{"id":9404,"date":"2025-07-29T13:14:21","date_gmt":"2025-07-29T13:14:21","guid":{"rendered":"https:\/\/wellows.com\/?p=9404"},"modified":"2025-09-11T11:15:15","modified_gmt":"2025-09-11T11:15:15","slug":"create-for-serp-and-llms","status":"publish","type":"post","link":"https:\/\/staging.wellows.com\/blog\/create-for-serp-and-llms\/","title":{"rendered":"How To Create Content Based on SERP and LLM trends (Agencies, Consultants, Startups)"},"content":{"rendered":"<p>Want to <strong>create content based on SERP and LLM trends<\/strong> that rank on Google and appear in answers from ChatGPT, Claude, or Gemini? As search evolves across both engines and AI models, the rules of visibility are shifting fast.<\/p>\n<p>Many still view this only through <strong>search engine optimization (SEO)<\/strong>, but visibility now means showing up in both Google\u2019s <strong>search engine results pages (SERP)<\/strong> and large language models (LLMs).<\/p>\n<p>A frequent question is: <em>\u201cWhat is SERP in digital marketing?\u201d<\/em> It\u2019s the page of results Google shows\u2014snippets, FAQs, videos, and now AI summaries. Another is: <em>\u201cWhat are the characteristics of LLM?\u201d<\/em> These models rely on semantic understanding and contextual reasoning, not just ranking signals.<\/p>\n<p>This raises: <em>\u201cHow is LLM used in technology?\u201d<\/em> Beyond chat, LLMs are shaping search, discovery, and decision-making by selecting which brands appear in AI-powered answers.<\/p>\n<p>To stay visible, brands must align with both SERP optimization and LLM visibility principles. Emerging AI assistants like <strong>KIVA<\/strong> show how structure, trust, and formatting decide what content gets surfaced.<\/p>\n<p>For lean teams, the <a href=\"https:\/\/staging.wellows.com\/solutions\/startups\/\" target=\"_blank\" rel=\"noopener\">AI SEO Agent for Startups<\/a> solution offers a direct path to scale SEO with SERP + LLM optimization built-in.<\/p>\n<div class=\"did-you-know-box\"><br \/>\nSemrush research shows <a href=\"https:\/\/www.semrush.com\/blog\/semrush-ai-overviews-study\/\">13%<\/a> of U.S. searches display AI summaries, 88% targeting informational queries. Structured content is no longer optional\u2014it\u2019s essential.<br \/>\n<\/div>\n<hr \/>\n<h2>How SERP Visibility Drives AI-Influenced Search Performance?<\/h2>\n<p>SERP feature optimization has evolved beyond simple blue links as search engines now display featured snippets, AI Overviews, and People Also Ask boxes, blending <a href=\"https:\/\/staging.wellows.com\/blog\/what-are-serps\/\" target=\"_blank\" rel=\"noopener\">traditional search results<\/a> with generative interfaces.<\/p>\n<p>This means visibility requires more than ranking\u2014it\u2019s about aligning your strategy to <strong>develop content tailored for Google\u2019s SERP<\/strong> and building formats that match query intent.<\/p>\n<h3>What does &#8216;create for SERP&#8217; mean?<\/h3>\n<p>To <strong>create for SERP<\/strong> is to design content that is both search-friendly and AI-aware. It involves steps like:<\/p>\n<ul>\n<li>Adding meta elements such as <strong>meta tags for SERP optimization<\/strong>.<\/li>\n<li>Writing keyword-aligned articles that <strong>build keyword-focused content for search engines<\/strong>.<\/li>\n<li>Implementing schema and markup to <strong>produce structured data for SERP enhancements<\/strong>.<\/li>\n<\/ul>\n<h3>Creating for SERP and Large Language Models<\/h3>\n<p>True optimization goes beyond Google. Marketers now face the challenge of creating for SERP and large language models simultaneously\u2014which is <a href=\"https:\/\/staging.wellows.com\/blog\/why-marketers-replace-spreadsheets-ai-agents\/test\/\" target=\"_blank\" rel=\"noopener\">why many are replacing spreadsheets and SOPs with AI agents<\/a> that integrate SERP and AI-driven visibility workflows. That means designing for<strong> search engine results pages and LLMs<\/strong>, or even <strong>developing content for SERP and LLMs<\/strong>, so your assets appear in both blue links and AI-generated responses.<\/p>\n<h3>SERP Visibility Goes Beyond Ranking<\/h3>\n<p>Ranking high is only effective if your format matches searcher expectations. Pages that show up in featured snippets, PAA boxes, or AI summaries often follow specific patterns:<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #A4D9F9 !important; border-color: #16a'><\/p>\n<ul>\n<li><strong>How-to guides<\/strong> include step-by-step tutorials, process documentation, and instructional content. They dominate task-based queries and frequently appear in featured snippets.<\/li>\n<li><strong>Listicles and comparison posts<\/strong> cover product roundups, versus articles, and evaluation matrices. They rank well for commercial investigation intent and trigger rich snippets.<\/li>\n<li><strong>User-generated content (UGC) and forums<\/strong> appear for trust-based or peer-seeking searches.<\/li>\n<\/ul>\n<p><\/div>\n<p>Focusing only on keywords while ignoring these format signals often creates broader <a class=\"decorated-link\" href=\"https:\/\/staging.wellows.com\/blog\/visibility-issues\/\" target=\"_new\" rel=\"noopener\" data-start=\"1082\" data-end=\"1149\">SEO visibility issues<\/a>, where content fails to perform across both Google SERPs and AI-driven summaries.<\/p>\n<h3>Analyze SERPs to Extract Content Opportunities<\/h3>\n<p>Manual audits don\u2019t scale, but automated SERP tools (SEOTesting, Semrush\u2019s SERP Features, Ahrefs\u2019 SERP Overview, BrightEdge DataCube, SE Ranking\u2019s SERP Checker) plus optimization platforms (Clearscope, MarketMuse, SurferSEO, ContentKing) can uncover gaps.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #A4D9F9 !important; border-color: #16a'>\n<p>Look for:<\/p>\n<ol>\n<li>Repeated format types across top-ranking pages<\/li>\n<li>Domain authority consistency or gaps<\/li>\n<li>Presence of multimedia, FAQs, or structured markup <\/div><\/li>\n<\/ol>\n<div class='emphasize-box tips '><div class='emphasize-box-inr'><\/p>\n<p>For example:<\/p>\n<ul>\n<li>If \u201cAI writing tools\u201d returns multiple product roundups, your brief should mirror that style.<\/li>\n<li>If UGC dominates for \u201cbest SEO communities,\u201d creating a forum-based roundup or social quote curation can improve alignment.<\/li>\n<\/ul>\n<p><\/div><\/div>\n<p>To scale your workflow after identifying these patterns, explore the blog <a href=\"https:\/\/staging.wellows.com\/blog\/ai-writing-assistants-increase-output\/\" target=\"_blank\" rel=\"noopener\">5 Tips to Triple Content Output Using AI Writing Assistants<\/a>, which explains how AI-driven workflows can help you act on SERP insights faster and generate search-aligned drafts at scale.<\/p>\n<h3>Turn SERP Visibility into Content Briefs<\/h3>\n<p>Every SERP pattern should inform your content brief. Before writing:<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #A4D9F9 !important; border-color: #16a'>\n<ul>\n<li>Choose a format (guide, list, video embed, review)<\/li>\n<li>Match the depth and tone of existing winners<\/li>\n<li>Use headers and subheaders to reflect popular content structure <\/div><\/li>\n<\/ul>\n<p>For a practical walkthrough on this process, see <a href=\"https:\/\/staging.wellows.com\/blog\/create-ai-content-brief\/\" target=\"_blank\" rel=\"noopener\">how to create an AI content brief<\/a> using KIVA showing step-by-step how SERP insights are transformed into structured, AI-aware outlines that perform across both search engines and generative platforms.<\/p>\n<div class=\"did-you-know-box\"><\/p>\n<p>According to Semrush\u2019s R&amp;D study (March 2025), <a href=\"https:\/\/www.semrush.com\/blog\/semrush-ai-overviews-study\/\" target=\"_blank\" rel=\"noopener\">88.1%<\/a> of search queries that triggered <strong>AI-generated answers<\/strong> also displayed structured results such as featured snippets or \u201cPeople Also Ask\u201d panels on page one.<\/p>\n<p><\/div>\n<hr \/>\n<h2>Why Large Language Models Extract Content Through Semantic Analysis?<\/h2>\n<p>AI content selection patterns reveal unique behaviors. Large language models like ChatGPT-4, Claude-3, and Gemini Pro don&#8217;t rank pages like traditional search algorithms. Instead, they use transformer architectures and attention mechanisms. These models employ semantic chunking, passage retrieval, and contextual analysis to identify and remix content blocks.<\/p>\n<p>These systems prioritize semantic relevance, clear structure, and trusted citations. Unlike Google, LLMs don\u2019t rely on traditional ranking signals like backlinks or keyword density. Instead, they extract information based on clarity, contextual fit, and answer quality.<\/p>\n<p>To better understand how these AI-driven citations compare to traditional SEO link-building, take a look at <a href=\"https:\/\/staging.wellows.com\/blog\/llm-citations-vs-backlinks\/\" target=\"_blank\" rel=\"noopener\">How Are LLM Citations Different from Backlinks?<\/a> where we break down the shifting role of trust and authority in generative search.<\/p>\n<div class=\"readability-container\"><h3><span class=\"readability-header\">LLMs Focus on Passage-Level Accuracy and Context<\/span><\/h3><ul class=\"readability-list\"><\/p>\n<ul>\n<li>LLMs retrieve content from specific passages that directly answer user prompts.<\/li>\n<li>They value well-defined, self-contained content blocks over long-form narrative.<\/li>\n<li>Semantic chunking ensures retrievability by aligning with user intent.\nFor example, well-structured Q&amp;A blocks often get cited in generative responses.<\/li>\n<\/ul>\n<p><\/ul><\/div>\n<div class=\"readability-container\"><h3><span class=\"readability-header\">Citation Bias and Trust Signals in LLM Outputs<\/span><\/h3><ul class=\"readability-list\"><\/p>\n<p>LLMs tend to cite high-trust sources like Wikipedia, Reddit threads, and reputable publishers.<\/p>\n<p>An internal <a href=\"https:\/\/staging.wellows.com\/insights\/chatgpt-citations-report\/\" target=\"_blank\" rel=\"noopener\">analysis by Wellows<\/a> used controlled research methodology. The study analyzed <strong>7,785 LLM-generated queries<\/strong> across <strong>12 industry verticals<\/strong>. These included healthcare, finance, e-commerce, SaaS, manufacturing, and legal services.<\/p>\n<p>Results showed <strong>48% of citations<\/strong> came from high-authority domains. These domains included news publishers, educational institutions, and government databases with domain authority scores above <strong>70<\/strong>.<\/p>\n<p>For commercial searches, the same study of Wellows revealed that <strong>66% of citations<\/strong> referenced product specifications or expert reviews. This shows that clear, detailed, and informative content is far more likely to be cited\u2014especially when it helps answer specific, product-driven questions.<\/p>\n<p>Semrush has also reported that nearly <a href=\"https:\/\/backlinko.com\/llm-seeding\">90%<\/a> <strong>of ChatGPT citations<\/strong> come from content beyond the top 20 Google results. This suggests that structure and clarity may outweigh traditional rankings when it comes to AI citation.<\/p>\n<p>Each LLM shows its own preference. For example, <a href=\"https:\/\/taktical.co\/blog\/use-these-4-ai-citation-strategies-to-increase-your-brand-visibility-in-llm-platform\/\">47%<\/a> <strong>of Perplexity\u2019s citations<\/strong> come from Reddit, highlighting the value of peer-generated insights.<\/p>\n<p><\/ul><\/div>\n<p><span data-sheets-root=\"1\">To explore this further, check out Why Generative Engines Love Reddit? for a breakdown of why forums dominate AI citation logic and how you can adapt your strategy to benefit from similar formats.<\/span><\/p>\n<div class=\"readability-container\"><h3><span class=\"readability-header\">Structuring Content for LLM Visibility<\/span><\/h3><ul class=\"readability-list\"><\/p>\n<p>To target LLM visibility effectively:<\/p>\n<ol>\n<li>Break content into small, labeled chunks (e.g., \u201cStep 1: Research SERP Trends\u201d).<\/li>\n<li>Embed clear signal cues like FAQs or TL;DR summaries.<\/li>\n<li>Incorporate cited facts, data, and credible sources that align with each model\u2019s citation behavior.<\/li>\n<\/ol>\n<p><\/ul><\/div>\n<p>This modular approach improves extractability, increasing the chance that an AI model will pick and cite your content.<\/p>\n<p>To apply this approach consistently, explore our guide on <a href=\"https:\/\/staging.wellows.com\/blog\/chunk-optimization-for-ai-search\/\" target=\"_blank\" rel=\"noopener\">Chunk optimization for AI SERPs<\/a>, where we break down how to label, format, and structure content blocks for maximum visibility across both search and AI interfaces.<\/p>\n<hr \/>\n<h2>How Content Alignment Maximizes SERP and LLM Visibility?<\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-9528 aligncenter\" src=\"https:\/\/staging.wellows.com\/wp-content\/uploads\/2025\/07\/Sahar-FI-49.webp\" alt=\"Content-Creation-Workflow-for-SERP-and-LLM-Alignment\" width=\"701\" height=\"394\" srcset=\"https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-49.webp 1280w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-49-300x169.webp 300w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-49-1024x576.webp 1024w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-49-768x432.webp 768w\" sizes=\"(max-width: 701px) 100vw, 701px\" \/><\/p>\n<p>Multi-platform content visibility requires semantic long form content creation strategies that align with both SERP optimization and LLM citation best practices through a methodical approach. Each article must match how people search and how platforms select, display, and summarize content.<\/p>\n<p>A step-by-step workflow ensures that each part of the article meets the expectations of Google Search and LLM tools like ChatGPT or Gemini.<\/p>\n<div class=\"link-list\"><\/p>\n<a class=\"link-item\" href=\"#1\"><span class=\"link-icon\">1<\/span>Perform Topic and Query Research<\/a>\n<a class=\"link-item\" href=\"#2\"><span class=\"link-icon\">2<\/span>Build a Clear Content Outline<\/a>\n<a class=\"link-item\" href=\"#3\"><span class=\"link-icon\">3<\/span>Write With Structure and Simplicity<\/a>\n<a class=\"link-item\" href=\"#4\"><span class=\"link-icon\">4<\/span>Include FAQs and Supporting Information<\/a>\n<p><a class=\"link-item\" href=\"#5\"><span class=\"link-icon\">5<\/span>Format the Article for Indexing and Reuse<\/a><\/div>\n<h3 id=\"1\">Step 1 \u2013 Perform Topic and Query Research<\/h3>\n<p>Effective research begins by identifying what the audience is already searching for. Query-based research helps structure content around real demand rather than assumptions.<\/p>\n<p>AI keyword research platforms reveal important patterns. Tools like <strong>KIVA, Semrush, Ahrefs,<\/strong> and <strong>AlsoAsked<\/strong> identify phrasing patterns and snippet formats. Content optimization tools like Clearscope, MarketMuse, and SurferSEO analyze ranking content structures. Analytics platforms including Google Search Console and Adobe Analytics provide performance data.<\/p>\n<div class=\"custom-callout\"><h4 id=\"1\"><strong>1. To guide research:<\/strong><\/h4><ul>\n<li>Use the \u201cQuestions\u201d filter in keyword research tools to extract real search queries<\/li>\n<li>Prioritize keywords that trigger featured snippets or FAQ blocks in Google Search<\/li>\n<li>Study the structure of top-ranking articles to identify formatting patterns<\/div><\/li>\n<\/ul>\n<p>Matching keyword intent and question phrasing improves discoverability across both SERPs and LLM outputs, especially when guided by <a href=\"https:\/\/staging.wellows.com\/blog\/how-ai-agents-use-serp-visibility\/\" target=\"_blank\" rel=\"noopener\">AI SEO agents using SERP visibility<\/a>, which surface query patterns and content structures that rank in search and get cited in AI responses.<\/p>\n<h3 id=\"2\">Step 2 \u2013 Build a Clear Content Outline<\/h3>\n<p>A clear content outline helps structure the article into answer-first sections. Google Search and LLM tools both favor writing that solves a problem upfront and supports the answer with details.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #B3D8FF !important; border-color: #16a'><\/p>\n<p><strong>To create a strong outline:<\/strong><\/p>\n<ul>\n<li>Choose one main idea or question per article<\/li>\n<li>Break the topic into logical sub-questions that become H2 or H3 headings<\/li>\n<li>Arrange sections to mirror the typical order of user discovery: <strong>definition \u2192 how-to \u2192 tips \u2192 FAQs\u00a0<\/strong><\/li>\n<\/ul>\n<p>A structured outline often begins with a definition of AI content, then moves into use cases, workflow integration, tool selection, and measurable outcomes, as shown in <a href=\"https:\/\/staging.wellows.com\/blog\/ai-content-marketing-workflow\/\" target=\"_blank\" rel=\"noopener\">How Marketers Use AI Content in Their Workflow<\/a>.<br \/>\n<\/div>\n<p>This structure helps guide both readers and search engines through the topic in a logical, intent-aligned flow.<\/p>\n<h3 id=\"3\">Step 3 \u2013 Write With Structure and Simplicity<\/h3>\n<p>Google Search prioritizes content that is easy to scan and understand. LLM tools extract content from pages that lead with the answer and minimize ambiguity.<\/p>\n<p>Writers should use formatting that signals clarity.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #B3D8FF !important; border-color: #16a'>\n<p><strong>To improve structure:<\/strong><\/p>\n<ul>\n<li>Begin each section with a one-sentence answer, followed by supporting explanation<\/li>\n<li>Keep paragraph length between 2\u20134 lines<\/li>\n<li>Use numbered lists or bullets to break down instructions\u00a0 <\/div><\/li>\n<\/ul>\n<p>Writing should rely on the active voice, neutral tone, and sentence lengths between 15\u201320 words for consistent readability. Overuse of transitional phrases or introductory filler should be avoided.<\/p>\n<h3 id=\"4\">Step 4 \u2013 Include FAQs and Supporting Information<\/h3>\n<p>Frequently asked questions improve SERP presence and help language models understand the full scope of the topic.<\/p>\n<p>These sections often appear as AI-generated answers, Google\u2019s \u201cPeople Also Ask\u201d boxes, or FAQ schema-enhanced listings.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #B3D8FF !important; border-color: #16a'><\/p>\n<p><strong>To build an effective FAQ section:<\/strong><\/p>\n<ul>\n<li>Select 3\u20135 questions based on actual user queries from keyword tools<\/li>\n<li>Label the section clearly with headings like \u201cFAQs,\u201d \u201cCommon Questions,\u201d or \u201cRelated Topics\u201d<\/li>\n<li>Answer each question in 40\u201360 words using complete sentences<\/li>\n<\/ul>\n<p><\/div>\n<p>To create high-impact FAQ sections, it\u2019s important to align with real user intent. One effective approach is using <a href=\"https:\/\/staging.wellows.com\/blog\/how-to-use-people-also-ask-data\/\" target=\"_blank\" rel=\"noopener\">People Also Ask data<\/a>, which provides actual search queries you can turn into precise, snippet-ready answers.<\/p>\n<p>According to <a href=\"https:\/\/developers.google.com\/search\/docs\/appearance\/structured-data\/faqpage\">Google\u2019s Search Central<\/a> (Webmaster Trends Team, 2023), properly marked-up FAQ sections using <strong>FAQPage schema<\/strong> may be displayed as rich results in search listings or Google Assistant, helping users find answers directly in search. [\/did_you_know]<\/p>\n<h3 id=\"5\">Step 5 \u2013 Format the Article for Indexing and Reuse<\/h3>\n<p>Content formatting affects how Google Search ranks the article and how LLM tools extract and display information.<\/p>\n<p>Articles must be built for scanning, understanding, and retrieval at both page-level and section-level. Using clear headers, structured data, and modular sections makes content more reusable and visible.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #B3D8FF !important; border-color: #16a'>\n<p><strong>To improve formatting:<\/strong><\/p>\n<ul>\n<li>Use consistent heading levels (H1 for the title, H2 for questions, H3 for supporting points)<\/li>\n<li>Keep paragraphs between 2\u20134 lines<\/li>\n<li>Insert internal links that match related topics using clear anchor phrases (e.g. \u201cSEO topic clusters\u201d instead of \u201cclick here\u201d)<\/li>\n<li>Apply <strong>FAQPage<\/strong> schema if the article includes a dedicated Q&amp;A section<\/li>\n<li>Repeat the main topic keywords naturally across sections without keyword stuffing <\/div><\/li>\n<\/ul>\n<p>Formatting should make every section function as a self-contained answer. When the reader (or\u00a0 a machine) lands in the middle of the article, the section should still make sense without scrolling.<\/p>\n<hr \/>\n<h2>How KIVA Maps Visibility Across Search Engines and LLMs<\/h2>\n<p>Modern content strategy requires more than keyword targeting. It depends on understanding how both search engines and large language models (LLMs) interpret, structure, and present information.<\/p>\n<p><a href=\"https:\/\/staging.wellows.com\/kiva\/\" target=\"_blank\" rel=\"noopener\">KIVA<\/a> by Wellows introduces a unified visibility framework designed to solve this challenge. It enables teams to move beyond isolated SEO tactics and embrace a connected, AI-first approach.<\/p>\n<p>One of the core capabilities is the <a href=\"https:\/\/staging.wellows.com\/kiva\/features\/serp-visibility\/\" target=\"_blank\" rel=\"noopener\">KIVA SERP Visibility feature<\/a>. It shows which content formats dominate Google results\u2014such as how-to guides, UGC, product roundups, or videos, so you can structure briefs aligned with real SERP behaviors.<\/p>\n<p>The other is the <a href=\"https:\/\/staging.wellows.com\/kiva\/features\/llms-visibility\/\" target=\"_blank\" rel=\"noopener\">KIVA LLM Visibility feature<\/a>. It analyzes how models like ChatGPT, Claude, and Gemini interpret phrasing, structure, and sources\u2014helping your team adapt content for AI citation and summary patterns.<\/p>\n<p>For teams wanting to scale these capabilities into broader automation, the guide on <a href=\"https:\/\/staging.wellows.com\/blog\/agentic-ai-marketing\/\" target=\"_blank\" rel=\"noopener\">Marketing With Agentic AI<\/a> shows how KIVA connects SERP and LLM insights into an autonomous execution framework.<\/p>\n<h3><strong>Step 1: Analyze SERP Behavior with KIVA&#8217;s SERP Visibility<\/strong><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-9526 aligncenter\" src=\"https:\/\/staging.wellows.com\/wp-content\/uploads\/2025\/07\/Sahar-FI-48.webp\" alt=\"KIVA-SERP-Visibility-feature\" width=\"701\" height=\"394\" srcset=\"https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-48.webp 1280w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-48-300x169.webp 300w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-48-1024x576.webp 1024w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-48-768x432.webp 768w\" sizes=\"(max-width: 701px) 100vw, 701px\" \/><\/p>\n<p>KIVA content optimization tool provides SERP visibility enhancement that goes beyond traditional keyword rankings to analyze search result optimization opportunities.\u00a0 It delivers a live breakdown of how your topic appears in search, including <strong>dominant content formats<\/strong>, <strong>layout structures<\/strong>, and <strong>competitor presence<\/strong>.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #D1ECF1 !important; border-color: #16a'>\n<p>With these insights, marketers can:<\/p>\n<ul>\n<li>Identify which content types perform best, such as how-to articles, UGC, or product reviews.<\/li>\n<li>Detect visual elements like featured snippets, video carousels, and PAA boxes<\/li>\n<li>Compare top-performing content against their own coverage<\/li>\n<li>Use interactive \u201cView\u201d functions to extract SERP structure instantly for content briefing <\/div><\/li>\n<\/ul>\n<p>This enables content teams to create briefs that reflect real search behavior. As a result, the content matches what Google currently ranks and what users expect to find.<\/p>\n<h3><strong>Step 2: Understand LLM Citation Patterns with KIVA&#8217;s LLM Visibility<\/strong><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-9527 aligncenter\" src=\"https:\/\/staging.wellows.com\/wp-content\/uploads\/2025\/07\/Sahar-FI-47-1.webp\" alt=\"LLM-Citation-Patterns-with-KIVA-LLM-Visibility\" width=\"701\" height=\"394\" srcset=\"https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-47-1.webp 1280w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-47-1-300x169.webp 300w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-47-1-1024x576.webp 1024w, https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-47-1-768x432.webp 768w\" sizes=\"(max-width: 701px) 100vw, 701px\" \/><\/p>\n<p>While SERP data shows what people click, LLMs like ChatGPT, Claude, and Gemini reveal what content is cited or summarized. KIVA\u2019s <strong>LLM Visibility<\/strong> feature analyzes how leading AI models interpret your topic, revealing phrasing logic, source preferences, and output structure.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #D1ECF1 !important; border-color: #16a'>\n<p>With LLM Visibility, you can:<\/p>\n<ul>\n<li>Retrieve model-generated queries across OpenAI, Claude, Gemini, and DeepSeek<\/li>\n<li>Discover which domains get cited most often, and why<\/li>\n<li>Uncover common content formats, such as listicles or step-based answers<\/li>\n<li>Measure brand frequency across multiple models<\/li>\n<li>Extract structural patterns to shape future content briefs <\/div><\/li>\n<\/ul>\n<p>It also provides model-specific visibility snapshots to show where you\u2019re winning, where you\u2019re missing out, and what opportunities exist for content improvement.<\/p>\n<div class=\"ai-trap\"><strong class=\"ai-trap-title\">How KIVA Unifies SERP and LLM Visibility<\/strong><\/p>\n<p>When used together, KIVA\u2019s dual visibility features enable teams to:<\/p>\n<ul>\n<li>\u2714 <strong>Identify<\/strong> what ranks in search and what gets cited in AI answers<\/li>\n<li>\u2714 <strong>Structure<\/strong> content using format and phrasing patterns based on real query data<\/li>\n<li>\u2714 <strong>Benchmark<\/strong> brand visibility across multiple models and search engines<\/li>\n<li>\u2714 <strong>Build<\/strong> content briefs faster with greater clarity and less trial and error<\/li>\n<\/ul>\n<p>By combining SERP rankings with LLM citation behavior, KIVA helps you produce content that meets the expectations of both search algorithms and generative models. The result is content that is easier to find, extract, and trust.<\/p>\n<p><\/div>\n<hr \/>\n<h2>Why LLM Tools Prioritize Structured Content Selection?<\/h2>\n<p>LLM tools such as ChatGPT, Perplexity, and Google\u2019s <a href=\"https:\/\/staging.wellows.com\/blog\/ai-overviews-optimization\/\" target=\"_blank\" rel=\"noopener\">AI Overviews<\/a> generate summaries by scanning public content and extracting sections that are clear, direct, and structurally consistent.<\/p>\n<p>Articles that follow logical heading hierarchies, answer user questions upfront, and use concise language are more likely to be quoted, summarized, or linked.<\/p>\n<h3>LLM Tools Prefer Question-Based Sections and Predictable Structure<\/h3>\n<p>Language models are built to answer natural language questions. Articles that use subheadings in the form of complete queries, such as \u201cHow do search engines identify structured content?\u201d These are easier for LLMs to understand and repackage.<\/p>\n<p>LLM tools scan headers, then check whether the paragraph that follows provides a clear and relevant answer.<\/p>\n<p>To increase the chance of selection:<\/p>\n<ul>\n<li>Phrase H2s and H3s as real questions<\/li>\n<li>Place the answer in the first 2\u20133 lines after the heading<\/li>\n<li>Limit technical terms unless followed by short definitions<\/li>\n<\/ul>\n<div class='emphasize-box tips '><div class='emphasize-box-inr'><\/p>\n<p>For example, an H2 like <strong>\u201cWhat Is a Semantic Keyword Cluster?\u201d<\/strong> followed by \u201cA semantic keyword cluster is a group of related search terms\u2026\u201d signals answer-first clarity. <\/div><\/div>\n<p>In the case of the <a href=\"https:\/\/staging.wellows.com\/kiva\/features\/chatgpt-visibility\/\" target=\"_blank\" rel=\"noopener\">KIVA ChatGPT Visibility feature<\/a>, these patterns are mapped directly into your content strategy\u2014showing how structured questions, bullet points, and concise answers improve your chances of inclusion in AI-generated summaries.<\/p>\n<h3>Clarity, Simplicity, and Sentence Structure Affect Extraction Quality<\/h3>\n<p>Content selected by LLM tools often shares specific patterns:<\/p>\n<ul>\n<li>Sentences average 15\u201320 words<\/li>\n<li>Factual tone and active voice dominate the section<\/li>\n<li>Entities are clearly named and described (e.g., \u201cSemrush is a keyword analysis platform\u2026\u201d)<\/li>\n<\/ul>\n<p>Excessive use of filler phrases like \u201cactually,\u201d \u201cessentially,\u201d or vague openers such as \u201cthis means that\u2026\u201d weakens the section\u2019s extraction potential. Clarity is measured not only by grammar but also by how quickly the core answer is presented.<\/p>\n<p>The <a href=\"https:\/\/staging.wellows.com\/kiva\/features\/claude-visibility\/\" target=\"_blank\" rel=\"noopener\">KIVA Claude Visibility feature<\/a> emphasizes this, showing how Claude prioritizes clean editorial tone, accurate attribution, and well-organized passage blocks with minimal promotional language\u2014especially for professional or knowledge-driven topics.<\/p>\n<div class=\"did-you-know-box\"><\/p>\n<p>According to SEOClarity\u2019s 2025 Research (DR\u202f85), <a href=\"https:\/\/www.seoclarity.net\/research\/ai-overviews-impact\">99.5%<\/a> <strong>of AI-Overview summaries<\/strong> reference content that appears among the <strong>top 10 results<\/strong> in Google Search. <\/div>\n<h3>LLM Tools Use Content Blocks, Not Whole Pages<\/h3>\n<p>Language models do not typically summarize full articles. Instead, they extract standalone sections, often focusing on the content beneath individual H2 or H3 headings, to answer specific user queries.<\/p>\n<p>This behaviour makes modular writing essential. Writers must ensure that:<\/p>\n<ul>\n<li>Each section works independently<\/li>\n<li>Sentences refer to the subject by name, not pronouns<\/li>\n<li>Internal references (e.g., \u201cthe above section\u201d) are avoided<\/li>\n<\/ul>\n<p>The <a href=\"https:\/\/staging.wellows.com\/kiva\/features\/gemini-visibility\/\" target=\"_blank\" rel=\"noopener\">KIVA Gemini Visibility feature<\/a> favors cleanly chunked content, especially when structured with metadata, headers, and schema that guide how information is interpreted and grouped by the model.<\/p>\n<p>Meanwhile, the <a href=\"https:\/\/staging.wellows.com\/kiva\/features\/deepseek-visibility\/\" target=\"_blank\" rel=\"noopener\">KIVA DeepSeek Visibility feature<\/a> shows a strong preference for forum-style language, community-sourced opinions, and context-rich responses, making it ideal for brands leveraging UGC and experience-based narratives.<\/p>\n<p>When every section contains enough context to stand alone, that section becomes eligible for <strong>direct inclusion in AI Overviews, summaries, or assistant-style tools<\/strong>.<\/p>\n<hr \/>\n<h2>How Different Business Types Require Tailored Implementation Strategies<\/h2>\n<p>While the core of SERP and LLM visibility remains universal, how you apply it varies based on team size, workflow speed, and client pressure.<\/p>\n<p>Agencies, consultants, and startups each face unique content challenges\u2014and need scalable ways to execute strategy fast without sacrificing results.<\/p>\n<h3>For Agencies \u2013 Scale AI-Optimized SEO Briefs Across Clients<\/h3>\n<p>Content visibility strategies for agencies require managing dozens of clients across industries while implementing SERP and LLM optimization techniques under tight deadlines. That means your systems must adapt quickly to shifts in SERP formats or LLM citation trends.<\/p>\n<p><strong>Agency action points:<\/strong><\/p>\n<ul>\n<li>Use content planning platforms that integrate real-time SERP snapshots and LLM query simulation.<\/li>\n<li>Standardize modular brief templates that reflect both keyword intent and model-extracted phrasing.<\/li>\n<li>Report client visibility across Google and AI channels with tools like AlsoAsked or LLM coverage tracking.<\/li>\n<\/ul>\n<h3>For Consultants \u2013 Translate Visibility into Strategy<\/h3>\n<p>Independent consultants need to prove results with fewer resources. Instead of manually checking Google and GPT responses, use a systemized visibility matrix \u2014the same AI-first approach used to <a href=\"https:\/\/staging.wellows.com\/blog\/tips-for-solo-marketers\/\" target=\"_blank\" rel=\"noopener\">scale SEO as a solo consultant<\/a>.<\/p>\n<p><strong>Consultant action points:<\/strong><\/p>\n<ol>\n<li>Analyze SERP types and AI citations per topic before pitching content.<\/li>\n<li>Align deliverables with both AI-friendly structure and human-first value.<\/li>\n<li>Use modular brief sections to plug into broader brand or editorial systems.<\/li>\n<\/ol>\n<p>This builds trust with clients who are increasingly aware of AI\u2019s role in content discovery. It also reinforces that <a href=\"https:\/\/staging.wellows.com\/blog\/without-team\/\" target=\"_blank\" rel=\"noopener\">SEO without a team<\/a> is not only possible, but highly effective when powered by the right visibility insights and strategic frameworks.<\/p>\n<h3>For Startups \u2013 Move Fast Without Guesswork<\/h3>\n<p>Startups need early visibility, but often lack bandwidth for deep SEO audits or custom AI analysis. <a href=\"https:\/\/staging.wellows.com\/blog\/how-startups-use-ai-for-seo\/\" target=\"_blank\" rel=\"noopener\">Startups use AI for SEO<\/a> to close that gap\u2014modular content helps them scale smarter, faster.<\/p>\n<p><strong>Startup action points:<\/strong><\/p>\n<ul>\n<li>Use hybrid research (SERP + LLM) to find \u201clow-content\u201d opportunities.<\/li>\n<li>Build evergreen clusters using repeatable formats (FAQs, how-tos, comparisons).<\/li>\n<li>Repurpose chunks for social, email, and support docs.<\/li>\n<\/ul>\n<p>To accelerate execution, startups can tap into frameworks like the <strong>KIVA AI SEO Agent<\/strong>, which distils AI behaviour and search data into actionable SEO structures.<\/p>\n<p>It helps content teams understand what search engines rank and what AI models cite\u2014without the need for manual audits or fragmented tooling.<\/p>\n<p>That\u2019s also why many startup teams are increasingly relying on content-specific AI agents\u2014here are <a href=\"https:\/\/staging.wellows.com\/blog\/why-use-ai-agents-for-writing\/\" target=\"_blank\" rel=\"noopener\">10 reasons writers are turning to AI<\/a> to simplify execution without sacrificing clarity or structure.\u201d<\/p>\n<hr \/>\n<h2>FAQs<\/h2>\n<div class=\"accordion accordion-shortcode w-100 id=\"faqAccordion\">\n        <\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq1\" aria-expanded=\"false\" aria-controls=\"faq1\">\n                    What are the benefits of creating for SERP?\n                <\/button>\n            <\/div>\n            <div id=\"faq1\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nThe main benefit is visibility across both search engines and AI models. When you create for search results and AI models, your content not only ranks higher in Google but also gets selected by LLMs like ChatGPT or Gemini. This dual optimization drives more clicks, citations, and user trust.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq2\" aria-expanded=\"false\" aria-controls=\"faq2\">\n                    How does SERP differ from LLM?\n                <\/button>\n            <\/div>\n            <div id=\"faq2\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nSERPs focus on ranking factors like backlinks and structured data, while LLMs extract content through semantic analysis. To cover both, brands must design for search engines and language models\u2014balancing keyword signals for Google with structured, answer-first writing for AI processors.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq3\" aria-expanded=\"false\" aria-controls=\"faq3\">\n                    What tools help in creating for SERP and LLM?\n                <\/button>\n            <\/div>\n            <div id=\"faq3\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nTools like Semrush and Ahrefs optimize SERP visibility, while KIVA and Perplexity analyze AI citation behavior. Together, they help teams develop for SERP and AI models, ensuring your content is discoverable on search engines and included in LLM-generated responses.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq4\" aria-expanded=\"false\" aria-controls=\"faq4\">\n                    What skills are needed to create for SERP and LLM?\n                <\/button>\n            <\/div>\n            <div id=\"faq4\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nWriters need SEO skills like keyword research and schema markup, but also must know how to build for search results and LLMs. That means structuring answers clearly, embedding trusted sources, and formatting content in modular chunks that machines can extract.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq5\" aria-expanded=\"false\" aria-controls=\"faq5\">\n                    Why is content optimization important for SERP and LLM?\n                <\/button>\n            <\/div>\n            <div id=\"faq5\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nOptimization ensures visibility across platforms. When you create for search results and AI models, you increase the chance of appearing in featured snippets, People Also Ask boxes, and AI summaries. Without optimization, your content risks being overlooked by both.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq6\" aria-expanded=\"false\" aria-controls=\"faq6\">\n                    How does LLM impact search engine optimization?\n                <\/button>\n            <\/div>\n            <div id=\"faq6\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nLLMs have expanded SEO beyond Google rankings. They favor clarity, chunked answers, and trusted sources. That\u2019s why it\u2019s crucial to design for search pages and language processors\u2014so your content performs in SERPs and AI-driven environments alike.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p><div class=\"accordion-item mb-3\">\n            <div class=\"accordion-header\">\n                <button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#faq7\" aria-expanded=\"false\" aria-controls=\"faq7\">\n                    What is the role of AI in search engine results?\n                <\/button>\n            <\/div>\n            <div id=\"faq7\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                    <br \/>\nAI powers SERP features like AI Overviews and influences how LLMs summarize content. When you design for search engines and language models, you ensure your articles are readable by humans and extractable by machines, giving your brand broader reach.<br \/>\n\n                <\/div>\n            <\/div>\n        <\/div><\/p>\n<p>\n    <\/div>\n<hr \/>\n<h2>Final Thought: Get Found Where It Counts<\/h2>\n<p>Today\u2019s visibility is no longer just about ranking. It\u2019s about relevance across every discovery moment.<\/p>\n<p>Whether a user types into Google or prompts an AI assistant, your content needs to show up clearly, confidently, and consistently. That requires purposeful structure, alignment with real search behavior, and content that speaks to both humans and machines.<\/p>\n<p>The creators and brands who master this balance will be the ones who rise above the noise.<\/p>\n<div class='highlighter-box p-3 mb-4 w-100' style='background: #B3D8FF !important; border-color: #16a'><\/p>\n<h3>Key Takeaways:<\/h3>\n<ul>\n<li>Break content into scannable, well-labeled sections<\/li>\n<li>Include verifiable data, clear answers, and trusted citations<\/li>\n<li>Match the tone, length, and format found in AI responses<\/li>\n<li>Use TL;DRs, lists, and FAQs for easy extraction<\/li>\n<li>Monitor both SERP and LLM performance to refine your strategy<\/li>\n<\/ul>\n<p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Want to create content based on SERP and LLM trends that rank on Google and appear in answers from ChatGPT, Claude, or Gemini? As search evolves across both engines and AI models, the rules of visibility are shifting fast. Many still view this only through search engine optimization (SEO), but visibility now means showing up [&hellip;]<\/p>\n","protected":false},"author":17,"featured_media":9414,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[],"class_list":["post-9404","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-content"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How To Create Content Based on SERP and LLM trends<\/title>\n<meta name=\"description\" content=\"Learn how to create for SERP and LLM by aligning content with Google and AI models. Boost visibility in SERPs and AI summaries with KIVA.\" \/>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How To Create Content Based on SERP and LLM trends\" \/>\n<meta property=\"og:description\" content=\"Learn how to create for SERP and LLM by aligning content with Google and AI models. Boost visibility in SERPs and AI summaries with KIVA.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/staging.wellows.com\/blog\/create-for-serp-and-llms\/\" \/>\n<meta property=\"og:site_name\" content=\"Wellows\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-29T13:14:21+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-09-11T11:15:15+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/staging.wellows.com\/blog\/wp-content\/uploads\/2025\/07\/Sahar-FI-46.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1280\" \/>\n\t<meta property=\"og:image:height\" content=\"720\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Ramesha Kamran\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@https:\/\/x.com\/ramesha_kamran\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ramesha Kamran\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"19 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"How To Create Content Based on SERP and LLM trends","description":"Learn how to create for SERP and LLM by aligning content with Google and AI models. 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