RankScale
Track your brand's visibility across ChatGPT, Gemini, Perplexity, and 17+ AI engines.
Best forEnterprise marketing teams and agencies that need broad AI-engine coverage
Our verdict
RankScale is a credible, actively used GEO/AI-visibility platform with broad engine coverage and genuine enterprise customers, but its credit-based pricing gets expensive fast for API and white-label access, and it stops short of proving ROI.
Re-verified 2026-07-21: pricing, tier limits, engine count (17+), and existing cons (attribution, credit consumption, reporting exports, score volatility) are all unchanged from the 2026-07-11 check. Added a genuine new capability not previously captured, Rankscale MCP, a read-only remote MCP server for Claude/ChatGPT/Cursor/Codex, plus three named, agency-attributed case studies (MiniFinder, SoWork, an AI SMS platform) from rankscale.ai/case-studies, and an expanded, corroborated named-customer list. Declined to publish a specific active-user count: the vendor's own homepage states both "2,000+" and "1,000+ active users" in different sections, a self-contradiction now flagged as a con rather than repeated as a fact.
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What's great
- Covers 17+ AI engines (ChatGPT, Perplexity, Gemini, Claude, Copilot, AI Overviews, and more) from the entry-level plan with no per-engine surcharges
- Citation analysis shows which sources AI engines actually cite, useful for shaping content strategy
- Used by large brands including Bosch, UBS, Cartier, O2, Otto, StepStone, and OMR, plus agencies like Coalition Technologies, Dentsu, Publicis Sapient, and WPP Media
- Publishes named, agency-attributed case studies with quantified results rather than only aggregate marketing claims, MiniFinder reached the #1 AI-search spot in 90 days, SoWork hit 100% visibility and a 63% market lead in 90 days, and an AI SMS platform generated $280K in pipeline from AI search
Watch-outs
- No traffic attribution: RankScale can't connect AI visibility to actual website sessions, leads, or revenue, there's no GA4 integration or conversion tracking
- Credit-based billing is unpredictable, engine costs vary from 0.25 to 2+ credits per query, and reviewers report exhausting monthly credits quickly on smaller plans
- Visibility scores can swing 10-15% week-to-week even without site changes due to underlying AI model volatility, and sentiment analysis isn't always accurate
- Client-ready reporting exports are limited, one reviewer found no way to export a clean overview list, making agency client reporting mostly manual
- Self-reported user counts are inconsistent: RankScale's own homepage states "2,000+" in its stats bar but "1,000+ active users" repeated in the hero, features, and closing call-to-action
Also note: No GA4 or analytics integration for connecting AI visibility to traffic or revenue · Diagnoses AI-visibility issues but provides no automated content fixes or schema deployment · REST API is gated behind the Growth ($385/mo) and Enterprise ($780/mo) tiers only · Sparse third-party review coverage on G2/Capterra makes independent at-scale reliability hard to verify
How RankScale compares
The other tools buyers weigh against RankScale, and when to pick each.
| Tool | Best when you want… |
|---|---|
| RankScaleThis page | Enterprise marketing teams and agencies that need broad AI-engine coverage |
| Frase | Frase bundles AI-visibility tracking into a full content-creation platform — SERP briefs, AI drafting, decay-repair — if you want one subscription that also writes the content that wins the citation back. |
What is RankScale?
RankScale is a GEO (generative engine optimization) platform that tracks how brands appear in AI-generated answers across ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, Copilot, DeepSeek, Grok, and Mistral. It gives marketers a visibility score, competitor benchmarking, and citation tracking across 17+ AI engines and 240+ countries. Clients include Bosch, UBS, Cartier, and O2, and pricing runs from an Essentials plan to an Enterprise tier with REST API access, positioning RankScale as an AI-search analytics suite for agencies, publishers, and enterprise marketing teams navigating the shift from traditional SEO to answer-engine visibility.
What does RankScale do?
RankScale runs scheduled prompts against 17+ AI engines, including ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Claude, Copilot, DeepSeek, Grok, and Mistral, and scores how often, how prominently, and how favorably a brand is mentioned in the generated answers. Each account gets brand dashboards that chart visibility score, share of voice, and sentiment trends over time, alongside auto-identified competitor benchmarking so teams can see how they stack up in the same AI responses. A citation-analysis module surfaces which sources the AI engines actually quote or link to, helping teams reverse-engineer what content earns a citation. RankScale also runs page audits, checking 200+ technical and content signals for AI-readiness, and a prompt-research tool that estimates search volume and intent for GEO-relevant queries. Credit-based billing meters usage: each engine query against a tracked prompt consumes a fraction of a credit, and pricier engines cost more per query. Growth and Enterprise plans add a REST API and white-label reporting options for agencies managing multiple client accounts.
How RankScale works
- Scheduled prompts run against 17+ AI engines, including ChatGPT, Perplexity, Google AI Overviews and AI Mode, Gemini, Claude, Copilot, DeepSeek, Grok and Mistral.
- Each account gets brand dashboards charting a visibility score, share of voice and sentiment trend over time, with competitors auto-identified for benchmarking.
- A citation-analysis module surfaces which sources the AI engines actually quote or link to for your prompts.
- Usage draws down a shared credit pool — each engine query against a tracked prompt consumes a fraction of a credit, with pricier engines costing more per query.
Who is RankScale for?
- Enterprise marketing teams and agencies that need broad AI-engine coverage (17+ engines) and competitor benchmarking, and can absorb credit-based pricing that scales toward $385-$780/month for API and white-label access.
- Agencies on the Growth plan that want white-label reporting and a REST API to manage AI-visibility reporting across many client brands from one account.
- Content teams that want to reverse-engineer what earns a citation, using the citation-analysis module to see which sources the AI engines already quote.
Key features
- Brand Visibility Dashboard: Central dashboard tracking a visibility score across monitored AI engines, filterable by engine and timeframe.
- AI Rank & Citation Tracking: Monitors rankings, share of voice, and which sources AI engines cite when answering brand-relevant prompts.
- Competitor Benchmarking: Auto-identifies competitors and compares visibility metrics side-by-side across the same AI responses.
- Page Audits: Analyzes 200+ technical and content signals, including 94+ deterministic technical checkpoints, to assess how AI-ready a given page is.
- Prompt Research: Estimates search volume and decodes user intent for GEO-relevant prompts via semantic analysis.
- Rankscale MCP: A read-only remote MCP server that lets Claude, ChatGPT, Cursor, and OpenAI Codex query live visibility, competitor, sentiment, and citation data via natural language, without dashboard or export access; it cannot modify brands, search terms, or settings.
What are RankScale's use cases?
- Enterprise brand-visibility monitoring: A marketing team at a large brand tracks how often and how favorably it's mentioned across ChatGPT, Gemini, and Perplexity, and benchmarks that visibility against named competitors over time.
- Agency AI-search reporting: An SEO agency on the Growth plan uses the REST API and white-label dashboards to report AI-visibility metrics across dozens of client brands from one account.
- Content AI-readiness audits: A content team runs page audits to identify technical and content gaps that may be preventing pages from being crawled or cited by AI engines.
What does RankScale integrate with?
- Looker Studio
- REST API (Growth & Enterprise plans)
- MCP (Claude, ChatGPT, Cursor, OpenAI Codex)
Why use RankScale?
- Covers 17+ AI engines from the entry-level plan with no per-engine add-on fees
- Citation analysis shows which sources AI engines actually quote, informing content strategy
- Competitor benchmarking auto-identifies rivals and compares visibility in the same AI responses
- Credit-based pricing scales from small teams up to agencies and enterprises with white-label and API access
Pros & cons
Pros
- Covers 17+ AI engines (ChatGPT, Perplexity, Gemini, Claude, Copilot, AI Overviews, and more) from the entry-level plan with no per-engine surcharges
- Citation analysis shows which sources AI engines actually cite, useful for shaping content strategy
- Used by large brands including Bosch, UBS, Cartier, O2, Otto, StepStone, and OMR, plus agencies like Coalition Technologies, Dentsu, Publicis Sapient, and WPP Media
- Publishes named, agency-attributed case studies with quantified results rather than only aggregate marketing claims, MiniFinder reached the #1 AI-search spot in 90 days, SoWork hit 100% visibility and a 63% market lead in 90 days, and an AI SMS platform generated $280K in pipeline from AI search
Cons
- No traffic attribution: RankScale can't connect AI visibility to actual website sessions, leads, or revenue, there's no GA4 integration or conversion tracking
- Credit-based billing is unpredictable, engine costs vary from 0.25 to 2+ credits per query, and reviewers report exhausting monthly credits quickly on smaller plans
- Visibility scores can swing 10-15% week-to-week even without site changes due to underlying AI model volatility, and sentiment analysis isn't always accurate
- Client-ready reporting exports are limited, one reviewer found no way to export a clean overview list, making agency client reporting mostly manual
- Self-reported user counts are inconsistent: RankScale's own homepage states "2,000+" in its stats bar but "1,000+ active users" repeated in the hero, features, and closing call-to-action
Limitations
- No GA4 or analytics integration for connecting AI visibility to traffic or revenue
- Diagnoses AI-visibility issues but provides no automated content fixes or schema deployment
- REST API is gated behind the Growth ($385/mo) and Enterprise ($780/mo) tiers only
- Sparse third-party review coverage on G2/Capterra makes independent at-scale reliability hard to verify
RankScale pricing
- Essentials$20 / month
- Pro$99 / month
- Growth$385 / month
- Enterprise$780 / month
See current pricing on rankscale.ai ↗Compare RankScale alternatives →
RankScale specs
Pricing
- Pricing model
- subscription
- Free tier
- ✗ No
Capabilities
- Public API
- ✓ Yes
RankScale review
RankScale is a credible, actively used GEO/AI-visibility platform with broad engine coverage and genuine enterprise customers, but its credit-based pricing gets expensive fast for API and white-label access, and it stops short of proving ROI.
Re-verified 2026-07-21: pricing, tier limits, engine count (17+), and existing cons (attribution, credit consumption, reporting exports, score volatility) are all unchanged from the 2026-07-11 check. Added a genuine new capability not previously captured, Rankscale MCP, a read-only remote MCP server for Claude/ChatGPT/Cursor/Codex, plus three named, agency-attributed case studies (MiniFinder, SoWork, an AI SMS platform) from rankscale.ai/case-studies, and an expanded, corroborated named-customer list. Declined to publish a specific active-user count: the vendor's own homepage states both "2,000+" and "1,000+ active users" in different sections, a self-contradiction now flagged as a con rather than repeated as a fact.
Frequently asked questions
Does RankScale have a free trial?
Which AI engines does RankScale track?
Does RankScale have an API?
Can RankScale prove AI visibility drives revenue?
Does RankScale connect to AI coding assistants like Claude or Cursor?
RankScale alternatives
- Frase
Frase bundles AI-visibility tracking into a full content-creation platform — SERP briefs, AI drafting, decay-repair — if you want one subscription that also writes the content that wins the citation back.
Get a quote from RankScale
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