{"slug":"OwkKJ8Q9w","url":"https://digiocular.com","query":"what does Digiocular do","score":66,"createdAt":"Wed Oct 14 2026 11:04:37 GMT+0000 (Coordinated Universal Time)","result":{"liveCheck":{"model":"claude-haiku-5-5","answer":"Digiocular is most likely the digital agency based in Manila, Philippines. It sells AI-driven web and marketing services to clients abroad, and it also builds its own software products.\n\n- **Services:** It designs and builds websites, custom web apps and AI automation, and runs full-stack digital marketing, for businesses worldwide. Its offerings include Social Media Management, Brand Launchpad, Performance Ads, Digital Content Creation, E-commerce, AEO/GEO, WhatsApp Marketing, Email Marketing, and Reputation Management.\n- **Clients:** Its site says it works with businesses in the US, UK, Europe, and India among them.\n- **In-house products:** It has built its own tools, including VectorCite, an AEO/GEO platform meant to get brands cited by AI assistants, and a lead-finder LMS for our clients & team. It also offers a free website audit at audit.digiocular.com that gives a free 60-second brand audit.\n\nNote that a separate open-source project called DigiOcular on GitHub is a Flutter app for eye-alignment tests and vision therapy. It is unrelated to the agency.","engine":"anthropic","status":"answered","analysis":{"outcome":"cited","matchedTerm":"digiocular","citedDomains":[{"own":true,"count":2,"domain":"digiocular.com"}],"ownCitations":["https://www.digiocular.com/blog","https://www.digiocular.com/"],"brandMentioned":true,"firstMentionAt":0},"checkedAt":"2026-10-14T11:04:28.955Z","citations":[{"url":"https://www.digiocular.com/blog","title":"Blog — Website, AEO/GEO & AI Automation Guides"},{"url":"https://www.digiocular.com/","title":"Digiocular"}],"retrieved":["https://www.digiocular.com/","https://www.digiocular.com/portfolio","https://en.wikipedia.org/wiki/Digiscoping","https://github.com/gyun-jin/DigiOcular","https://www.digiocular.com/blog","https://en.wikipedia.org/wiki/DIGIC","https://en.wikipedia.org/wiki/Ocular_(disambiguation)","https://en.wikipedia.org/wiki/DigiSync","https://www.mayoclinic.org/drugs-supplements/digoxin-oral-route/description/drg-20072646"],"engineLabel":"Claude"},"liveEngines":[],"rubric":{"overall":66,"summary":{"ok":34,"weak":2,"absent":11,"total":47},"categories":[{"category":"structure","score":89,"signals":[{"key":"json-ld-presence","category":"structure","label":"JSON-LD structured data","score":0.8,"severity":"ok","detail":"2 JSON-LD blocks found.","remedy":null},{"key":"json-ld-validity","category":"structure","label":"JSON-LD validity","score":1,"severity":"ok","detail":"2 of 2 JSON-LD blocks parse cleanly.","remedy":null},{"key":"json-ld-relevance","category":"structure","label":"Schema type matches query intent","score":1,"severity":"ok","detail":"Schema types include a informational-intent type (FAQPage).","remedy":null},{"key":"faq-schema","category":"structure","label":"FAQ / Q&A schema","score":1,"severity":"ok","detail":"FAQPage / QAPage schema present — directly cited by AI Overviews and Perplexity.","remedy":null},{"key":"h1-quality","category":"structure","label":"H1 quality","score":1,"severity":"ok","detail":"H1: \"A website thatwins customers.\" (29 chars).","remedy":null},{"key":"h2-coverage","category":"structure","label":"H2 subtopic coverage","score":1,"severity":"ok","detail":"8 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":null},{"key":"lists","category":"structure","label":"Lists (bulleted / numbered)","score":1,"severity":"ok","detail":"13 lists found.","remedy":null},{"key":"tables","category":"structure","label":"Comparison tables","score":0.5,"severity":"ok","detail":"No tables. 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GEO factor #1 for credibility-weighted citation."},{"key":"statistic-density","category":"authority","label":"Statistic density","score":1,"severity":"ok","detail":"80 numerical facts (~3.5 per 100 words).","remedy":null},{"key":"quotations","category":"authority","label":"Expert quotations","score":1,"severity":"ok","detail":"4 blockquotes + 0 long inline quotes.","remedy":null},{"key":"author-byline","category":"authority","label":"Author byline","score":0.6,"severity":"weak","detail":"Author byline only partially marked up.","remedy":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag."},{"key":"date-markup","category":"authority","label":"Publish + update date markup","score":0,"severity":"absent","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."},{"key":"freshness","category":"authority","label":"Content freshness","score":0,"severity":"absent","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\">`."},{"key":"technical-terms","category":"authority","label":"Technical / domain vocabulary","score":0.8995173321632296,"severity":"ok","detail":"369 multi-syllable words (~16.2% of total).","remedy":null}]},{"category":"content","score":66,"signals":[{"key":"direct-answer","category":"content","label":"Direct answer in the lead","score":0,"severity":"absent","detail":"0 of 4 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."},{"key":"query-coverage","category":"content","label":"Query-term coverage","score":1,"severity":"ok","detail":"100% of query terms appear somewhere on the page.","remedy":null},{"key":"entity-coverage","category":"content","label":"Named-entity coverage","score":1,"severity":"ok","detail":"154 distinct proper-noun entities mentioned.","remedy":null},{"key":"readability","category":"content","label":"Readability (Flesch Reading Ease)","score":0.8,"severity":"ok","detail":"Reading-ease score: 60.0 (target 60-70).","remedy":null},{"key":"length","category":"content","label":"Content depth","score":1,"severity":"ok","detail":"2279 words. 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Ahrefs's 75k-brand study measured YouTube as the SINGLE strongest correlation (0.737) with AI citation across ChatGPT, AI Mode, and AI Overviews."},{"key":"sub-query-coverage","category":"content","label":"Sub-query coverage","score":1,"severity":"ok","detail":"3/3 decomposed sub-questions addressed on the page.","remedy":null}]},{"category":"trust","score":100,"signals":[{"key":"https","category":"trust","label":"HTTPS","score":1,"severity":"ok","detail":"Page served over HTTPS.","remedy":null},{"key":"canonical","category":"trust","label":"Canonical URL","score":1,"severity":"ok","detail":"Canonical: https://www.digiocular.com","remedy":null},{"key":"viewport","category":"trust","label":"Mobile-friendly viewport","score":1,"severity":"ok","detail":"Viewport meta tag present.","remedy":null},{"key":"twitter-card","category":"trust","label":"Twitter Card","score":1,"severity":"ok","detail":"Twitter Card metadata present.","remedy":null},{"key":"meta-description","category":"trust","label":"Meta description","score":1,"severity":"ok","detail":"Meta description: 151 chars (target 50-160).","remedy":null},{"key":"ai-bot-access","category":"trust","label":"AI crawler access (robots.txt)","score":1,"severity":"ok","detail":"robots.txt lets every AI search and answer crawler fetch this page.","remedy":null},{"key":"llms-txt-presence","category":"trust","label":"llms.txt present at /llms.txt","score":1,"severity":"ok","detail":"/llms.txt found. Informational only — SE Ranking's study of ~300,000 domains (Nov 2025) found llms.txt doesn't affect how AI systems see or cite pages, so it carries no weight in this score.","remedy":null}]},{"category":"eeat","score":43,"signals":[{"key":"first-person","category":"eeat","label":"First-person language","score":1,"severity":"ok","detail":"62 first-person pronouns (2.7% of words). Target 0.5-3%.","remedy":null},{"key":"case-study-evidence","category":"eeat","label":"Case study / concrete examples","score":0.6666666666666666,"severity":"weak","detail":"2 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."},{"key":"author-credentials","category":"eeat","label":"Author bio with credentials","score":0,"severity":"absent","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)."},{"key":"byline-depth","category":"eeat","label":"Byline depth (link + reviewer + date)","score":0,"severity":"absent","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."},{"key":"brand-entity","category":"eeat","label":"Brand recognized as Wikidata entity","score":0,"severity":"absent","detail":"No Wikidata entry matched. 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External recognition is a top authority signal."},{"key":"privacy-terms","category":"eeat","label":"Privacy + Terms links","score":1,"severity":"ok","detail":"Privacy ✓, Terms ✓.","remedy":null},{"key":"contact-info","category":"eeat","label":"Contact information","score":0.8,"severity":"ok","detail":"email ✓, phone ✓, address ✗, contact link ✓","remedy":null}]}],"signals":[{"key":"json-ld-presence","category":"structure","label":"JSON-LD structured data","score":0.8,"severity":"ok","detail":"2 JSON-LD blocks found.","remedy":null},{"key":"json-ld-validity","category":"structure","label":"JSON-LD validity","score":1,"severity":"ok","detail":"2 of 2 JSON-LD blocks parse cleanly.","remedy":null},{"key":"json-ld-relevance","category":"structure","label":"Schema type matches query intent","score":1,"severity":"ok","detail":"Schema types include a informational-intent type (FAQPage).","remedy":null},{"key":"faq-schema","category":"structure","label":"FAQ / Q&A schema","score":1,"severity":"ok","detail":"FAQPage / QAPage schema present — directly cited by AI Overviews and Perplexity.","remedy":null},{"key":"h1-quality","category":"structure","label":"H1 quality","score":1,"severity":"ok","detail":"H1: \"A website thatwins customers.\" (29 chars).","remedy":null},{"key":"h2-coverage","category":"structure","label":"H2 subtopic coverage","score":1,"severity":"ok","detail":"8 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":null},{"key":"lists","category":"structure","label":"Lists (bulleted / numbered)","score":1,"severity":"ok","detail":"13 lists found.","remedy":null},{"key":"tables","category":"structure","label":"Comparison tables","score":0.5,"severity":"ok","detail":"No tables. 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Meso: 5.9 chunks/section avg. Micro: 0.00% visual emphasis.","remedy":null},{"key":"outbound-authority-links","category":"authority","label":"Outbound links to authoritative sources","score":0,"severity":"absent","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."},{"key":"citation-density","category":"authority","label":"Inline citations and attributions","score":0,"severity":"absent","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."},{"key":"statistic-density","category":"authority","label":"Statistic density","score":1,"severity":"ok","detail":"80 numerical facts (~3.5 per 100 words).","remedy":null},{"key":"quotations","category":"authority","label":"Expert quotations","score":1,"severity":"ok","detail":"4 blockquotes + 0 long inline quotes.","remedy":null},{"key":"author-byline","category":"authority","label":"Author byline","score":0.6,"severity":"weak","detail":"Author byline only partially marked up.","remedy":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag."},{"key":"date-markup","category":"authority","label":"Publish + update date markup","score":0,"severity":"absent","detail":"No structured publish date. 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The GEO paper measured this as the #2 citation-lift factor.","explainer":"0 links to authoritative domains (.edu, .gov, named sources)."},{"key":"citation-density","title":"Inline citations and attributions","kind":"structure","priority":"high","content":"Add inline citations ([1], [2]) or attribution phrases (\"according to X\"). GEO factor #1 for credibility-weighted citation.","explainer":"0 bracketed citations + 0 attribution phrases (per 200 words: 0%). Replace every [bracketed] value before publishing."},{"key":"author-byline","title":"Author byline","kind":"structure","priority":"medium","content":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag.","explainer":"Author byline only partially marked up."},{"key":"date-markup","title":"Publish + update date markup","kind":"structure","priority":"high","content":"Add `<time datetime=\"...\">` for published date AND a `<meta property=\"article:modified_time\">` for updates.","explainer":"No structured publish date. Freshness ranking can't be applied."},{"key":"freshness","title":"Content freshness","kind":"structure","priority":"high","content":"Add a parseable date — `<time datetime=\"2026-01-15\">` or `<meta property=\"article:modified_time\">`.","explainer":"No parseable date — engines treat undated content as stale."},{"key":"direct-answer","title":"Direct answer in the lead","kind":"copy","priority":"high","content":"Open the page with a direct, complete answer to the buyer query — engines extract their citation snippet from the lead paragraph.","explainer":"0 of 4 query terms appear in the first paragraph."}]},"comparisonPages":[{"url":"https://en.wikipedia.org/wiki/Digiscoping","title":"","rank":1},{"url":"https://github.com/gyun-jin/DigiOcular","title":"","rank":2},{"url":"https://en.wikipedia.org/wiki/DIGIC","title":"","rank":3},{"url":"https://en.wikipedia.org/wiki/Ocular_(disambiguation)","title":"","rank":4}]}}