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    <title>Kollavo Blog</title>
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    <description>Strategy, research and playbooks on winning visibility in AI-generated answers.</description>
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    <lastBuildDate>Mon, 10 Aug 2026 18:59:56 GMT</lastBuildDate>
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      <title>Which Sites Do LLMs Cite Most? What We See Across Thousands of Answers</title>
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      <description>AI answers do not pull from random corners of the web. Here are the source types that show up again and again — and what that means for where you publish.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Citation Sources</category>
      <pubDate>Mon, 10 Aug 2026 18:59:56 GMT</pubDate>
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      <title>How to Earn Citations in Trade Publications (Without a PR Agency)</title>
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      <description>Trade publications are among the sources AI reaches for most. Here is a practical, non-agency process for getting into them.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Citation Sources</category>
      <pubDate>Mon, 10 Aug 2026 18:59:56 GMT</pubDate>
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    <item>
      <title>Do Press Releases Get Cited by AI? An Honest Answer</title>
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      <description>Wire distribution is cheap and fast, which makes it tempting. Here is what press releases actually do for AI citations — and what they do not.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Citation Sources</category>
      <pubDate>Mon, 10 Aug 2026 18:59:56 GMT</pubDate>
    </item>
    <item>
      <title>GEO for SaaS: How to Get Your Product Recommended by AI</title>
      <link>https://kollavo.com/blog/geo-for-saas-companies</link>
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      <description>Buyers now ask ChatGPT for software recommendations instead of reading review sites. Here is the playbook for SaaS brands that want to be named.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Industry Playbooks</category>
      <pubDate>Mon, 10 Aug 2026 18:58:41 GMT</pubDate>
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      <title>GEO for Local Service Businesses: Getting Recommended in Your City</title>
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      <description>When someone asks an assistant for a plumber, dentist or contractor nearby, three names come back. Here is how to be one of them.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Industry Playbooks</category>
      <pubDate>Mon, 10 Aug 2026 18:58:41 GMT</pubDate>
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    <item>
      <title>GEO for Ecommerce: Getting Products into AI Recommendations</title>
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      <description>Shoppers ask assistants what to buy. Product pages alone will not get you named — here is what does.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Industry Playbooks</category>
      <pubDate>Mon, 10 Aug 2026 18:58:41 GMT</pubDate>
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    <item>
      <title>GEO for Agencies: How to Sell and Deliver AI Visibility</title>
      <link>https://kollavo.com/blog/geo-for-agencies</link>
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      <description>Clients are already asking why ChatGPT recommends their competitor. Here is how to scope, price and deliver AI visibility work without guessing.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Industry Playbooks</category>
      <pubDate>Mon, 10 Aug 2026 18:58:41 GMT</pubDate>
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    <item>
      <title>How to Get Cited by Perplexity: What Actually Works</title>
      <link>https://kollavo.com/blog/how-to-get-cited-by-perplexity</link>
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      <description>Perplexity shows its sources on every answer, which makes it the best place to reverse-engineer AI citations. Here is how to earn a spot.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 10 Aug 2026 18:57:12 GMT</pubDate>
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    <item>
      <title>How to Get Cited by Claude</title>
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      <description>Claude is conservative about sources and increasingly search-grounded. Here is what earns a citation, and why it is a useful stress test.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 10 Aug 2026 18:57:12 GMT</pubDate>
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    <item>
      <title>How to Get Cited by Google Gemini</title>
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      <description>Gemini blends model knowledge with Google grounding. That combination changes which signals matter — here is the practical breakdown.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 10 Aug 2026 18:57:12 GMT</pubDate>
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    <item>
      <title>How to Get Cited in Google AI Overviews and AI Mode</title>
      <link>https://kollavo.com/blog/how-to-get-cited-in-google-ai-overviews</link>
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      <description>AI Overviews pull from pages Google already trusts, then fan the query out into sub-questions. Here is how to be the source it quotes.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 10 Aug 2026 18:57:12 GMT</pubDate>
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    <item>
      <title>How to Get Cited by ChatGPT: The Practical Playbook</title>
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      <description>ChatGPT cites sources through search-grounded answers. Here is exactly what makes it pick your brand — and the five things to fix first.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 10 Aug 2026 18:57:12 GMT</pubDate>
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    <item>
      <title>The GEO Content Audit: A 12-Point Checklist for AI-Ready Pages</title>
      <link>https://kollavo.com/blog/geo-content-audit-checklist</link>
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      <description>The GEO Content Audit is a 12-point evaluation system designed to score a webpage&apos;s likelihood of being selected as a source citation by LLMs. By auditing variables like markdown boundaries, Entity Recognition, schema structures, and JS fallback rendering, brands can optimize pages specifically for LLM extraction. This tactical methodology ensures your content is selected, chunked, and dynamically cited across ChatGPT, Perplexity, Gemini, and Claude.</description>
      <dc:creator>Kollavo Team</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Wed, 15 Jul 2026 12:33:36 GMT</pubDate>
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    <item>
      <title>Zero-Click to Zero-Query: How AI Search Is Rewriting Funnel Economics</title>
      <link>https://kollavo.com/blog/zero-click-to-zero-query-ai-funnel</link>
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      <description>AI search is systematically dismantling the traditional inbound marketing funnel, shifting the battleground from driving site traffic to securing placements inside LLM context windows. As search moves from zero-click to predictive, zero-query answers, enterprises must treat conversational interfaces like Perplexity and ChatGPT as their primary conversion layer. Survival requires abandoning legacy CTR metrics for Share of Model (SoM) and structurally optimizing middle-of-funnel content for machine ingestion.</description>
      <dc:creator>Kollavo Team</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Wed, 15 Jul 2026 12:33:36 GMT</pubDate>
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    <item>
      <title>The Freshness Signal: How Often LLMs Recrawl and Why It Matters for Citations</title>
      <link>https://kollavo.com/blog/freshness-signal-llm-recrawl</link>
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      <description>To secure citations in search-enabled LLMs like Perplexity, Gemini, and ChatGPT, publishers must optimize for real-time retrieval-augmented generation (RAG) loops and active web crawlers. AI search engines rely on a combination of proprietary spiders (such as OAI-SearchBot and PerplexityBot) and commercial search indexes to fetch freshly indexed metadata and page deltas. Securing consistent citation real estate requires aligning your publication frequency with LLM crawl tempos and deploying precise structural signals like `dateModified` schemas and validation headers.</description>
      <dc:creator>Kollavo Team</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Wed, 15 Jul 2026 12:33:36 GMT</pubDate>
    </item>
    <item>
      <title>Prompt-Level Optimization: Ranking for the Question Behind the Question</title>
      <link>https://kollavo.com/blog/prompt-level-optimization-ai-search</link>
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      <description>AI search engines do not match user queries to surface keywords; instead, they run orchestrator agents to decompose complex, multi-variable prompts into distinct, latent sub-intents. To rank in systems like ChatGPT Search, Perplexity, Gemini, and Claude, brands must transition to Prompt-Level Optimization (PLO). This framework structures content to directly satisfy the functional, economic, and operational constraints embedded within a user&apos;s conversational intent.</description>
      <dc:creator>Kollavo Team</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Wed, 15 Jul 2026 12:33:36 GMT</pubDate>
    </item>
    <item>
      <title>GEO Attribution: How to Measure Traffic and Revenue From AI Answers</title>
      <link>https://kollavo.com/blog/geo-attribution-measuring-ai-traffic</link>
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      <description>Measuring traffic and revenue from AI search engines requires deploying a hybrid attribution model that combines specific LLM referrer identification, custom GA4 channel groupings, and a forward-deployed UTM strategy. Because over 70% of generative search clicks register as direct traffic due to browser containment and in-app sandboxes, organizations must implement the AI Referrer Reconstruct Framework to statistically isolate and attribute dark AI traffic spikes. Connecting these sessions directly to CRMs and transaction nodes is the absolute path to calculating GEO-specific CAC and pipeline ROI.</description>
      <dc:creator>Kollavo Team</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Wed, 15 Jul 2026 12:33:36 GMT</pubDate>
    </item>
    <item>
      <title>Citation Anchors: The On-Page Signals That Make LLMs Quote You</title>
      <link>https://kollavo.com/blog/citation-anchors-on-page-signals</link>
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      <description>To secure citations in LLM-driven search engines like Perplexity, ChatGPT, and Gemini, publishers must transition from writing for human narrative flows to engineering &apos;Citation Anchors.&apos; These are highly scannable, structurally isolated on-page text elements—such as definitional copulas, markdown stat blocks, named proprietary frameworks, and schema-mapped comparative tables—designed to match the precise vector retrieval mechanics of Retrieval-Augmented Generation (RAG). By embedding these high-density informational nodes into your content, you directly feed the attention heads of generative models, forcing them to lift and cite your brand as the canonical source.</description>
      <dc:creator>Kollavo Team</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Wed, 15 Jul 2026 12:33:36 GMT</pubDate>
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    <item>
      <title>Query Fan-Out: How AI Search Turns One Query Into Many (and How to Rank)</title>
      <link>https://kollavo.com/blog/query-fan-out-guide</link>
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      <description>Query fan-out is how AI search engines expand a single question into a swarm of sub-queries, retrieve passages for each, and synthesize one answer. Here is how it works and how to win the fan-out.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Mon, 13 Jul 2026 08:29:59 GMT</pubDate>
    </item>
    <item>
      <title>What Is Query Fan-Out in AI Search? A Plain-English Explanation</title>
      <link>https://kollavo.com/blog/what-is-query-fan-out</link>
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      <description>Query fan-out is how AI search decomposes one question into many hidden sub-queries to build a single answer. Here is a plain-English breakdown with examples.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Mon, 13 Jul 2026 07:29:59 GMT</pubDate>
    </item>
    <item>
      <title>Query Fan-Out for GEO: How to Optimize for AI Sub-Queries</title>
      <link>https://kollavo.com/blog/query-fan-out-geo</link>
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      <description>Generative Engine Optimization means winning the query fan-out. Learn how to model sub-queries, structure content for passage retrieval, and measure AI citations.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Mon, 13 Jul 2026 06:29:59 GMT</pubDate>
    </item>
    <item>
      <title>How Google AI Mode Uses Query Fan-Out (and How to Rank in It)</title>
      <link>https://kollavo.com/blog/google-ai-mode-query-fan-out</link>
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      <description>Google AI Mode uses a query fan-out technique to answer complex questions. Here is how it works, why it changes SEO, and how to structure content to get cited.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 13 Jul 2026 05:29:59 GMT</pubDate>
    </item>
    <item>
      <title>Query Fan-Out in ChatGPT, Gemini &amp; Perplexity: How Each One Expands Your Query</title>
      <link>https://kollavo.com/blog/query-fan-out-chatgpt-gemini-perplexity</link>
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      <description>ChatGPT, Gemini, and Perplexity all decompose your question before answering. Here is how query fan-out differs across each engine and how to get cited in all three.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Platform-Specific</category>
      <pubDate>Mon, 13 Jul 2026 04:29:59 GMT</pubDate>
    </item>
    <item>
      <title>How to Write Content That Answers the Full Query Fan-Out</title>
      <link>https://kollavo.com/blog/write-content-for-query-fan-out</link>
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      <description>Winning query fan-out is a content-structure problem. Here is a step-by-step method to plan, write, and structure content that gets retrieved across every sub-query.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Content Structure</category>
      <pubDate>Mon, 13 Jul 2026 03:29:59 GMT</pubDate>
    </item>
    <item>
      <title>Query Fan-Out vs Traditional Keyword Research: What Changes for SEO</title>
      <link>https://kollavo.com/blog/query-fan-out-vs-keyword-research</link>
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      <description>Keyword research finds what people type; query fan-out is what engines generate. Here is how they differ, where they overlap, and how to combine them for AI search.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Measurement &amp; Tools</category>
      <pubDate>Mon, 13 Jul 2026 02:29:59 GMT</pubDate>
    </item>
    <item>
      <title>FAQ Schema: How to Structure FAQs So AI Cites Them</title>
      <link>https://kollavo.com/blog/faq-schema-how-to-structure-faqs-for-ai</link>
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      <description>FAQ schema is FAQPage structured data (JSON-LD) that labels question-answer pairs on your page so machines can parse them unambiguously. Combined with a well-written FAQ section — concise, self-contained answers under real question headings — it creates a dense cluster of quotable question-answer units. Content with schema markup has a 2.5x higher chance of appearing in AI answers, and FAQs are the most extraction-friendly format you can add.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Content Structure</category>
      <pubDate>Thu, 09 Jul 2026 18:51:00 GMT</pubDate>
    </item>
    <item>
      <title>Question-Based Headings: How to Match the Way People Ask AI</title>
      <link>https://kollavo.com/blog/question-based-headings-for-ai-search</link>
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      <description>Question-based headings phrase your H2s and H3s as the exact questions users ask AI — &quot;How much does GEO cost?&quot; instead of &quot;Pricing.&quot; Because AI retrieval matches the meaning of a query to the meaning of your content, headings that mirror real questions retrieve more reliably and get cited more often. They also make each section a self-contained, extractable answer unit.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Content Structure</category>
      <pubDate>Thu, 09 Jul 2026 18:50:24 GMT</pubDate>
    </item>
    <item>
      <title>Answer Capsules: How to Write the Blocks LLMs Quote Verbatim</title>
      <link>https://kollavo.com/blog/answer-capsules-how-to-write-blocks-llms-quote</link>
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      <description>An answer capsule is a 2–4 sentence, 40–60 word block placed at the top of a page or section that states the complete answer to the target question in plain, self-contained language. It is the most extractable unit of content for LLMs — because it needs no surrounding context, models can lift it directly into an AI answer and cite you. Adding capsules is the single fastest way to raise citation rate.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Content Structure</category>
      <pubDate>Thu, 09 Jul 2026 18:49:47 GMT</pubDate>
    </item>
    <item>
      <title>How to Structure Content So LLMs Quote It: The Complete Guide</title>
      <link>https://kollavo.com/blog/how-to-structure-content-so-llms-quote-it</link>
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      <description>To get quoted by LLMs, structure content for extraction: lead every page and section with a 2–4 sentence answer capsule, phrase headings as the questions users actually ask, keep paragraphs short and self-contained, use lists and tables for scannable facts, and add a schema-backed FAQ section. Extractable structure — not word count — is the single biggest lever on whether ChatGPT, Perplexity, Claude, and Gemini cite you.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Content Structure</category>
      <pubDate>Thu, 09 Jul 2026 18:49:13 GMT</pubDate>
    </item>
    <item>
      <title>AI Referral Traffic: Track Visitors from ChatGPT, Perplexity &amp; Gemini</title>
      <link>https://kollavo.com/blog/ai-referral-traffic-tracking</link>
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      <description>AI referral traffic is the visits AI assistants send when users click citations. Learn how to find it in analytics, measure quality, and prove business impact.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Measurement &amp; Tools</category>
      <pubDate>Wed, 08 Jul 2026 09:00:00 GMT</pubDate>
    </item>
    <item>
      <title>Share of Voice in AI Search: Measuring Your Brand vs Competitors</title>
      <link>https://kollavo.com/blog/share-of-voice-ai-search</link>
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      <description>Share of voice is your share of all brand mentions in AI answers. Learn the formula, how to measure it across ChatGPT, Perplexity and Gemini, and how to act on the gaps.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Measurement &amp; Tools</category>
      <pubDate>Tue, 07 Jul 2026 09:00:00 GMT</pubDate>
    </item>
    <item>
      <title>LLM Citation Rate: How to Track How Often AI Cites You</title>
      <link>https://kollavo.com/blog/llm-citation-rate-how-to-track</link>
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      <description>LLM citation rate is the share of prompts where AI mentions or cites your brand. Learn the formula, how to sample it reliably, and the mistakes that corrupt the number.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Measurement &amp; Tools</category>
      <pubDate>Mon, 06 Jul 2026 09:00:00 GMT</pubDate>
    </item>
    <item>
      <title>How to Measure AI Visibility: The Complete Metrics Guide</title>
      <link>https://kollavo.com/blog/how-to-measure-ai-visibility-metrics-guide</link>
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      <description>AI visibility is measured with four metrics: citation rate, share of voice, sentiment/positioning, and AI referral traffic. Here&apos;s how to track each and build a system.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>Measurement &amp; Tools</category>
      <pubDate>Sun, 05 Jul 2026 09:00:00 GMT</pubDate>
    </item>
    <item>
      <title>GEO for Beginners: Your 30-Day Starter Checklist</title>
      <link>https://kollavo.com/blog/geo-for-beginners-your-30-day-starter-checklist</link>
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      <description>To start getting cited by LLMs in 30 days, complete these steps: allow AI crawlers in robots.txt (Day 1), add an llms.txt file (Day 2), implement Article and FAQPage schema (Days 3–5), rewrite your top 10 pages to front-load answers (Days 6–15), run your first LVS baseline test (Day 16), publish one original data post (Days 17–25), and earn three high-DA brand mentions (Days 26–30). Most brands see first citations within 4–8 weeks of completing these steps.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 12:04:06 GMT</pubDate>
    </item>
    <item>
      <title>The 5 Pillars of GEO: A Framework for Getting Cited by LLMs</title>
      <link>https://kollavo.com/blog/the-5-pillars-of-geo-a-framework-for-getting-cited-by-llms</link>
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      <description>The 5 Pillars of GEO are: (1) Content Structure — formatting content for AI extraction; (2) Technical Setup — making your site machine-readable by AI crawlers; (3) Authority Signals — building domain and author credibility that LLMs verify; (4) Entity Recognition — establishing your brand as a known, coherent entity in AI knowledge systems; and (5) Measurement — tracking citation frequency and iterating. Brands that execute all five simultaneously achieve citation authority 3–4x faster than those focusing on a single pillar.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 12:03:06 GMT</pubDate>
    </item>
    <item>
      <title>How AI Search Works: From Crawl to Citation</title>
      <link>https://kollavo.com/blog/how-ai-search-works-from-crawl-to-citation</link>
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      <description>AI search systems work in three stages. First, AI crawlers index web content (crawl). Second, when a query arrives, the system retrieves the most relevant indexed content using semantic search (retrieve). Third, the language model reads the retrieved content and writes a synthesized response, choosing which sources to cite (generate). Understanding each stage reveals exactly where to intervene to become a cited source.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 12:02:06 GMT</pubDate>
    </item>
    <item>
      <title>The LLM Visibility Score: The Metric Replacing Search Rankings</title>
      <link>https://kollavo.com/blog/the-llm-visibility-score-the-metric-replacing-search-rankings</link>
      <guid isPermaLink="true">https://kollavo.com/blog/the-llm-visibility-score-the-metric-replacing-search-rankings</guid>
      <description>The LLM Visibility Score (LVS) is a brand&apos;s citation frequency across a defined set of AI-generated responses, expressed as a percentage. It answers: &quot;Of all the times a user asks an AI about my category, how often does my brand appear in the response?&quot; LVS is replacing traditional keyword ranking as the primary measure of AI search performance in 2026.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 12:01:06 GMT</pubDate>
    </item>
    <item>
      <title>Why LLMs Cite Some Sources and Ignore Others</title>
      <link>https://kollavo.com/blog/why-llms-cite-some-sources-and-ignore-others</link>
      <guid isPermaLink="true">https://kollavo.com/blog/why-llms-cite-some-sources-and-ignore-others</guid>
      <description>LLMs cite sources that are extractable (the answer is clearly stated and self-contained), verifiable (the content includes data, citations, or specific claims), authoritative (the domain is widely recognized), and technically accessible (AI crawlers are permitted and schema markup is present). Content that buries conclusions, lacks specifics, or blocks AI bots is systematically ignored — regardless of how good the underlying information is.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 12:00:06 GMT</pubDate>
    </item>
    <item>
      <title>GEO vs SEO vs AEO: Key Differences Explained</title>
      <link>https://kollavo.com/blog/geo-vs-seo-vs-aeo-key-differences-explained</link>
      <guid isPermaLink="true">https://kollavo.com/blog/geo-vs-seo-vs-aeo-key-differences-explained</guid>
      <description>GEO (Generative Engine Optimization), SEO (Search Engine Optimization), and AEO (Answer Engine Optimization) are three distinct but related disciplines. SEO targets ranked link lists in traditional search engines. AEO targets featured snippets and direct answer boxes. GEO targets citations inside AI-generated responses from LLMs like ChatGPT, Claude, and Perplexity. In 2026, all three matter — but GEO is the fastest-growing priority.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 11:59:06 GMT</pubDate>
    </item>
    <item>
      <title>What Is GEO? The Definitive Guide to Generative Engine Optimization</title>
      <link>https://kollavo.com/blog/what-is-geo-generative-engine-optimization</link>
      <guid isPermaLink="true">https://kollavo.com/blog/what-is-geo-generative-engine-optimization</guid>
      <description>Generative Engine Optimization (GEO) is the practice of structuring your content, authority signals, and technical setup so AI platforms — ChatGPT, Claude, Perplexity, and Gemini — cite your brand as a source.</description>
      <dc:creator>Kollavo</dc:creator>
      <category>GEO Fundamentals</category>
      <pubDate>Sun, 28 Jun 2026 08:00:00 GMT</pubDate>
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