Metrics explanation

How Score, Visibility, and Position are calculated from AI model responses.

Example scenario: BrandX & "Best Smartphones"

Assume we track BrandX across 4 queries, with 2 AI models (ChatGPT + Perplexity) per query.

Query: "top smartphones 2024"
- BrandX at positions 2, 7 (best: 2)
- BrandX at positions 4, 9 (best: 4)
Query: "best android phone"
- BrandX at positions 5 (best: 5)
- BrandX at positions 3 (best: 3), domain at 5
Query: "iphone vs samsung"
- BrandX not found
- BrandX domain at 6
Query: "latest google pixel review"
- BrandX not found
- BrandX not found

Total queries: 4. Total responses: 8. Responses with BrandX: 4. Queries with BrandX: 2.

Key distinction: responses vs queries

Most metrics (Score, Position, Total Mentions) are based on responses: each model answer counts separately (1 query × 2 models = 2 responses). If BrandX appears multiple times in one response, only the best (lowest) position is used.

Only "Distinct Queries" metrics count unique queries (1 query × 2 models = 1 distinct query).

Score (0-100)

Score converts brand position in AI answers into a normalized value from 0 to 100. Higher is better.

Let N be total responses, Pi the best position in response i, and M the max position considered (30).

If Pi = 1, then NVi = 1.
If Pi >= M or not found, then NVi = 0.
Otherwise, NVi = 1 - (Pi - 1) / (M - 1).

Average the NVi values across all responses, then multiply by 100.

Score = ((1/N) * Sum(NVi)) * 100
NVi = 1 - (Pi - 1) / (M - 1)  (if 1 <= Pi < M), else 0

Example: BrandX Score

Query 1, ChatGPT (2): NV = 0.97
Query 1, Perplexity (4): NV = 0.90
Query 2, ChatGPT (5): NV = 0.86
Query 2, Perplexity (best 3): NV = 0.93
Query 3, ChatGPT (none): NV = 0.00
Query 3, Perplexity (domain 6): NV = 0.83
Query 4 (both none): NV = 0.00

Sum of NV = 4.48. Average = 4.48 / 8 = 0.560. Final Score = 56.0.

Score stays comparable when raw positions fluctuate: higher values mean better visibility relative to the top slot and how often you appear.

Visibility (0-100%)

Visibility is the percentage of AI responses where your brand (or a competitor) was mentioned. Higher is better.

Count responses with a mention, divide by total responses across queries and models. We count responses, not every duplicate mention inside one answer.

Visibility = (Distinct Mentions (Responses) / Total responses) * 100%

Example: BrandX Visibility

BrandX appears in 5 of 8 responses → Visibility = (5 / 8) * 100% = 63%.

Position (1–30)

Position is the average ranking of your brand across responses where it was mentioned. Lower is better (1 is best).

Sum best positions for mentioned responses, then divide by the mention count. If there are no mentions, position is N/A.

Position = Sum(Pi * Ii) / Sum(Ii)

Example: BrandX Position

Best positions 2, 4, 5, 3, and 6 → sum 20 across 5 responses → average 4.0.