Methodology
Published in full — a score nobody can check is a score nobody should trust
What one observation is
An answer naming a competitor but not the tracked brand still counts in the denominator — being absent is a result. An answer naming no brand at all is excluded, because nobody lost it.
Two data sources
Search surfaces
default- Brand order
- From the export
- Demand weighting
- Available
Named AI models
- Brand order
- Extracted by us
- Demand weighting
- Not available
Visibility score
The headline number
Reach = answers naming the brand
÷ all answers in scope
Prominence = mean attention, where present
Quality = mean quality gate, where present
Score = 100 × ( R^0.4 × P^0.3 × Q^0.3 )^1Quality gate
One verifiable sub-gate today: whether the brand's own domain was among the sources the model used. 1.0 if yes, 0.6 if no. Spec correctness and market availability need retailer and catalogue data this export does not carry.
λ = 1
Presentation only — mathematically cannot change ranking order. Published and frozen because it is the most gameable constant here.
Attention by rank
1 / log₂(rank + 1) — the standard information-retrieval discount, borrowed not invented
Competitive rating
Every answer naming two or more brands becomes a set of matches
P(a beats b) = e^θa / (e^θa + e^θb) θ fitted by MM iteration to reproduce the observed record, normalised Σθ = 0. Strength = 1500 + 400θ / ln(10)
No chosen weights
Nothing here is tuned — the rating is whatever best explains the match record. That is why the fit check is published beside it on the Competitive page.
Half-win prior
Each observed pair carries a half-win each way. Without it a brand that never loses has no finite rating and the fit silently degenerates.
Confidence
Bootstrapped over 300 resamples, seeded so results are reproducible
Two brands whose intervals overlap are not meaningfully different, and the overview says so in words rather than presenting a ranking the data does not support.
Suppression thresholds
A dash is more honest than a precise-looking number built on nothing
Below this the score shows — instead of a number.
Below this the score shows — instead of a number.
Known limitations
Quality is half-built
Two of four intended gates — spec correctness and market availability — need retailer and catalogue data not in these exports.
No time dimension
The primary export carries no date, so this is a snapshot rather than a trend.
Rank inferred on the model source
Reliable for ranked lists, rougher for flowing prose.
Short brands need an allowlist
LG, HP, 3M and GE are two characters. A length filter silently deleted them during development, so the allowlist is explicit and visible.
Entity list is not exhaustive
Retailers and marketplaces are separated from brands by an explicit list — auditable, but incomplete.
Not externally validated
Reproducible and defensible. Whether the scores predict commercial outcomes is still open.
Ingested 2026-08-11T06:07:31Z · /sessions/zealous-beautiful-gates/mnt/categories