AI Recommendation Score (ARS)

AI Recommendation Score (ARS) is MencionAI’s proprietary 0–100 index of how strongly AI assistants recommend a brand across monitored prompts and models. Use it for month-over-month tracking: one headline number plus a transparent component breakdown.

Product explainers: What is ARS? · How to read ARS

Why ARS

Metric	What it answers
Plan visibility score	Coverage of mentions/citations for models your plan tracks (Command Center overview).
Share of voice / mentions	Competitive mix and presence volume.
ARS	Recommendation strength over time—not only binary presence.

Formula

ARS is a weighted sum of eight component scores (each 0–100), rounded to an integer in 0–100.

Component	Weight	API field
Frequency	20%	`frequency`
Position	15%	`position`
Citation quality	15%	`citation_quality`
Model coverage	15%	`model_coverage`
Sentiment	10%	`sentiment`
Share of voice	10%	`share_of_voice`
Prompt breadth	10%	`prompt_breadth`
Consistency	5%	`consistency`

When daily history is thin, consistency is omitted and the other weights are renormalized.

Components (short)

Frequency — Share of analyzed prompt×model cells where the brand is recommended or mentioned.
Position — How high the brand ranks when AI lists recommendations (rank 1 → 100, 2–3 → 70, else lower).
Citation quality — Among presence cells: URL citations and own-domain citations.
Model coverage — Share of planned providers with at least one brand presence.
Sentiment — Normalized tone of brand mentions (neutral baseline when sparse).
Share of voice — Brand mentions ÷ (brand + competitor mentions).
Prompt breadth — Share of distinct monitored prompts with brand presence.
Consistency — Stability of recent daily ARS values.

Where to read ARS

Surface	Details
Product	Dashboard → AI Recommendation Score (`/dashboard/command-center/ars`)
Public API v2	`ars_score` + `ars_components` on visibility summary/overview; `ars_score` on series points
Public API v1	Scores are not available (counts only; v1 is frozen)

Example (v2 summary fields):

{
  "ars_score": 62,
  "ars_components": {
    "frequency": 70,
    "position": 55,
    "citation_quality": 40,
    "model_coverage": 80,
    "sentiment": 58,
    "share_of_voice": 45,
    "prompt_breadth": 60,
    "consistency": 90
  }
}

Interpreting ARS

Prefer multi-week / MoM trends over single-day spikes.
When the headline moves, inspect components—frequency vs position vs SoV tell different GEO stories.
Keep the prompt set stable when comparing periods.
Treat ARS and plan visibility score as complementary (strength vs coverage).

AI Recommendation Score