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Industry Metrics

See how AI describes your market, which brands it treats as leaders, and where your client actually sits in that landscape.

Industry Metrics turns AI answers into a live competitive map: tiers, buying criteria, shortlists, and content gaps.

Before you can improve a client's AI visibility, you need to know who already owns the conversation. Most teams jump straight into content without understanding which brands AI treats as leaders, what buying criteria it uses, and which shortlists they are missing from.

Leaders
HubSpot
Known for: Scale, Ease of Use
Salesforce
Challengers
Your Client
Known for: Integrations
Niche
Pipedrive
Known for: Visual Pipelines

Key competitive metrics Industry Metrics tracks

Tier Classification

Whether AI treats a brand as a Leader, Challenger, or Niche player.

AI Share of Voice (SoV)

How often each brand is mentioned across the tracked AI answers.

Share of Synthesis (SoS)

How often each brand’s domain is cited as a source, not just named.

Answer Placement Score (APS)

How high each brand appears in AI’s recommendations (top, middle, bottom).

Answer Sentiment

Whether AI’s descriptions are mostly positive, neutral, or negative.

Fame Claims

The 1–2 differentiators AI keeps repeating for each brand.

Persona‑Based Shortlists

Which brands AI recommends for Budget, Quality, and Scale buyers.

Information Gaps

Topics and criteria where AI’s knowledge is thin or outdated.

Leaders
Brand A 82%
Brand B 71%
Challengers
Brand C 45%
Brand D 38%
Niche
Brand E 22%
Brand F 14%

How AI Market Leaderboard works

  • We run a fixed set of buyer prompts across AI engines for your category.
  • We extract every brand mentioned and cited, then group them into tiers.
  • We compute SoV, SoS, APS, and sentiment for each brand from the same runs.

What AI thinks buyers care about

Industry Metrics reads how AI compares providers and pulls out the buying criteria and shortlists it uses for different buyer types.

Extracted Criteria
  • Price / Affordability
  • Reliability
  • Integrations
  • Support Quality
  • Ease of Setup
Budget Persona
Zoho CRM
"Highly affordable for small teams"
Freshsales
"Great entry-level pricing"
Pipedrive
"Cost-effective pipelines"
Quality Persona
Your Client
"Best-in-class integrations"
HubSpot
"Seamless UX and features"
Salesforce
"Most robust ecosystem"
Scale Persona
Salesforce
"Unmatched enterprise scale"
Microsoft Dynamics
"Deep stack integration"
Oracle CX
"Complex global deployments"

This is how you see which criteria you win, where competitors dominate, and which criteria no one owns yet.

Where the market — and AI — has gaps

Info Gap

Compliance for Indian SMBs

AI answers are vague or outdated here.

Missing Criterion

Migration support for agencies

AI fails to list providers offering this.

Info Gap

API limits on entry tiers

AI answers are contradictory across engines.

Opportunity

ROI tracking for B2B tech

No clear category winner defined by AI.

These gaps become your content roadmap: the exact topics where one good explainer can turn your client into the default source.

How Industry Metrics runs an audit

  • Define the sector and your client’s brand, then auto‑enrich with basic industry and region data.
  • Run a 4‑stage pipeline across AI engines: landscape, buying criteria, persona shortlists, information gaps.
  • Calculate shared metrics (SoV, SoS, APS, sentiment) for your client and 15–20 competitors from the same run.
  • Overlay your client on that map: tier, criteria wins, shortlist appearances, missing criteria.

What you'll see

AI Market Leaderboard

Rankings with tier badges (Leader, Challenger, Niche), presence scores, and fame claims.

Buying Criteria Breakdown

Factors AI uses to evaluate providers (price, reliability, integrations, etc.).

Persona‑based AI Shortlists

Brand recommendations for Budget, Quality, and Scale buyers, with AI's own reasoning.

Client Overlay Card

Shows your client's tier, shortlist appearances, and missing criteria.

Answer Placement & Sentiment

How prominently AI recommends brands and the sentiment of those recommendations.

Source Classification

Categorized citations (Community, Review, Media, etc.) showing where authority lives.

Information Gaps

Topics where AI’s answers are vague, giving you targeted content opportunities.

Exportable Audits

CSV for leaderboards and JSON for full structured audit data.

What's included

  • Auto‑enriched company profiles via Tavily
  • Sector‑specific prompts and criteria extraction
  • Standardised buyer personas (Budget, Quality, Scale)
  • AI Market Leaderboard with tier classifications
  • Buying Criteria analysis and reasoning
  • Client Overlay view for missing criteria
  • Information Gap detection
  • Source Classification across 6+ source types

Pipeline breakdown

1

Brand & Sector Setup

Enter brand name and domain. We auto‑enrich industry, geo, and descriptions via Tavily.

2

Review & Refine

Tighten the industry label, specify primary markets, and choose buyer personas.

3

Run Landscape Audit

A 4‑stage pipeline maps active brands, extracts criteria, builds shortlists, and finds gaps.

4

Landscape Mapping

Brands are grouped into tiers (Leaders, Challengers, Niche) and their 'fame claims' extracted.

5

Criteria & Shortlists

Identifies top buying criteria and builds shortlists for Budget, Quality, and Scale personas.

6

Overlay & Export

Overlays your client onto the map. Export everything to CSV/JSON for decks.

Built for Agency Workflows

  • New client discovery Walk into pitches knowing which brands AI treats as leaders and where the client is invisible.
  • Competitive messaging Use AI’s descriptions of competitors' strengths to refine your client's positioning.
  • Content roadmap planning Turn Information Gaps into a focused list of criteria to build definitive content around.
  • Authority & PR planning Focus PR on the specific channels (reviews, communities, media) that actually influence AI.
  • Quarterly business reviews Bring a visual AI Market Leaderboard to QBRs to prove how your work shifts AI demand.
  • Uncontested positioning Identify buying criteria where no single brand is strongly associated yet, and own them.

Frequently asked questions

Everything you need to know about AI visibility tracking and search intelligence.

What is AI visibility, and how do you actually measure it?

AI visibility is how often, and in what context, your brand shows up when people ask AI assistants like ChatGPT, Gemini, Claude, Grok, or Perplexity for recommendations. Most teams still measure this by manually typing prompts into each chatbot and eyeballing the results — which doesn't scale past a handful of queries. PhantomRank automates that process: it runs your brand through dozens of buyer-journey prompts across all five engines on a schedule, so you get a real measurement instead of a spot-check.

Is AI visibility a rank, or a probability?

It's a probability, not a rank — and any tool selling you a fixed position is misrepresenting how AI actually works. Because AI answers vary run to run, the useful metric is how often your brand appears across repeated queries — for example, showing up in 6 of 10 runs of the same prompt category, tracked over time. That's how PhantomRank reports visibility: as a trend built from repeated, structured measurement, not a single lucky (or unlucky) snapshot.

Are GEO, AEO, and AI SEO different from regular SEO?

They're the same discipline evolving, not a separate one — but the mechanics genuinely shift. Traditional SEO optimizes to rank; GEO and AEO optimize to be cited inside a generated answer. That means structure matters more (self-contained sections, clear verdicts, comparison tables) and keyword density matters less. PhantomRank tracks both sides: whether you show up (visibility) and whether AI trusts you enough to cite you as a source (synthesis).

Why do AI answers change every time I ask — doesn't that make tracking pointless?

It makes word-for-word tracking pointless, which is exactly why PhantomRank doesn't do that. Instead of comparing exact phrasing, we convert each AI response into a vector embedding and measure its semantic similarity to your brand's core messaging — a method we call semantic resonance. The wording can shift every time the model answers; the underlying meaning, and therefore the resonance score, stays stable enough to actually track over weeks and months.

How do you avoid prompt bias when testing brand visibility?

By never handing the model your brand name to begin with. If a prompt already contains your brand, you're testing whether the AI can repeat a name you gave it — not whether it surfaces you naturally. PhantomRank runs category-level, persona-based prompts that mirror how real buyers actually ask ('best CRM for a 10-person agency'), so what comes back reflects genuine visibility, not a fed answer.

Can I track ROI or attribution from AI search traffic?

Partially, and PhantomRank is built to close that gap rather than pretend it doesn't exist. Attribution from AI tools is genuinely harder than from Google — most people don't type 'found you on ChatGPT' into a lead form. What you can do is correlate periods of higher Share of Synthesis with pipeline and self-reported attribution, and track referral traffic from the citations AI does generate. It's directional, not perfect — and we'd rather tell you that than oversell a dashboard that claims otherwise.

Is there a "Search Console" for AI search?

Not from the AI platforms themselves — none of them offer an official visibility dashboard the way Google Search Console does. That's the specific gap PhantomRank fills: one dashboard that queries ChatGPT, Gemini, Claude, Grok, and Perplexity on a recurring schedule and gives you the equivalent view — mentions, citations, and crawl behavior — that Search Console gives you for classic search.

What kind of content actually gets cited by AI engines?

Content built in self-contained, quotable chunks — not classic long-form narrative blog posts. AI engines pull cleanly from sections that work as standalone answers, put a clear verdict in the first two or three sentences, and use structured formats like comparison tables and FAQs. PhantomRank's Information Gap Analysis tells you which specific topics in your category AI is currently answering badly, so you know exactly where writing this kind of content will move the needle.

What's the difference between being mentioned and being cited?

A mention means AI named your brand in its answer. A citation means it linked back to your site as a source. The gap between them matters more than most teams realize: a brand mentioned constantly but never cited is winning awareness and losing referral traffic. PhantomRank tracks both separately — AI Share of Voice for mentions, Share of Synthesis for citations — because optimizing for one doesn't automatically improve the other.

Which AI engines does PhantomRank track?

ChatGPT, Gemini, Claude, Grok, and Perplexity — across 28 model variants — the engines Indian and global buyers actually use for research and recommendations, tracked in one place instead of five separate manual checks.

What's a "crawl pool" gap?

It's when an AI engine crawls your page while researching an answer, reads it, and still chooses to cite a competitor instead. That's not an awareness problem — your site was found — it's a content relevance or authority gap, and it's specific enough to fix.

Can I control what AI says about my brand?

No tool can guarantee that, and any tool claiming 'control' over AI answers isn't being straight with you. PhantomRank gives you an accurate diagnostic of where you stand today — including the probability-based visibility and semantic resonance scores above — and a content roadmap to close specific, identified gaps.

Stop guessing what ChatGPT says about you.

PhantomRank gives you the diagnostics, competitor benchmarks, and concrete content strategy to build visibility where your next buyers are actually looking.