vesremont.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. Brand recognized as Wikidata entity

   Fix 1 · E-E-A-T · +4 points

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

   Do this: 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.

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

2. Direct answer in the lead

   Fix 2 · Content · +3 points

   Now: 0 of 1 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

3. Outbound links to authoritative sources

   Fix 3 · 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

4. BLUF — answer in first 100 words

   Fix 4 · Content · +3 points

   Now: First 100 words cover 0/1 query terms.

   Do this: 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.

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

5. Query-term coverage

   Fix 5 · Content · +2 points

   Now: 0% of query terms appear somewhere on the page.

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

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