Articles

Insurance companies get cited by AI when they publish authoritative coverage explanations, regulatory compliance information, and carrier appetite guides that answer the specific questions insurance buyers ask at each stage of their research. Unlike other B2B categories where buyers start with vendor discovery, insurance buyers begin with educational queries about coverage types before they consider … Read more

AEO and traditional demand generation are not competing strategies. They operate at different points in the buyer journey. AEO handles the dark funnel where buyers complete vendor research inside AI systems that generate zero trackable signals — this is the dark funnel at its most consequential. Traditional demand gen handles the visible funnel where buyers … Read more

G2 is not just a review collection platform. For AEO purposes, it functions as a content creation platform where every element of your profile becomes citation-eligible third-party content that AI systems treat as credible validation. Your profile description, customer reviews, Q&A responses, and integration listings all contribute to your Share of LLM in ways that … Read more

Writing a comparison page that gets cited by AI requires neutrality, specificity, and structure. Most B2B comparison pages fail because they read like promotional content rather than analysis. AI systems cite pages that provide factual, extractable information about product tradeoffs, not vendor marketing. Why comparison pages are the highest-value AEO content type Comparison queries drive … Read more

A query library is a structured set of test queries a B2B company runs regularly across AI platforms to measure Share of LLM, identify citation gaps, and track competitor positioning. Without a query library, AEO measurement becomes anecdotal. You check a few queries when you think about it, draw no conclusions, and make no decisions. … Read more

The practical difference between AEO and GEO isn’t what you optimize, it’s when you measure impact. AEO targets immediate citations in current AI responses with results visible in 2-4 weeks. GEO builds long-term brand entity understanding in AI systems with compounding returns over 12-24 months. Most activities serve both purposes simultaneously, but understanding the timing … Read more

Building an AI-friendly content architecture requires three distinct tiers of content working together: foundational pages that teach AI systems what your company does, query-specific pages that answer targeted buyer questions, and authority pages that establish expertise. Most B2B companies have the foundational pieces buried, gated, or poorly structured — the three reasons this destroys citation … Read more

Cybersecurity vendors face a different AEO challenge than other B2B companies. Security buyers run compliance queries before anything else, ask architecture-specific questions, and validate technical capabilities through AI systems that prioritize certification data over marketing content. Generic AEO tactics miss the mark because cybersecurity buying follows compliance-first logic. The vendors getting cited understand this sequence. … Read more

B2B vendors face a new challenge: AI agents now research, evaluate, and score companies without human intervention at each step. When a buyer asks their AI assistant to “research the top 5 AP automation platforms and give me a comparison matrix,” that agent crawls vendor websites, pulls data from review sites, synthesizes comparisons, and delivers … Read more

B2B SaaS companies face a unique AEO challenge. While other B2B categories optimize for awareness queries like “what is supply chain management,” software buyers ask technical validation questions: “does HubSpot integrate with Salesforce,” “what’s the API rate limit for Stripe,” or “does Okta support SSO with our ERP.” These queries require deep technical content, not … Read more