{"id":26384,"date":"2026-09-28T11:00:30","date_gmt":"2026-09-28T11:00:30","guid":{"rendered":"https:\/\/blog.wellows.com\/?p=26384"},"modified":"2026-09-29T11:31:47","modified_gmt":"2026-09-29T11:31:47","slug":"llm-rank-tracking","status":"publish","type":"post","link":"https:\/\/wellows.com\/blog\/llm-rank-tracking\/","title":{"rendered":"LLM Rank Tracking Explained: How to Measure Your Place in AI Answers (2026)"},"content":{"rendered":"<style>body{background:#fff;color:#1F2333;font-family:Georgia,serif;font-size:17px;line-height:1.7;margin:0}.wrap{max-width:760px;margin:0 auto;padding:24px 16px}h1,h2,h3{font-family:system-ui,sans-serif;color:#1F2333}h1{font-size:34px;line-height:1.2}h2{font-size:27px;margin-top:40px}h3{font-size:21px}<\/style>\n<p><!-- Wellows blog: LLM Rank Tracking. Paste into the Classic Editor TEXT tab. Put the H1 in the post title field. Yellow highlights are placeholders to fill before publishing. --><\/p>\n<div style=\"background: #F3F1FF; border: 1px solid #DCD7FF; border-radius: 12px; padding: 22px 24px; margin: 24px 0;\">\n<div style=\"font-size: 18px; font-weight: 800; color: #4b3fd6; margin-bottom: 12px;\">Key Takeaways<\/div>\n<ul style=\"margin: 0; padding-left: 20px;\">\n<li style=\"margin: 0 0 10px;\"><strong>It measures odds, not a spot:<\/strong> LLM rank tracking runs the same prompts through AI engines many times and reports how often you appear. One screenshot tells you almost nothing.<\/li>\n<li style=\"margin: 0 0 10px;\"><strong>Citations beat mentions:<\/strong> Being named is nice. Being linked as a source is what carries authority and sends clicks, so track the two separately.<\/li>\n<li style=\"margin: 0 0 10px;\"><strong>Five engines, five systems:<\/strong> ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode pull from different sources. A win on one says little about the others.<\/li>\n<li style=\"margin: 0 0 10px;\"><strong>Measure what users see:<\/strong> Answers in the consumer apps can differ from what an API returns. Your tracking should reflect the screen your buyer looks at.<\/li>\n<li style=\"margin: 0 0 10px;\"><strong>Your AI reputation already exists:<\/strong> The sources AI engines cite shape how they describe you. Tracking shows you the exact pages behind that story.<\/li>\n<li style=\"margin: 0 0 10px;\"><strong>Tracking only pays off with action:<\/strong> Every gap you find should map to a page to fix, a source to pitch or a piece to publish.<\/li>\n<\/ul>\n<\/div>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong><strong>LLM rank tracking<\/strong> means running a fixed set of real buyer prompts through ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode, again and again, and logging if your brand appears, if it\u2019s cited as a source, where it sits and how it\u2019s described. You get rates to watch, not one position.<\/p>\n<p>If you\u2019ve been trying to work out how to rank in AI Overviews, this is the piece most advice skips: you can\u2019t improve a position you\u2019ve never measured properly. And the audience is large. Google said in May 2026 that AI Overviews has over 2.5 billion monthly active users and AI Mode has passed 1 billion (<a style=\"color: #4b3fd6;\" href=\"https:\/\/blog.google\/innovation-and-ai\/sundar-pichai-io-2026\/\" rel=\"noopener nofollow noreferrer\">Google, 2026<\/a>).<\/p>\n<h2>What Is LLM Rank Tracking?<\/h2>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong>LLM rank tracking tells you how visible your brand is inside answers written by large language models. You pick the prompts that matter to your business, run them on each AI engine many times, and log presence, citations, position and sentiment. The output is a trend line per prompt and per engine, not a single number.<\/p>\n<div style=\"border: 2px solid #4B3FD6; border-radius: 12px; padding: 20px 22px; margin: 24px 0; background: #fff;\">\n<div style=\"display: inline-block; background: #4B3FD6; color: #fff; font-size: 12px; font-weight: bold; letter-spacing: 1px; text-transform: uppercase; padding: 4px 10px; border-radius: 20px; margin-bottom: 10px;\">\ud83d\udcd8 Definition<\/div>\n<div style=\"font-size: 18px; font-weight: bold; color: #1f2333; margin-bottom: 6px;\">LLM rank tracking<\/div>\n<div style=\"font-size: 16px; line-height: 1.6; color: #1f2333;\">The repeated measurement of how often, where and how favorably a brand appears in AI generated answers for a defined set of prompts, broken down by AI engine and by whether the brand is mentioned, cited as a source, or missing.<\/div>\n<\/div>\n<h3>Why \u201crank\u201d means something different inside an AI answer<\/h3>\n<p>In classic search, position 3 is position 3 for most people at a given moment. In an AI answer, there\u2019s no fixed list. The model writes a fresh response each time, sometimes names you first, sometimes fourth, sometimes not at all.<\/p>\n<p>So the useful question changes. It stops being \u201cwhere do I rank?\u201d and becomes \u201cout of 20 runs of this prompt, how often was I there, and how often was I the source?\u201d<\/p>\n<h3>Then vs. now<\/h3>\n<div style=\"overflow-x: auto; margin: 24px 0; border: 1px solid #E3E5EE; border-radius: 10px;\">\n<table style=\"width: 100%; min-width: 560px; border-collapse: collapse; font-size: 15px; line-height: 1.5; margin: 0; border: none;\">\n<thead>\n<tr>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\"><\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">Classic rank tracking<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">LLM rank tracking<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Unit you track<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Keyword<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Prompt (a full question, often long tail)<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">What you record<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">One position, one URL<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Presence, citation, position in the answer, sentiment, cited sources<\/td>\n<\/tr>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">How often it changes<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Days or weeks<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Between runs of the same prompt<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Samples needed<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">One check per day<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Several runs per prompt per engine<\/td>\n<\/tr>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Where results live<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">One results page<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Five engines with different source pools<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">What \u201cwinning\u201d means<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Top 3 blue link<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Being named and linked as a trusted source<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h2>GEO, AEO and AI SEO Rank Tracking: Are They the Same Thing?<\/h2>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong>Mostly, yes. GEO rank tracking (generative engine optimization), AEO rank tracking (answer engine optimization), AI SEO rank tracking and LLM rank tracking all describe the same job: measuring your visibility in answers written by AI.<\/p>\n<p>The labels lean in slightly different directions, though:<\/p>\n<div style=\"display: flex; flex-wrap: wrap; gap: 12px; margin: 20px 0;\">\n<div style=\"flex: 1 1 200px; border: 1px solid #E3E5EE; border-top: 4px solid #4B3FD6; border-radius: 10px; padding: 16px; background: #fff;\">\n<div style=\"font-weight: bold; color: #1f2333; margin-bottom: 6px;\">GEO rank tracking<\/div>\n<div style=\"font-size: 15px; color: #5b6075; line-height: 1.5;\">Usually covers the full set of generative engines, including ChatGPT and Perplexity.<\/div>\n<\/div>\n<div style=\"flex: 1 1 200px; border: 1px solid #E3E5EE; border-top: 4px solid #4B3FD6; border-radius: 10px; padding: 16px; background: #fff;\">\n<div style=\"font-weight: bold; color: #1f2333; margin-bottom: 6px;\">AEO rank tracking<\/div>\n<div style=\"font-size: 15px; color: #5b6075; line-height: 1.5;\">Tends to focus on direct answer formats, such as Google AI Overviews and featured answers.<\/div>\n<\/div>\n<div style=\"flex: 1 1 200px; border: 1px solid #E3E5EE; border-top: 4px solid #4B3FD6; border-radius: 10px; padding: 16px; background: #fff;\">\n<div style=\"font-weight: bold; color: #1f2333; margin-bottom: 6px;\">AI SEO rank tracking<\/div>\n<div style=\"font-size: 15px; color: #5b6075; line-height: 1.5;\">The term SEO teams use when they bolt AI visibility onto an existing search report.<\/div>\n<\/div>\n<\/div>\n<p>Pick whichever word your stakeholders already use. The method below works for all of them. For the wider strategy behind the labels, see our comparison of <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/seo-vs-geo\/\">SEO vs. GEO<\/a>.<\/p>\n<h2>What Should You Track in LLM Rank Tracking?<\/h2>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong>Track five things per prompt and per engine: mention rate, citation rate, position in the answer, sentiment and the source URLs the engine relied on. Then roll them into share of voice against your competitors. Anything less leaves you guessing why a number moved.<\/p>\n<h3>The core metrics<\/h3>\n<div style=\"overflow-x: auto; margin: 24px 0; border: 1px solid #E3E5EE; border-radius: 10px;\">\n<table style=\"width: 100%; min-width: 560px; border-collapse: collapse; font-size: 15px; line-height: 1.5; margin: 0; border: none;\">\n<thead>\n<tr>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">Metric<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">What it measures<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">Why it matters<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">Watch out for<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Mention rate<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Share of runs where your brand is named<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Basic awareness inside AI answers<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Counts a passing name drop the same as a recommendation<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Citation rate<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Share of runs where your page is linked as a source<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Authority and referral traffic<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Some engines hide sources behind a click<\/td>\n<\/tr>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Position in answer<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Where you appear among the brands named<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">First named tends to get the attention<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Only meaningful as an average across many runs<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Sentiment<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Whether the description is positive, neutral or negative<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Shows the story the model tells about you<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Needs the source URL to be fixable<\/td>\n<\/tr>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Share of voice<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Your mentions or citations as a share of all tracked brands<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Competitive context<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Changes when you add or drop competitors from the set<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">AI visibility score<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">A weighted blend of the above<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">A single number for reporting<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Useless without the parts underneath it<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h3>Mentions and citations are different wins<\/h3>\n<p>This is where most reports go wrong. A mention means the model said your name. A citation means it pointed to your page as evidence, which is the version that carries authority and can send a visitor your way.<\/p>\n<p>The gap between the two is bigger than most teams expect. In a Wellows study of 20.5 million AI citations across five engines (March to July 2026), 90.4% of cited sources didn\u2019t mention any tracked brand at all, and only 4.5% were a brand\u2019s own page used as the source (<a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/does-domain-authority-matter-for-ai-citations\/\">Wellows, 2026<\/a>). If your tracking only counts mentions, you\u2019re missing most of the picture.<\/p>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 12px; padding: 18px 20px; margin: 24px 0; background: #fff;\">\n<div style=\"font-weight: bold; font-size: 15px; color: #1f2333; margin-bottom: 8px;\">What 20.5 million AI citations actually pointed to<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">No tracked brand named<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 90.4%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">90.4%<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">Third party page names a brand<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 5.1%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">5.1%<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">Brand\u2019s own page cited<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 4.5%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">4.5%<\/div>\n<\/div>\n<div style=\"font-size: 13px; color: #5b6075; margin-top: 10px;\">Source: <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/does-domain-authority-matter-for-ai-citations\/\">Wellows, 2026<\/a>. Five engines, March to July 2026.<\/div>\n<\/div>\n<h3>Sentiment and your shadow reputation<\/h3>\n<p>Every brand has a <strong>shadow reputation<\/strong> in AI: the version of you the models describe when you\u2019re not in the room, built from sources you didn\u2019t write. A review thread from 2023, an outdated comparison page, a forum complaint. If an engine cites it, it shapes the answer.<\/p>\n<p>That\u2019s why sentiment on its own isn\u2019t enough. You need the specific URLs behind a negative description, because a page is something you can respond to, update or outrank. A vague \u201csentiment dipped\u201d is not.<\/p>\n<div style=\"background: #FFF8E6; border: 1px solid #F5D27A; border-radius: 12px; padding: 20px 22px; margin: 24px 0;\">\n<div style=\"font-size: 17px; font-weight: 800; color: #8a5a00; margin-bottom: 8px;\">\ud83d\udca1 Did you know?<\/div>\n<div style=\"font-size: 16px; line-height: 1.6; color: #1f2333;\">In the same Wellows study, only 44.3% of sources with a domain authority under 40 that were cited in April to June were still being cited two months later. For domains rated 90 and above, it was 92.0% (<a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/does-domain-authority-matter-for-ai-citations\/\">Wellows, 2026<\/a>). Citations from smaller sites come and go, so a single month of data will mislead you.<\/div>\n<div style=\"margin-top: 14px;\">\n<div style=\"font-size: 13px; font-weight: bold; color: #8a5a00; margin-bottom: 4px;\">Share of sources still cited two months later<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 6px 0;\">\n<div style=\"flex: 0 0 110px; font-size: 14px;\">DA under 40<\/div>\n<div style=\"flex: 1; background: #FBE7B5; border-radius: 6px; height: 18px; overflow: hidden;\">\n<div style=\"width: 44.3%; background: #D98E04; height: 18px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 52px; text-align: right; font-weight: bold; font-size: 14px;\">44.3%<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 6px 0;\">\n<div style=\"flex: 0 0 110px; font-size: 14px;\">DA 40 to 69<\/div>\n<div style=\"flex: 1; background: #FBE7B5; border-radius: 6px; height: 18px; overflow: hidden;\">\n<div style=\"width: 67.0%; background: #D98E04; height: 18px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 52px; text-align: right; font-weight: bold; font-size: 14px;\">67.0%<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 6px 0;\">\n<div style=\"flex: 0 0 110px; font-size: 14px;\">DA 70 to 89<\/div>\n<div style=\"flex: 1; background: #FBE7B5; border-radius: 6px; height: 18px; overflow: hidden;\">\n<div style=\"width: 86.5%; background: #D98E04; height: 18px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 52px; text-align: right; font-weight: bold; font-size: 14px;\">86.5%<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 6px 0;\">\n<div style=\"flex: 0 0 110px; font-size: 14px;\">DA 90 and above<\/div>\n<div style=\"flex: 1; background: #FBE7B5; border-radius: 6px; height: 18px; overflow: hidden;\">\n<div style=\"width: 92.0%; background: #D98E04; height: 18px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 52px; text-align: right; font-weight: bold; font-size: 14px;\">92.0%<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2>Why Do LLM Rankings Change Every Time You Check?<\/h2>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong>Because AI engines generate each answer fresh, and the sources they retrieve shift with the phrasing, the user\u2019s location, the time and the model version. Even with every setting locked, outputs can vary. That\u2019s why a single check is an anecdote and repeated runs are data.<\/p>\n<h3>The models themselves vary<\/h3>\n<p>Researchers at Thinking Machines Lab ran the same prompt 1,000 times on an open model at temperature zero (the setting meant to remove randomness) and still got 80 different completions (<a style=\"color: #4b3fd6;\" href=\"https:\/\/thinkingmachines.ai\/blog\/defeating-nondeterminism-in-llm-inference\/\" rel=\"noopener nofollow noreferrer\">Thinking Machines Lab, 2025<\/a>). Consumer AI apps add search, personalization and product modules on top of that. Treat this as directional, since it was a lab test on one model, but the lesson holds.<\/p>\n<div style=\"margin: 24px 0;\">\n<div style=\"display: flex; flex-wrap: wrap; gap: 12px;\">\n<div style=\"flex: 1 1 180px; background: #F3F1FF; border-radius: 12px; padding: 18px; text-align: center;\">\n<div style=\"font-size: 34px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">1,000<\/div>\n<div style=\"font-size: 14px; color: #1f2333; margin-top: 6px; line-height: 1.4;\">runs of the same prompt<\/div>\n<\/div>\n<div style=\"flex: 1 1 180px; background: #F3F1FF; border-radius: 12px; padding: 18px; text-align: center;\">\n<div style=\"font-size: 34px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">80<\/div>\n<div style=\"font-size: 14px; color: #1f2333; margin-top: 6px; line-height: 1.4;\">different answers returned<\/div>\n<\/div>\n<div style=\"flex: 1 1 180px; background: #F3F1FF; border-radius: 12px; padding: 18px; text-align: center;\">\n<div style=\"font-size: 34px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">0<\/div>\n<div style=\"font-size: 14px; color: #1f2333; margin-top: 6px; line-height: 1.4;\">temperature setting (meant to remove randomness)<\/div>\n<\/div>\n<\/div>\n<div style=\"font-size: 13px; color: #5b6075; margin-top: 10px;\">Source: <a style=\"color: #4b3fd6;\" href=\"https:\/\/thinkingmachines.ai\/blog\/defeating-nondeterminism-in-llm-inference\/\" rel=\"noopener nofollow noreferrer\">Thinking Machines Lab, 2025<\/a>.<\/div>\n<\/div>\n<h3>The source pool moves too<\/h3>\n<p>Engines also change what they trust. The Wellows domain authority study found ChatGPT\u2019s median cited domain authority jumped 16 points in a single week of July 2026, landing at 51 after a March to June baseline of 35 (<a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/does-domain-authority-matter-for-ai-citations\/\">Wellows, 2026<\/a>). Nothing on your site changed, yet your odds of being cited did.<\/p>\n<div style=\"display: flex; flex-wrap: wrap; align-items: center; justify-content: center; gap: 16px; border: 1px solid #E3E5EE; border-radius: 12px; padding: 20px; margin: 24px 0; text-align: center;\">\n<div>\n<div style=\"font-size: 13px; color: #5b6075; text-transform: uppercase; letter-spacing: 1px;\">March to June 2026<\/div>\n<div style=\"font-size: 40px; font-weight: 800; color: #5b6075;\">35<\/div>\n<\/div>\n<div style=\"font-size: 30px; color: #4b3fd6;\">\u279c<\/div>\n<div>\n<div style=\"font-size: 13px; color: #5b6075; text-transform: uppercase; letter-spacing: 1px;\">After July 7 to 14<\/div>\n<div style=\"font-size: 40px; font-weight: 800; color: #4b3fd6;\">51<\/div>\n<\/div>\n<div style=\"flex-basis: 100%; font-size: 14px; color: #1f2333;\">ChatGPT median cited domain authority, one week apart<\/div>\n<\/div>\n<h3>The API isn\u2019t the app<\/h3>\n<p>A lot of tracking runs prompts through a model\u2019s API because it\u2019s cheap. The trouble is that the API answer often differs from what a person sees in the ChatGPT or Gemini app, where web search, shopping modules and location all come into play.<\/p>\n<p>If the goal is to know what your buyer sees, measure the screen your buyer sees.<\/p>\n<h2>How to Set Up LLM Rank Tracking: 7 Steps<\/h2>\n<p>Here\u2019s a setup you can start on Monday. It works for one brand or twenty clients.<\/p>\n<ol style=\"margin: 24px 0; padding: 0;\">\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">1<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Build a prompt set of 30 to 100 real questions.<\/strong>Pull them from sales calls, support tickets, People Also Ask and your own search queries. Mix category questions (\u201cbest payroll software for a 20 person team\u201d), comparison questions and problem questions. Our guide to <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/how-to-find-queries-for-geo\/\">finding queries for GEO<\/a> covers where to source them.<\/span><\/li>\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">2<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Tag every prompt by intent and topic.<\/strong>Group prompts into topic clusters so you can report by theme. Wellows analysis of 2.37 million AI citations found a brand\u2019s AI visibility can vary by more than 4.5x across topics within its own niche (<a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/how-to-rank-in-chatgpt\/\">Wellows<\/a>), so a single blended number hides your weak spots.<\/span><\/li>\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">3<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Pick your engines and treat each one separately.<\/strong>Track all five major engines, but never average them into one number before you\u2019ve read them individually (the table below shows why).<\/span><\/li>\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">4<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Set a sampling plan.<\/strong>Run each prompt several times per engine per cycle and track weekly. . Keep location and language fixed so changes mean something.<\/span><\/li>\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">5<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Capture the answer as a user sees it.<\/strong>Record the full response, every brand named, every source URL and the position of each. Browser based collection gets you closer to the real app experience than API calls.<\/span><\/li>\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">6<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Add three to five competitors.<\/strong>Share of voice only means something against named rivals. Watch where their visibility rises and which URLs are doing the lifting.<\/span><\/li>\n<li style=\"display: flex; gap: 16px; align-items: flex-start; border: 1px solid #E3E5EE; border-radius: 12px; padding: 16px 18px; margin: 0 0 12px; background: #fff; list-style: none;\"><span style=\"flex: 0 0 36px; height: 36px; border-radius: 50%; background: #4B3FD6; color: #fff; font-weight: 800; display: flex; align-items: center; justify-content: center; font-size: 16px;\">7<\/span><span style=\"flex: 1; line-height: 1.6;\"><strong style=\"display: block; color: #1f2333; font-size: 17px; margin-bottom: 4px;\">Turn every gap into a task and review monthly.<\/strong>For each prompt where you\u2019re missing or described badly, write down the fix: a page to update, a third party source to pitch, a new piece to publish. Then check next month whether the rate moved.<\/span><\/li>\n<\/ol>\n<h3>How the five engines differ<\/h3>\n<div style=\"overflow-x: auto; margin: 24px 0; border: 1px solid #E3E5EE; border-radius: 10px;\">\n<table style=\"width: 100%; min-width: 560px; border-collapse: collapse; font-size: 15px; line-height: 1.5; margin: 0; border: none;\">\n<thead>\n<tr>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">Engine<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">How it shows sources<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">Median cited DA (Mar to Jun 2026)<\/th>\n<th style=\"background: #4B3FD6; color: #fff; text-align: left; padding: 12px 14px; font-weight: 600; border: none;\">What to watch<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">ChatGPT<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Inline links and a sources panel when it searches the web<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">35<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Whether search triggers at all for your prompt; answers without search carry no citations<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Gemini<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Source links on grounded answers<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">39<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Differences between the app and Google Search surfaces<\/td>\n<\/tr>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Perplexity<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Numbered citations on nearly every answer<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">34<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">The most citation friendly engine, so a good early signal<\/td>\n<\/tr>\n<tr style=\"background: #F8F8FC;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Google AI Overviews<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Link cards beside the summary<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">47<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Only appears for some queries, so track how often it triggers<\/td>\n<\/tr>\n<tr style=\"background: #FFFFFF;\">\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top; font-weight: 600; color: #1f2333;\">Google AI Mode<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Links throughout a conversational answer<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">48<\/td>\n<td style=\"padding: 12px 14px; border: none; border-top: 1px solid #E3E5EE; vertical-align: top;\">Follow up turns can change which sources appear<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 12px; padding: 18px 20px; margin: 24px 0; background: #fff;\">\n<div style=\"font-weight: bold; font-size: 15px; color: #1f2333; margin-bottom: 8px;\">Median domain authority of cited sources, by engine<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">Google AI Mode<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 80.0%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">48<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">Google AI Overviews<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 78.3%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">47<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">Gemini<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 65.0%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">39<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">ChatGPT<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 58.3%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">35<\/div>\n<\/div>\n<div style=\"display: flex; align-items: center; gap: 10px; margin: 8px 0;\">\n<div style=\"flex: 0 0 150px; font-size: 14px; color: #1f2333;\">Perplexity<\/div>\n<div style=\"flex: 1; background: #ECEAF7; border-radius: 6px; height: 22px; overflow: hidden;\">\n<div style=\"width: 56.7%; background: #4B3FD6; height: 22px; border-radius: 6px;\"><\/div>\n<\/div>\n<div style=\"flex: 0 0 58px; text-align: right; font-weight: bold; font-size: 14px; color: #1f2333;\">34<\/div>\n<\/div>\n<div style=\"font-size: 13px; color: #5b6075; margin-top: 10px;\">Source: <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/does-domain-authority-matter-for-ai-citations\/\">Wellows, 2026<\/a>. March to June 2026 baseline.<\/div>\n<\/div>\n<p>Notice the split. The two Google surfaces lean toward higher authority domains, while ChatGPT and Perplexity cite smaller sites far more often.<\/p>\n<p>The same study found 66.5% of domains under DA 40 were cited by only one of the five engines. One engine\u2019s result is not your AI visibility.<\/p>\n<h2>How Do You Rank in AI Overviews (and Prove You Did)?<\/h2>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong>You rank in AI Overviews by being the clearest, most trusted answer to the narrow questions Google generates around a query, and you prove it with prompt level tracking. Search Console won\u2019t tell you which competitor got cited when you didn\u2019t, so you need a separate record of every AI Overview for your priority queries.<\/p>\n<h3>What should I know about how to rank in AI Overviews?<\/h3>\n<p>Three things matter most for measurement:<\/p>\n<ul>\n<li><strong>AI Overviews don\u2019t show for every query.<\/strong> In Pew Research Center data from March 2025, about 18% of Google searches produced an AI summary (<a style=\"color: #4b3fd6;\" href=\"https:\/\/www.pewresearch.org\/short-reads\/2025\/07\/22\/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results\/\" rel=\"noopener nofollow noreferrer\">Pew Research Center, 2025<\/a>). Track trigger rate first. That share has likely grown since, so check it on your own queries.<\/li>\n<li><strong>Google fans out your query.<\/strong> AI Mode and AI Overviews answer related sub questions behind the scenes, so your tracking set should include those follow ups, not only the head term.<\/li>\n<li><strong>Authority helps, but it\u2019s not the gate.<\/strong> In the Wellows study, 40.8% of AI Overview citations came from domains under DA 40.<\/li>\n<\/ul>\n<h3>How to show up in AI Overviews with SEO<\/h3>\n<p>Solid SEO gets you into the pool Google retrieves from. Structured, direct answers, current facts and third party mentions get you picked from that pool.<\/p>\n<p>For the full workflow, read our guide on <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/how-to-rank-in-google-ai-overviews\/\">how to rank in Google AI Overviews<\/a>. Then use the tracking setup above to check if it worked.<\/p>\n<h2>What Makes the Best LLM Rank Tracking Setup?<\/h2>\n<p>People searching for the best AI SEO rank tracking or the best LLM SEO rank tracking tool are usually asking one question: can I trust these numbers enough to act on them? Judge any tool or homegrown setup against these criteria.<\/p>\n<div style=\"display: flex; flex-wrap: wrap; gap: 14px; margin: 24px 0;\">\n<div style=\"flex: 1 1 260px; background: #EEFAF2; border: 1px solid #BFE8CD; border-radius: 12px; padding: 18px 20px;\">\n<div style=\"font-weight: 800; color: #16794a; margin-bottom: 10px; font-size: 17px;\">Look for<\/div>\n<ul style=\"margin: 0; padding: 0;\">\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705All five engines tracked separately, including Google AI Mode<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705Answers captured the way a user sees them in the app<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705Citations and mentions reported as separate metrics<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705The source URLs behind each answer, with sentiment attached<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705Repeated runs per prompt, with rates rather than single positions<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705Competitor tracking on the same prompts and schedule<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u2705A clear route from gap to action (content, outreach, page updates)<\/li>\n<\/ul>\n<\/div>\n<div style=\"flex: 1 1 260px; background: #FDF0F0; border: 1px solid #F3C7C7; border-radius: 12px; padding: 18px 20px;\">\n<div style=\"font-weight: 800; color: #b42318; margin-bottom: 10px; font-size: 17px;\">Be wary of<\/div>\n<ul style=\"margin: 0; padding: 0;\">\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u274cA single \u201cAI rank\u201d with no breakdown underneath<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u274cAPI only collection with no mention of how it compares to the app<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u274cMention counts presented as citations<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u274cDaily screenshots of one run per prompt<\/li>\n<li style=\"display: flex; gap: 8px; margin: 0 0 8px; list-style: none;\">\u274cDashboards that show the problem and stop there<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<h3>What a useful report line looks like<\/h3>\n<div style=\"display: flex; flex-wrap: wrap; gap: 14px; margin: 24px 0;\">\n<div style=\"flex: 1 1 240px; border: 1px solid #F3C7C7; border-radius: 12px; padding: 18px 20px; background: #FDF0F0;\">\n<div style=\"font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #b42318; margin-bottom: 8px;\">Before<\/div>\n<div style=\"font-size: 16px; line-height: 1.6; font-style: italic;\">\u201cBrand visibility in ChatGPT: 62. Up 4 points.\u201d<\/div>\n<\/div>\n<div style=\"flex: 1 1 240px; border: 1px solid #BFE8CD; border-radius: 12px; padding: 18px 20px; background: #EEFAF2;\">\n<div style=\"font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #16794a; margin-bottom: 8px;\">After<\/div>\n<div style=\"font-size: 16px; line-height: 1.6; font-style: italic;\">\u201cOn 40 payroll prompts, ChatGPT named us in 38% of runs and cited our pages in 11%. Competitor A was cited in 24%, mostly via two comparison pages from third party review sites. We\u2019re pitching both publishers this month.\u201d<\/div>\n<\/div>\n<\/div>\n<p>The second version tells your boss what happened and what you\u2019re doing about it. That\u2019s the standard.<\/p>\n<div style=\"background: #F3F1FF; border: 1px solid #DCD7FF; border-left: 5px solid #4B3FD6; border-radius: 12px; padding: 22px 24px; margin: 24px 0;\">\n<div style=\"font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 8px;\">How Wellows helps<\/div>\n<div style=\"font-size: 16px; line-height: 1.6; color: #1f2333;\">This is the job Wellows is built for. It runs your prompts across ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode, tells you whether you were cited or only mentioned, and surfaces the exact URLs shaping your <strong style=\"color: #4b3fd6;\">shadow reputation<\/strong>. The same scan runs on your competitors, so you can see which sources lift their visibility and where they\u2019re exposed.<\/div>\n<\/div>\n<h2>Your LLM Rank Tracking Checklist<\/h2>\n<p>Copy this into your project tool.<\/p>\n<style>.wlwck{background:#F3F1FF;border:1px solid #DCD7FF;border-radius:16px;padding:22px;margin:28px 0;color:#1F2333;font-size:16px;line-height:1.5}.wlwck *{box-sizing:border-box}.wlwck-top{display:flex;flex-wrap:wrap;align-items:center;justify-content:space-between;gap:12px;margin-bottom:14px}.wlwck-title{font-size:19px;font-weight:800;color:#4B3FD6}.wlwck-count{font-size:14px;font-weight:700;color:#1F2333}.wlwck-bar{height:10px;background:#E2DEFF;border-radius:10px;overflow:hidden;margin:0 0 18px}.wlwck-fill{height:10px;width:0;background:#4B3FD6;border-radius:10px;transition:width .3s ease}.wlwck-grid{display:flex;flex-wrap:wrap;gap:12px}.wlwck-col{flex:1 1 230px;background:#fff;border:1px solid #E3E5EE;border-radius:12px;padding:16px}.wlwck-h{font-weight:800;color:#4B3FD6;font-size:16px;margin:0 0 10px;display:flex;justify-content:space-between}.wlwck-h span{font-size:13px;color:#5B6075;font-weight:700}.wlwck label{display:flex;gap:10px;align-items:flex-start;padding:8px;margin:0 0 4px;border-radius:8px;cursor:pointer;font-size:15px;transition:background .15s}.wlwck label:hover{background:#F6F5FF}.wlwck input[type=checkbox]{flex:0 0 auto;width:19px;height:19px;margin:2px 0 0;accent-color:#4B3FD6;cursor:pointer}.wlwck input:checked+span{text-decoration:line-through;color:#8A8FA3}.wlwck-actions{display:flex;flex-wrap:wrap;gap:10px;margin-top:16px}.wlwck-btn{appearance:none;border:1px solid #4B3FD6;background:#fff;color:#4B3FD6;font-weight:700;font-size:14px;padding:9px 18px;border-radius:30px;cursor:pointer;line-height:1.2}.wlwck-btn:hover{background:#4B3FD6;color:#fff}.wlwck-done{display:none;margin-top:14px;background:#EEFAF2;border:1px solid #BFE8CD;color:#16794A;border-radius:10px;padding:12px 14px;font-weight:700;font-size:15px}.wlwck.is-done .wlwck-done{display:block}<\/style>\n<div id=\"wlwck\" class=\"wlwck\">\n<div class=\"wlwck-top\">\n<div class=\"wlwck-title\">LLM Rank Tracking Checklist<\/div>\n<div class=\"wlwck-count\"><span class=\"wlwck-n\">0<\/span> of 15 done<\/div>\n<\/div>\n<div class=\"wlwck-bar\">\n<div class=\"wlwck-fill\"><\/div>\n<\/div>\n<div class=\"wlwck-grid\">\n<div class=\"wlwck-col\">\n<div class=\"wlwck-h\">Setup <span class=\"wlwck-gc\">0\/5<\/span><\/div>\n<p><label><input type=\"checkbox\" data-id=\"i1\">30 to 100 prompts drawn from real customer language<\/label><label><input type=\"checkbox\" data-id=\"i2\">Every prompt tagged by topic and intent<\/label><label><input type=\"checkbox\" data-id=\"i3\">ChatGPT, Gemini, Perplexity, AI Overviews and AI Mode all tracked<\/label><label><input type=\"checkbox\" data-id=\"i4\">Location, language and account state fixed for every run<\/label><label><input type=\"checkbox\" data-id=\"i5\">Three to five named competitors added<\/label><\/p>\n<\/div>\n<div class=\"wlwck-col\">\n<div class=\"wlwck-h\">Every cycle <span class=\"wlwck-gc\">0\/5<\/span><\/div>\n<p><label><input type=\"checkbox\" data-id=\"i6\">Several runs per prompt per engine<\/label><label><input type=\"checkbox\" data-id=\"i7\">Mention rate and citation rate logged separately<\/label><label><input type=\"checkbox\" data-id=\"i8\">Position and sentiment recorded per run<\/label><label><input type=\"checkbox\" data-id=\"i9\">Every cited source URL saved<\/label><label><input type=\"checkbox\" data-id=\"i10\">Negative descriptions traced to a specific page<\/label><\/p>\n<\/div>\n<div class=\"wlwck-col\">\n<div class=\"wlwck-h\">Every month <span class=\"wlwck-gc\">0\/5<\/span><\/div>\n<p><label><input type=\"checkbox\" data-id=\"i11\">Visibility reviewed by topic cluster, not only in total<\/label><label><input type=\"checkbox\" data-id=\"i12\">Engine results read one at a time before blending<\/label><label><input type=\"checkbox\" data-id=\"i13\">Each gap assigned a fix and an owner<\/label><label><input type=\"checkbox\" data-id=\"i14\">Last month\u2019s fixes checked against this month\u2019s rates<\/label><label><input type=\"checkbox\" data-id=\"i15\">Findings shared in one plain language summary<\/label><\/p>\n<\/div>\n<\/div>\n<div class=\"wlwck-done\">\ud83c\udf89 All 15 done. Your tracking setup is ready to report on.<\/div>\n<div class=\"wlwck-actions\"><button class=\"wlwck-btn\" type=\"button\" data-act=\"copy\">Copy checklist<\/button><button class=\"wlwck-btn\" type=\"button\" data-act=\"reset\">Reset<\/button><\/div>\n<\/div>\n<p><script>(function(){var r=document.getElementById('wlwck');if(!r){return;}var K='wlwck_llm_rank_tracking';var boxes=[].slice.call(r.querySelectorAll('input[type=checkbox]'));var saved={};try{saved=JSON.parse(localStorage.getItem(K)||'{}');}catch(e){}boxes.forEach(function(b){if(saved[b.getAttribute('data-id')]){b.checked=true;}});function up(){var d=0,s={};boxes.forEach(function(b){if(b.checked){d++;s[b.getAttribute('data-id')]=1;}});r.querySelector('.wlwck-n').textContent=d;r.querySelector('.wlwck-fill').style.width=Math.round(d*100\/boxes.length)+'%';[].slice.call(r.querySelectorAll('.wlwck-col')).forEach(function(c){var cb=c.querySelectorAll('input'),k=0;[].slice.call(cb).forEach(function(x){if(x.checked){k++;}});c.querySelector('.wlwck-gc').textContent=k+'\/'+cb.length;});if(d===boxes.length){r.classList.add('is-done');}else{r.classList.remove('is-done');}try{localStorage.setItem(K,JSON.stringify(s));}catch(e){}}boxes.forEach(function(b){b.addEventListener('change',up);});r.addEventListener('click',function(e){var a=e.target.getAttribute('data-act');if(a==='reset'){boxes.forEach(function(b){b.checked=false;});up();}if(a==='copy'){var t='LLM Rank Tracking Checklist\\n';[].slice.call(r.querySelectorAll('.wlwck-col')).forEach(function(c){t+='\\n'+c.querySelector('.wlwck-h').firstChild.textContent.trim()+'\\n';[].slice.call(c.querySelectorAll('label')).forEach(function(l){t+=(l.querySelector('input').checked?'[x] ':'[ ] ')+l.textContent.trim()+'\\n';});});var btn=e.target;function ok(){btn.textContent='Copied';setTimeout(function(){btn.textContent='Copy checklist';},1800);}if(navigator.clipboard){navigator.clipboard.writeText(t).then(ok);}else{var ta=document.createElement('textarea');ta.value=t;document.body.appendChild(ta);ta.select();document.execCommand('copy');document.body.removeChild(ta);ok();}}});up();})();<\/script><\/p>\n<p>If you\u2019d rather audit your current state first, our <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/blog\/ai-search-visibility-audit-checklist\/\">AI search visibility audit checklist<\/a> is a good starting point.<\/p>\n<h2>What Results Can You Expect From LLM Rank Tracking?<\/h2>\n<p style=\"border-left: 4px solid #4B3FD6; background: #F3F1FF; padding: 14px 18px; border-radius: 0 8px 8px 0; margin: 0 0 20px;\"><strong style=\"display: block; font-size: 12px; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 4px;\">Short answer<\/strong>Tracking alone won\u2019t lift a single number. What it gives you is the evidence to decide where to act, and a way to prove the actions worked.<\/p>\n<h3>Reporting confidence<\/h3>\n<p>The first payoff is usually internal. When leadership asks \u201care we showing up in ChatGPT?\u201d, you can answer with rates per topic and per engine instead of a screenshot someone took on their phone.<\/p>\n<h3>Traffic, with honest expectations<\/h3>\n<p>Clicks from AI answers are real but smaller than classic search clicks. Pew found Google users clicked a traditional result in 8% of visits with an AI summary, against 15% without one, and clicked a link inside the summary itself in only 1% of visits (<a style=\"color: #4b3fd6;\" href=\"https:\/\/www.pewresearch.org\/short-reads\/2025\/07\/22\/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results\/\" rel=\"noopener nofollow noreferrer\">Pew Research Center, 2025<\/a>). That data is from March 2025, so treat it as a baseline rather than today\u2019s number.<\/p>\n<div style=\"margin: 24px 0;\">\n<div style=\"display: flex; flex-wrap: wrap; gap: 12px;\">\n<div style=\"flex: 1 1 180px; background: #F3F1FF; border-radius: 12px; padding: 18px; text-align: center;\">\n<div style=\"font-size: 34px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">15%<\/div>\n<div style=\"font-size: 14px; color: #1f2333; margin-top: 6px; line-height: 1.4;\">clicked a result on pages <strong>without<\/strong> an AI summary<\/div>\n<\/div>\n<div style=\"flex: 1 1 180px; background: #F3F1FF; border-radius: 12px; padding: 18px; text-align: center;\">\n<div style=\"font-size: 34px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">8%<\/div>\n<div style=\"font-size: 14px; color: #1f2333; margin-top: 6px; line-height: 1.4;\">clicked a result on pages <strong>with<\/strong> an AI summary<\/div>\n<\/div>\n<div style=\"flex: 1 1 180px; background: #F3F1FF; border-radius: 12px; padding: 18px; text-align: center;\">\n<div style=\"font-size: 34px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">1%<\/div>\n<div style=\"font-size: 14px; color: #1f2333; margin-top: 6px; line-height: 1.4;\">clicked a link <strong>inside<\/strong> the AI summary<\/div>\n<\/div>\n<\/div>\n<div style=\"font-size: 13px; color: #5b6075; margin-top: 10px;\">Source: <a style=\"color: #4b3fd6;\" href=\"https:\/\/www.pewresearch.org\/short-reads\/2025\/07\/22\/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results\/\" rel=\"noopener nofollow noreferrer\">Pew Research Center, 2025<\/a>. Browsing data from 900 US adults, March 2025.<\/div>\n<\/div>\n<p>What this means in practice: when a click does happen, it usually comes from a citation. Another reason to track citations separately from mentions.<\/p>\n<h3>Pipeline and influence<\/h3>\n<p>A lot of AI influence never shows up as a click. The buyer reads the answer, remembers the brand and searches for it later.<\/p>\n<p>Watching branded search volume alongside your citation rate is the simplest way to spot this.<\/p>\n<div style=\"border: 2px solid #4B3FD6; border-radius: 14px; padding: 20px 22px; margin: 24px 0;\">\n<div style=\"font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6; margin-bottom: 12px;\">\ud83d\udcca Quotable stats<\/div>\n<div style=\"display: flex; flex-wrap: wrap; gap: 16px;\">\n<div style=\"flex: 1 1 220px;\">\n<div style=\"font-size: 38px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">2.5 billion<\/div>\n<div style=\"font-size: 15px; margin-top: 4px;\">monthly active users of Google AI Overviews. <a style=\"color: #4b3fd6;\" href=\"https:\/\/blog.google\/innovation-and-ai\/sundar-pichai-io-2026\/\" rel=\"noopener nofollow noreferrer\">Google, May 2026<\/a><\/div>\n<\/div>\n<div style=\"flex: 1 1 220px;\">\n<div style=\"font-size: 38px; font-weight: 800; color: #4b3fd6; line-height: 1.1;\">900 million<\/div>\n<div style=\"font-size: 15px; margin-top: 4px;\">weekly active users of ChatGPT, as disclosed by OpenAI. <a style=\"color: #4b3fd6;\" href=\"https:\/\/techcrunch.com\/2026\/02\/27\/chatgpt-reaches-900m-weekly-active-users\" rel=\"noopener nofollow noreferrer\">TechCrunch, February 2026<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2>How Wellows Handles LLM Rank Tracking<\/h2>\n<p>Everything above can be done with spreadsheets and a lot of patience. Wellows runs the same workflow for you, across ChatGPT, Gemini, Perplexity, Google AI Overviews and Google AI Mode, and ties each gap to something your team can do about it. Here\u2019s how each part maps to the setup steps.<\/p>\n<div style=\"display: flex; flex-wrap: wrap; gap: 8px; margin: 18px 0 26px;\"><span style=\"background: #F3F1FF; color: #4b3fd6 !important; border: 1px solid #DCD7FF; border-radius: 30px; padding: 6px 14px; font-size: 14px; font-weight: bold;\">Steps 1 to 4: Prompt Tracking<\/span><span style=\"background: #F3F1FF; color: #4b3fd6 !important; border: 1px solid #DCD7FF; border-radius: 30px; padding: 6px 14px; font-size: 14px; font-weight: bold;\">Step 5: LLM Citations<\/span><span style=\"background: #F3F1FF; color: #4b3fd6 !important; border: 1px solid #DCD7FF; border-radius: 30px; padding: 6px 14px; font-size: 14px; font-weight: bold;\">Step 6: AI Visibility Score<\/span><span style=\"background: #F3F1FF; color: #4b3fd6 !important; border: 1px solid #DCD7FF; border-radius: 30px; padding: 6px 14px; font-size: 14px; font-weight: bold;\">Step 7: Content and Outreach<\/span><\/div>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 16px; padding: 24px; margin: 0 0 24px; background: #FFFFFF;\">\n<p style=\"margin: 0 0 6px; font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6 !important;\">The dashboard at a glance<\/p>\n<h3 style=\"margin: 0 0 10px;\">Brand Visibility Overview: your whole tracking setup on one screen<\/h3>\n<p style=\"margin: 0 0 12px; color: #1f2333 !important;\">Before you dig into any single step, the overview tells you where you stand. It shows your rank, visibility score, total citations split into explicit and implicit, and a trend line against the competitors you track, with a short written brief on what changed since the last scans.<\/p>\n<ul style=\"margin: 0 0 0; padding-left: 20px; color: #1f2333 !important;\">\n<li>A plain language brief on who is gaining ground and where<\/li>\n<li>Explicit and implicit citations counted separately<\/li>\n<li>Your prompt, topic, competitor and country coverage in one bar, with gaps flagged<\/li>\n<\/ul>\n<figure style=\"margin: 18px 0 0;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px;\" src=\"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png\" alt=\"Wellows Brand Visibility Overview showing rank, visibility score, explicit and implicit citations, and a visibility trend against competitors\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">Brand Visibility Overview in Wellows<\/figcaption><\/figure>\n<\/div>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 16px; padding: 24px; margin: 0 0 24px; background: #FFFFFF;\">\n<p style=\"margin: 0 0 6px; font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6 !important;\">Steps 1 to 4<\/p>\n<h3 style=\"margin: 0 0 10px;\">Prompt Tracking: see every prompt where you show up (or don\u2019t)<\/h3>\n<p style=\"margin: 0 0 12px; color: #1f2333 !important;\">Add the prompts your buyers actually ask and Wellows checks them daily across the major AI engines. You see where your brand appeared, where it was overlooked, and which competitor took the spot instead.<\/p>\n<ul style=\"margin: 0 0 18px; padding-left: 20px; color: #1f2333 !important;\">\n<li>Filter results by platform, region, intent and competitor<\/li>\n<li>Spot the prompts where you\u2019re mentioned but never cited<\/li>\n<li>Keep location and prompt wording fixed, so trends mean something<\/li>\n<\/ul>\n<figure style=\"margin: 0;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px; background: #F8F8FC;\" src=\"https:\/\/wellows.com\/images\/prompt-tracking-hero.svg\" alt=\"Wellows Prompt Tracking view showing brand presence by prompt across AI platforms\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">Prompt Tracking in Wellows<\/figcaption><\/figure>\n<p style=\"margin: 14px 0 0;\"><a style=\"color: #4b3fd6 !important; font-weight: bold; text-decoration: none;\" href=\"https:\/\/wellows.com\/features\/prompt-tracking\/\">See how Prompt Tracking works \u279c<\/a><\/p>\n<\/div>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 16px; padding: 24px; margin: 0 0 24px; background: #FFFFFF;\">\n<p style=\"margin: 0 0 6px; font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6 !important;\">Step 5<\/p>\n<h3 style=\"margin: 0 0 10px;\">LLM Citations: know if you were cited, not only mentioned<\/h3>\n<p style=\"margin: 0 0 12px; color: #1f2333 !important;\">This is the part most tracking misses. Wellows separates explicit citations (your own pages used as the source) from implicit ones (third party pages the engines trust that talk about your category), and shows the exact source URL behind each.<\/p>\n<ul style=\"margin: 0 0 18px; padding-left: 20px; color: #1f2333 !important;\">\n<li>Track citations, the metric that carries authority and clicks<\/li>\n<li>See the exact URLs shaping your <strong>shadow reputation<\/strong>, the version of your brand the models describe when you\u2019re not in the room<\/li>\n<li>Turn each missing source into an outreach or content task<\/li>\n<\/ul>\n<figure style=\"margin: 0;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px; background: #F8F8FC;\" src=\"https:\/\/wellows.com\/images\/llm-citations-hero.svg\" alt=\"Wellows citation tracking showing explicit vs. implicit citation distribution and citation score\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">Explicit and implicit citations, with the source behind each<\/figcaption><\/figure>\n<p style=\"margin: 14px 0 0;\"><a style=\"color: #4b3fd6 !important; font-weight: bold; text-decoration: none;\" href=\"https:\/\/wellows.com\/features\/llm-citations\/\">See how LLM Citations works \u279c<\/a><\/p>\n<\/div>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 16px; padding: 24px; margin: 0 0 24px; background: #FFFFFF;\">\n<p style=\"margin: 0 0 6px; font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6 !important;\">Step 6<\/p>\n<h3 style=\"margin: 0 0 10px;\">AI Visibility Score: one number, with the breakdown underneath<\/h3>\n<p style=\"margin: 0 0 12px; color: #1f2333 !important;\">The AI Visibility Score is a 0 to 100 measure of the share of citations your brand earns against your competitors. It updates daily and splits by platform, so a strong week in Perplexity can\u2019t hide a weak one in AI Overviews.<\/p>\n<ul style=\"margin: 0 0 18px; padding-left: 20px; color: #1f2333 !important;\">\n<li>Competitor leaderboard on the same prompts and schedule<\/li>\n<li>Per platform breakdown across all five engines<\/li>\n<li>History over time, so you can prove what your fixes did<\/li>\n<\/ul>\n<figure style=\"margin: 0;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px; background: #F8F8FC;\" src=\"https:\/\/wellows.com\/images\/ai-visibility-score-hero.svg\" alt=\"Wellows AI Visibility Score dashboard with competitor leaderboard and per platform breakdown\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">AI Visibility Score with competitor leaderboard<\/figcaption><\/figure>\n<p style=\"margin: 18px 0 0; color: #1f2333 !important;\">The per model view goes one level deeper. It shows how often each brand appears on each engine and calls out your weakest one, with the next moves to close that gap.<\/p>\n<figure style=\"margin: 18px 0 0;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px;\" src=\"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-across-llms-anon.png\" alt=\"Wellows Brand Visibility Across LLMs table comparing brand visibility on Google AI Overviews and ChatGPT, with recommended next steps\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">Brand Visibility Across LLMs, with the weakest engine flagged<\/figcaption><\/figure>\n<p style=\"margin: 14px 0 0;\"><a style=\"color: #4b3fd6 !important; font-weight: bold; text-decoration: none;\" href=\"https:\/\/wellows.com\/features\/ai-visibility-score\/\">See how the AI Visibility Score works \u279c<\/a><\/p>\n<\/div>\n<div style=\"border: 1px solid #E3E5EE; border-radius: 16px; padding: 24px; margin: 0 0 24px; background: #FFFFFF;\">\n<p style=\"margin: 0 0 6px; font-size: 12px; font-weight: 800; letter-spacing: 1px; text-transform: uppercase; color: #4b3fd6 !important;\">Step 7<\/p>\n<h3 style=\"margin: 0 0 10px;\">Content Opportunities and Outreach: close the gaps you found<\/h3>\n<p style=\"margin: 0 0 12px; color: #1f2333 !important;\">Tracking only pays off when it turns into work. Wellows shows the topics where competitors get cited and you don\u2019t, with suggested titles and intent, then finds the sites where your brand is missing and gives you verified contacts to pitch.<\/p>\n<ul style=\"margin: 0 0 18px; padding-left: 20px; color: #1f2333 !important;\">\n<li>Content ideas ranked by likely citation impact<\/li>\n<li>Outreach targets on the sources AI engines already trust<\/li>\n<li>Verified editor and site owner contacts, ready to export<\/li>\n<\/ul>\n<div style=\"display: flex; flex-wrap: wrap; gap: 14px;\">\n<figure style=\"margin: 0; flex: 1 1 260px;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px;\" src=\"https:\/\/wellows.com\/wp-content\/uploads\/2026\/02\/Find-Content-Opportunities-to-Earn-AI-Citations-scaled.png\" alt=\"Wellows Content Opportunities dashboard\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">Content Opportunities<\/figcaption><\/figure>\n<figure style=\"margin: 0; flex: 1 1 260px;\"><img decoding=\"async\" style=\"width: 100%; height: auto; display: block; border: 1px solid #E3E5EE; border-radius: 12px;\" src=\"https:\/\/wellows.com\/wp-content\/uploads\/2026\/02\/Identify-Outreach-Opportunities-to-Earn-AI-Citations-scaled.png\" alt=\"Wellows Outreach dashboard showing citation score and outreach opportunities\"><figcaption style=\"font-size: 14px; color: #5b6075 !important; margin-top: 8px; text-align: center;\">Outreach opportunities<\/figcaption><\/figure>\n<\/div>\n<p style=\"margin: 14px 0 0;\"><a style=\"color: #4b3fd6 !important; font-weight: bold; text-decoration: none;\" href=\"https:\/\/wellows.com\/features\/content-opportunities\/\">Content Opportunities \u279c<\/a> \u00a0\u00a0 <a style=\"color: #4b3fd6 !important; font-weight: bold; text-decoration: none;\" href=\"https:\/\/wellows.com\/features\/outreach\/\">Outreach \u279c<\/a><\/p>\n<\/div>\n<h2>Conclusion<\/h2>\n<p>LLM rank tracking comes down to three habits: sample repeatedly, separate citations from mentions, and read each engine on its own. Get those right and the numbers start telling you what to fix.<\/p>\n<p>Start small. Pick 30 prompts this week, run them across all five engines, and log every cited URL. You\u2019ll have your first real gap list by Friday.<\/p>\n<div style=\"background: linear-gradient(135deg,#4B3FD6,#7A6CF0); border-radius: 16px; padding: 28px 26px; margin: 28px 0; text-align: center; color: #ffffff !important;\">\n<p style=\"font-size: 22px; font-weight: 800; line-height: 1.3; margin: 0 0 10px; color: #ffffff !important;\">See where AI engines cite you, and where they don\u2019t<\/p>\n<p style=\"font-size: 16px; line-height: 1.6; margin: 0 auto 18px; max-width: 620px; color: #ffffff !important; opacity: 0.95;\">Wellows tracks your prompts across ChatGPT, Gemini, Perplexity, AI Overviews and AI Mode, shows you where you\u2019re cited and where your <strong style=\"color: #ffffff !important;\">shadow reputation<\/strong> comes from, and turns the gaps into content and outreach work you can act on.<\/p>\n<p style=\"margin: 0;\"><a style=\"display: inline-block; background: #FFFFFF !important; color: #4b3fd6 !important; font-weight: 800; padding: 12px 28px; border-radius: 30px; text-decoration: none !important; border: none; box-shadow: 0 4px 14px rgba(0,0,0,0.15);\" href=\"https:\/\/wellows.com\/features\/\">Explore Wellows<\/a><\/p>\n<\/div>\n<p>`<\/p>\n<p>See how it fits your broader <a style=\"color: #4b3fd6;\" href=\"https:\/\/wellows.com\/ai-visibility-measurement\/\">AI visibility measurement<\/a> plan.<\/p>\n<div class=\"accordion accordion-shortcode w-100 id=\" faqaccordion>\n        <br>\n<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 is LLM rank tracking in simple terms?\n                <\/button>\n            <\/div>\n            <div id=\"faq1\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     LLM rank tracking checks how often AI tools like ChatGPT, Gemini, and Perplexity mention or cite your brand when people ask questions about your category. You run the same prompts repeatedly, record the results per engine, and watch the rates change over time. It\u2019s the AI search version of keyword rank tracking, built around probability instead of fixed positions. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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 is LLM rank tracking different from regular SEO rank tracking?\n                <\/button>\n            <\/div>\n            <div id=\"faq2\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     Regular rank tracking records one position for one keyword on one results page. LLM rank tracking records presence, citations, position within the answer, and sentiment across several runs and several engines, because AI answers change between runs. You also track the source URLs each engine relied on, which tells you why you appeared or didn\u2019t. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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                    How many prompts should I track?\n                <\/button>\n            <\/div>\n            <div id=\"faq3\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     Start with 30 to 100 prompts that reflect real buyer questions, grouped by topic. Fewer than 30 makes the numbers jumpy; more than a few hundred gets hard to act on for a small team. Add prompts as you learn which topics drive business, and retire ones nobody asks anymore. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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                    How often should I run LLM rank tracking?\n                <\/button>\n            <\/div>\n            <div id=\"faq4\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     Weekly works for most brands, with several runs per prompt per engine each cycle. Daily tracking makes sense for competitive categories or during a launch. Review trends monthly, since AI engines can shift which sources they trust within a single week, and a monthly view smooths out the noise. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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                    Is being mentioned by ChatGPT the same as being cited?\n                <\/button>\n            <\/div>\n            <div id=\"faq5\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     No. A mention means ChatGPT named your brand in the answer. A citation means it linked to your page as a source. Citations carry more authority and are where referral clicks come from, so track them as a separate metric. Plenty of brands get mentioned often and cited rarely. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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                    Can I track AI rankings manually?\n                <\/button>\n            <\/div>\n            <div id=\"faq6\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     You can for a handful of prompts, using a clean browser session and a spreadsheet. It breaks down quickly, though. Five engines, several runs per prompt, and dozens of prompts add up to hundreds of checks per cycle, and manual checks miss the cited source URLs that explain each result. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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                    Why does my brand show up in Perplexity but not ChatGPT?\n                <\/button>\n            <\/div>\n            <div id=\"faq7\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     The engines pull from different source pools and weigh authority differently. Industry research shows most smaller domains are cited by only one major engine. Perplexity cites sources on nearly every answer, while ChatGPT only cites when it searches the web. Check which URLs each engine cites for your prompts to find the gap. \n                <\/div>\n            <\/div>\n        <\/div><br>\n<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=\"#faq8\" aria-expanded=\"false\" aria-controls=\"faq8\">\n                    Does domain authority affect LLM rankings?\n                <\/button>\n            <\/div>\n            <div id=\"faq8\" class=\"accordion-collapse collapse\" data-bs-parent=\"#faqAccordion\">\n                <div class=\"accordion-body\">\n                     It matters, but less than many expect. Analysis of millions of AI citations shows that a large percentage of cited sources have moderate domain authority. Higher authority sites tend to hold citations longer and appear across more engines, so authority helps consistency more than it decides entry. \n                <\/div>\n            <\/div>\n        <\/div><br>\n\n    <\/div>\n","protected":false},"excerpt":{"rendered":"<p>Key Takeaways It measures odds, not a spot: LLM rank tracking runs the same prompts through AI engines many times and reports how often you appear. One screenshot tells you almost nothing. Citations beat mentions: Being named is nice. Being linked as a source is what carries authority and sends clicks, so track the two [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_wellows_next_index":"index","footnotes":""},"categories":[10,7],"tags":[],"class_list":["post-26384","post","type-post","status-publish","format-standard","hentry","category-blog","category-content"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>LLM Rank Tracking Explained: How to Measure AI Answers<\/title>\n<meta name=\"description\" content=\"LLM rank tracking shows if ChatGPT, Gemini and Google AI cite your brand or skip it. Learn the metrics and a checklist to start this week.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/wellows.com\/blog\/llm-rank-tracking\/\" \/>\n<meta property=\"og:locale\" content=\"en\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"LLM Rank Tracking Explained: How to Measure AI Answers\" \/>\n<meta property=\"og:description\" content=\"LLM rank tracking shows if ChatGPT, Gemini and Google AI cite your brand or skip it. Learn the metrics and a checklist to start this week.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/wellows.com\/blog\/llm-rank-tracking\/\" \/>\n<meta property=\"og:site_name\" content=\"Wellows\" \/>\n<meta property=\"article:published_time\" content=\"2026-09-28T11:00:30+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-09-29T11:31:47+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png\" \/>\n<meta name=\"author\" content=\"Sharmeen Saleem\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Sharmeen Saleem\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"12 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"LLM Rank Tracking Explained: How to Measure AI Answers","description":"LLM rank tracking shows if ChatGPT, Gemini and Google AI cite your brand or skip it. Learn the metrics and a checklist to start this week.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/wellows.com\/blog\/llm-rank-tracking\/","og_locale":"en","og_type":"article","og_title":"LLM Rank Tracking Explained: How to Measure AI Answers","og_description":"LLM rank tracking shows if ChatGPT, Gemini and Google AI cite your brand or skip it. Learn the metrics and a checklist to start this week.","og_url":"https:\/\/wellows.com\/blog\/llm-rank-tracking\/","og_site_name":"Wellows","article_published_time":"2026-09-28T11:00:30+00:00","article_modified_time":"2026-09-29T11:31:47+00:00","og_image":[{"url":"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png","type":"","width":"","height":""}],"author":"Sharmeen Saleem","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Sharmeen Saleem","Est. reading time":"12 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#article","isPartOf":{"@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/"},"author":{"name":"Sharmeen Saleem","@id":"https:\/\/blog.wellows.com\/#\/schema\/person\/e1ddaf0c402a88409c4f5c14c8034af7"},"headline":"LLM Rank Tracking Explained: How to Measure Your Place in AI Answers (2026)","datePublished":"2026-09-28T11:00:30+00:00","dateModified":"2026-09-29T11:31:47+00:00","mainEntityOfPage":{"@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/"},"wordCount":4153,"commentCount":0,"publisher":{"@id":"https:\/\/blog.wellows.com\/#organization"},"image":{"@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#primaryimage"},"thumbnailUrl":"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png","articleSection":["Blog","Content"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/blog.wellows.com\/llm-rank-tracking\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/","url":"https:\/\/blog.wellows.com\/llm-rank-tracking\/","name":"LLM Rank Tracking Explained: How to Measure AI Answers","isPartOf":{"@id":"https:\/\/blog.wellows.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#primaryimage"},"image":{"@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#primaryimage"},"thumbnailUrl":"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png","datePublished":"2026-09-28T11:00:30+00:00","dateModified":"2026-09-29T11:31:47+00:00","description":"LLM rank tracking shows if ChatGPT, Gemini and Google AI cite your brand or skip it. Learn the metrics and a checklist to start this week.","breadcrumb":{"@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/blog.wellows.com\/llm-rank-tracking\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#primaryimage","url":"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png","contentUrl":"https:\/\/wellows.com\/wp-content\/uploads\/2026\/09\/wellows-brand-visibility-overview-anon.png"},{"@type":"BreadcrumbList","@id":"https:\/\/blog.wellows.com\/llm-rank-tracking\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/blog.wellows.com\/"},{"@type":"ListItem","position":2,"name":"LLM Rank Tracking Explained: How to Measure Your Place in AI Answers (2026)"}]},{"@type":"WebSite","@id":"https:\/\/blog.wellows.com\/#website","url":"https:\/\/blog.wellows.com\/","name":"Wellows","description":"","publisher":{"@id":"https:\/\/blog.wellows.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/blog.wellows.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/blog.wellows.com\/#organization","name":"Wellows","alternateName":"Wellows","url":"https:\/\/blog.wellows.com\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/blog.wellows.com\/#\/schema\/logo\/image\/","url":"https:\/\/wellows.com\/wp-content\/uploads\/2025\/04\/wellows-logo.png","contentUrl":"https:\/\/wellows.com\/wp-content\/uploads\/2025\/04\/wellows-logo.png","width":324,"height":281,"caption":"Wellows"},"image":{"@id":"https:\/\/blog.wellows.com\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/blog.wellows.com\/#\/schema\/person\/e1ddaf0c402a88409c4f5c14c8034af7","name":"Sharmeen Saleem","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/blog.wellows.com\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/414a8a1495f026a5c1db213c04666cc3caeba765152a367352b3a7d97cb834b7?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/414a8a1495f026a5c1db213c04666cc3caeba765152a367352b3a7d97cb834b7?s=96&d=mm&r=g","caption":"Sharmeen Saleem"},"url":"https:\/\/wellows.com\/blog\/author\/sharmeen-saleem\/"}]}},"wellows_reading_time":24,"wellows_author":{"name":"Sharmeen Saleem","slug":"sharmeen-saleem","role":"","avatar":"","description":""},"wellows_next_index":"index","_links":{"self":[{"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/posts\/26384","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/users\/45"}],"replies":[{"embeddable":true,"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/comments?post=26384"}],"version-history":[{"count":16,"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/posts\/26384\/revisions"}],"predecessor-version":[{"id":26413,"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/posts\/26384\/revisions\/26413"}],"wp:attachment":[{"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/media?parent=26384"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/categories?post=26384"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wellows.com\/blog\/wp-json\/wp\/v2\/tags?post=26384"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}