AI Share of Voice
Category Visibility Share
Most companies remain unaware of their true visibility share in artificial intelligence. While tracking rankings on Google, their competitors are capturing 80% of direct recommendations on ChatGPT and Perplexity for queries defining commercial purchase intent.
Description
Most companies remain unaware of their true visibility share in artificial intelligence. While tracking rankings on Google, their competitors are capturing 80% of direct recommendations on ChatGPT and Perplexity for queries defining commercial purchase intent.
We measure, audit, and benchmark your brand's AI Share of Voice (SoV) against every category competitor. We evaluate mention share, citation share, and preferred recommendation share across hundreds of commercial prompts, providing an authoritative quantitative assessment of your market position in the generative era.
As a specialized capability, Category Visibility Share provides a focused approach to the technical and strategic requirements of the AI Share of Voice domain. We design custom operational protocols, implement rigorous validation, and give the organization full control over this critical factor to secure a sustainable competitive advantage across the language model and generative AI ecosystem.
Impact Thesis & Return on Investment
Executive visibility into brand penetration across AI, enabling marketing and content budget allocation with surgical precision to capture voice share from category leaders. In today's corporate ecosystem, securing presence and accuracy across foundation models represents not only a competitive advantage, but a critical defensive barrier against the disintermediation of traditional digital traffic.
Methodology
Scheduled batch execution of category prompt batteries; computation of relevance-weighted mention shares; analysis of semantic clusters dominated by competitors; monthly comparative benchmark.
Technology Stack
- Technology Ecosystem: OpenAI Batch API, Anthropic API, Perplexity API, PostgreSQL, Metabase / Superset, Python Pandas, Scikit-learn.
- Semantic Standards: W3C Semantic Web Standards, Schema.org @graph, RDF/OWL ontologies, OpenAPI 3.1.
- Validation Protocols: Continuous evaluation with LLM-as-a-Judge, semantic guardrails, and regression testing in continuous integration pipelines.
Deliverables
- Monthly AI Share of Voice report broken down by competitor and AI platform.
- AI leadership quadrant matrix (Leaders, Challengers, Emerging, Laggards).
- Query gap analysis pinpointing competitor visibility where your brand is absent.
- Interactive executive AI Share of Voice dashboard.
Success KPIs
- Total weighted AI Share of Voice in the category (>35% leadership target).
- Recommendation Share (percentage of times the brand ranks as recommendation #1).
- Visibility gap ratio against the primary competitor (Gap Ratio).
- Month-over-month growth of mention share in commercial prompts.
Who is it for?
Who it is for
Chief Marketing Officers (CMOs), CEOs, and Heads of Strategy at competitive companies in saturated markets.
Who it is NOT for
State monopolies or companies operating in markets without direct competition.
Other AI Share of Voice services
- 01
AI Share of Voice
Most companies remain unaware of their true visibility share in artificial intelligence.
→ - 02
Brand Visibility Share
Most companies remain unaware of their true visibility share in artificial intelligence.
→ - 03
Query-Level Share
Most companies remain unaware of their true visibility share in artificial intelligence.
→ - 04
Citation Share
Most companies remain unaware of their true visibility share in artificial intelligence.
→ - 05
Recommendation Share
Most companies remain unaware of their true visibility share in artificial intelligence.
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Let's work together
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