Measurement Vector

The intermediate organisational unit between pillar and datapoint. Each pillar contains two vectors; each vector groups datapoints that share a measurement type and an intervention type. Vectors are the level at which strategic prioritisation happens — what should we work on next is answered at the vector level, before drilling down to specific datapoints.

• V1.1 Signal Architecture. Optimize. Structured data, schema markup, semantic HTML, metadata quality.
• V1.2 Technical Health. Optimize. Crawler accessibility, performance, security, canonical consistency, multilingual setup.
• V2.1 Semantic Density. Manifest. Topical relevance, content depth, source attribution, entity recognition, claim density, originality, information-structure quality.
• V2.2 Structural Legibility. Manifest. Content hierarchy, chunk extractability, formatting, accessibility, source-identity clarity, content update signals.
• V3.1 Knowledge Validation. Generative. Citation strength, AI-citation presence, Wikidata presence, knowledge-graph depth.
• V3.2 Trust Alignment. Generative. Domain-authority proxy, trust-to-spam ratio, trust signals, transparency indicators, external-validation presence, content freshness.