How We Calculate AI Visibility Scores
Heres exactly how we measure, score, and rank each brand in real AI answer-engine responses, week after week.
By PingAura Data Team · Updated January 2026
In short
We test how AI assistants mention brands by asking them the questions real buyers ask across 25 industries, then score each brand from 0-100 based on how often it appears, how prominently, and how much of the conversation it owns. The scores refresh weekly so you can track changes over time.
How is each score determined?
Every brand gets a 0-100 composite score built from four weighted factors: presence and mention quality (20%), position in the answer (25%), query coverage (25%), and share of voice (30%). Scores are measured weekly from real AI answer-engine responses with live web search, using 25 non-branded, high-intent consumer prompts per industry.
1. Data Collection
We ask AI answer engines the same set of questions and track which brands get mentioned, recommended, and cited. The questions cover different ways people actually search for products and services in each industry.
How the prompts are built
- 25 prompts per industry across 5 trending topics
- Strictly non-branded — no brand names in any prompt
- High purchase intent — phrased like real buyer questions
- India-specific — ₹ budgets, regulations, cities, climate
- Answers measured with live web search grounding
Topics are refreshed from current search trends, so prompts follow what Indian consumers are actually asking right now — from monsoon waterproofing to the newest budget smartphones.
2. Scoring Components
The AI Visibility Score is a composite metric derived from four key components, each measuring a different aspect of brand presence in AI responses.
Presence & Mention Quality
Whether the brand appears in the answer at all, weighted by how it appears: an explicit recommendation counts more than a passing mention, and a warning counts against the brand.
Position & Prominence
Where in the response the brand appears matters. Brands mentioned first, featured as top recommendations, or highlighted as examples receive higher scores than those mentioned in passing.
Query Coverage
When AI platforms cite sources, we analyze whether the brand is cited from authoritative sources. Citations from industry publications, official sources, and trusted review sites contribute more.
Share of Voice
We measure across how many different query types the brand appears. Brands visible across diverse queries (general, comparative, feature-specific) score higher than those appearing only for specific queries.
3. Score Calculation
AI Visibility Score Formula
Score = (MF × 0.40) + (PP × 0.25) + (CQ × 0.20) + (QC × 0.15)Mention Frequency
Position & Prominence
Citation Quality
Query Coverage
Each component is normalized to a 0-100 scale within the industry before the weighted average is calculated. The final score is rounded to the nearest integer.
4. Share of Voice
Share of Voice (SoV) represents the percentage of total AI mentions a brand receives compared to all competitors in its industry. It's calculated as:
SoV = (Brand Mentions / Total Industry Mentions) × 100A brand with 12.5% Share of Voice in the banking industry means that out of all bank mentions across all AI queries, this brand accounts for 12.5% of them. Higher SoV indicates stronger competitive positioning.
5. Data Quality & Validation
Cross-Platform Validation
We verify brand mentions across multiple AI platforms to ensure consistency and filter out platform-specific anomalies.
Hallucination Filtering
Our systems detect and filter AI hallucinations by cross-referencing with verified brand databases and industry records.
Statistical Normalization
Scores are normalized using statistical methods to ensure fair comparison across different industry sizes and query volumes.
Regular Audits
We conduct weekly audits of our data collection and scoring systems to maintain accuracy and reliability.
6. Update Frequency
The AI Visibility Index is refreshed weekly to reflect the latest AI response patterns. This allows brands to:
- Track visibility trends over time
- Identify sudden changes in AI visibility
- Measure impact of visibility optimization efforts
- Monitor competitive movements in real-time
Glossary of Terms
- AI Visibility Score
- A 0-100 composite score measuring how prominently a brand appears in AI-generated answers.
- Share of Voice (SoV)
- The percentage of total industry AI mentions that a brand receives.
- Citation Rate
- How frequently AI models cite a brand when answering queries in its industry.
- Prompt Dominance
- The breadth of query types for which a brand appears in AI responses.
- AEO (Answer Engine Optimization)
- The practice of optimizing content and online presence to improve visibility in AI-generated answers.
Frequently Asked Questions
We systematically query AI answer engines with live web search using 25 non-branded, high-intent prompts per industry. These cover different user intents like brand comparisons, product recommendations, and feature-specific queries. We parse the responses to extract mentions, citations, and direct recommendations.
We cross-reference mentions across several AI tools, filter out obvious hallucinations, and use statistical methods to catch anomalies. Data is regularly audited against known brand facts.
The Index is refreshed weekly. We re-run every industry's full prompt set so brands can spot trends, catch sudden shifts, and measure the impact of their optimization work.
Brands that score well typically have: (1) Strong online presence with authoritative content, (2) Frequent mentions and citations across trusted sources, (3) Consistent brand info across the web, (4) Good coverage in industry publications and reviews, (5) Positive sentiment in customer feedback.
The AI Visibility Score reflects genuine brand presence across the web. While brands can improve their scores through legitimate means (quality content, building citations, improving online presence), artificial manipulation attempts are unlikely to be effective as AI models draw from diverse, authoritative sources.
Scores are calculated relative to competitors within each industry. This means a bank with a score of 80 is compared against other banks, not against mobile phone brands. We use industry-specific query sets to ensure relevant comparisons.
What is AI Visibility?
Understand what AI visibility means, why it matters for brands, and how the index works.
Learn MoreHow to Improve Your Scores
Practical AEO strategies to boost your brand's presence in AI-generated answers.
View StrategiesSee the Methodology in Action
Explore the AI Visibility rankings for your industry and see how our methodology translates into actionable insights.