{"id":84,"date":"2026-04-22T09:16:03","date_gmt":"2026-04-22T14:16:03","guid":{"rendered":"https:\/\/tampawebtech.com\/news\/?p=84"},"modified":"2026-04-22T09:27:50","modified_gmt":"2026-04-22T14:27:50","slug":"the-two-aeo-lanes-why-perplexity-and-gemini-are-more-alike-than-different-2","status":"publish","type":"post","link":"https:\/\/tampawebtech.com\/news\/the-two-aeo-lanes-why-perplexity-and-gemini-are-more-alike-than-different-2\/","title":{"rendered":"The Two AEO Lanes: Why Perplexity and Gemini Are More Alike Than Different"},"content":{"rendered":"<p><!--\n  The Two AEO Lanes: Why Perplexity and Gemini Are More Alike Than Different\n  Tampa Web Technologies \u2014 TWT News\n  URL: \/twt-news\/two-aeo-lanes-perplexity-gemini-similar\/\n--><\/p>\n<p><!-- BLOCK 1: HERO --><\/p>\n\n\n<style>\r\n.twt-two-hero { background: #0b3d91; padding: 68px 48px; }\r\n.twt-two-hero__inner { max-width: 820px; margin: 0 auto; }\r\n.twt-two-hero__eyebrow {\r\n  display: inline-block; background: #f97316; color: #fff;\r\n  font-family: 'DM Sans', sans-serif; font-size: 12px; font-weight: 600;\r\n  letter-spacing: 0.08em; text-transform: uppercase;\r\n  padding: 4px 12px; border-radius: 4px; margin-bottom: 20px;\r\n}\r\n.twt-two-hero h1 {\r\n  font-family: 'DM Serif Display', serif; font-size: 44px; font-weight: 400;\r\n  color: #fff; line-height: 1.15; margin: 0 0 20px 0;\r\n}\r\n.twt-two-hero__sub {\r\n  font-family: 'DM Sans', sans-serif; font-size: 19px;\r\n  color: rgba(255,255,255,0.85); line-height: 1.6; margin: 0 0 24px 0;\r\n}\r\n.twt-two-hero__byline {\r\n  font-family: 'DM Sans', sans-serif; font-size: 13px;\r\n  color: rgba(255,255,255,0.55); border-top: 1px solid rgba(255,255,255,0.15);\r\n  padding-top: 16px; margin-top: 24px;\r\n  letter-spacing: 0.02em;\r\n}\r\n@media (max-width: 900px) { .twt-two-hero { padding: 56px 32px; } .twt-two-hero h1 { font-size: 34px; } }\r\n@media (max-width: 600px) { .twt-two-hero { padding: 48px 24px; } .twt-two-hero h1 { font-size: 28px; } .twt-two-hero__sub { font-size: 17px; } }\r\n<\/style>\r\n<div class=\"twt-two-hero\">\r\n  <div class=\"twt-two-hero__inner\">\r\n    <span class=\"twt-two-hero__eyebrow\">TWT News \u2014 AEO Analysis<\/span>\r\n    <h1>The Two AEO Lanes: Why Perplexity and Gemini Are More Alike Than Different<\/h1>\r\n    <p class=\"twt-two-hero__sub\">The industry talks about three AI engines as three separate playbooks. The data says otherwise. Perplexity and Gemini share roughly 80% of their citation philosophy. For most brands, the real AEO planning question is not three-way \u2014 it is two-way.<\/p>\r\n    <p class=\"twt-two-hero__byline\">Tampa Web Technologies \u00b7 AEO Research<\/p>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 2: LEAD --><\/p>\n\n\n<style>\r\n.twt-two-lead { background: #fff; padding: 56px 48px; }\r\n.twt-two-lead__inner { max-width: 720px; margin: 0 auto; }\r\n.twt-two-lead h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 28px; font-weight: 400;\r\n  color: #3232a4; margin: 0 0 20px 0;\r\n}\r\n.twt-two-lead p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 18px; color: #222;\r\n  line-height: 1.75; margin: 0 0 18px 0;\r\n}\r\n.twt-two-lead__dropcap {\r\n  font-family: 'DM Serif Display', serif; font-size: 56px;\r\n  color: #0b3d91; float: left; line-height: 0.9;\r\n  padding: 8px 10px 0 0; margin: 0;\r\n}\r\n@media (max-width: 600px) { .twt-two-lead { padding: 44px 24px; } .twt-two-lead p { font-size: 17px; } .twt-two-lead__dropcap { font-size: 44px; } }\r\n<\/style>\r\n<div class=\"twt-two-lead\">\r\n  <div class=\"twt-two-lead__inner\">\r\n    <p><span class=\"twt-two-lead__dropcap\">T<\/span>he standard framing of AI search optimization treats ChatGPT, Perplexity, and Gemini as three engines requiring three strategies. Run the numbers across a 547-citation dataset and the framing breaks down. Perplexity and Gemini are much closer to each other than either is to ChatGPT.<\/p>\r\n    <p>The practical implication: you do not need three AEO playbooks. You need two \u2014 one for ChatGPT, one that covers Perplexity and Gemini together with targeted calibration.<\/p>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 3: THE OVERLAP DATA --><\/p>\n\n\n<style>\r\n.twt-two-data { background: #f7f8f9; padding: 56px 48px; }\r\n.twt-two-data__inner { max-width: 820px; margin: 0 auto; }\r\n.twt-two-data h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 30px; font-weight: 400;\r\n  color: #3232a4; margin: 0 0 22px 0;\r\n}\r\n.twt-two-data p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 17px; color: #222;\r\n  line-height: 1.75; margin: 0 0 18px 0;\r\n}\r\n.twt-two-data__table {\r\n  background: #fff; border-radius: 6px; overflow: hidden;\r\n  margin: 24px 0; border: 1px solid #e5e7eb;\r\n  font-family: 'DM Sans', sans-serif; font-size: 14px;\r\n}\r\n.twt-two-data__table-row {\r\n  display: grid; grid-template-columns: 1.5fr 1fr 1fr 1fr;\r\n  padding: 12px 18px; border-bottom: 1px solid #f0f0f0;\r\n}\r\n.twt-two-data__table-row:last-child { border-bottom: none; }\r\n.twt-two-data__table-row--head {\r\n  background: #0b3d91; color: #fff; font-weight: 600;\r\n  text-transform: uppercase; font-size: 12px; letter-spacing: 0.05em;\r\n}\r\n.twt-two-data__table-row--head > div { color: #fff; }\r\n.twt-two-data__table-row--highlight { background: #fef3e8; }\r\n.twt-two-data__table-row > div:first-child { font-weight: 600; color: #0b3d91; }\r\n.twt-two-data__table-row--head > div:first-child { color: #fff; }\r\n@media (max-width: 600px) { .twt-two-data { padding: 44px 24px; } .twt-two-data h2 { font-size: 26px; } .twt-two-data__table { font-size: 13px; } .twt-two-data__table-row { padding: 10px 12px; } }\r\n<\/style>\r\n<div class=\"twt-two-data\">\r\n  <div class=\"twt-two-data__inner\">\r\n    <h2>Where the three engines actually land<\/h2>\r\n    <p>Across 547 citations in our study, the source type distribution shows the real pattern. Perplexity and Gemini cluster together. ChatGPT sits alone.<\/p>\r\n    <div class=\"twt-two-data__table\">\r\n      <div class=\"twt-two-data__table-row twt-two-data__table-row--head\">\r\n        <div>Source type<\/div><div>Perplexity<\/div><div>Gemini<\/div><div>ChatGPT<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>Brand \/ trade<\/div><div>76.3%<\/div><div>70.8%<\/div><div>95.0%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row twt-two-data__table-row--highlight\">\r\n        <div>YouTube<\/div><div>8.2%<\/div><div>14.3%<\/div><div>1.2%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>Social (FB \/ IG \/ X)<\/div><div>3.1%<\/div><div>4.2%<\/div><div>0%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>Financial aggregators<\/div><div>4.6%<\/div><div>1.2%<\/div><div>0%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>LinkedIn<\/div><div>2.6%<\/div><div>1.2%<\/div><div>0%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>Reddit \/ forums<\/div><div>2.1%<\/div><div>1.8%<\/div><div>1.2%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>PR wire<\/div><div>1.5%<\/div><div>1.8%<\/div><div>0%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>Retail marketplace<\/div><div>0%<\/div><div>2.4%<\/div><div>0%<\/div>\r\n      <\/div>\r\n      <div class=\"twt-two-data__table-row\">\r\n        <div>Google properties<\/div><div>0%<\/div><div>1.8%<\/div><div>0%<\/div>\r\n      <\/div>\r\n    <\/div>\r\n    <p>Every non-brand source type that appears meaningfully in the dataset appears in both Perplexity and Gemini. ChatGPT is the only engine that essentially ignores all of them.<\/p>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 4: WHAT THEY SHARE --><\/p>\n\n\n<style>\r\n.twt-two-share { background: #fff; padding: 56px 48px; }\r\n.twt-two-share__inner { max-width: 720px; margin: 0 auto; }\r\n.twt-two-share h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 30px; font-weight: 400;\r\n  color: #3232a4; margin: 0 0 22px 0;\r\n}\r\n.twt-two-share p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 17px; color: #222;\r\n  line-height: 1.75; margin: 0 0 18px 0;\r\n}\r\n.twt-two-share h3 {\r\n  font-family: 'DM Serif Display', serif; font-size: 22px;\r\n  color: #3232a4; margin: 28px 0 10px 0;\r\n}\r\n@media (max-width: 600px) { .twt-two-share { padding: 44px 24px; } .twt-two-share h2 { font-size: 26px; } }\r\n<\/style>\r\n<div class=\"twt-two-share\">\r\n  <div class=\"twt-two-share__inner\">\r\n    <h2>What Perplexity and Gemini share<\/h2>\r\n    <p>Three structural traits bind Perplexity and Gemini together and separate them from ChatGPT.<\/p>\r\n\r\n    <h3>1. Both reach outside brand domains at nearly double the rate<\/h3>\r\n    <p>Perplexity pulls 76.3% of its citations from brand and trade sources. Gemini pulls 70.8%. ChatGPT sits at 95%. That gap matters \u2014 it means roughly a quarter of Perplexity and Gemini&#8217;s citation surface is places ChatGPT rarely visits.<\/p>\r\n\r\n    <h3>2. Both accept structurally weaker pages<\/h3>\r\n    <p>Median Page Structure Score is 10 for Perplexity, 20 for Gemini, 60 for ChatGPT. Over half the pages cited by Perplexity and Gemini score 20 or below on structural quality. ChatGPT filters aggressively for structure; the other two do not.<\/p>\r\n    <p>What is happening: Perplexity and Gemini substitute platform authority for page structure. A YouTube video with weak metadata still gets cited if it is on topic. An Amazon product page with no schema still appears for product queries. The platform does the work the page cannot.<\/p>\r\n\r\n    <h3>3. They share 48 domains ChatGPT does not visit<\/h3>\r\n    <p>Looking at the overlap: 48 domains appear in both Perplexity and Gemini citations in our dataset. Of those, 28 are never cited by ChatGPT. LinkedIn, Yahoo Finance, Facebook, Instagram, PRNewswire, and the main retailer sites are all shared Perplexity-Gemini territory that ChatGPT essentially excludes.<\/p>\r\n    <p>If you are investing in LinkedIn company page depth, financial aggregator accuracy, or PR wire distribution, you are working the Perplexity-Gemini lane. None of those investments show up in ChatGPT&#8217;s citation pool.<\/p>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 5: WHERE THEY DIVERGE --><\/p>\n\n\n<style>\r\n.twt-two-diverge { background: #0b3d91; padding: 64px 48px; }\r\n.twt-two-diverge__inner { max-width: 820px; margin: 0 auto; }\r\n.twt-two-diverge h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 30px; font-weight: 400;\r\n  color: #fff; margin: 0 0 22px 0;\r\n}\r\n.twt-two-diverge p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 17px;\r\n  color: rgba(255,255,255,0.85); line-height: 1.75; margin: 0 0 18px 0;\r\n}\r\n.twt-two-diverge__split {\r\n  display: grid; grid-template-columns: 1fr 1fr; gap: 16px; margin: 24px 0;\r\n}\r\n.twt-two-diverge__col {\r\n  background: rgba(255,255,255,0.06); border-left: 3px solid #00b4d8;\r\n  padding: 22px 26px; border-radius: 0 6px 6px 0;\r\n}\r\n.twt-two-diverge__col h3 {\r\n  font-family: 'DM Serif Display', serif; font-size: 20px;\r\n  color: #fff; margin: 0 0 12px 0;\r\n}\r\n.twt-two-diverge__col p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 15px;\r\n  color: rgba(255,255,255,0.85); line-height: 1.7; margin: 0 0 10px 0;\r\n}\r\n.twt-two-diverge__col strong { color: #fff; }\r\n@media (max-width: 700px) { .twt-two-diverge__split { grid-template-columns: 1fr; } }\r\n@media (max-width: 600px) { .twt-two-diverge { padding: 48px 24px; } .twt-two-diverge h2 { font-size: 26px; } }\r\n<\/style>\r\n<div class=\"twt-two-diverge\">\r\n  <div class=\"twt-two-diverge__inner\">\r\n    <h2>Where Perplexity and Gemini split apart<\/h2>\r\n    <p>They are not identical. Three calibration differences matter when you are building out the shared lane.<\/p>\r\n    <div class=\"twt-two-diverge__split\">\r\n      <div class=\"twt-two-diverge__col\">\r\n        <h3>Gemini leans Google ecosystem<\/h3>\r\n        <p><strong>YouTube at 14.3%<\/strong> (vs Perplexity&#8217;s 8.2%). Amazon at 2.4% (vs 0% for Perplexity). Google.com properties at 1.8% (vs 0% for Perplexity).<\/p>\r\n        <p>If you are chasing Gemini and AI Overviews specifically, video production and Google Business Profile depth matter more than anywhere else.<\/p>\r\n      <\/div>\r\n      <div class=\"twt-two-diverge__col\">\r\n        <h3>Perplexity leans financial and community<\/h3>\r\n        <p><strong>Financial aggregators at 4.6%<\/strong> (vs Gemini&#8217;s 1.2%). LinkedIn at 2.6% (vs 1.2%). Reddit at 2.1% (vs 1.8%).<\/p>\r\n        <p>If you are chasing Perplexity specifically, Crunchbase and Yahoo Finance data accuracy plus active LinkedIn company pages do disproportionate work.<\/p>\r\n      <\/div>\r\n    <\/div>\r\n    <p>These are calibration dials, not separate strategies. The underlying playbook \u2014 platform presence, entity surface, content depth outside your own domain \u2014 is the same. What shifts is which platforms get the most investment.<\/p>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 6: THE TWO-LANE MODEL --><\/p>\n\n\n<style>\r\n.twt-two-lanes { background: #f7f8f9; padding: 64px 48px; }\r\n.twt-two-lanes__inner { max-width: 820px; margin: 0 auto; }\r\n.twt-two-lanes h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 30px; font-weight: 400;\r\n  color: #3232a4; margin: 0 0 22px 0;\r\n}\r\n.twt-two-lanes p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 17px; color: #222;\r\n  line-height: 1.75; margin: 0 0 18px 0;\r\n}\r\n.twt-two-lanes__lane {\r\n  background: #fff; padding: 28px 32px; margin: 16px 0;\r\n  border-radius: 8px; border-left: 4px solid #06d6a0;\r\n}\r\n.twt-two-lanes__lane h3 {\r\n  font-family: 'DM Serif Display', serif; font-size: 24px;\r\n  color: #0b3d91; margin: 0 0 14px 0;\r\n}\r\n.twt-two-lanes__lane p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 16px; color: #222;\r\n  line-height: 1.7; margin: 0 0 12px 0;\r\n}\r\n.twt-two-lanes__lane ul { margin: 8px 0 0 0; padding: 0; list-style: none; }\r\n.twt-two-lanes__lane li {\r\n  font-family: 'DM Sans', sans-serif; font-size: 15px; color: #222;\r\n  line-height: 1.6; padding: 6px 0 6px 22px; position: relative;\r\n}\r\n.twt-two-lanes__lane li:before {\r\n  content: \"\u2192\"; position: absolute; left: 0; color: #06d6a0; font-weight: 600;\r\n}\r\n.twt-two-lanes__lane strong { color: #0b3d91; }\r\n@media (max-width: 600px) { .twt-two-lanes { padding: 48px 24px; } .twt-two-lanes h2 { font-size: 26px; } .twt-two-lanes__lane { padding: 22px 24px; } }\r\n<\/style>\r\n<div class=\"twt-two-lanes\">\r\n  <div class=\"twt-two-lanes__inner\">\r\n    <h2>The two-lane AEO planning model<\/h2>\r\n    <p>Collapsing the three-engine framework into two parallel workstreams makes resource allocation cleaner.<\/p>\r\n\r\n    <div class=\"twt-two-lanes__lane\">\r\n      <h3>Lane 1: Your brand domain (ChatGPT leverage)<\/h3>\r\n      <p>Everything that lives on your own site. Page structure, schema markup, answer extraction, technical documentation, entity signaling. This is the lane where ChatGPT&#8217;s 95% brand-and-trade preference translates directly into citations.<\/p>\r\n      <p>Benefit spillover: high-PSS brand pages also appear in Gemini&#8217;s citation pool, since 20.5% of Gemini citations go to pages scoring 70+. Investment here is not wasted on the shared lane \u2014 but Perplexity rewards it less.<\/p>\r\n      <ul>\r\n        <li>Priority pages at PSS 70 or higher across five pillars<\/li>\r\n        <li>Organization schema with complete sameAs array<\/li>\r\n        <li>Declarative answer structure, not marketing copy<\/li>\r\n        <li>Technical documentation with specifications, not just benefits<\/li>\r\n        <li>Wikipedia or Wikidata presence where eligible<\/li>\r\n      <\/ul>\r\n    <\/div>\r\n\r\n    <div class=\"twt-two-lanes__lane\">\r\n      <h3>Lane 2: Platform and entity surface (Perplexity + Gemini shared leverage)<\/h3>\r\n      <p>Everything that lives off your site \u2014 on platforms AI engines trust as authorities. This is where the 48 shared Perplexity-Gemini domains sit. Investment here compounds across both engines with calibration for which matters more in your vertical.<\/p>\r\n      <ul>\r\n        <li><strong>YouTube channel<\/strong> with specific, captioned, technical content (Gemini-heavy)<\/li>\r\n        <li><strong>LinkedIn company page<\/strong> fully populated, not a stub (Perplexity-heavy)<\/li>\r\n        <li><strong>Financial aggregator accuracy<\/strong> \u2014 Crunchbase, Yahoo Finance, ZoomInfo (Perplexity-heavy)<\/li>\r\n        <li><strong>Google Business Profile<\/strong> complete for any local surface area (Gemini-heavy)<\/li>\r\n        <li><strong>Amazon product listings<\/strong> optimized if you sell products (Gemini only)<\/li>\r\n        <li><strong>PR wire distribution<\/strong> for real news events (shared)<\/li>\r\n        <li><strong>Reddit monitoring and legitimate participation<\/strong> (shared)<\/li>\r\n      <\/ul>\r\n    <\/div>\r\n\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 7: IMPLICATIONS --><\/p>\n\n\n<style>\r\n.twt-two-impl { background: #fff; padding: 56px 48px; }\r\n.twt-two-impl__inner { max-width: 720px; margin: 0 auto; }\r\n.twt-two-impl h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 30px; font-weight: 400;\r\n  color: #3232a4; margin: 0 0 22px 0;\r\n}\r\n.twt-two-impl p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 17px; color: #222;\r\n  line-height: 1.75; margin: 0 0 18px 0;\r\n}\r\n.twt-two-impl h3 {\r\n  font-family: 'DM Serif Display', serif; font-size: 21px;\r\n  color: #3232a4; margin: 28px 0 10px 0;\r\n}\r\n@media (max-width: 600px) { .twt-two-impl { padding: 44px 24px; } .twt-two-impl h2 { font-size: 26px; } }\r\n<\/style>\r\n<div class=\"twt-two-impl\">\r\n  <div class=\"twt-two-impl__inner\">\r\n    <h2>What this changes about AEO resource allocation<\/h2>\r\n\r\n    <h3>Single-engine strategies are even weaker than they looked<\/h3>\r\n    <p>The standard critique of single-engine AEO is that it covers only a third of citation surface. The two-lane framing makes this sharper. A brand optimizing only for ChatGPT is investing entirely in Lane 1. It is not just missing one engine \u2014 it is missing the entire shared lane that covers two engines simultaneously.<\/p>\r\n\r\n    <h3>Brand-domain-only AEO is the most common waste pattern<\/h3>\r\n    <p>We see this constantly: agencies sell Lane 1 work \u2014 schema audits, content structure improvements, Wikipedia efforts \u2014 then report AI visibility gains that only show up in ChatGPT. The Perplexity and Gemini citation data does not move because the brand has no YouTube presence, a stub LinkedIn page, stale Crunchbase data, and no PR wire activity. Half the problem is unaddressed.<\/p>\r\n\r\n    <h3>Lane 2 work is often cheaper and faster than Lane 1<\/h3>\r\n    <p>A complete LinkedIn company page takes an afternoon. Accurate Crunchbase data takes a morning. Google Business Profile completion is an hour of work for a business with the information on hand. Five captioned YouTube videos take a month, not a quarter. These are not seven-figure investments. For a brand with no Lane 2 presence, the first wins are fast and visible.<\/p>\r\n\r\n    <h3>Lane 1 still matters, just not alone<\/h3>\r\n    <p>This is not an argument against brand domain investment. ChatGPT citations carry real weight and the structural work to earn them remains the hardest and most durable AEO moat a brand can build. But a brand with excellent Lane 1 work and zero Lane 2 presence is visible on one engine and invisible on two. The two-lane model ensures neither side is orphaned.<\/p>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 8: CLUSTER LINKS --><\/p>\n\n\n<style>\r\n.twt-two-cluster { background: #3232a4; padding: 48px 48px; }\r\n.twt-two-cluster__inner { max-width: 820px; margin: 0 auto; }\r\n.twt-two-cluster h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 24px; font-weight: 400;\r\n  color: #fff; margin: 0 0 20px 0;\r\n}\r\n.twt-two-cluster__grid { display: grid; grid-template-columns: repeat(3, 1fr); gap: 12px; }\r\n.twt-two-cluster__card {\r\n  background: rgba(255,255,255,0.08); border-radius: 6px;\r\n  padding: 18px; text-decoration: none; color: inherit; display: block;\r\n  transition: background 200ms;\r\n}\r\n.twt-two-cluster__card:hover { background: rgba(255,255,255,0.14); }\r\n.twt-two-cluster__card h3 {\r\n  font-family: 'DM Serif Display', serif; font-size: 16px;\r\n  color: #fff; margin: 0 0 6px 0;\r\n}\r\n.twt-two-cluster__card p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 12px;\r\n  color: rgba(255,255,255,0.8); line-height: 1.5; margin: 0 0 8px 0;\r\n}\r\n.twt-two-cluster__link {\r\n  font-family: 'DM Sans', sans-serif; font-size: 11px;\r\n  color: #00b4d8; font-weight: 600;\r\n  text-transform: uppercase; letter-spacing: 0.06em;\r\n}\r\n@media (max-width: 900px) { .twt-two-cluster__grid { grid-template-columns: 1fr; } }\r\n@media (max-width: 600px) { .twt-two-cluster { padding: 40px 24px; } }\r\n<\/style>\r\n<div class=\"twt-two-cluster\">\r\n  <div class=\"twt-two-cluster__inner\">\r\n    <h2>Related analysis<\/h2>\r\n    <div class=\"twt-two-cluster__grid\">\r\n      <a href=\"\/ai-architecture\/how-to-dominate-all-three-ai-search-engines\/\" class=\"twt-two-cluster__card\">\r\n        <h3>The three-engine pillar<\/h3>\r\n        <p>The original framework comparing ChatGPT, Perplexity, and Gemini citation behavior.<\/p>\r\n        <span class=\"twt-two-cluster__link\">Read \u2192<\/span>\r\n      <\/a>\r\n      <a href=\"\/ai-architecture\/how-to-dominate-chatgpt-ai-search\/\" class=\"twt-two-cluster__card\">\r\n        <h3>Lane 1: Dominate ChatGPT<\/h3>\r\n        <p>Brand primary domain, PSS 70+, schema-rich pages. The full ChatGPT playbook.<\/p>\r\n        <span class=\"twt-two-cluster__link\">Read \u2192<\/span>\r\n      <\/a>\r\n      <a href=\"\/ai-architecture\/how-to-dominate-perplexity-ai-search\/\" class=\"twt-two-cluster__card\">\r\n        <h3>Lane 2 (Perplexity side)<\/h3>\r\n        <p>Five surfaces framework: YouTube, LinkedIn, financial aggregators, Reddit, Facebook.<\/p>\r\n        <span class=\"twt-two-cluster__link\">Read \u2192<\/span>\r\n      <\/a>\r\n      <a href=\"\/ai-architecture\/how-to-win-google-ai-overviews\/\" class=\"twt-two-cluster__card\">\r\n        <h3>Lane 2 (Gemini \/ AI Overviews side)<\/h3>\r\n        <p>YouTube dominance, Google Business Profile, Amazon, Google ecosystem preference.<\/p>\r\n        <span class=\"twt-two-cluster__link\">Read \u2192<\/span>\r\n      <\/a>\r\n      <a href=\"\/search-architecture\/the-85-earned-media-claim-is-wrong\/\" class=\"twt-two-cluster__card\">\r\n        <h3>The earned media myth<\/h3>\r\n        <p>Owned content dominates AI citations 4:1 across the full 547-citation dataset.<\/p>\r\n        <span class=\"twt-two-cluster__link\">Read \u2192<\/span>\r\n      <\/a>\r\n      <a href=\"\/ai-architecture\/how-carrier-owned-hvac-ai-visibility\/\" class=\"twt-two-cluster__card\">\r\n        <h3>Carrier HVAC case study<\/h3>\r\n        <p>How a single-event launch produced 43% owned citation share through two-domain architecture.<\/p>\r\n        <span class=\"twt-two-cluster__link\">Read \u2192<\/span>\r\n      <\/a>\r\n    <\/div>\r\n  <\/div>\r\n<\/div>\n\n\n<p><!-- BLOCK 9: CTA --><\/p>\n\n\n<style>\r\n.twt-two-cta { background: #0b3d91; padding: 52px 48px; text-align: center; }\r\n.twt-two-cta__inner { max-width: 600px; margin: 0 auto; }\r\n.twt-two-cta h2 {\r\n  font-family: 'DM Serif Display', serif; font-size: 26px; font-weight: 400;\r\n  color: #fff; margin: 0 0 14px 0;\r\n}\r\n.twt-two-cta p {\r\n  font-family: 'DM Sans', sans-serif; font-size: 16px;\r\n  color: rgba(255,255,255,0.85); line-height: 1.6; margin: 0 0 22px 0;\r\n}\r\n.twt-two-cta__btn {\r\n  display: inline-block; background: #f97316; color: #fff;\r\n  font-family: 'DM Sans', sans-serif; font-size: 15px; font-weight: 600;\r\n  padding: 13px 26px; border-radius: 6px; text-decoration: none;\r\n}\r\n.twt-two-cta__btn:hover { background: #ea6c0a; color: #fff; }\r\n@media (max-width: 600px) { .twt-two-cta { padding: 44px 24px; } .twt-two-cta h2 { font-size: 22px; } }\r\n<\/style>\r\n<div class=\"twt-two-cta\">\r\n  <div class=\"twt-two-cta__inner\">\r\n    <h2>Audit your two-lane coverage<\/h2>\r\n    <p>Tampa Web Technologies maps AEO investment across both lanes. Most brands are strong on one and thin on the other. We tell you which.<\/p>\r\n    <a href=\"\/contact\" class=\"twt-two-cta__btn\">Request a Two-Lane Audit<\/a>\r\n  <\/div>\r\n<\/div>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>TWT News \u2014 AEO Analysis The Two AEO Lanes: Why Perplexity and Gemini Are More Alike Than Different The industry talks about three AI engines as three separate playbooks. The data says otherwise. Perplexity and Gemini share roughly 80% of their citation philosophy. For most brands, the real AEO planning question is not three-way \u2014 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":83,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5,114,115,6,8,7],"tags":[],"class_list":["post-84","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-aeo","category-ai-news","category-analysis","category-geo","category-guides","category-seo"],"_links":{"self":[{"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/posts\/84","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/comments?post=84"}],"version-history":[{"count":1,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/posts\/84\/revisions"}],"predecessor-version":[{"id":90,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/posts\/84\/revisions\/90"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/media\/83"}],"wp:attachment":[{"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/media?parent=84"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/categories?post=84"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tampawebtech.com\/news\/wp-json\/wp\/v2\/tags?post=84"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}