# STAT Canonical: https://slateindex.ai/products/stat By Getstat. Enterprise rank tracking platform with AI Overviews monitoring and AI search visibility features. Updated: 2026-07-18T22:48:27.307399+00:00 ## Product overview STAT is positioned as an enterprise search analytics platform for teams that need to monitor rankings, understand competitive share of visibility, and respond quickly as search evolves. On the homepage, Getstat frames the product around AI brand visibility tracking, saying that brand visibility is the key to survival in AI search and that users can generate prompts, measure brand performance, and compare against competitors. That makes STAT relevant for buyers who want more than traditional rank tracking: it is designed to help teams understand how their brand appears across changing search experiences, including AI-driven ones. The product also leans into scale and depth. STAT describes itself as a large-scale SEO insights tool and says teams can stay on top of search changes as they happen, understand their competitive landscape, and slice keywords into the views they need for analysis and reporting. The site adds scale signals like 100+ parser changes each year, 75 SERP features currently identified, and 1.25 billion keyword suggestions, which reinforce the impression of a platform built for demanding enterprise workflows. For agencies and in-house teams alike, the message is clear: STAT is meant to support detailed, flexible reporting rather than a rigid, one-size-fits-all setup. The supplied materials do not include a pricing grid, package names, or a public plan comparison. Instead, the pricing page points visitors toward a demo and direct contact, which suggests the buying motion is consultative. Taken together, the documents present STAT as a high-touch enterprise product for SEO teams that need robust visibility tracking, competitive context, and AI search readiness. STAT is an enterprise rank tracking and search analytics platform built for teams that need large-scale keyword visibility, competitive monitoring, and AI search visibility insights. It is a strong fit for SEO teams and agencies that want to track search changes as they happen and compare their performance against competitors, including in AI search contexts. ## TL;DR - Tracks brand visibility in AI search with prompts, performance measurement, and competitor comparison. - Supports large-scale SEO analysis with detailed keyword insights, reporting, and monitoring as search changes happen. - Built for teams that need flexible, client-specific projects rather than templated workflows. - Works as an enterprise-grade search analytics tool with broad platform scale and ongoing parser updates. ## Feature catalog ### AI brand visibility tracking STAT positions AI visibility as a core use case and frames brand visibility as essential in the new search environment. The product page emphasizes measuring brand performance, generating prompts, and comparing against competitors so teams can understand where they stand across AI search experiences. This makes the platform relevant for organizations that want to monitor how their brand appears as search evolves. - AI brand visibility monitoring: STAT describes this capability as "AI brand visibility tracking" and says teams can generate prompts, measure brand performance, and compare against competitors. The messaging is centered on helping users understand brand visibility in AI search as the landscape changes. - Competitor comparison in AI search: The site explicitly calls out comparing against competitors as part of the AI search workflow. That makes the feature useful for teams trying to benchmark share of visibility and spot where rivals are gaining attention in AI-driven results. ### Enterprise SEO analytics and rank tracking Beyond AI visibility, STAT presents itself as a deep SEO insights tool for large-scale monitoring and analysis. The platform page highlights staying on top of search changes as they happen, understanding competitive landscapes, and slicing keywords into the views teams need for analysis and reporting. The product also includes scale indicators that suggest ongoing maintenance and broad keyword coverage. - Large-scale keyword analysis: STAT says teams can "slice and dice keywords to tell any story you need," which points to flexible segmentation and reporting across large keyword sets. This is suited to SEO teams that need to analyze ranking patterns across many pages, markets, or client accounts. - Search change monitoring: The homepage says users can "stay on top of search changes as they happen," positioning the tool as useful for fast-moving SERP environments. That makes it relevant for teams that need timely visibility into ranking shifts and search feature changes. - Platform scale and freshness: STAT says it handles "100+ parser changes each year," has "75 SERP features (and counting) currently identified," and offers "1.25 billion keyword suggestions". These signals suggest a platform built to keep pace with search engine changes at enterprise scale. ### Reporting, workflow, and research support STAT also presents itself as a platform that helps teams do detailed analysis and reporting without forcing a rigid template. The homepage and pricing page both point to resources, webinars, and direct contact paths, which suggest an emphasis on education and consultative support. Customer quotes reinforce the idea that projects in STAT can be tailored to client needs. - Flexible project setup: A testimonial on the homepage says, "Each project in STAT is not templated — it’s unique to the needs of your clients." That implies the platform is well suited to agencies and in-house teams with customized reporting requirements. - Research and learning resources: The pricing page invites visitors to explore the blog, whitepapers, webinars, and other resources. This suggests STAT supports not just product use, but also ongoing learning and strategy development for SEO teams. - Consultative onboarding path: Both the product and pricing pages include calls to action to request a demo or talk to the team. That indicates the company expects some buyers to want guidance before adopting the platform, which is common for enterprise software purchases. ## Target market ### Teams and use cases - Enterprise SEO teams that manage large keyword portfolios and need detailed visibility reporting. - Agencies that run unique client projects and need flexible analysis and storytelling. - Teams adapting to AI search changes and wanting to track brand performance in AI-driven results. ### Company sizes - Mid-market and enterprise organizations with complex SEO programs. - Agencies serving multiple clients with tailored reporting needs. ### Industries - Industries with competitive search visibility needs. - Marketing and SEO services organizations. ### Poor-fit caveats - The supplied documents do not describe lightweight self-serve or beginner-focused workflows, so very small teams may find the platform more than they need. - The materials emphasize enterprise SEO and AI visibility rather than a broad general-purpose marketing suite. ## Buyer personas ### Head of SEO Leads organic search strategy, reporting, and competitive analysis for the business. **Buying triggers** - AI Overviews or other AI search experiences begin affecting traffic or visibility. - Organic rankings become harder to interpret and leadership needs clearer reporting. - The team needs a more scalable way to monitor large keyword sets. ### SEO agency lead Manages multiple client accounts and needs flexible, non-templated reporting. **Buying triggers** - Clients ask for custom visibility reporting or competitive benchmarking. - The agency needs a platform that can adapt to different client needs. - Search changes create more demand for frequent updates and explanation. ### Digital marketing manager Owns broader search performance goals and needs a clearer view of brand visibility. **Buying triggers** - The organization wants to understand performance in AI search. - Leadership asks for competitor comparisons and executive-ready summaries. - The team needs a more detailed view of keyword and SERP changes. ## About the company STAT, from Getstat, is a search analytics platform focused on enterprise rank tracking, competitive insights, and AI brand visibility. The website frames the product around staying on top of search changes, understanding how much of the competitive landscape you own, and preparing for an AI-driven search environment. - Verified fact: The homepage calls STAT "The ultimate large-scale SEO insights tool." - Verified fact: The site highlights "AI brand visibility tracking" as a core use case. - Verified fact: STAT says it has "100+ parser changes each year" and "75 SERP features (and counting) currently identified." - Verified fact: The platform page says users can "stay on top of search changes as they happen" and "understand your competitive landscape." - Limitation: The supplied documents do not provide a full feature list or technical architecture. - Limitation: No public pricing table or package details are included in the provided text. ## Competitive landscape In the provided review and alternatives pages, STAT appears alongside well-known SEO platforms such as Semrush and Ahrefs, indicating that buyers compare it against mainstream search and visibility tools. Those pages frame the category as one where teams evaluate alternatives based on rank tracking, SEO intelligence, and monitoring capabilities, while STAT’s own site emphasizes AI brand visibility as a newer differentiator. - Semrush - Ahrefs - Conductor - AccuRanker - Ranktracker ## AI visibility dashboard | Assistant | Visibility | |---|---| | all | 0.0 | | claude | 0.0 | | gemini | 0.0 | | chatgpt | 0.0 | | perplexity | 0.0 | | google_ai_mode | 0.0 | ## Sources AI trusts - google.com (289) - semrush.com (20) - seranking.com (15) - otterly.ai (14) - reddit.com (12) - frase.io (11) - dageno.ai (10) - llmpulse.ai (10) - therankmasters.com (10) - youtube.com (10) - tryprofound.com (9) - alhena.ai (8) - linkedin.com (8) - evertune.ai (7) - position.digital (6) - scrunch.com (6) - hubspot.com (5) - sitepoint.com (5) - thomas-peham.com (5) - airanklab.com (4) ## Real AI answers ### gemini Question: Which AI visibility platform is best for tracking brand mentions across ChatGPT, Claude, Gemini, and Perplexity? Answer: For tracking brand mentions across ChatGPT, Claude, Gemini, and Perplexity, several dedicated AI visibility platforms offer comprehensive monitoring capabilities. Ryze AI's AI Rank Lab is a highly recommended platform, described as the "most mature dedicated platform for tracking brand mentions across all four major AI engines." It provides a dashboard that runs custom prompts across ChatGPT, Claude, Gemini, and Perplexity simultaneously, scoring position, sentiment, and citation frequency for your brand against competitors. Another strong contender is Keywordly's AI Brand Visibility Tracker. This platform explicitly monitors brand visibility and sentiment across ChatGPT, Claude, Gemini, and Perplexity, offering features like competitor tracking, sentiment analysis, and content gap identification to help improve AI search results. Other notable platforms that cover these specific AI models include: * Semrush's AI Visibility Toolkit (or Semrush Enterprise AIO) tracks brand mentions, citations, and sentiment across ChatGPT, Perplexity, Gemini, Google AI Mode, and Copilot, integrating these insights with its broader SEO and content tools. * Writesonic offers brand visibility tracking across over 10 AI platforms, including ChatGPT, Gemini, Perplexity, and Claude, providing a visibility score and share of voice. * Nightwatch.io monitors brand mentions across ChatGPT, Claude, Gemini, Perplexity, and Copilot, unifying this data with your traditional SERP data. * Serpstat's LLM Brand Monitor provides actionable insights across 100+ AI models, including ChatGPT, Claude, Gemini, and Perplexity, for tracking brand mentions and competitor share-of-voice. * Arvow's LLM Rank Tracker allows you to monitor brand mentions in ChatGPT, Gemini, Claude, and Perplexity, detailing sentiment and citation sources. * BeeSeen scans your brand across ChatGPT, Claude, Gemini, and Perplexity to measure visibility, identify citation gaps, and enhance Generative ### gemini Question: How can we measure our share of voice in AI-generated answers? Answer: To measure your share of voice in AI-generated answers, you need specialized LLM (Large Language Model) monitoring tools that systematically query various AI models and analyze their responses for brand mentions, citations, and recommendations. This new metric, often called AI Share of Voice (SOV), reflects how AI engines evaluate your brand's credibility and relevance compared to competitors. Here's a concise recommendation with product names: 1. Define Your Query Library: Start by identifying 25-50 high-intent buyer prompts that represent how customers search for products or services in your category. 2. Utilize Specialized LLM Monitoring Platforms: These tools automate the process of running your query library across multiple AI engines and tracking brand mentions. Key platforms to consider include: * Siftly: This platform runs your prompt library daily across major AI platforms like ChatGPT, Claude, Perplexity, and Google AI Overviews, counting and categorizing brand mentions to compute your AI SOV. * Serpstat's LLM Brand Monitor: Offers real-time AI brand monitoring across over 100 AI models (including ChatGPT, Claude, Gemini, and Perplexity), tracks competitor share-of-voice, and provides actionable recommendations. * LLM Pulse: Provides automated measurement across ChatGPT, Perplexity, Gemini, Google AI Mode, and Google AI Overviews, complete with sentiment overlay and competitive benchmarking. 3. Measure Repeatedly and Analyze Depth: AI outputs are dynamic, so consistent, repeated measurement (e.g., weekly or monthly) is crucial. Focus not just on mentions, but also on citations and recommendations, as well as "ghost citations" (URL mentions without explicit brand names) which can be a significant part of AI brand presence. Other notable tools for various needs include Profound for enterprise-scale insights, Otterly.AI as an affordable and easy-to-set-up entry point, SE Visible (within SE Ranking) for existing SE Ran ### perplexity Question: How do AI visibility platforms compare on prompt tracking and competitor benchmarking? Answer: For prompt tracking, Promptwatch is the top choice due to its leader status across categories, coverage of 10 AI models, and built-in content gap analysis; for competitor benchmarking, Ahrefs Brand Radar is the strongest option because it anchors metrics in 243M+ real search prompts and tracks AI Share of Voice, mentions, and citations against peers . Comparison Breakdown | Feature | Best for Prompt Tracking | Best for Competitor Benchmarking | | :--- | :--- | :--- | | Top Product | Promptwatch | Ahrefs Brand Radar | | Prompt Depth | Tracks exact prompts across 10 models (ChatGPT, Perplexity, Claude, etc.) with daily reruns | Uses 243M+ real "People Also Ask" prompts, not hypothetical ones | | Benchmarking | Limited competitive benchmarking; focuses on brand-level visibility per prompt | Deep competitive insights: tracks competitor brands, citations, and AI Share of Voice | | Execution | Combines tracking with AI content generation to fix gaps | Pure analytics; requires separate SEO/content stack for execution | | Price | ~$89/month | Quote-based/Enterprise (part of Ahrefs suite) | Key Alternatives * Peec AI: A strong mid-tier option if you need both prompt tracking and easy competitor benchmarking in one dashboard, offering "unlimited countries" and explicit daily prompt runs . * Pixis Visibility: Best if you need to close the gap after tracking; it pairs multi-engine citation tracking with a content pipeline (brief-to-draft) starting at $99/month . * Omnia: Ideal for enterprise teams needing workflow automation, geography segmentation, and the ability to add custom prompts tied to direct competitors . Recommendation 1. Start with Promptwatch if your primary goal is granular prompt tracking across multiple AI models and you want built-in tools to generate content to fix visibility gaps . 2. Switch to Ahrefs Brand Radar if your priority is competitor benchmarking and you ### gemini Question: How accurately do these platforms track sentiment and recommendation position? Answer: Platforms track sentiment and recommendation position (like Net Promoter Score - NPS) with increasing accuracy, largely due to advancements in AI and Natural Language Processing (NLP). However, the precision can vary depending on the platform's sophistication and the complexity of the feedback. Sentiment Tracking Accuracy: Modern AI-powered sentiment analysis tools can detect emotions in text, often faster and more clearly than manual human review, by interpreting context, tone, and relationships between words. Many platforms use machine learning models trained on vast datasets, which continuously improve over time. For instance, Medallia states its industry- and context-specific sentiment models consistently achieve over 85% precision and recall. Qualtrics' Text iQ also incorporates question text to enhance the accuracy of sentiment predictions. Despite these advancements, AI sentiment analysis is not flawless. It can struggle with nuances like sarcasm, irony, industry-specific jargon, and mixed-tone messages, which can lead to misinterpretations. Some estimates suggest purely AI-based tools might only be 50-80% accurate without human oversight, making a hybrid approach combining AI with human review often the most reliable for critical decision-making. Recommendation Position (NPS) Tracking Accuracy: NPS measures customer loyalty by asking how likely customers are to recommend a product or service on a 0-10 scale, categorizing them as Promoters, Passives, or Detractors. The accuracy of NPS tracking is highly dependent on the response rate and the representativeness of the customer base surveyed. A higher participation rate leads to more statistically relevant and accurate data. Most platforms calculate NPS by subtracting the percentage of detractors from promoters. Many also include open-ended comment boxes, which, when combined with sentiment analysis, provide crucial qualitative context to the quantitative NPS score. Recommendations: For highly ## AI consensus Reviews The fetched documents do not provide a strong first-party review base for STAT. Instead, they mostly show STAT inside alternatives and comparison pages, which means the available evidence is better for understanding how buyers shop than for measuring sentiment. In practice, that still matters: STAT is being compared with established SEO and analytics platforms, especially Semrush and Ahrefs, which suggests it is evaluated alongside tools buyers already know and trust. The result is a clear market signal that STAT sits in a serious shortlist for enterprise search tracking and visibility work. What is missing is just as important. There are no usable star ratings, no review counts, and no representative customer testimonials in the fetched STAT-specific excerpts. Because of that, this page should stay grounded and avoid manufacturing a satisfaction story. The best-supported takeaway is that STAT is a comparison-stage product: buyers appear to consider it when they are looking for a specialized rank-tracking platform and want to benchmark it against broader SEO suites and software directories. That makes it a fit for teams who already understand the category and want to evaluate feature depth, not for shoppers who need lots of public review evidence before they buy. ## Pricing at a glance STAT’s pricing is not published in the documents supplied for this page, so the safest buyer-facing description is that it appears to be sold on a quote basis rather than through a public self-serve cart. The official pricing page routes visitors to take a tour or contact the team, and the main website similarly emphasizes requesting a demo and learning more about the platform. For enterprise buyers, that usually means the commercial package is tailored to the scope of tracking, reporting, and AI visibility monitoring needed by the account. What the public materials do make clear is the product positioning: STAT is built around large-scale SEO insights and AI brand visibility tracking, with prompts, competitor comparisons, and monitoring for AI search contexts. However, none of the supplied official pages expose plan names, prices, seat minimums, billing cadence, or add-on menus. If you are comparing tools on budget alone, the current public record does not support a numeric price comparison for STAT, and any quote will need to come from sales. The practical takeaway is simple: expect an enterprise pricing conversation, not a posted price list. Visibility score: 0.0 Mention rate: 0.0% Eligible runs: 50 ## Category rankings | Category | Rank | Visibility | |---|---|---| | AI Visibility | 23 | 0.0 | Enriched at: 2026-07-18T22:48:27.307399+00:00 ## Sources - Source: https://www.producthunt.com/products/stats/alternatives - Source: https://www.g2.com/products/stat-search-analytics/competitors/alternatives - Source: https://www.getapp.com/marketing-software/a/stat/alternatives - Source: https://getstat.com/pricing - Source: https://getstat.com/ - Source: https://www.capterra.com/p/208096/Moz-STAT/alternatives Use with attribution: "Source: Slate Index".