# AI Prompt Tracking Platform The search landscape has fundamentally shifted. Our proprietary AI Prompt Tracking Platform monitors your brand's visibility across all primary AI engines, revealing not just where you appear, but why. [Schedule A Demo](/contact) ## Two Dashboards. Complete AI Visibility. Most AI tracking tools show where you appear, but not why. Our AI Prompt Tracking Platform brings together two dashboards: - **Visibility Dashboard** for tracking AI search visibility, competitors, citations, and entities. - **Signals Dashboard** for analyzing the content signals associated with citation performance. Together, they show where you stand, why pages earn citations, and what to do next. ## Visibility Dashboard Track brand presence across 5+ AI engines including ChatGPT, Google AI Mode, and Gemini with 9+ specialized analysis tabs covering competitive intelligence, entity recognition, shopping visibility, and more. ### Competitive Intelligence Benchmark your AI search visibility against key competitors across all platforms. See market share shifts, identify emerging threats, and spot opportunities where competitors aren't being cited. ### Cited Pages & Domains Track exactly which pages and domains AI engines cite when responding to prompts in your space. Understand citation positioning, frequency, and which content formats earn the most references. ### Domain Authority Mapping Analyze the domain landscape that AI engines draw from for your target queries. Identify which authoritative sources dominate citations and where your domain ranks in the citation hierarchy. ### Prompts & Citations Deep Dive Drill into individual prompts to see full AI responses, citation placement, and HTML exports. Analyze how AI engines interpret your target queries and where your brand appears (or doesn't) in each response. ### Query Fan-Out Analysis Analyze prompts at scale to understand how queries fan out across AI platforms. See which content signals matter for different query types, compare engine-specific behaviors, and identify cross-client trends. Built on BigQuery for enterprise-scale analysis of thousands of prompts. ## What the Visibility Dashboard Tracks Ten specialized tabs covering every dimension of AI search performance. ### Brand Mentions Track every time AI engines mention your brand, products, or key personnel across 5+ AI engines including ChatGPT, Google AI Mode, and Gemini. ### Competitive Intelligence Compare AI visibility against competitors. See who's gaining share, who's losing ground, and where the gaps are. ### Multi-Platform Coverage Unified tracking across 5+ AI engines including ChatGPT, Google AI Mode, and Gemini with platform-specific insights and comparison. ### Web Search Query Extraction Discover which traditional search queries AI engines associate with your prompts, bridging the gap between AI and organic search. ### Entity Recognition Named entity extraction reveals how AI models categorize your brand, products, and industry associations. ### Citation Tracking Domain, URL, and position-level citation data showing exactly where and how your content gets referenced. ## Signals Dashboard The industry's first AI citation signal analysis engine. Go beyond 'what' to understand 'why': the content signals that determine whether AI engines cite your pages. ### Signal Trends Track how content signals evolve across AI engines over time. Trend lines reveal which page attributes are growing in correlation with citations and which are declining, surfacing shifts in what AI models prioritize as new versions launch. Understand whether signals like pricing transparency or structured data are gaining or losing weight, so your optimization strategy adapts to where AI search is heading, not where it was. ### Signals by Page Type Not every signal matters equally across every page format. This view breaks down signal prevalence by page type across cited URLs, showing what percentage of landing pages, product pages, blog posts, resource hubs, and other formats carry each on-page attribute. The analysis is scoped to your competitive set, so the data reflects what actually drives citations in your specific industry and category. The signals that matter for B2B SaaS product pages won't be the same ones that matter for e-commerce category pages. Use it to identify which signals are table stakes for a given page type in your space and which represent gaps your competitors haven't closed yet. ### Content Alignment Understand exactly which parts of your pages AI engines are pulling from when they cite you. Content Alignment maps specific passages from cited URLs to the corresponding sections of AI responses, classifying each match by type (direct quote, paraphrased, factual claim, data point) and confidence score. Section-level analysis reveals which content formats and page regions drive the most value, while prompt-level breakdowns show how different queries extract different parts of the same page. Instead of just knowing a page was cited, you see precisely what content earned the citation and how the AI model used it. ### Discovery Signals Beyond our predefined signal checks, the AI model independently identifies additional page attributes it considers relevant to citation decisions. These discovery signals surface patterns we didn't explicitly define, from breadcrumb navigation to estimated reading time to faculty credentials. Because AI models generate varied naming for similar concepts, our Signal Intelligence layer groups raw discoveries into normalized categories for unified analysis, turning thousands of unstructured observations into actionable insight. ### Cross-Engine Citations Not every URL gets cited by just one AI platform. This view isolates the pages that appear across multiple engines, revealing which content has earned authority beyond a single algorithm's preference. The cross-engine rate tracks what percentage of all cited URLs show up in two or more engines, normalized against your total tracking volume so the metric doesn't inflate as you scale. Monthly trend lines break down which engines are driving the overlap and whether cross-platform visibility is growing or consolidating. We use it to identify the pages and reverse-engineer what makes them structurally different from single-engine citations. ### Prompt-to-Signal Correlation Uncover which prompt patterns drive specific content signals. N-gram fragment analysis maps word patterns in AI queries to the page-level signals that correlate with citations, showing you exactly what content attributes matter for each type of buyer question. ## Predefined + AI-Discovered Signals The Signals Dashboard combines two layers of analysis. 15 predefined signals check for known citation drivers like structured data, content freshness, and authority indicators. But the real depth comes from discovery: the AI model independently identifies thousands of additional page attributes it considers relevant to citation decisions, surfacing patterns no predefined checklist would catch. - **15 predefined signals** cover the fundamentals: content structure, quality indicators, authority markers, freshness, technical factors, and schema markup - **5,000+ discovery signals** identified autonomously by the AI across analyzed pages, capturing attributes like pricing transparency, faculty credentials, breadcrumb navigation, and estimated reading time - **Signal Intelligence grouping** normalizes the varied naming that AI models produce, mapping raw discoveries into categories like Authority, Content Structure, and Freshness for unified analysis - **Multi-engine comparison** reveals how different AI engines weight the same signals differently, so you can tailor optimization by platform - **Trend tracking** shows how signal importance shifts over time as new model versions launch and priorities change The combination means you're not limited to checking what you already know matters. The platform continuously expands its understanding of what drives AI citations as the landscape evolves. ## From Data to Strategy 01. **Prompt Universe Definition** — We work with you to define the prompts that matter: the questions your buyers ask AI when evaluating solutions in your category. We scale to thousands of prompts across your full competitive landscape. 02. **Multi-Engine Data Collection** — Our tracking infrastructure queries 5+ AI engines including ChatGPT, Google AI Mode, and Gemini at regular intervals, capturing full responses, citations, entity mentions, and web search queries associated with each prompt. 03. **Signal Analysis & Correlation** — The Signals Dashboard analyzes every cited page against 100+ content signals, building a Signal Lift Matrix that quantifies what drives citations for your specific industry, query types, and competitive set. 04. **Strategy & Optimization** — Insights flow directly into page-level optimization recommendations. Every strategy is backed by signal correlation data, not intuition. We track impact over time and adjust as AI engine algorithms evolve. ## Why This Isn't Another Prompt Tracker Most AI visibility tools just count mentions. We engineered something fundamentally different. | | Generic AI Trackers | Nectiv's AI Tracker | | --- | --- | --- | | Analysis Depth | Brand mention counts and basic visibility scores | Full signal correlation analysis explaining why pages get cited | | Data Architecture | Single-tenant SaaS with limited query volume | BigQuery + Firestore hybrid built for enterprise-scale tracking | | Data Transparency | Aggregated dashboards, no raw data access | Full HTML exports, raw JSON, and deep-dive investigation tools | | Signal Intelligence | Manual content audits based on general best practices | 100+ AI-discovered signals with quantified lift per engine | | Strategy Output | Generic optimization checklists | Page-level recommendations backed by signal correlation data | | Cross-Client Insights | Isolated single-account analysis | Cross-client pattern recognition surfaces industry-wide shifts early | ## Built for B2B Brands Serious About AI Search The AI Prompt Tracking Platform isn't a generic SaaS tool. It's proprietary technology built by practitioners who manage AI search strategy for B2B brands every day. Every feature exists because we needed it to drive better outcomes for our clients. The platform runs on a BigQuery + Firestore architecture designed for enterprise-scale analysis. Insights don't live in dashboards alone. They feed directly into page-level strategy, content optimization priorities, and competitive positioning. When we recommend an optimization, it's backed by quantified signal correlation data specific to your industry, your pages, and your competitive landscape. ## See How Your Brand Appears Across AI Search [Book A Demo](/contact)