How does Five Blocks measure success?
Five Blocks measures success against engagement-specific KPIs defined at the outset - typically search prominence for priority keywords, Knowledge Panel status and accuracy, AI narrative sentiment and source quality, Wikipedia article stability, and client satisfaction - with IMPACT and AIQ supplying the underlying quantitative data.
Five Blocks measures success against objectives defined at the outset of each engagement rather than against a single fixed scorecard. Because reputation goals differ by client – a public company defending a Knowledge Panel has different priorities than an executive correcting an AI narrative – the specific KPIs are agreed up front and then tracked over the life of the engagement. The quantitative data underlying these measurements comes from two proprietary platforms: IMPACT™ for search reputation and AIQ for AI narrative.
Common success metrics
- Search prominence
- The visibility of preferred content in search results for priority keywords, tracked daily through IMPACT™ across keywords, languages, and locations.
- Knowledge Panel status and accuracy
- Whether Google displays a Knowledge Panel for the entity and whether its facts are correct. Because panel content is generated automatically from Google’s Knowledge Graph – drawing chiefly on Wikipedia and Wikidata – accuracy is measured at the panel and at the underlying sources that feed it.
- AI narrative sentiment and source quality
- How AI engines describe the subject and which sources they draw on, monitored through AIQ across eight major AI engines.
- Wikipedia stability
- The status of the Wikipedia article and whether it stays accurate and stable over time – significant because the article feeds the Knowledge Panel and is among the most heavily weighted sources used by AI engines.
- Client satisfaction
- The client’s own assessment of whether the engagement met its stated objectives.

Why the metrics connect
These measures are not independent. A stable, accurate Wikipedia article tends to improve Knowledge Panel accuracy, which in turn shapes how AI engines describe the subject – so movement on one KPI often shows up in the others. Tracking them together, with IMPACT™ and AIQ supplying the numbers, is what lets an engagement show progress against the objectives set at the start.
Last reviewed: 19/05/2026