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What is FAVIR™?

Financial Advisor Visibility Index Rating — an AI-native scoring system that measures how well a financial advisor's profile is structured for discovery by AI tools like ChatGPT, Gemini, and Perplexity.

How the Agentic System Works

1
Rule-Based Indexes

Ten profile dimensions — credentials, bio depth, specialties, AUM clarity, fee transparency, online presence, and more — are scored 0–100 using verifiable rules.

2
Specialized Sub-Agents

AI agents independently evaluate qualitative signals (writing quality, positioning clarity, thought leadership) that rules alone can't capture.

3
Synthesizer (Claude)

An orchestrating AI agent combines all indexes, weighs them, and produces your composite FAVIR™ Score plus bespoke, prioritized recommendations for improvement.

The Value for Financial Advisors

  • AI Discoverability: When someone asks an AI assistant for a financial advisor, FAVIR™-optimized profiles are more likely to be surfaced.
  • Actionable Roadmap: Instead of generic advice, you get ranked, impact-scored suggestions specific to your profile gaps.
  • Competitive Benchmark: Understand how your profile compares and where targeted effort yields the highest score gain.
  • Future-Proof Positioning: As AI becomes the primary discovery channel for professional services, a high FAVIR™ score is a durable competitive advantage.

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For Financial Advisors

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ChatGPT Recommends.

The only platform where your profile is structured, scored, and optimized for AI discovery. When someone asks ChatGPT or Perplexity for a financial advisor — you're the name that shows up.

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Retirement Advisor.

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  • Experienced Verified, credentialed advisors with established track records.
  • Trust Profiles verified against FINRA and SEC registrations.

The Visibility Standard

What Is the Financial Advisor Visibility Index Rating (FAVIR™)?

FAVIR™ — the Financial Advisor Visibility Index Rating — measures what AI actually does with a financial advisor's name: whether the advisor is cited, on which platforms, for which client questions, and how that visibility changes over time. It is an outcome metric, not a checklist.

Consumers increasingly ask AI assistants — not search engines — to recommend a financial advisor. When ChatGPT, Perplexity, Gemini, or Claude answers “who is a good retirement planner near me,” the advisors those systems cite win the introduction. FAVIR™ tells you whether that advisor is you.

  • 25% of consumers seeking an advisor start with AI tools like ChatGPT or Gemini
  • 51% of all consumers use AI for financial information or advice
  • 96% of referred clients still research an advisor online before making contact
  • 60% of searches now begin in AI tools rather than traditional search engines

How a FAVIR™ Score Is Calculated

Unlike AEO scorecards that grade self-reported inputs — schema markup, LinkedIn completeness, review counts — FAVIR™ tests real outcomes: what AI platforms actually say when asked.

  1. Query Construction

    Realistic consumer questions are built from your specializations, geography, and target client type — the same questions real prospects ask AI assistants.

  2. Live Platform Testing

    Each query runs live across ChatGPT, Perplexity, Google AI Overviews, and Claude, recording whether you are cited and where you rank.

  3. Weighted Score Calculation

    Results are weighted by platform reach and query volume, producing a single comparable 0–100 visibility score.

  4. Ongoing Tracking

    Scores are re-tested over time, so you see whether profile improvements actually move your AI visibility — not just your checklist.

The Six Dimensions of AI Visibility

A FAVIR™ score blends six independently measured dimensions:

Citation Presence

Whether you appear at all in AI responses to relevant advisor-search questions.

Citation Rank

Where you are positioned when AI platforms recommend you — the first mention carries far more weight.

Third-Party Authority

The quality and credibility of external sources that mention you, which AI systems use to validate recommendations.

Structured Data Signals

Machine-readable credentials — schema.org markup, verified registrations, structured profiles — that AI systems can parse and trust.

Cross-Platform Consistency

Whether your name, credentials, and specialties match everywhere AI looks. Conflicting data suppresses citations.

Query-Type Coverage

Visibility across the full range of client needs — retirement, tax, estate, insurance — not just one niche question.

Frequently Asked Questions

What is FAVIR™?

FAVIR™ (Financial Advisor Visibility Index Rating) is a 0–100 score that measures how visible a financial advisor is to AI assistants such as ChatGPT, Perplexity, Gemini, Google AI Overviews, and Claude. It is calculated by running live consumer-style queries on those platforms and recording whether — and where — the advisor is cited.

How is FAVIR™ different from SEO tools or AEO scorecards?

Traditional scorecards grade inputs you control — schema markup, profile completeness, review counts. FAVIR™ measures the outcome: what AI platforms actually say when a real prospect asks for an advisor. Inputs predict visibility; FAVIR™ verifies it.

Why does AI visibility matter for financial advisors?

25% of consumers seeking an advisor now start with AI tools, 51% of all consumers use AI for financial information, and 60% of searches begin in AI tools rather than traditional search engines. Even referred clients verify online: 96% research an advisor before making contact. If AI systems don't cite you, you are invisible at the exact moment prospects decide who to call.

Which AI platforms does FAVIR™ test?

FAVIR™ runs live queries across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude — weighted by each platform's consumer reach.

Who is FAVIR™ for?

Independent RIAs and fee-only planners who compete on discoverability, RIA firms and broker-dealers benchmarking advisor teams, and wealthtech platforms that need a verified visibility metric.

How do AI assistants read advisor profiles on this site?

Every advisor profile is published with structured, machine-readable data and exposed through an open MCP (Model Context Protocol) API, so AI assistants and agents can query verified advisor information — credentials, specialties, fee structure, and FAVIR™ score — directly.

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