# AEO + AI Search A unified program covering on-page optimization, off-site brand signals, and proprietary tracking. Built for brands serious about growing visibility in the AI-era. [Schedule A Free Consultation](/contact) ## Three Pillars, One System 01. **On-Page Optimization** — Proven SEO foundations plus AI-specific analysis from proprietary signal data. Make your pages the ones AI models want to cite. 02. **Off-Site Brand Signals** — External placements that serve both traditional link equity and AI citation influence. 03. **Tracking & Monitoring** — Proprietary AI Visibility Platform reveals where you appear, why, and how visibility changes over time. ## On-Page: Strategic Foundations The always-on practices that AI discoverability is built on. ### Bot Rendering & Crawlability Ensure AI crawlers and search engines can access and render all content. Audit for client-side rendering gaps. ### Semantic Optimization Proper heading hierarchy, semantic HTML, and structured data that helps AI models identify entities and relationships. ### URL Structure & Internal Linking Clean URL patterns and linking architecture that reinforces topic authority and content relationships. ### Content Structure Clear topic organization, comprehensive coverage, and well-defined sections that AI models can parse and cite. ### Technical Accessibility Audit for rendering gaps, crawl barriers, and discoverability issues that prevent bots from seeing your pages. ### Continuous Maintenance Ongoing monitoring to catch new rendering or crawlability issues as your site evolves. ## On-Page: AI-Specific Analysis Beyond the strategic foundations, our tactical layer uses proprietary data to inform AI-specific optimization. We study what pages AI models are actually citing for your target queries: which formats earn citations, which topics appear most frequently, where competitors are cited and you are not. This informs new content creation based on proven citation patterns, not theoretical keyword research. The Signals Dashboard goes further, analyzing which specific content attributes correlate with AI citations for your industry. **15 predefined signals plus thousands of AI-discovered signals**, quantified through the Signal Lift Matrix, driving page-by-page optimization recommendations grounded in data. ## Signals Dashboard: Page-Level Optimization Quantified signal data driving every optimization recommendation. ### 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. ### Signal Discovery Engine 15 predefined signal categories plus 5,000+ AI-discovered signals across structure, quality, authority, freshness, and technical factors. Our Signal Intelligence layer normalizes raw discoveries into unified categories for analysis. ### Multi-Engine Analysis Different AI platforms weight signals differently. Recommendations tailored by engine, not generic one-size-fits-all guidelines. ### 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. ## Off-Site: Extend Your Presence Beyond Your Domain Every external placement serves both traditional search and AI search. ### Citation Pattern Analysis Identify which publications and content formats AI models cite for your category. ### Traditional Link Building Targeted do-follow backlinks on vetted publishers through listicles, reviews, and editorial features. ### AI Citation Building Placements structured to match proven AI citation patterns, positioning your brand in the ecosystem models draw from. ### Community Monitoring Awareness-level monitoring across Reddit and industry forums with strategic recommendations. ## Tracking: AI Visibility Platform Proprietary tracking across ChatGPT, Perplexity, and Google AI Mode. ### Competitive Intelligence Benchmark AI visibility against competitors across all platforms. See market share shifts and spot opportunities. ### Cited Pages & Domains Track which pages and domains earn AI citations in your space. Understand citation frequency and content formats. ### AI Traffic Analysis GA4-based reporting on sessions, engagement, and conversions from AI search sources. ### Prompts & Citations Drill into individual prompts to see full AI responses, citation placement, and how each engine interprets your queries. ### Query Fan-Out Scale analysis of how queries fan out across AI platforms. BigQuery-powered for enterprise-level data volumes. ## How the Pillars Connect Three pillars, one feedback loop. Each cycle produces better data, more targeted execution, and stronger results. ### Tracking Informs On-Page The Signals Dashboard reveals which content attributes correlate with AI citations. Those insights feed directly into page-level optimization recommendations and content gap analysis. ### Tracking Informs Off-Site Citation analysis reveals which publications and content formats AI models reference most. That intelligence drives targeting strategy for off-site placements. ### On-Page and Off-Site Reinforce Strong on-page content gives external placements more authority to point to. External placements drive citation signals that strengthen on-page visibility. ### Tracking Measures Impact As on-page and off-site efforts take effect, the tracking layer measures changes in citation share, competitive positioning, and AI-driven traffic. Results feed back into the next cycle. ## From Data to Strategy to Results 01. **Track & Analyze** — The AI Visibility Platform surfaces where your brand appears, which competitors dominate, and what content signals drive citations. 02. **Optimize On-Page** — Signal data informs page-level recommendations. Citation analysis guides new content creation. Foundations ensure bots can find everything. 03. **Build Off-Site** — Citation intelligence targets off-site placements to the publications and formats AI models already trust. 04. **Measure & Iterate** — Track changes in brand mentions, citation share, and AI-driven traffic. Feed results back into the next cycle. ## How This Differs from Generic AI Consulting | | Generic AI/GEO Consultant | Nectiv AI Search | | --- | --- | --- | | Tracking | Third-party prompt tools | Proprietary AI Visibility Platform | | Analysis | Counts mentions | Signal Lift Matrix explains why pages get cited | | On-Page | General AI guidelines | Page-level recs from quantified signal data | | Off-Site | Not typically offered | Integrated brand signal building | | Measurement | Periodic snapshots | Closed-loop tracking to outcomes | | Scale | Limited prompts, single engine | BigQuery-powered, multi-engine, thousands of prompts | | Intelligence | Single-client analysis | Cross-client trend analysis surfacing industry-wide AI shifts | | Integration | Standalone project | Unified with broader SEO through Adaptive Workflows | ## Flexible Budget, Adaptive Focus AI Search is one component of Nectiv's ongoing engagement. No locked-in service allocations: budgets shift month to month based on where the data says to focus. Three configurations within your engagement: - **Full AI Search Program** (On-Page + Off-Site + Tracking): Comprehensive AI search management across all three pillars. - **On-Page AI Optimization** (Strategic Layer + Tactical Layer + Tracking): AI-specific on-page strategy and optimization backed by signal data. - **Tracking & Monitoring** (Visibility Dashboard + Signals Dashboard + Reporting): Ongoing AI visibility monitoring, competitive benchmarking, and signal analysis. All managed within the Adaptive Workflow Framework alongside traditional SEO, content, and technical initiatives. ## Ready to Discuss AI Search Strategy for Your Brand? [Book a Meeting](/contact)