AI & Searchgrowth

AI Citation Score

Measure how AI cites your brand — over time

What it does

AI Citation Score (ACS) is NordicPulse's methodology for measuring how strongly a brand is cited in AI answers. You observe a real LLM answer and record four sub-scores: Visibility (S), Position (P), Source diversity (D), and Tone & accuracy (T). The tool computes ACS = S×0.40 + P×0.30 + D×0.20 + T×0.10, adjusts for market, and combines multiple prompts into an intent-weighted composite (cACS). Each run is stored per project so you can track change over time and compare run against run. The number always comes from code, never an AI guess — the sub-scores are observations you can inspect beside the score.

The Problem

You can't tell if your AI visibility is actually improving.

The Solution

A reproducible score based on observed AI answers.

Features

FAQ

Does the AI guess the score?
No. You observe a real AI answer and pick the rubric values for S/P/D/T. The score is computed deterministically in code (S×0.40 + P×0.30 + D×0.20 + T×0.10), adjusted for market. The model never generates the number.
What's the difference between raw and adjusted score?
Raw ACS is the plain weighted average. Adjusted ACS multiplies by a market multiplier (e.g. ×1.35 for Norwegian) and caps at 100. Both are shown separately so the adjustment is transparent.
What does it cost?
10 credits per completed run. The tool calls no paid API — you run the prompts yourself — so the price covers platform and storage.
Try AI Citation Score free