Language Model Visibility: 4-Week Implementation Roadmap

In AI answers, visibility is binary — you are either cited or you are invisible — so “ranking” is no longer the goal; being selected is. This Google Sheets workbook operationalises Lesson 2.2 into a four-week plan that moves your content from invisible to frequently cited, with time estimates and a measurable target. Created by Beatrice Gamba for the AI Search & Agentic SEO course, it is built around one number: your citation rate.

The roadmap runs across four weeks totalling 36–50 hours, with an expected 15–25 percentage-point lift in citation rate. Week 1 establishes your baseline — build 10–20 representative queries, test them across ChatGPT, Claude, Perplexity and Gemini, and run an entity-clarity audit plus a competitive citation analysis. Week 2 executes the content changes — replace vague references with named entities, add plain-language equivalents to technical terms, source every factual claim with a date, and move key entities into the first 500 tokens. Week 3 implements schema.org JSON-LD across your top pages and validates it. Week 4 re-tests with the same query set so every gain is attributable. Task Details, Metrics Tracking and Resources & Tools tabs are included.

Use this for:
‧ Baselining and then measurably improving your citation rate across the major AI platforms
‧ Running a structured entity-clarity audit on your most important pages
‧ Converting technical copy into dual-register, extractable, well-sourced claims
‧ Planning and validating a schema.org JSON-LD rollout
‧ Tracking hours, tasks and metrics so improvements are attributable to specific changes

This is perfect for SEO and content teams who want a time-boxed, measurable programme for improving how often AI systems cite their content — not a list of tips, but a plan with a baseline, a target and a re-test.