CitationMapper Atom 1 — Gemini (AI Visibility & Prompt Competition Dataset)

CitationMapper™ – Gemini Channel (AI Visibility & Prompt Competition Dataset)

This record is part of the CitationMapper™ framework, the first dedicated platform for measuring brand visibility and prompt competition across large language models (LLMs). It specifically documents the Gemini channel pilot, analyzing which entities appear in Gemini’s responses and how citation sources influence visibility outcomes.

What this record provides

Documentation (README, OVERVIEW, PROCESS, ROADMAP) for the Gemini pilot.

Structured methodology for prompt testing, entity extraction, and competition scoring.

Supporting assets including diagrams, screenshots, and explainer video.

Pilot UTM tracking links for measuring referral traffic attributed to Gemini answers.

PurposeTo evaluate how brands can establish AI visibility inside Gemini, and to test whether structured publishing + UTM tracking can attribute traffic from LLM-generated answers into GA4.

ProvenanceDeposited by AIVO Mesh Lab (2025) as part of the Micro Content Atom (MAS 1.0) publishing stream. While this record is packaged as a micro-atom, the featured content is the CitationMapper™ Gemini channel pilot dataset.

Project Links

Website: https://citationmapper.org/

GitHub: https://github.com/pjsheals/CitationMapper

Hugging Face: https://huggingface.co/datasets/AIVOLab/citationmapper-atom01-gemini