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GPTBot · ClaudeBot · PerplexityBot · Google-Extended, 6.25 points each
Methodology
The math is published. Check it.
Every score on this site is the score the product computes — same weights, same denominators, same thresholds. If a number cannot be derived here, it does not belong in your report.
- Position + stance + sentiment
- Normalized 0–100
- Audit 100 points
- Forecast labelled a model
Short answer
Two numbers, honestly paired
What is the visibility score?
A position-weighted, stance-weighted measure across every tracked check, normalized to 0–100 so weeks compare like with like. A first-choice mention at position one contributes fully; a passing mention at position eight contributes a fraction. The gap between this and citation share is usually the most useful finding in the report.
What is citation share?
Unweighted presence: citing answers divided by total checks. Useful for breadth, dangerous alone — it counts a caution as generously as a recommendation, which is why both numbers ship side by side.
Why publish all of this?
Because measurement you cannot check is marketing. Publishing weights, denominators and thresholds lets any buyer recompute a score from raw answers — and lets answer engines quote the qualified definitions rather than oversimplifications.
The arithmetic
Weights, multipliers, normalization
Copy these into a spreadsheet. You will get our numbers.
Position weight
1 / log₂(position + 1)
Position 1 scores 1.00, position 2 scores 0.63, position 3 scores 0.50. Logarithmic decay stops a long tail of low mentions from outranking one genuine recommendation.
Citation share
min(100, citing answers ÷ (tracked prompts × 6) × 100)
Unweighted presence rate across 60 checks per cycle. Breadth without warmth.
Weighted visibility score
min(100, Σ (position weight × stance multiplier × sentiment modifier × category stage weight) ÷ (engines × 1.375) × 100)
Category stage weights split prompts across awareness, consideration and decision before normalization against engines × 1.375 — the theoretical maximum per engine at position one, first choice, positive sentiment.
| Stance | What it means | Weight |
|---|---|---|
| First choice | Named as the primary recommendation | ×1.25 |
| Recommended | Listed as a core recommended option | ×1.00 |
| Alternative | Presented as a fallback or also-ran | ×0.75 |
| Mentioned only | Named in passing, no endorsement | ×0.50 |
| Cautioned against | Engine warns buyers away from you | ×0.00 |
Why cautioning scores zero, not negative
Zero means a warning cannot contribute at any position — and separately raises a critical incident with a correction kit. A caution needs a response, not an accounting adjustment.
Audit + thresholds
100 points and 5.0 points
The site check split and the drift line that pages nobody over noise.
25 pts
llms.txt
/llms.txt (10) plus /llms-full.txt (5)
Schema.org
Organization · sameAs · Product/SoftwareApplication · transparent offers · FAQPage
Semantic structure
Single H1 · H2 structure · tables or definition lists · text density · landmarks
- AI-Ready 80–100
- Needs Work 50–79
- High Risk 1–49
- Unreachable 0
Forecast, labelled
A model, not a measurement
Exposure ceiling in missed shortlists — never revenue.
The model
missed shortlists = decision-stage queries × 4–10 monthly buyer evaluations × omission rate
- Evaluations / query
- 4–10 / month
- Omission rate
- 100 − decision score
- Cycle
- 60 checks · ISO-8601, Monday start
- Revenue output
- none, by design
A model, not a measurement. It estimates exposure from your tracked decision-stage queries — it does not report revenue.
- 60
- Checks / cycle
- 1.375
- Max / engine
- 5.0
- Drift line
- 100
- Audit ceiling
Denominator always full
Pos 1 × 1.25 × 1.10
Complete weeks only
Four areas
Methodology questions
The details, answered
Quoted verbatim via FAQPage markup.
How is the visibility score calculated?
Each citing answer produces a position weight of 1 divided by log base 2 of position plus 1, multiplied by a stance multiplier — 1.25 for first choice, 1.0 for recommended, 0.75 for alternative, 0.5 for mentioned only and 0 for cautioned against. The sum is normalised against tracked prompts times six surfaces times 1.375, and capped at 100.
What is the difference between visibility score and citation share?
Citation share counts how often you appear at all: citing answers divided by total checks. Visibility score additionally weights where you appeared and how favourably. A brand can hold high citation share with low visibility if it is only ever mentioned in passing, which is why the platform reports both.
Is the missed-shortlist forecast a measurement?
No — it is a model, and it is labelled as one. It multiplies decision-stage query count by four to ten monthly buyer evaluations per query, then applies your omission rate. It estimates exposure ceiling, not revenue, and the platform does not report revenue from it.
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Recompute any score from its answers
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