Share of Voice

Benchmark your brand’s presence across Search.

AI is now the discovery layer. Customers rely on Google’s AI Overviews, Amazon’s Rufus, ChatGPT, and Copilot to make decisions long before they reach your website.
But in an AI-driven world, rankings no longer tell you whether AI systems talk about you at all.

AI Growth Hub’s Share of Voice Audit gives you a precise, data-driven benchmark of how often your brand is mentioned, recommended, or excluded across search engines and large language models — and reveals the technical, content, and entity factors shaping your visibility.

This is the foundation of any serious AI visibility strategy.

THE PAIN POINT

Your brand may have market presence, category authority, and strong SEO — yet still be invisible to AI systems.

Common issues we uncover include:

• LLMs recommending competitors but not mentioning your brand

• Google’s AI Overviews omitting you entirely

• Amazon Rufus pushing alternative products

• LLMs relying on outdated or inaccurate data about your brand

• Weak structured data or missing entity definition

• Content that models cannot extract, understand, or cite

• Competitors overweighted due to stronger publisher or Wikipedia presence

If AI systems don’t “know” your brand, customers never see you — no matter how strong your traditional SEO is.

Your visibility in LLMs is now a competitive advantage.
And right now, you don't know what you’re missing.

THE SOLUTION

The Share of Voice Audit provides a complete visibility baseline across search AI and large language models.

You’ll see exactly:

• When and where you appear in AI-generated answers

• How often competitors are recommended instead

• What data sources models pull from

• Where your entity signals are missing or weak

• Why models include or exclude your brand

• Which actions will increase your AI visibility the fastest

This audit replaces guesswork with clarity — giving you the intelligence needed to win in the AI discovery ecosystem.

HOW WE DO IT

Our methodology combines technical AI SEO, entity engineering, and model-specific evaluation.

1. AI Share of Voice Analysis

We test your target category, product, and brand queries across:

• Google Search + AI Overviews

• Bing + Copilot

• Amazon search + Rufus

• Walmart / Instacart / vertical retail search

• ChatGPT, Claude, Gemini, Perplexity
  We measure mention frequency, order, omission rate, and competitor share.

2. Entity & Data Layer Audit

We evaluate the technical backbone models rely on:

• Schema & structured data depth

• Product metadata

• Wikipedia & Wikidata alignment

• Publisher authority footprint

• Entity completeness and consistency

• LLM-friendly content availability

3. Citation & Source Mapping

We identify the exact domains, documents, and sources that models are using to make recommendations — and where your brand is missing.

4. AI Red-Team Testing

We stress-test each model for:

• Hallucinations

• Outdated information

• Misattributed brand details

• Compliance, medical, or reputational risks

5. Roadmap & Visibility Plan

We translate the findings into a clear 30/60/90-day plan that prioritises the biggest visibility wins.

WHAT YOU GET

The deliverables are built for senior technical and digital leaders who need clarity and immediate actionability.

You receive:

• A full Share of Voice benchmark across all major LLMs and search AI

• Competitive visibility analysis

• Entity and structured data audit

• Publisher and citation gap analysis

• AI hallucination and risk report

• Detailed 30/60/90-day roadmap

• Executive summary for CTO/CISO/VP Digital stakeholders

Everything is designed to drive visibility, reduce risk, and enhance brand accuracy across AI systems.

THE OUTCOME

With a Share of Voice Audit, you move from uncertainty to control.
You will:

• Understand your real visibility across AI systems

• Know exactly why competitors are outranking or replacing you

• Improve inclusion in LLM-generated answers

• Strengthen your entity signals across search and AI ecosystems

• Reduce hallucination and compliance risk

• Align teams around a clear AI visibility strategy

• Build a defensible position in category-defining AI surfaces

AI discovery is now the battleground for customer attention.
This audit ensures your brand isn’t invisible in the systems shaping decisions.

Website Tech Optimization

Make Your Brand Machine-Legible for AI-Powered Search

AI systems like ChatGPT, Perplexity, Bing Copilot, Google SGE, and Amazon Rufus are now major discovery channels. These models crawl, parse, and interpret websites to decide which brands to surface in answers, recommendations, and summaries.
If your site isn’t technically sound, you don’t just lose rankings — you lose visibility inside the AI ecosystem.

The Pain Point

Your website may look great to humans, but invisible to machines.

AI search relies on technical signals: crawlability, structured data, site speed, accessibility, clean architecture, and entity consistency.
If these foundations are weak, AIs struggle to ingest your content, understand your brand, or recognise your products.

The result:
Competitors with machine-readable sites are chosen as the authoritative sources — not you.

Our Solution

We transform your website into a fully AI-readable, entity-rich, technically flawless data source.
Our Website Tech Optimization service ensures AI systems can crawl you, understand you, and surface you across all emerging discovery surfaces.

This is the foundation layer of AI visibility — the layer everything else depends on.

How We Do It

We apply a structured, engineering-led process to make your site machine-legible:

1. Technical Crawlability & Indexation

• Robots.txt and sitemap optimisation

• Deep crawl diagnostics

• Removal of blocks, dead ends, and crawl traps

• Architecture simplification and internal linking clean-up

2. Structured Data & Entity Mapping

• Organization, Product, FAQ, HowTo, and Review schema

• Schema cleanup and error resolution

• Entity alignment with knowledge graphs (Wikidata, GMB, Wikipedia)

• Creation of machine-readable relationships between categories and products

3. Performance & Accessibility Upgrades

• Core Web Vitals improvements

• Semantic HTML structure

• Accessibility: alt text, ARIA roles, heading hierarchy

• Render path, script, and resource optimisation

4. Technical Hygiene & Trust Signals

• Canonicalisation, metadata consistency, clean URL patterns

• HTTPS & security checks

• Duplicate content and legacy template removal

• Template-level technical quality improvements

5. AI Ingestion Testing

• LLM browse-test scenarios

• Perplexity / SGE retrieval simulations

• Structured data validation and ingestion score

What You Get

A complete, machine-ready technical environment built for AI-driven discovery:

• Full Technical AI Visibility Audit

• Complete schema deployment & validation

• Fixed crawl errors, sitemap rebuild, robots.txt optimisation

• Accessibility and performance uplift (Core Web Vitals)

• Entity mapping and structured knowledge alignment

• AI ingestion readiness score + before/after benchmarking

• Technical documentation for engineering teams

• A future-proof technical foundation for all AI visibility strategy

The Outcome

Your website becomes a trusted, machine-legible source of truth that AI systems can easily ingest, understand, and recommend.

You gain:

• Higher inclusion in AI-generated answers

• Increased brand presence in ChatGPT, Perplexity, Copilot, and SGE

• Stronger entity recognition for products, categories, and authors

• More citations, summaries, and product recommendations

• A long-term technical advantage your competitors can’t easily replicate

When AI systems understand your content, they promote your brand.
Website Tech Optimization ensures they can.

Content Optimizations

Transform Your Content Into AI-Ready Authority

Pain Point

Your content may be excellent for human readers—but when it comes to AI, it often goes unseen. LLMs and AI-powered search don’t rank pages like traditional search engines—they extract answers, synthesize insights, and cite authoritative sources. Without structured, retrievable content, your expertise stays buried, leaving your brand invisible in AI-driven channels.

Our Solution

We optimize your content to be AI-ready, ensuring your brand is not just found—but trusted and cited. Using SOP-driven workflows, we turn your website into a coherent, high-authority knowledge graph that AI models can reliably access and reuse.

How We Do It

1. Topic Mapping & Authority Clusters – Define your core topics and subtopics, ensuring every page strengthens your domain expertise.

2. Content SOPs – Standardize structure, terminology, and semantic clarity so every asset is AI-friendly.

3. Retrievability Scoring – Evaluate content for clarity, entity density, and extractability, highlighting what AI can and cannot parse.

4. Content Refinement & Optimization – Audit existing pages, refine language, add cross-links, and enrich entities to maximize AI recall.

5. Continuous Measurement – Track AI visibility and iteratively improve content based on retrievability and citation metrics.

What You Get

• Fully structured, SOP-aligned content ready for AI extraction

• Improved internal linking and topical coherence

• Semantic clarity across all pages and assets

• Actionable retrievability scores to prioritize optimization

• Scalable content creation framework for future growth

The Outcome

Your content stops competing for attention and starts earning it—AI models cite your brand, surface your expertise in answers, and drive measurable traffic, trust, and visibility. In short, your website becomes a recognized authority for both humans and AI.

KNOWELEDGE GRAPHS

STRUCTURED DATA & KNOWELEGE GRAPHS

1. AI Understands Entities, Not Just Keywords

• Tools like ChatGPT don’t think in “keywords” the way SEO does — they build entity maps (people, places, products, brands, relationships).

• Structured data (schema markup, knowledge graphs) makes it easier for AIs to recognize your brand as an entity and connect it to your category, products, and authority.

2. Structured Data = Machine Readability

• Schema markup (Organization, Product, FAQ, HowTo, Review, etc.) provides contextual signals in a format that AIs can parse quickly.

• Without structured data, AI may overlook or misinterpret your content.

• With structured data, AI can pull direct answers, product specs, FAQs, and attributes straight into responses.

3. Knowledge Graphs Power Brand Recognition

• ChatGPT and other LLMs lean heavily on structured knowledge sources like Wikidata, Google’s Knowledge Graph, and industry databases.

• If your brand is absent from these graphs, AI may fail to associate you with your category — or worse, default to citing your competitors.

4. Industry Directories Act as Structured Authority Sources

• Specialized knowledge bases (Crunchbase for startups, IMDB for media, Healthgrades for healthcare, TripAdvisor for travel) feed directly into AI training and retrieval.

• Being present and complete in these directories strengthens your authority footprint.

Tactics

1. Implement Schema Markup on Your Site

   • Organization schema → brand info, logo, sameAs links.

   • Product schema → product specs, ratings, availability.

   • FAQ schema → common customer questions.

   • Author schema → expertise, linked profiles.

2. Ensure Your Brand Exists in Wikidata

   • Wikidata is a central knowledge base powering both Wikipedia and Google’s Knowledge Graph.

   • Add or update your entity entry with accurate brand details, aliases, and links.

3. Optimize Knowledge Graph Entries

   • Claim and update your Google Knowledge Panel.

   • Ensure consistent NAP (name, address, phone) and branding across platforms.

4. Align With Industry Directories

   • Add and maintain accurate profiles in sector-specific databases.

   • Example: Crunchbase (business), IMDB (media), Healthgrades (medical), TripAdvisor (hospitality).