Know how AI tools describe, cite, and recommend your brand.
Track 23 metrics across 12 engines — from mentions and citations to competitor pressure and sentiment — so you know exactly where your brand stands in AI answers.
AI Crawler Intelligence
AI crawler reads found across tracked pages.
Pages available to support AI answers and citations.
Pages blocked by robots, auth gates, noindex, or stale access rules.
GPTBot / 184 hits / 9 minutes ago
PerplexityBot / 162 hits / 18 minutes ago
ClaudeBot / 147 hits / 31 minutes ago
Google-Extended / 128 hits / 47 minutes ago
OAI-SearchBot / 117 hits / 1 hour ago
Common Crawl / 12 hits / 2 hours ago
Crawled
Cited
Citation Rate
mentions / rank / answer summary / owned citations
citations / source quality / competitor pages / freshness
entity clarity / brand presence / page coverage / sentiment
message quality / proof gaps / recommended alternatives / summary accuracy
Competitor alternative pages
AI answers cite competitor-owned pages when users ask for shortlists and alternatives.
Blocked crawler recovery
Blocked assets and stale PDFs reduce the pages available for answer citation.
Agency reporting workflow
Agency prompts ask for client-ready reporting and recurring monitoring examples.
Know if the brand appears
Track 23 metrics including visibility score, mention rate, answer position, entity recognition, and sentiment across the prompts buyers ask before they click.
See who wins instead
Use share of voice, competitor pressure, prompt difficulty scoring, and competitive moat analysis to find prompts where rivals own the recommendation and identify the fastest path to overtake them.
Fix the cited source trail
Use owned citation share, source quality, crawler-to-citation correlation, citation velocity tracking, and generated content briefs to decide and prioritize the next content action.
AI Visibility Score
A rollup score for whether the brand is mentioned, cited, recommended, and framed well across monitored prompts.
Brand Mention Rate
How often the brand appears in AI visibility answers across the tracked prompt set.
Answer Position
Average placement when the answer lists vendors, products, agencies, or recommended sources.
AI Share of Voice
The brand's share of answer mentions compared with named competitors in the same prompt cluster, weighted by prompt intent and audience reach.
Narrative Drivers
Top cited domains and specific prompts shaping the brand's story, revealing influential publishers for outreach and the exact queries driving conversation.
Competitor Pressure
Prompts where competitors appear ahead of the brand or own the recommendation completely.
Sentiment Quality
Whether answer wording is positive, neutral, mixed, or negative when the brand is mentioned.
Owned Citation Share
How often answers cite owned pages instead of third-party, competitor, community, or directory sources.
Source Quality Score
A quality read on the sources shaping the answer, including owned pages, reviews, media coverage, listicles, Reddit, YouTube, and news.
Crawler Citation Match
How often cited pages have recent AI crawler activity, so crawler access can be connected to later answer evidence.
Opportunity Backlog
Open fixes generated from missed mentions, weak citations, competitor wins, content gaps, and readiness issues.
Prompt Volume
Estimated monthly search demand behind tracked prompts, derived from real search behavior rather than synthetic queries.
Geo Distribution
Geographic breakdown of brand mentions across countries and regions where AI platforms reference the brand.
Citation Quality Score
How citation-ready your content is across 6 dimensions: fact density, structured data, entity clarity, named frameworks, freshness, and answer readiness.
Social Thread Coverage
Reddit, Hacker News, LinkedIn, and other social threads where your brand or competitors are discussed — the training signals AI models use.
Entity Recognition Score
How consistently AI models correctly identify, describe, and contextualize your brand — measuring mention consistency, context accuracy, and disambiguation across engines.
Prompt Difficulty
Estimated difficulty of earning a brand mention for each prompt, factoring competitor density, citation authority, answer consistency, and intent competitiveness.
Citation Readiness
How ready your content is to be cited by AI models across 6 dimensions: fact density, structured data, entity clarity, named frameworks, freshness, and answer readiness.
Citation Velocity
Week-over-week citation momentum — whether the brand is gaining or losing AI citation ground. Complements AISoV by measuring trajectory rather than market share at a point in time.
AEO Content Score
Answer Engine Optimization readiness across 7 factors: E-E-A-T signals, schema markup, direct answer quality, content freshness, structured formats, readability, and fact density.
Prompt-Space Occupancy
Percentage of monitored prompts where the brand appears. Use it as a directional coverage metric and compare it against repeated scans, competitor pressure, and source quality.
Visibility Volatility
How much the brand's visibility fluctuates across scan cycles. Low volatility means AI models reliably include the brand; high volatility means inconsistent citation patterns.
Multi-Platform Citation Impact
How widely the brand is cited across different AI platforms. Use it as a directional cross-platform authority signal and validate conversion lift against your own analytics.
15–48%
Public trackers show wide variance in Google AI Overview prevalence. Treat query-set and industry ranges as directional, not universal.
12
Configured answer engines are documented in the live product model and should be monitored with plan-specific engine caps.
5
Core recurring report surfaces are documented in the live product model and should stay aligned with the current plan and engine configuration.
23
Documented visibility metrics are measured from saved answer evidence rather than from a single vanity score.
6
No-signup free tools give teams a public baseline before they commit to recurring monitoring.
25+
The public AI visibility category now spans funded, bootstrapped, and suite-attached vendors across monitoring, optimization, and enterprise workflows.
Daily
Daily monitoring is now the baseline expectation on paid AI visibility tiers, but the exact evidence model still varies by vendor.
$99+
Dedicated AI visibility pricing usually begins around entry paid tiers, while higher-volume reporting and enterprise workflows move materially higher.
25–50 prompts
2026 monitoring playbooks still need enough buyer-intent prompt depth before teams trust trend claims; one-off checks are useful entry points, not durable measurement.
38% fewer organic clicks
Recent field studies show AI answer surfaces can materially change click behavior, so answer presence and citations should be treated as executive reporting inputs.
21,143 citations
Recent GEO research shows citation counts and answer influence diverge, so reports should expose answer excerpts, source quality, and confidence labels.
CCBench + TerminalBench
Terminal coding agents are now a real workflow category; this product uses that shift to connect AI visibility findings to local orchestration instead of leaving teams at the dashboard.
11,500 queries
Public research now shows a meaningful share of buyers starting product discovery in AI assistants, not only in classic search results.
850K websites
AI-referral conversion benchmarks are directionally strong, but teams should validate impact with first-party attribution instead of treating any public benchmark as a universal multiplier.
14.2% vs 2.8% organic
Practitioner research shows GEO topical clusters can outperform isolated pages when depth, linking, and canonical structure are real.
Prompt-first
2026 GEO calendars should begin with buyer prompt research and answer-gap analysis, then publish pages measured with recurring monitors.
Brand visibility ROI
What improved AI visibility means for brands
Measure
AI traffic attribution
Compare AI-assisted visits and conversions against your own organic, paid, and direct baselines instead of relying on generic market averages.
Improve
Citation readiness
Strengthen answer-first copy, entity clarity, schema, third-party proof, and canonical source pages so AI systems have better evidence to cite.
< 30 min/week
Management time
After initial setup, maintaining an AI visibility program can take under 30 minutes per week when teams review saved answer evidence, prioritize briefs, and ship the highest-impact fixes first.
Platform Comparison
How brand monitoring compares across AI visibility platforms
The AI visibility market now includes 25+ tools spanning lightweight monitoring, optimization platforms, and enterprise suites. Many still emphasize aggregate scores first. prompts-gpt.com focuses on prompt-level evidence, citation intelligence, and content action workflows across 23 metrics and 12 AI engines.
| Capability | Prompts-GPT.com | Otterly / Foglift / Peec | Profound / Semrush / Qwairy |
|---|---|---|---|
| Prompt-level answer evidence | Full answer text, citations, sentiment, entity context | Aggregate score only (Otterly, Foglift) | Score + limited evidence (Profound, Peec) |
| AI engines monitored | 12 engines (ChatGPT, Google AI, Google AI Mode, Perplexity, Google Gemini, +7 more) | 4–6 engines (Otterly: 4 core + 2 add-ons, Peec: 6) | 5–10 engines (Profound: 10+, Qwairy: 10+) |
| Visibility metrics per scan | 23 documented metrics | 3–5 metrics (Semrush, Otterly) | 5–8 metrics (Qwairy GEO Score: 4 dimensions) |
| Competitor tracking | Mention share, recommendation order, source analysis, competitive moat scoring | Basic mention count (Foglift, Targetlytics) | SoV + position tracking (Profound, Qwairy) |
| Citation source classification | 14 source types: Owned, Competitor, Review, Reddit, YouTube, Hacker News, LinkedIn, Twitter/X, GitHub, Stack Overflow, and more | Basic URL list (Otterly) | Domain-level only (Peec, Semrush) |
| Citation quality scoring | 6-dimension scoring (fact density, schema, entity, frameworks, freshness, answer readiness) | Multi-factor GEO audit workflow (Otterly) | AEO Score 0-100 (Surfaced) |
| Entity recognition scoring | Consistency, context accuracy, disambiguation across all engines | Not available | Not available |
| Prompt difficulty scoring | 4-factor: competitor density, citation authority, answer consistency, intent weight | Not available | Not available |
| Content brief generation | Automated from answer gaps with citation optimization | Manual only (Otterly, Peec) | AI agents or guided workflows on higher-tier / sales-led platforms (Profound, Surva.ai) |
| Social thread tracking | Reddit, HN, LinkedIn, Twitter/X, GitHub, Stack Overflow | Not available (most platforms) | Reddit only (Semrush Enterprise, May 2026) |
| Free tools (no signup) | 6 tools (checker, market search, GEO scorer, query gen, llms.txt, Codex) | 0–1 tools (Otterly: GEO pages, HubSpot: AEO grader) | 1 tool (Ahrefs: free checker, Sona: 17-check audit) |
| Export formats | PDF, CSV, Markdown, JSON | PDF/CSV only (Otterly, Peec) | CSV + API (Qwairy, Profound Enterprise) |
What is AI brand visibility monitoring?
AI brand visibility monitoring tracks how answer engines mention, cite, and recommend your brand when buyers ask product or category questions. Because generated answers increasingly shape discovery before a website visit, this has become a core marketing function.
- 23 metrics per scan across 12 engines
- 14 public citation source types with quality scoring
- Competitor tracking with moat analysis
- Content brief generation from answer gaps
- Entity recognition and citation velocity
- 6 free tools with no signup required
Frequently asked questions about brand monitoring
What is AI brand visibility monitoring?
AI brand visibility monitoring tracks how AI answer engines like ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek, Meta AI, and Google AI Overviews mention, describe, cite, and recommend a brand when buyers ask product or category questions. It captures answer text, brand mentions, competitor context, cited sources, sentiment, entity recognition, and citation velocity per prompt. Because generated answers increasingly shape discovery before a website visit, monitoring AI visibility is now a core brand workflow.
How many AI engines does prompts-gpt.com monitor for brands?
prompts-gpt.com monitors brand visibility across 12 AI answer engines: ChatGPT, Google AI, Google AI Mode, Perplexity, Google Gemini, Anthropic Claude, and 6 more. Each scan captures 23 visibility metrics including mention rate, citation share, competitor pressure, sentiment, entity recognition, citation velocity, prompt difficulty, AEO content scoring, prompt-space occupancy (PSOS), and visibility volatility.
Can I monitor competitor brand mentions in AI answers?
Yes. The platform tracks competitor mentions, recommendation order, cited sources, share of voice, and citation velocity across monitored prompts. You can compare which competitors win specific prompt clusters and identify the source evidence behind their recommendations.
How long does it take to see visibility improvements?
Visibility changes depend on prompt difficulty, source quality, competitor pressure, and model refresh behavior. The platform helps teams shorten the loop by turning missing mentions into content briefs, source fixes, schema tasks, and recurring validation scans.
Do I need a paid plan to start brand monitoring?
No. 6 free tools are available without signup, including the AI Brand Visibility Checker which provides an instant baseline. Paid plans add recurring monitoring within plan-specific engine caps, historical trend tracking, content briefs, citation velocity tracking, prompt difficulty scoring, and export capabilities.
How does prompts-gpt.com compare to Otterly, Profound, or Semrush?
Otterly, Profound, Semrush, Peec, Ahrefs, and Searchable all provide serious AI visibility monitoring capabilities. prompts-gpt.com differentiates by pairing 23 metrics per scan, 6 free tools, persona analysis, source context, and content briefs for implementation workflows.