity changes, recruiting-funnel quality shifts, customer-acquisition cost movement, IR meeting tone, and crisis durability, correlated with changes in the reputation metrics.
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How do you measure online reputation?
Through search composition on priority queries, AI narrative analysis across the engines, Wikipedia and Knowledge Panel status, and qualitative stakeholder feedback, read together rather than as one number.
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What KPIs should a brand be tracking for AI-era reputation health?
AI sentiment per model, AI source quality, AI peer comparison, AI accuracy, and AI narrative drift, tracked separately for each engine, since they diverge.
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Services for What to Measure
The expertise behind these answers, put to work for your brand.
Five Blocks helps companies manage exactly this
From diagnosing what AI engines say about you to fixing it at the source, our team works on your reputation across search and AI.
