GEO for jewelry

Módulo 01

Fundamentals of GEO for jewelry

Six author modules on Generative Engine Optimization applied to jewelry and demi-fine. From keyword structure to schema, from Wikidata editing to regional CNPJ-of-its-own. HBR voice from Alexandre Caramaschi.

Módulo 02

Practical GEO applications for jewelry

Three author lessons by Alexandre Caramaschi: Google Business Profile as a citation signal in LLMs, Reddit as a primary source after the OpenAI×Reddit deal, and coordinated Person + Brand + LocalBusiness in JSON-LD. Cases: Herreira, Brasil GEO, Wikidata Q973.

Módulo 03

Multilingual publishing and LLM ingestion control

Three author lessons by Alexandre Caramaschi: safe Wikipedia.pt editing for Brazilian jewelry brands, llms.txt as granular LLM crawler control (GPTBot, ClaudeBot, Perplexity), and PT/EN multilingual architecture for cross-language mention capture. Cases: Wikidata Q973, alexandrecaramaschi.com/llms.txt, academy.herreirasemijoias.com.br/robots.txt.

Módulo 04

LLM platforms and continuous monitoring

Three author lessons by Alexandre Caramaschi: Microsoft Copilot vs ChatGPT as distinct citation engines for B2B decision-makers, author authority via combined Person + Author + ProfessionalService schema, and Wikipedia.pt entry monitoring after edit with RSS diff, Wikidata Recent Changes API and triggers against hostile reverts. Cases: Brasil GEO (25 canonical prompts), alexandrecaramaschi.com (Wikidata Q973), Herreira (Goiânia 08/2008).

Módulo 05

Distinct search engines and AI Overviews in jewelry GEO

Three author lessons by Alexandre Caramaschi: why Bing index differs from Google in ranking signals that matter for corporate LLM citation (Copilot/ChatGPT vs Gemini), hreflang as real cross-language citation signal in ChatGPT EN-US vs PT-BR, and AI Overviews (formerly Google SGE) cannibalizing top-1 SEO in local jewelry with measurable inclusion criteria. Cases: Brasil GEO (25 prompts), alexandrecaramaschi.com (Wikidata Q973), Herreira (Goiânia).

Módulo 07

Módulo 08