Skip to content

supabase.com

Record 1GUIsN57k · May 31, 2026

for “open source firebase alternative”

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

54/100 readiness

Readiness needs work

How ready the page is to be cited, across 30 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

30 signals, each measured from the page itself: 16 pass, 5 weak, 9 missing. Open any signal for the detail and the fix. This record was scored on an earlier, 30-signal version of the rubric; it has 47 signals today. Every signal is documented in the rubric.

Structure

73/100
  • JSON-LD structured data70

    1 JSON-LD block found.

  • JSON-LD validity100

    1 of 1 JSON-LD block parse cleanly.

  • Schema type matches query intent40

    Schema types found (Organization, WebSite) don't match a informational buyer intent.

    Fix: Add an Article JSON-LD block: the highest-leverage schema type for a "open source firebase alternative" query.

  • FAQ / Q&A schema0

    No FAQPage / QAPage schema: AI Overviews preferentially cite pages exposing structured Q&A.

    Fix: Add a FAQPage schema with 3-5 questions buyers actually ask. The single most direct path to AI Overview citation.

  • H1 quality100

    H1: "Build in a weekendScale to millions" (35 chars).

  • H2 subtopic coverage100

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

  • Lists (bulleted / numbered)100

    11 lists found.

  • Comparison tables50

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

  • Image alt-text coverage100

    185 of 185 images have alt text (100%).

  • Open Graph metadata100

    Open Graph title, description, and image all present.

Authority

20/100
  • 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 density47

    10 numerical facts (~0.5 per 100 words).

    Fix: Add concrete statistics with sources. AI engines preferentially cite paragraphs containing numbers: a GEO paper §4.1 finding.

  • Expert quotations0

    0 blockquotes + 0 long inline quotes.

    Fix: 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).

  • Author byline0

    No author byline. E-E-A-T penalises anonymous content.

    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

    504 multi-syllable words (~23.9% of total).

Content

53/100
  • Direct answer in the lead0

    0 of 4 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 coverage50

    50% of query terms appear somewhere on the page.

    Fix: Cover every term in the buyer query at least once. Missing terms make embeddings drift and competitor pages win retrieval.

  • Named-entity coverage100

    65 distinct proper-noun entities mentioned.

  • Readability (Flesch Reading Ease)20

    Reading-ease score: 39.7 (target 60-70).

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

  • Content depth100

    2106 words. Target 300-2500: engines bias toward focused depth.

  • Information density30

    Unique-word ratio: 21.0% (target 40-60%).

    Fix: High word repetition signals thin content: break out distinct subtopics.

  • Definitional sentences100

    10 definitional sentences.

Trust

100/100
  • HTTPS100

    Page served over HTTPS.

  • Canonical URL100

    Canonical: https://supabase.com/

  • Mobile-friendly viewport100

    Viewport meta tag present.

  • Twitter Card100

    Twitter Card metadata present.

  • Meta description100

    Meta description: 159 chars (target 50-160).

The Fix Kit

Readiness needs work (54/100): 9 structural patches needed. Paste-ready patches, filled from what your page already states. Anything in [brackets] is yours to fill in before publishing.

Article JSON-LD

Schema markup · High priority

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

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Build in a weekendScale to millions",
  "description": "Build production-grade applications with a Postgres database, Authentication, instant APIs, Realtime, Functions, Storage and Vector embeddings. Start for free.",
  "url": "https://supabase.com/",
  "datePublished": "2026-05-31",
  "author": {
    "@type": "Person",
    "name": "Add author name"
  },
  "publisher": {
    "@type": "Organization",
    "name": "Supabase",
    "logo": {
      "@type": "ImageObject",
      "url": "https://supabase.com/logo.png"
    }
  }
}
</script>

FAQPage JSON-LD

Schema markup · High priority

FAQPage is the single most-cited schema type by Google AI Overviews. Add 3-5 Q&A pairs covering what buyers ask.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Postgres Database?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add a 1-2 sentence answer here, mentioning the key entity / number / claim that buyers searching \"open source firebase alternative\" would expect."
      }
    },
    {
      "@type": "Question",
      "name": "What is Authentication?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add a 1-2 sentence answer here, mentioning the key entity / number / claim that buyers searching \"open source firebase alternative\" would expect."
      }
    },
    {
      "@type": "Question",
      "name": "What is Edge Functions?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add a 1-2 sentence answer here, mentioning the key entity / number / claim that buyers searching \"open source firebase alternative\" would expect."
      }
    },
    {
      "@type": "Question",
      "name": "What is Storage?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add a 1-2 sentence answer here, mentioning the key entity / number / claim that buyers searching \"open source firebase alternative\" would expect."
      }
    }
  ]
}
</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": "Supabase",
  "url": "https://supabase.com",
  "logo": "https://supabase.com/logo.png",
  "sameAs": [
    "https://twitter.com/your-handle",
    "https://linkedin.com/company/your-org"
  ]
}
</script>

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.

Statistic density

Page structure · Medium priority

10 numerical facts (~0.5 per 100 words).

Add concrete statistics with sources. AI engines preferentially cite paragraphs containing numbers: a GEO paper §4.1 finding.

Expert quotations

Page structure · High priority

0 blockquotes + 0 long inline quotes.

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).

Author byline

Page structure · High priority

No author byline. E-E-A-T penalises anonymous content.

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.

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:54/100 readiness
  2. OpenRe-check after you ship the fixes

Audit by VectorCite · vectorcite.digiocular.com