digiocular.com

Ship these, in this order

Ranked by the points each fix adds to readiness, using the rubric’s own weights. Each card’s points assume the fixes above it are already done.

1. Direct answer in the lead

   Fix 1 · Content · +4 points

   Now: 0 of 8 query terms appear in the first paragraph.

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

   Effort: 2 to 4 hours · Signal score now 0/100

2. Outbound links to authoritative sources

   Fix 2 · Authority · +3 points

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

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

   Effort: 2 to 4 hours · Signal score now 0/100

3. Brand recognized as Wikidata entity

   Fix 3 · E-E-A-T · +3 points

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

   Do this: Create a Wikidata entry for "digiocular" (and a Wikipedia article when notable). Answer engines key off knowledge graph membership, so this is the single highest-leverage move for "is this a real, recognized brand?"

   Effort: 1 to 2 days · Signal score now 0/100

4. Inline citations and attributions

   Fix 4 · Authority · +3 points

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

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

   Effort: 2 to 4 hours · Signal score now 0/100

5. Content freshness

   Fix 5 · Authority · +3 points

   Now: No parseable date: engines treat undated content as stale.

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

   Effort: 2 to 4 hours · Signal score now 0/100