{"slug":"DZ89liPIV","url":"https://vesremont.com/","query":"bitrix","score":39,"createdAt":"Thu Sep 24 2026 22:09:47 GMT+0000 (Coordinated Universal Time)","result":{"fixKit":{"grouped":{"copy":[{"key":"h2-coverage","kind":"structure","title":"H2 subtopic coverage","content":"Break the page into at least 4 H2 sections, each answering one aspect of the buyer query. Engines surface specific H2s as citations.","priority":"high","explainer":"0 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2."},{"key":"lists","kind":"structure","title":"Lists (bulleted / numbered)","content":"Add 2-3 bulleted lists summarising key points. They're the single most-cited structural element in AI summaries.","priority":"high","explainer":"No lists — AI engines preferentially cite list items because they pack into answer summaries cleanly."},{"key":"internal-linking","kind":"structure","title":"Internal linking quality","content":"Rewrite generic anchor text (\"click here\", \"read more\") to descriptive phrases that include the target page's topic — anchors are direct citation context.","priority":"medium","explainer":"131 internal links (83 with descriptive anchors), 0 external."},{"key":"page-weight","kind":"structure","title":"Page weight + render-blocking","content":"Reduce page weight: trim HTML to <300 KB; add loading=\"lazy\" to images below the fold. Heavy pages get down-ranked in retrieval as a Core Web Vitals proxy.","priority":"medium","explainer":"363 KB HTML, 0 blocking script(s), 0 blocking stylesheet(s), 48/48 images without lazy-load."},{"key":"structural-depth","kind":"structure","title":"GEO-SFE structural depth (macro/meso/micro)","content":"Three-level structural depth (validated +17.3% citation lift, GEO-SFE arXiv:2603.29979): use H1→H2→H3 hierarchy, 5+ paragraphs/lists per H2 section, and 1-5% visual emphasis (bold/italic/code) to flag retrieval-worthy spans.","priority":"medium","explainer":"Macro: max heading depth H1 (H1=1, H2=0, H3=0, H4=0). Meso: 35.0 chunks/section avg. Micro: 0.00% visual emphasis."},{"key":"outbound-authority-links","kind":"structure","title":"Outbound links to authoritative sources","content":"Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.","priority":"high","explainer":"0 links to authoritative domains (.edu, .gov, named sources)."}],"schemas":[{"key":"primary-schema","kind":"schema-json-ld","title":"Article JSON-LD","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"Article\",\n  \"headline\": \"Товары для дома, ремонта, строительства и профессиональных задач\",\n  \"description\": \"Vesremont — интернет-гипермаркет для ремонта и дома: инструмент, электрика и свет, стройматериалы, крепёж, сантехника и другие категории. Оплата картой, СБП, наличными или по счёту с НДС; доставка и самовывоз.\",\n  \"url\": \"https://vesremont.com/\",\n  \"datePublished\": \"2026-09-24\",\n  \"author\": {\n    \"@type\": \"Person\",\n    \"name\": \"Add author name\"\n  },\n  \"publisher\": {\n    \"@type\": \"Organization\",\n    \"name\": \"Vesremont\",\n    \"logo\": {\n      \"@type\": \"ImageObject\",\n      \"url\": \"https://vesremont.com/logo.png\"\n    }\n  }\n}\n</script>","priority":"high","explainer":"A Article schema is the strongest single AEO signal for a informational query. Paste this in the <head>."},{"key":"faq-schema","kind":"schema-json-ld","title":"FAQPage JSON-LD","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is Denatonium?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Denatonium is an organic ion and one of the bitterest chemical compounds known, with bitterness thresholds of 0.05 ppm for the benzoate and 0.01 ppm for the saccharinate. Commercially, it is usually available in salts such as denatonium benzoate or as denatonium saccharinate (BIT\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Why does Denatonium matter?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"A 1-2 sentence explanation of the practical value or impact.\"\n      }\n    }\n  ]\n}\n</script>","priority":"high","explainer":"FAQPage is the single most-cited schema type by Google AI Overviews. Add 3-5 Q&A pairs covering what buyers ask."},{"key":"organization-schema","kind":"schema-json-ld","title":"Organization JSON-LD","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"Organization\",\n  \"name\": \"Vesremont\",\n  \"url\": \"https://vesremont.com\",\n  \"logo\": \"https://vesremont.com/logo.png\",\n  \"sameAs\": [\n    \"https://twitter.com/your-handle\",\n    \"https://linkedin.com/company/your-org\"\n  ]\n}\n</script>","priority":"medium","explainer":"Organization schema gives the engine an E-E-A-T anchor — pages without one are treated as anonymous."}],"metadata":[]},"patches":[{"key":"primary-schema","kind":"schema-json-ld","title":"Article JSON-LD","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"Article\",\n  \"headline\": \"Товары для дома, ремонта, строительства и профессиональных задач\",\n  \"description\": \"Vesremont — интернет-гипермаркет для ремонта и дома: инструмент, электрика и свет, стройматериалы, крепёж, сантехника и другие категории. Оплата картой, СБП, наличными или по счёту с НДС; доставка и самовывоз.\",\n  \"url\": \"https://vesremont.com/\",\n  \"datePublished\": \"2026-09-24\",\n  \"author\": {\n    \"@type\": \"Person\",\n    \"name\": \"Add author name\"\n  },\n  \"publisher\": {\n    \"@type\": \"Organization\",\n    \"name\": \"Vesremont\",\n    \"logo\": {\n      \"@type\": \"ImageObject\",\n      \"url\": \"https://vesremont.com/logo.png\"\n    }\n  }\n}\n</script>","priority":"high","explainer":"A Article schema is the strongest single AEO signal for a informational query. Paste this in the <head>."},{"key":"faq-schema","kind":"schema-json-ld","title":"FAQPage JSON-LD","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is Denatonium?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Denatonium is an organic ion and one of the bitterest chemical compounds known, with bitterness thresholds of 0.05 ppm for the benzoate and 0.01 ppm for the saccharinate. Commercially, it is usually available in salts such as denatonium benzoate or as denatonium saccharinate (BIT\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Why does Denatonium matter?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"A 1-2 sentence explanation of the practical value or impact.\"\n      }\n    }\n  ]\n}\n</script>","priority":"high","explainer":"FAQPage is the single most-cited schema type by Google AI Overviews. Add 3-5 Q&A pairs covering what buyers ask."},{"key":"organization-schema","kind":"schema-json-ld","title":"Organization JSON-LD","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"Organization\",\n  \"name\": \"Vesremont\",\n  \"url\": \"https://vesremont.com\",\n  \"logo\": \"https://vesremont.com/logo.png\",\n  \"sameAs\": [\n    \"https://twitter.com/your-handle\",\n    \"https://linkedin.com/company/your-org\"\n  ]\n}\n</script>","priority":"medium","explainer":"Organization schema gives the engine an E-E-A-T anchor — pages without one are treated as anonymous."},{"key":"h2-coverage","kind":"structure","title":"H2 subtopic coverage","content":"Break the page into at least 4 H2 sections, each answering one aspect of the buyer query. Engines surface specific H2s as citations.","priority":"high","explainer":"0 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2."},{"key":"lists","kind":"structure","title":"Lists (bulleted / numbered)","content":"Add 2-3 bulleted lists summarising key points. They're the single most-cited structural element in AI summaries.","priority":"high","explainer":"No lists — AI engines preferentially cite list items because they pack into answer summaries cleanly."},{"key":"internal-linking","kind":"structure","title":"Internal linking quality","content":"Rewrite generic anchor text (\"click here\", \"read more\") to descriptive phrases that include the target page's topic — anchors are direct citation context.","priority":"medium","explainer":"131 internal links (83 with descriptive anchors), 0 external."},{"key":"page-weight","kind":"structure","title":"Page weight + render-blocking","content":"Reduce page weight: trim HTML to <300 KB; add loading=\"lazy\" to images below the fold. Heavy pages get down-ranked in retrieval as a Core Web Vitals proxy.","priority":"medium","explainer":"363 KB HTML, 0 blocking script(s), 0 blocking stylesheet(s), 48/48 images without lazy-load."},{"key":"structural-depth","kind":"structure","title":"GEO-SFE structural depth (macro/meso/micro)","content":"Three-level structural depth (validated +17.3% citation lift, GEO-SFE arXiv:2603.29979): use H1→H2→H3 hierarchy, 5+ paragraphs/lists per H2 section, and 1-5% visual emphasis (bold/italic/code) to flag retrieval-worthy spans.","priority":"medium","explainer":"Macro: max heading depth H1 (H1=1, H2=0, H3=0, H4=0). Meso: 35.0 chunks/section avg. Micro: 0.00% visual emphasis."},{"key":"outbound-authority-links","kind":"structure","title":"Outbound links to authoritative sources","content":"Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.","priority":"high","explainer":"0 links to authoritative domains (.edu, .gov, named sources)."}],"headline":"Currently uncited (39/100) — 9 foundational patches required"},"rubric":{"overall":39,"signals":[{"key":"json-ld-presence","label":"JSON-LD structured data","score":0.7,"detail":"1 JSON-LD block found.","remedy":null,"weight":0.13,"category":"structure","severity":"weak"},{"key":"json-ld-validity","label":"JSON-LD validity","score":1,"detail":"1 of 1 JSON-LD block parse cleanly.","remedy":null,"weight":0.1,"category":"structure","severity":"ok"},{"key":"json-ld-relevance","label":"Schema type matches query intent","score":0.4,"detail":"Schema types found (WebSite, WebPage, ItemList, Organization, Store) don't match a informational buyer intent.","remedy":"Add a Article JSON-LD block — the highest-leverage schema type for a \"bitrix\" query.","weight":0.12,"category":"structure","severity":"weak"},{"key":"faq-schema","label":"FAQ / Q&A schema","score":0,"detail":"No FAQPage / QAPage schema — AI Overviews preferentially cite pages exposing structured Q&A.","remedy":"Add a FAQPage schema with 3-5 questions buyers actually ask. The single most direct path to AI Overview citation.","weight":0.1,"category":"structure","severity":"absent"},{"key":"h1-quality","label":"H1 quality","score":1,"detail":"H1: \"Товары для дома, ремонта, строительства и профессиональных з…\" (64 chars).","remedy":null,"weight":0.1,"category":"structure","severity":"ok"},{"key":"h2-coverage","label":"H2 subtopic coverage","score":0,"detail":"0 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":"Break the page into at least 4 H2 sections, each answering one aspect of the buyer query. Engines surface specific H2s as citations.","weight":0.09,"category":"structure","severity":"absent"},{"key":"lists","label":"Lists (bulleted / numbered)","score":0,"detail":"No lists — AI engines preferentially cite list items because they pack into answer summaries cleanly.","remedy":"Add 2-3 bulleted lists summarising key points. They're the single most-cited structural element in AI summaries.","weight":0.08,"category":"structure","severity":"absent"},{"key":"tables","label":"Comparison tables","score":0.5,"detail":"No tables. Comparison / specification tables are heavily cited for product and technical queries.","remedy":null,"weight":0.07,"category":"structure","severity":"ok"},{"key":"alt-text","label":"Image alt-text coverage","score":1,"detail":"48 of 48 images have alt text (100%).","remedy":null,"weight":0.05,"category":"structure","severity":"ok"},{"key":"open-graph","label":"Open Graph metadata","score":1,"detail":"Open Graph title, description, and image all present.","remedy":null,"weight":0.06,"category":"structure","severity":"ok"},{"key":"internal-linking","label":"Internal linking quality","score":0.5534351145038168,"detail":"131 internal links (83 with descriptive anchors), 0 external.","remedy":"Rewrite generic anchor text (\"click here\", \"read more\") to descriptive phrases that include the target page's topic — anchors are direct citation context.","weight":0.08,"category":"structure","severity":"weak"},{"key":"page-weight","label":"Page weight + render-blocking","score":0.6000000000000001,"detail":"363 KB HTML, 0 blocking script(s), 0 blocking stylesheet(s), 48/48 images without lazy-load.","remedy":"Reduce page weight: trim HTML to <300 KB; add loading=\"lazy\" to images below the fold. Heavy pages get down-ranked in retrieval as a Core Web Vitals proxy.","weight":0.06,"category":"structure","severity":"weak"},{"key":"structural-depth","label":"GEO-SFE structural depth (macro/meso/micro)","score":0.52,"detail":"Macro: max heading depth H1 (H1=1, H2=0, H3=0, H4=0). Meso: 35.0 chunks/section avg. Micro: 0.00% visual emphasis.","remedy":"Three-level structural depth (validated +17.3% citation lift, GEO-SFE arXiv:2603.29979): use H1→H2→H3 hierarchy, 5+ paragraphs/lists per H2 section, and 1-5% visual emphasis (bold/italic/code) to flag retrieval-worthy spans.","weight":0.1,"category":"structure","severity":"weak"},{"key":"outbound-authority-links","label":"Outbound links to authoritative sources","score":0,"detail":"0 links to authoritative domains (.edu, .gov, named sources).","remedy":"Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.","weight":0.16,"category":"authority","severity":"absent"},{"key":"citation-density","label":"Inline citations and attributions","score":0,"detail":"0 bracketed citations + 0 attribution phrases (per 200 words: 0%).","remedy":"Add inline citations ([1], [2]) or attribution phrases (\"according to X\"). GEO factor #1 for credibility-weighted citation.","weight":0.14,"category":"authority","severity":"absent"},{"key":"statistic-density","label":"Statistic density","score":1,"detail":"225 numerical facts (~23.7 per 100 words).","remedy":null,"weight":0.13,"category":"authority","severity":"ok"},{"key":"quotations","label":"Expert quotations","score":0,"detail":"0 blockquotes + 0 long inline quotes.","remedy":"Include at least one direct quote from a named expert, ideally in a <blockquote>. Quote-rich pages are 28% more likely to be cited (GEO paper).","weight":0.11,"category":"authority","severity":"absent"},{"key":"author-byline","label":"Author byline","score":0,"detail":"No author byline. E-E-A-T penalises anonymous content.","remedy":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag.","weight":0.1,"category":"authority","severity":"absent"},{"key":"date-markup","label":"Publish + update date markup","score":0,"detail":"No structured publish date. Freshness ranking can't be applied.","remedy":"Add `<time datetime=\"...\">` for published date AND a `<meta property=\"article:modified_time\">` for updates.","weight":0.09,"category":"authority","severity":"absent"},{"key":"freshness","label":"Content freshness","score":0,"detail":"No parseable date — engines treat undated content as stale.","remedy":"Add a parseable date — `<time datetime=\"2026-01-15\">` or `<meta property=\"article:modified_time\">`.","weight":0.13,"category":"authority","severity":"absent"},{"key":"technical-terms","label":"Technical / domain vocabulary","score":1,"detail":"228 multi-syllable words (~24.0% of total).","remedy":null,"weight":0.14,"category":"authority","severity":"ok"},{"key":"direct-answer","label":"Direct answer in the lead","score":0,"detail":"0 of 1 query terms appear in the first paragraph.","remedy":"Open the page with a direct, complete answer to the buyer query — engines extract their citation snippet from the lead paragraph.","weight":0.18,"category":"content","severity":"absent"},{"key":"query-coverage","label":"Query-term coverage","score":0,"detail":"0% of query terms appear somewhere on the page.","remedy":"Cover every term in the buyer query at least once. Missing terms make embeddings drift and competitor pages win retrieval.","weight":0.15,"category":"content","severity":"absent"},{"key":"entity-coverage","label":"Named-entity coverage","score":1,"detail":"16 distinct proper-noun entities mentioned.","remedy":null,"weight":0.14,"category":"content","severity":"ok"},{"key":"readability","label":"Readability (Flesch Reading Ease)","score":0.2,"detail":"Reading-ease score: 116.9 (target 60-70).","remedy":"Page reads too simple — engines down-rank content that lacks domain specificity. Add precise terminology.","weight":0.11,"category":"content","severity":"absent"},{"key":"length","label":"Content depth","score":1,"detail":"949 words. Target 300-2500 — engines bias toward focused depth.","remedy":null,"weight":0.1,"category":"content","severity":"ok"},{"key":"info-density","label":"Information density","score":1,"detail":"Unique-word ratio: 46.6% (target 40-60%).","remedy":null,"weight":0.1,"category":"content","severity":"ok"},{"key":"definitions","label":"Definitional sentences","score":0,"detail":"0 definitional sentences.","remedy":"Include definitional sentences (\"X is...\", \"X refers to...\"). Engines specifically extract definitions for AI Overview snippets.","weight":0.1,"category":"content","severity":"absent"},{"key":"bluf-answer","label":"BLUF — answer in first 100 words","score":0,"detail":"First 100 words cover 0/1 query terms.","remedy":"Put the answer in the FIRST 100 words — Perplexity's pipeline summarizes that exact span before reranking. \"BLUF\" (bottom-line-up-front) is the format that wins.","weight":0.16,"category":"content","severity":"absent"},{"key":"mega-page-coverage","label":"Mega-page coverage (what/who/how/pricing)","score":0,"detail":"0/4 facets covered (what ✗, who ✗, how ✗, pricing ✗).","remedy":"Cover what / who / how / pricing in the same URL. Chatoptic's 75k-page study found the top 4.8% of repeatedly-cited pages share this single-URL completeness.","weight":0.14,"category":"content","severity":"absent"},{"key":"youtube-embed","label":"YouTube video presence","score":0,"detail":"No YouTube presence.","remedy":"Embed (or link to) a YouTube video covering this topic. Ahrefs's 75k-brand study measured YouTube as the SINGLE strongest correlation (0.737) with AI citation across ChatGPT, AI Mode, and AI Overviews.","weight":0.13,"category":"content","severity":"absent"},{"key":"sub-query-coverage","label":"Sub-query coverage","score":0,"detail":"0/3 decomposed sub-questions addressed on the page.","remedy":"Cover the sub-questions buyers actually ask along with the seed query. Currently failing on: what is bitrix · how does bitrix work · bitrix alternatives","weight":0.13,"category":"content","severity":"absent"},{"key":"https","label":"HTTPS","score":1,"detail":"Page served over HTTPS.","remedy":null,"weight":0.25,"category":"trust","severity":"ok"},{"key":"canonical","label":"Canonical URL","score":1,"detail":"Canonical: https://vesremont.com/","remedy":null,"weight":0.15,"category":"trust","severity":"ok"},{"key":"viewport","label":"Mobile-friendly viewport","score":1,"detail":"Viewport meta tag present.","remedy":null,"weight":0.15,"category":"trust","severity":"ok"},{"key":"twitter-card","label":"Twitter Card","score":1,"detail":"Twitter Card metadata present.","remedy":null,"weight":0.1,"category":"trust","severity":"ok"},{"key":"meta-description","label":"Meta description","score":1,"detail":"Meta description: 209 chars (target 50-160).","remedy":null,"weight":0.35,"category":"trust","severity":"ok"},{"key":"ai-bot-access","label":"AI retrieval-bot access (robots.txt)","score":1,"detail":"robots.txt allows all AI retrieval bots — your pages are eligible for citation.","remedy":null,"weight":0.12,"category":"trust","severity":"ok"},{"key":"llms-txt-presence","label":"llms.txt present at /llms.txt","score":1,"detail":"/llms.txt found and non-empty — IDE agents (Cursor, Claude Code, Copilot, Windsurf) and Claude.ai will use it for retrieval.","remedy":null,"weight":0.08,"category":"trust","severity":"ok"},{"key":"first-person","label":"First-person language","score":0,"detail":"0 first-person pronouns (0.0% of words). Target 0.5-3%.","remedy":"Add first-person language showing lived experience — \"we\", \"our team\", \"I\". Google rates first-person as direct evidence of the new E-for-Experience EEAT pillar.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"case-study-evidence","label":"Case study / concrete examples","score":0,"detail":"0 case-study patterns matched (examples, results, hands-on phrases).","remedy":"Add at least 2-3 concrete examples or mini-case-studies. \"We helped X achieve Y\" beats abstract claims; AI engines preferentially cite pages with measurable outcomes.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"author-credentials","label":"Author bio with credentials","score":0,"detail":"No `.author-bio` / `[itemprop=\"author\"]` element found.","remedy":"Add an author-bio section with the author's name, role, and credentials (degree, years of experience, certifications).","weight":0.13,"category":"eeat","severity":"absent"},{"key":"byline-depth","label":"Byline depth (link + reviewer + date)","score":0,"detail":"no linked byline, no reviewer, no date","remedy":"Strengthen the byline: link author name to an author profile page; add \"reviewed by\" / \"edited by\" markup; mark published + modified dates explicitly.","weight":0.08,"category":"eeat","severity":"absent"},{"key":"brand-entity","label":"Brand recognized as Wikidata entity","score":0,"detail":"No Wikidata entry matched. AI engines preferentially cite brands they recognize as knowledge-graph entities.","remedy":"Create a Wikidata entry for \"vesremont\" (and a Wikipedia article when notable). The single highest-leverage move for \"is this a real, recognized brand?\" — answer engines key off knowledge graph membership.","weight":0.16,"category":"eeat","severity":"absent"},{"key":"press-mentions","label":"Press / media mentions","score":0,"detail":"0 press-mention pattern(s) matched.","remedy":"Add a \"Featured in\" / \"As seen in\" strip listing publications that have covered you. External recognition is a top authority signal.","weight":0.11,"category":"eeat","severity":"absent"},{"key":"privacy-terms","label":"Privacy + Terms links","score":0.5,"detail":"Privacy ✗, Terms ✓.","remedy":"Add Privacy Policy and Terms of Service links (typically in the footer). Their absence is a hard trust-floor signal — Google's quality raters down-rank pages that lack them.","weight":0.13,"category":"eeat","severity":"weak"},{"key":"contact-info","label":"Contact information","score":1,"detail":"email ✓, phone ✓, address ✓, contact link ✓","remedy":null,"weight":0.13,"category":"eeat","severity":"ok"}],"summary":{"ok":18,"weak":6,"total":47,"absent":23},"categories":[{"score":54,"signals":[{"key":"json-ld-presence","label":"JSON-LD structured data","score":0.7,"detail":"1 JSON-LD block found.","remedy":null,"weight":0.13,"category":"structure","severity":"weak"},{"key":"json-ld-validity","label":"JSON-LD validity","score":1,"detail":"1 of 1 JSON-LD block parse cleanly.","remedy":null,"weight":0.1,"category":"structure","severity":"ok"},{"key":"json-ld-relevance","label":"Schema type matches query intent","score":0.4,"detail":"Schema types found (WebSite, WebPage, ItemList, Organization, Store) don't match a informational buyer intent.","remedy":"Add a Article JSON-LD block — the highest-leverage schema type for a \"bitrix\" query.","weight":0.12,"category":"structure","severity":"weak"},{"key":"faq-schema","label":"FAQ / Q&A schema","score":0,"detail":"No FAQPage / QAPage schema — AI Overviews preferentially cite pages exposing structured Q&A.","remedy":"Add a FAQPage schema with 3-5 questions buyers actually ask. The single most direct path to AI Overview citation.","weight":0.1,"category":"structure","severity":"absent"},{"key":"h1-quality","label":"H1 quality","score":1,"detail":"H1: \"Товары для дома, ремонта, строительства и профессиональных з…\" (64 chars).","remedy":null,"weight":0.1,"category":"structure","severity":"ok"},{"key":"h2-coverage","label":"H2 subtopic coverage","score":0,"detail":"0 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":"Break the page into at least 4 H2 sections, each answering one aspect of the buyer query. Engines surface specific H2s as citations.","weight":0.09,"category":"structure","severity":"absent"},{"key":"lists","label":"Lists (bulleted / numbered)","score":0,"detail":"No lists — AI engines preferentially cite list items because they pack into answer summaries cleanly.","remedy":"Add 2-3 bulleted lists summarising key points. They're the single most-cited structural element in AI summaries.","weight":0.08,"category":"structure","severity":"absent"},{"key":"tables","label":"Comparison tables","score":0.5,"detail":"No tables. Comparison / specification tables are heavily cited for product and technical queries.","remedy":null,"weight":0.07,"category":"structure","severity":"ok"},{"key":"alt-text","label":"Image alt-text coverage","score":1,"detail":"48 of 48 images have alt text (100%).","remedy":null,"weight":0.05,"category":"structure","severity":"ok"},{"key":"open-graph","label":"Open Graph metadata","score":1,"detail":"Open Graph title, description, and image all present.","remedy":null,"weight":0.06,"category":"structure","severity":"ok"},{"key":"internal-linking","label":"Internal linking quality","score":0.5534351145038168,"detail":"131 internal links (83 with descriptive anchors), 0 external.","remedy":"Rewrite generic anchor text (\"click here\", \"read more\") to descriptive phrases that include the target page's topic — anchors are direct citation context.","weight":0.08,"category":"structure","severity":"weak"},{"key":"page-weight","label":"Page weight + render-blocking","score":0.6000000000000001,"detail":"363 KB HTML, 0 blocking script(s), 0 blocking stylesheet(s), 48/48 images without lazy-load.","remedy":"Reduce page weight: trim HTML to <300 KB; add loading=\"lazy\" to images below the fold. Heavy pages get down-ranked in retrieval as a Core Web Vitals proxy.","weight":0.06,"category":"structure","severity":"weak"},{"key":"structural-depth","label":"GEO-SFE structural depth (macro/meso/micro)","score":0.52,"detail":"Macro: max heading depth H1 (H1=1, H2=0, H3=0, H4=0). Meso: 35.0 chunks/section avg. Micro: 0.00% visual emphasis.","remedy":"Three-level structural depth (validated +17.3% citation lift, GEO-SFE arXiv:2603.29979): use H1→H2→H3 hierarchy, 5+ paragraphs/lists per H2 section, and 1-5% visual emphasis (bold/italic/code) to flag retrieval-worthy spans.","weight":0.1,"category":"structure","severity":"weak"}],"category":"structure"},{"score":27,"signals":[{"key":"outbound-authority-links","label":"Outbound links to authoritative sources","score":0,"detail":"0 links to authoritative domains (.edu, .gov, named sources).","remedy":"Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.","weight":0.16,"category":"authority","severity":"absent"},{"key":"citation-density","label":"Inline citations and attributions","score":0,"detail":"0 bracketed citations + 0 attribution phrases (per 200 words: 0%).","remedy":"Add inline citations ([1], [2]) or attribution phrases (\"according to X\"). GEO factor #1 for credibility-weighted citation.","weight":0.14,"category":"authority","severity":"absent"},{"key":"statistic-density","label":"Statistic density","score":1,"detail":"225 numerical facts (~23.7 per 100 words).","remedy":null,"weight":0.13,"category":"authority","severity":"ok"},{"key":"quotations","label":"Expert quotations","score":0,"detail":"0 blockquotes + 0 long inline quotes.","remedy":"Include at least one direct quote from a named expert, ideally in a <blockquote>. Quote-rich pages are 28% more likely to be cited (GEO paper).","weight":0.11,"category":"authority","severity":"absent"},{"key":"author-byline","label":"Author byline","score":0,"detail":"No author byline. E-E-A-T penalises anonymous content.","remedy":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag.","weight":0.1,"category":"authority","severity":"absent"},{"key":"date-markup","label":"Publish + update date markup","score":0,"detail":"No structured publish date. Freshness ranking can't be applied.","remedy":"Add `<time datetime=\"...\">` for published date AND a `<meta property=\"article:modified_time\">` for updates.","weight":0.09,"category":"authority","severity":"absent"},{"key":"freshness","label":"Content freshness","score":0,"detail":"No parseable date — engines treat undated content as stale.","remedy":"Add a parseable date — `<time datetime=\"2026-01-15\">` or `<meta property=\"article:modified_time\">`.","weight":0.13,"category":"authority","severity":"absent"},{"key":"technical-terms","label":"Technical / domain vocabulary","score":1,"detail":"228 multi-syllable words (~24.0% of total).","remedy":null,"weight":0.14,"category":"authority","severity":"ok"}],"category":"authority"},{"score":25,"signals":[{"key":"direct-answer","label":"Direct answer in the lead","score":0,"detail":"0 of 1 query terms appear in the first paragraph.","remedy":"Open the page with a direct, complete answer to the buyer query — engines extract their citation snippet from the lead paragraph.","weight":0.18,"category":"content","severity":"absent"},{"key":"query-coverage","label":"Query-term coverage","score":0,"detail":"0% of query terms appear somewhere on the page.","remedy":"Cover every term in the buyer query at least once. Missing terms make embeddings drift and competitor pages win retrieval.","weight":0.15,"category":"content","severity":"absent"},{"key":"entity-coverage","label":"Named-entity coverage","score":1,"detail":"16 distinct proper-noun entities mentioned.","remedy":null,"weight":0.14,"category":"content","severity":"ok"},{"key":"readability","label":"Readability (Flesch Reading Ease)","score":0.2,"detail":"Reading-ease score: 116.9 (target 60-70).","remedy":"Page reads too simple — engines down-rank content that lacks domain specificity. Add precise terminology.","weight":0.11,"category":"content","severity":"absent"},{"key":"length","label":"Content depth","score":1,"detail":"949 words. Target 300-2500 — engines bias toward focused depth.","remedy":null,"weight":0.1,"category":"content","severity":"ok"},{"key":"info-density","label":"Information density","score":1,"detail":"Unique-word ratio: 46.6% (target 40-60%).","remedy":null,"weight":0.1,"category":"content","severity":"ok"},{"key":"definitions","label":"Definitional sentences","score":0,"detail":"0 definitional sentences.","remedy":"Include definitional sentences (\"X is...\", \"X refers to...\"). Engines specifically extract definitions for AI Overview snippets.","weight":0.1,"category":"content","severity":"absent"},{"key":"bluf-answer","label":"BLUF — answer in first 100 words","score":0,"detail":"First 100 words cover 0/1 query terms.","remedy":"Put the answer in the FIRST 100 words — Perplexity's pipeline summarizes that exact span before reranking. \"BLUF\" (bottom-line-up-front) is the format that wins.","weight":0.16,"category":"content","severity":"absent"},{"key":"mega-page-coverage","label":"Mega-page coverage (what/who/how/pricing)","score":0,"detail":"0/4 facets covered (what ✗, who ✗, how ✗, pricing ✗).","remedy":"Cover what / who / how / pricing in the same URL. Chatoptic's 75k-page study found the top 4.8% of repeatedly-cited pages share this single-URL completeness.","weight":0.14,"category":"content","severity":"absent"},{"key":"youtube-embed","label":"YouTube video presence","score":0,"detail":"No YouTube presence.","remedy":"Embed (or link to) a YouTube video covering this topic. Ahrefs's 75k-brand study measured YouTube as the SINGLE strongest correlation (0.737) with AI citation across ChatGPT, AI Mode, and AI Overviews.","weight":0.13,"category":"content","severity":"absent"},{"key":"sub-query-coverage","label":"Sub-query coverage","score":0,"detail":"0/3 decomposed sub-questions addressed on the page.","remedy":"Cover the sub-questions buyers actually ask along with the seed query. Currently failing on: what is bitrix · how does bitrix work · bitrix alternatives","weight":0.13,"category":"content","severity":"absent"}],"category":"content"},{"score":100,"signals":[{"key":"https","label":"HTTPS","score":1,"detail":"Page served over HTTPS.","remedy":null,"weight":0.25,"category":"trust","severity":"ok"},{"key":"canonical","label":"Canonical URL","score":1,"detail":"Canonical: https://vesremont.com/","remedy":null,"weight":0.15,"category":"trust","severity":"ok"},{"key":"viewport","label":"Mobile-friendly viewport","score":1,"detail":"Viewport meta tag present.","remedy":null,"weight":0.15,"category":"trust","severity":"ok"},{"key":"twitter-card","label":"Twitter Card","score":1,"detail":"Twitter Card metadata present.","remedy":null,"weight":0.1,"category":"trust","severity":"ok"},{"key":"meta-description","label":"Meta description","score":1,"detail":"Meta description: 209 chars (target 50-160).","remedy":null,"weight":0.35,"category":"trust","severity":"ok"},{"key":"ai-bot-access","label":"AI retrieval-bot access (robots.txt)","score":1,"detail":"robots.txt allows all AI retrieval bots — your pages are eligible for citation.","remedy":null,"weight":0.12,"category":"trust","severity":"ok"},{"key":"llms-txt-presence","label":"llms.txt present at /llms.txt","score":1,"detail":"/llms.txt found and non-empty — IDE agents (Cursor, Claude Code, Copilot, Windsurf) and Claude.ai will use it for retrieval.","remedy":null,"weight":0.08,"category":"trust","severity":"ok"}],"category":"trust"},{"score":21,"signals":[{"key":"first-person","label":"First-person language","score":0,"detail":"0 first-person pronouns (0.0% of words). Target 0.5-3%.","remedy":"Add first-person language showing lived experience — \"we\", \"our team\", \"I\". Google rates first-person as direct evidence of the new E-for-Experience EEAT pillar.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"case-study-evidence","label":"Case study / concrete examples","score":0,"detail":"0 case-study patterns matched (examples, results, hands-on phrases).","remedy":"Add at least 2-3 concrete examples or mini-case-studies. \"We helped X achieve Y\" beats abstract claims; AI engines preferentially cite pages with measurable outcomes.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"author-credentials","label":"Author bio with credentials","score":0,"detail":"No `.author-bio` / `[itemprop=\"author\"]` element found.","remedy":"Add an author-bio section with the author's name, role, and credentials (degree, years of experience, certifications).","weight":0.13,"category":"eeat","severity":"absent"},{"key":"byline-depth","label":"Byline depth (link + reviewer + date)","score":0,"detail":"no linked byline, no reviewer, no date","remedy":"Strengthen the byline: link author name to an author profile page; add \"reviewed by\" / \"edited by\" markup; mark published + modified dates explicitly.","weight":0.08,"category":"eeat","severity":"absent"},{"key":"brand-entity","label":"Brand recognized as Wikidata entity","score":0,"detail":"No Wikidata entry matched. AI engines preferentially cite brands they recognize as knowledge-graph entities.","remedy":"Create a Wikidata entry for \"vesremont\" (and a Wikipedia article when notable). The single highest-leverage move for \"is this a real, recognized brand?\" — answer engines key off knowledge graph membership.","weight":0.16,"category":"eeat","severity":"absent"},{"key":"press-mentions","label":"Press / media mentions","score":0,"detail":"0 press-mention pattern(s) matched.","remedy":"Add a \"Featured in\" / \"As seen in\" strip listing publications that have covered you. External recognition is a top authority signal.","weight":0.11,"category":"eeat","severity":"absent"},{"key":"privacy-terms","label":"Privacy + Terms links","score":0.5,"detail":"Privacy ✗, Terms ✓.","remedy":"Add Privacy Policy and Terms of Service links (typically in the footer). Their absence is a hard trust-floor signal — Google's quality raters down-rank pages that lack them.","weight":0.13,"category":"eeat","severity":"weak"},{"key":"contact-info","label":"Contact information","score":1,"detail":"email ✓, phone ✓, address ✓, contact link ✓","remedy":null,"weight":0.13,"category":"eeat","severity":"ok"}],"category":"eeat"}]},"diagnostics":{"serp":{"ddg":false,"wikipedia":false},"embeddingsLoaded":false,"competitorsFetched":0},"serpContext":{"query":"bitrix","results":[],"degraded":{"ddg":false,"wikipedia":false},"entities":[{"qid":"Q414815","url":"https://en.wikipedia.org/wiki/Denatonium","title":"Denatonium","description":"Denatonium is an organic ion and one of the bitterest chemical compounds known, with bitterness thresholds of 0.05 ppm for the benzoate and 0.01 ppm for the saccharinate. Commercially, it is usually available in salts such as denatonium benzoate or as denatonium saccharinate (BIT"},{"qid":"Q30378","url":"https://en.wikipedia.org/wiki/Kamaz","title":"Kamaz","description":"KAMAZ is a Russian manufacturer of trucks, buses, and engines headquartered in Naberezhnye Chelny."},{"qid":"Q48988733","url":"https://en.wikipedia.org/wiki/Stroygazmontazh","title":"Stroygazmontazh","description":"Stroygazmontazh, also called the S.G.M. Group, is an infrastructure construction firm that operates in Russia primarily via its subsidiaries, specializing in the creation of oil and gas transportation systems. The company was founded in 2008 with operations in construction—partic"}]},"semanticVoid":[],"centroidShift":null,"citationVerdict":{"rank":null,"cited":false,"cohort":0,"margin":0},"retrievalRanking":[]}}