What is AI Visibility?

AI Visibility is the degree to which a business, person, or brand is accurately understood, trusted, and selected by AI systems such as ChatGPT, Perplexity, Google Gemini, and Microsoft Copilot when users ask relevant questions. NinjaAI is Jason Todd Wade's AI Visibility agency, helping brands improve their presence across AI answer engines and generative search systems.

What is GEO — Generative Engine Optimization?

GEO (Generative Engine Optimization) is the practice of structuring content, entities, and authority signals so that AI-powered search engines and generative AI systems select and cite your business in their responses. NinjaAI provides GEO services from Orlando, Florida, serving clients nationally.

What is AEO — Answer Engine Optimization?

AEO (Answer Engine Optimization) is the discipline of structuring content so that AI answer engines — including ChatGPT, Perplexity, and Google's AI Overviews — extract and present your content as the authoritative answer to user queries.

Who is Jason Todd Wade?

Jason Todd Wade is the founder of NinjaAI, an AI Visibility agency based in Orlando, Florida. He helps brands improve how they are discovered, interpreted, recommended, and cited across AI answer engines, generative search systems, Google AI Overviews, ChatGPT, Gemini, Perplexity, and Claude. His research and methodology infrastructure is developed through BackTier, a separate research and infrastructure entity.

How long does the 80-query HEO audit take to run?

A complete 80-query audit across all four platforms (ChatGPT, Perplexity, Gemini, Copilot) takes approximately 4–6 hours for a single practitioner running queries manually and recording results. Using a structured spreadsheet with the query templates pre-loaded reduces this to 3–4 hours. The entity-direct queries (Category 4) typically take less time since responses are shorter and more factual. Plan for a full business day to run the audit, score all six metrics, and document findings.

Should I run all four query categories or just one?

Run all four categories for a complete baseline audit. Each category tests a different layer of HEO performance: Category 1 (Category Queries) tests PCR and CF; Category 2 (Problem-Aware Queries) tests AEO content architecture; Category 3 (Comparison Queries) tests whether your specific differentiators are in the AI's knowledge; Category 4 (Entity-Direct Queries) tests CAR. Skipping any category produces an incomplete picture and may lead to misattributing a metric problem to the wrong HEO phase.

What counts as a 'citation' for scoring purposes?

A citation is any response that includes the entity's business name — spelled correctly or with minor variation — in the body of the AI's answer. It does not need to be a recommendation to count as a citation. Mentions in lists, comparisons, or factual statements all count. What distinguishes a citation from a recommendation is the presence of an explicit endorsement signal, which is scored separately in the Recommendation Rate (RR) metric.

How do I handle AI responses that change between runs?

AI responses are non-deterministic — the same query can produce different results on consecutive runs. For baseline auditing, run each query once and record the result. For ongoing measurement at Day 30, 60, and 90, run each query once per cycle on the same platform. Do not average multiple runs of the same query in the same cycle. The goal is a consistent measurement methodology across cycles, not statistical precision within a single run.

What if my entity does not appear in any responses at Day 0?

A Day 0 ERS of 0.0–0.5 and PCR of 0–25% is common for businesses that have not implemented any HEO work. This is the baseline state that Phase 01 (Entity Audit) and Phase 02 (SEO Foundation Build) are designed to address. The most common cause is entity ambiguity — multiple conflicting name variants across directories — combined with absent or incomplete structured data. Begin with NAP normalization and Schema.org foundation deployment before re-running the audit at Day 30.

Can I use this template for a competitor audit?

Yes. The 80-query test suite and six metric formulas apply to any entity. Running the same query set against a competitor produces a comparable metric set that can be used for competitive benchmarking. Replace the entity name in Category 4 queries with the competitor's name. Note that CAR is particularly revealing for competitors — AI systems often carry outdated or inaccurate data about businesses that have not actively managed their entity layer.

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HEO Audit Template · NinjaAI

The HEO Baseline Audit Template

The complete 80-query test suite for establishing your Hybrid Engine Optimization baseline. Four query categories. Four AI platforms. Six metric calculation formulas. This is the exact methodology NinjaAI uses to measure every HEO engagement at Day 0, Day 30, Day 60, and Day 90.

Total Queries

AI Platforms

Query Categories

Metric Formulas

~5h

Audit Duration

Audit Procedure

8-Step Scoring Procedure

Prepare Your Query Set

Download or copy the 80-query template. Replace [Business Name], [service type], [city], [problem], and [use case] placeholders with your entity's specific values. Prepare one row per query in your tracking spreadsheet with columns for: Query, Platform, Response (Y/N), Citation Text, Recommendation Signal (Y/N), Factual Claims (5 checkboxes), Sentiment (Positive/Neutral/Negative).

Run Category 1 — Category Queries

Run all 20 Category Queries on ChatGPT. Record whether the entity appears in each response. Then run the same 20 queries on Perplexity, Gemini, and Copilot. Total: 80 query runs for Category 1.

Run Category 2 — Problem-Aware Queries

Run all 20 Problem-Aware Queries on all four platforms. Record citation presence, recommendation signals, and sentiment framing for each response.

Run Category 3 — Comparison Queries

Run all 20 Comparison Queries on all four platforms. Focus on whether the entity's specific differentiators, credentials, or outcomes appear in the AI's comparative answers.

Run Category 4 — Entity-Direct Queries

Run all 20 Entity-Direct Queries on all four platforms. For each citation, verify five factual claims: business name, location, primary service, a specific credential or outcome, and contact method. Record accuracy for each claim.

Calculate ERS

For each platform, assign a score 0–5 based on the best response quality observed across all 80 queries: 0=Not found, 1=Mentioned incorrectly, 2=Mentioned correctly, 3=Listed as option, 4=Recommended, 5=Primary recommendation. Average the four platform scores.

Calculate PCR, CF, CAR, RR, and CFS

Using your completed tracking spreadsheet, apply each metric formula: PCR = platforms with ≥1 citation ÷ 4 × 100; CF = citations per platform ÷ 20; CAR = correct factual claims ÷ total claims checked × 100; RR = citations with recommendation signal ÷ total citations × 100; CFS = positive citations ÷ total citations × 100.

Document Baseline and Schedule Re-Audit

Record all six metric scores as your Day 0 baseline. Schedule re-audits at Day 30, Day 60, and Day 90. Compare each cycle against the Day 0 baseline and the 90-day targets defined in the HEO Metrics Tracker.

Query Library

80-Query Test Suite

Replace all bracketed placeholders with your entity's specific values before running. Run each category on all four platforms: ChatGPT, Perplexity, Gemini, and Copilot.

ChatGPTPerplexityGeminiCopilot

Queries where the AI must recommend a provider in your category. These test whether you appear as an option at all.

01Who are the best [service type] in [city]?

02What [service type] do you recommend in [city]?

03Top [service type] near [city]

04Best [service type] for [use case] in [city]

05Which [service type] should I hire in [city]?

06Highly rated [service type] in [city]

07Who provides [service type] in [city]?

08Trusted [service type] in [city]

09Affordable [service type] in [city]

10Experienced [service type] in [city]

11Local [service type] in [city]

12Reputable [service type] in [city]

13Award-winning [service type] in [city]

14Most recommended [service type] in [city]

15Established [service type] in [city]

16[City] [service type] recommendations

17Find a [service type] in [city]

18Who should I call for [service type] in [city]?

19Good [service type] in [city]

20Professional [service type] in [city]

Metric Formulas

Six Core HEO Metric Calculations

ERSEntity Representation Score

Scale: 0–5 integer · 90-Day Target: ≥ 3.5

What to Measure

Manual rating per platform: 0 = Not found, 1 = Mentioned incorrectly, 2 = Mentioned correctly, 3 = Listed as an option, 4 = Recommended, 5 = Primary recommendation. Average across all 4 platforms.

Calculation Formula

ERS = (ChatGPT score + Perplexity score + Gemini score + Copilot score) ÷ 4

How to Interpret Results

ERS below 2.0 indicates entity ambiguity — the AI cannot reliably find or identify the business. ERS 2.0–3.4 indicates presence without recommendation authority. ERS 3.5+ indicates the entity is recognized and recommended.

All Six Metrics at a Glance

Code	Metric	Scale	Formula	90-Day Target
ERS	Entity Representation Score	0–5 integer	ERS = (ChatGPT score + Perplexity score + Gemini score + Copilot score) ÷ 4	≥ 3.5
PCR	Platform Coverage Rate	0–100%	PCR = (Platforms with ≥1 citation ÷ 4) × 100	100%
CF	Citation Frequency	0–20 per platform	CF (per platform) = Responses mentioning entity ÷ 20 queries. CF (aggregate) = Total citations across all 4 platforms ÷ 80 total queries.	≥ 12/20 on primary platform
CAR	Citation Accuracy Rate	0–100%	CAR = (Correct factual claims ÷ Total factual claims checked) × 100	≥ 90%
RR	Recommendation Rate	0–100% of citations	RR = (Citations with recommendation signal ÷ Total citations) × 100	≥ 40%
CFS	Citation Favorability Score	Positive / Neutral / Negative distribution	CFS = (Positive citations ÷ Total citations) × 100 for Positive %; same for Neutral and Negative.	≥ 60% Positive

Audit FAQ

Common Audit Questions

HEO Resource Cluster

Coined by Jason Todd Wade →

HEO Definition

The canonical 2,500-word definition of Hybrid Engine Optimization.

ninjaai.com/heo →

Implementation Checklist

47-point checklist across the five-phase HEO implementation sequence.

ninjaai.com/heo-implementation-checklist →

Metrics Tracker

Scoring rubrics, measurement methodology, and 90-day targets for all six metrics.

ninjaai.com/heo-metrics-tracker →

Case Study

Documented 90-day HEO engagement with all six metric progressions.

ninjaai.com/heo-case-study →