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digiocular.com

Record 1sBOgqsi6 · Oct 14, 2026

for “best web design agency for small businesses”

This audit was run before live answers existed, so it has no observed verdict.

62/100 readiness

Good readiness, with closable gaps

How ready the page is to be cited, across 47 signals. Readiness, not a citation count.

Comparison not run. This audit ran without any competing pages to compare against, so there is no ranking to show.

The live answer

No live answer for this audit

This audit doesn't include a live answer from Claude. The score, comparison and fixes below are complete.

Run a fresh audit

How your page compares

No comparison pages were available for this audit.

Readiness, signal by signal

47 signals, each measured from the page itself: 31 pass, 6 weak, 10 missing. Open any signal for the detail and the fix. Every signal is documented in the rubric.

Structure

81/100
  • JSON-LD structured data80

    2 JSON-LD blocks found.

  • JSON-LD validity100

    2 of 2 JSON-LD blocks parse cleanly.

  • Schema type matches query intent40

    Schema types found (Organization, ProfessionalService, WebSite, WebPage, FAQPage) don't match a transactional buyer intent.

    Fix: Add a Product JSON-LD block: the highest-leverage schema type for a "best web design agency for small busines" query.

  • FAQ / Q&A schema100

    FAQPage / QAPage schema present: directly cited by AI Overviews and Perplexity.

  • H1 quality100

    H1: "A website thatwins customers." (29 chars).

  • H2 subtopic coverage100

    8 H2 headings: answer engines decompose a buyer query into subtopics and match each to an H2.

  • Lists (bulleted / numbered)100

    13 lists found.

  • Comparison tables20

    No tables. Comparison / specification tables are heavily cited for product and technical queries.

    Fix: Add a comparison table: engines cite tables nearly verbatim when answering compare/spec queries.

  • Image alt-text coverage92

    12 of 13 images have alt text (92%).

  • Open Graph metadata100

    Open Graph title, description, and image all present.

  • Internal linking quality70

    122 internal links (122 with descriptive anchors), 38 external.

  • Page weight + render-blocking71

    281 KB HTML, 1 blocking script(s), 2 blocking stylesheet(s), 6/13 images without lazy-load.

  • GEO-SFE structural depth (macro/meso/micro)80

    Macro: max heading depth H3 (H1=1, H2=8, H3=26, H4=0). Meso: 5.9 chunks/section avg. Micro: 0.00% visual emphasis.

Authority

44/100
  • Outbound links to authoritative sources0

    0 links to authoritative domains (.edu, .gov, named sources).

    Fix: Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.

  • Inline citations and attributions0

    0 bracketed citations + 0 attribution phrases (per 200 words: 0%).

    Fix: Add inline citations ([1], [2]) or attribution phrases ("according to X"). GEO factor #1 for credibility-weighted citation.

  • Statistic density100

    61 numerical facts (~3.0 per 100 words).

  • Expert quotations100

    4 blockquotes + 0 long inline quotes.

  • Author byline60

    Author byline only partially marked up.

    Fix: Add a visible author byline (a `<div class="byline">` or `[rel="author"]`) AND a `<meta name="author">` tag.

  • Publish + update date markup0

    No structured publish date. Freshness ranking can't be applied.

    Fix: Add `<time datetime="...">` for published date AND a `<meta property="article:modified_time">` for updates.

  • Content freshness0

    No parseable date: engines treat undated content as stale.

    Fix: Add a parseable date: `<time datetime="2026-01-15">` or `<meta property="article:modified_time">`.

  • Technical / domain vocabulary100

    442 multi-syllable words (~21.4% of total).

Content

64/100
  • Direct answer in the lead0

    0 of 7 query terms appear in the first paragraph.

    Fix: Open the page with a direct, complete answer to the buyer query: engines extract their citation snippet from the lead paragraph.

  • Query-term coverage71

    71% of query terms appear somewhere on the page.

  • Named-entity coverage100

    101 distinct proper-noun entities mentioned.

  • Readability (Flesch Reading Ease)50

    Reading-ease score: 48.6 (target 60-70).

    Fix: Page reads too academic: shorter sentences and simpler vocabulary lift citation rate by ~12% (GEO §4.3).

  • Content depth100

    2064 words. Target 300-2500: engines bias toward focused depth.

  • Information density100

    Unique-word ratio: 46.0% (target 40-60%).

  • Definitional sentences100

    7 definitional sentences.

  • BLUF — answer in first 100 words30

    First 100 words cover 3/7 query terms.

    Fix: 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.

  • Mega-page coverage (what/who/how/pricing)100

    4/4 facets covered (what ✓, who ✓, how ✓, pricing ✓).

  • YouTube video presence0

    No YouTube presence.

    Fix: 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.

  • Sub-query coverage100

    4/4 decomposed sub-questions addressed on the page.

Trust

100/100
  • HTTPS100

    Page served over HTTPS.

  • Canonical URL100

    Canonical: https://www.digiocular.com

  • Mobile-friendly viewport100

    Viewport meta tag present.

  • Twitter Card100

    Twitter Card metadata present.

  • Meta description100

    Meta description: 151 chars (target 50-160).

  • AI retrieval-bot access (robots.txt)100

    robots.txt allows all AI retrieval bots: your pages are eligible for citation.

  • llms.txt present at /llms.txt100

    /llms.txt found and non-empty: IDE agents (Cursor, Claude Code, Copilot, Windsurf) and Claude.ai will use it for retrieval.

E-E-A-T

36/100
  • First-person language70

    62 first-person pronouns (3.0% of words). Target 0.5-3%.

  • Case study / concrete examples33

    1 case-study patterns matched (examples, results, hands-on phrases).

    Fix: 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.

  • Author bio with credentials0

    No `.author-bio` / `[itemprop="author"]` element found.

    Fix: Add an author-bio section with the author's name, role, and credentials (degree, years of experience, certifications).

  • Byline depth (link + reviewer + date)0

    no linked byline, no reviewer, no date

    Fix: Strengthen the byline: link author name to an author profile page; add "reviewed by" / "edited by" markup; mark published + modified dates explicitly.

  • Brand recognized as Wikidata entity0

    No Wikidata entry matched. AI engines preferentially cite brands they recognize as knowledge-graph entities.

    Fix: Create a Wikidata entry for "digiocular" (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.

  • Press / media mentions0

    0 press-mention pattern(s) matched.

    Fix: Add a "Featured in" / "As seen in" strip listing publications that have covered you. External recognition is a top authority signal.

  • Privacy + Terms links100

    Privacy ✓, Terms ✓.

  • Contact information80

    email ✓, phone ✓, address ✗, contact link ✓

The Fix Kit

Good readiness, with closable gaps (62/100): 8 patches to close the gaps. Paste-ready patches, filled from what your page already states. Anything in [brackets] is yours to fill in before publishing.

Product JSON-LD

Schema markup · High priority

A Product schema is the strongest single AEO signal for a transactional query. Paste this in the <head>.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "A website thatwins customers.",
  "description": "Custom websites from $349 USD, built by Digiocular, an AI-native agency in Manila, Philippines, for businesses in India, the Philippines and worldwide.",
  "url": "https://digiocular.com",
  "brand": {
    "@type": "Brand",
    "name": "Digiocular"
  }
}
</script>

Organization JSON-LD

Schema markup · Medium priority

Organization schema gives the engine an E-E-A-T anchor: pages without one are treated as anonymous.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Digiocular",
  "url": "https://digiocular.com",
  "logo": "https://digiocular.com/logo.png",
  "sameAs": [
    "https://twitter.com/your-handle",
    "https://linkedin.com/company/your-org"
  ]
}
</script>

Comparison tables

Page structure · Medium priority

No tables. Comparison / specification tables are heavily cited for product and technical queries.

Add a comparison table: engines cite tables nearly verbatim when answering compare/spec queries.

Outbound links to authoritative sources

Page structure · High priority

0 links to authoritative domains (.edu, .gov, named sources).

Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.

Inline citations and attributions

Page structure · High priority

0 bracketed citations + 0 attribution phrases (per 200 words: 0%).

Add inline citations ([1], [2]) or attribution phrases ("according to X"). GEO factor #1 for credibility-weighted citation.

Author byline

Page structure · Medium priority

Author byline only partially marked up.

Add a visible author byline (a `<div class="byline">` or `[rel="author"]`) AND a `<meta name="author">` tag.

Publish + update date markup

Page structure · High priority

No structured publish date. Freshness ranking can't be applied.

Add `<time datetime="...">` for published date AND a `<meta property="article:modified_time">` for updates.

Content freshness

Page structure · High priority

No parseable date: engines treat undated content as stale.

Add a parseable date: `<time datetime="2026-01-15">` or `<meta property="article:modified_time">`.

Rather not ship these yourself?

The Digiocular team can make the changes and check the answer again with you.

See done-for-you

Close the gap, then check again.

The console re-checks the questions you track on a schedule, keeps the history, and tells you whether a fix moved the answer. Or run another free check now.

Re-check schedule

  1. Checked:62/100 readiness
  2. OpenRe-check after you ship the fixes

Audit by VectorCite · vectorcite.digiocular.com