CitationMapper Process
🔍 Step 1 — Enter a Target Prompt
Users begin by entering a target prompt into CitationMapper.
Examples:
- “Best AI visibility tools”
- “Which competitors show up in ChatGPT for [industry]?”
- “How difficult is it to rank for ‘top AI marketing platforms’?”
This prompt becomes the starting point for visibility analysis.
🏷 Step 2 — Search Tier 1 Sources
CitationMapper queries trusted Tier 1 platforms where LLMs draw their knowledge from, including:
- Wikidata
- Hugging Face
- Zenodo
- Medium
- GitHub
The system checks which entities are associated with the entered prompt.
🌐 Step 3 — Entity Extraction
From these results, CitationMapper identifies the entities that currently hold visibility for the prompt.
- Entities may be tools, companies, datasets, or publications.
- Each entity is logged exactly as it appears on the source platform.
📊 Step 4 — Competition Scoring
CitationMapper calculates a Prompt Visibility Competition Score (PVCS™), based on:
- How many entities are linked to the prompt.
- Presence across multiple Tier 1 sources.
- Relative strength of those sources.
This shows how hard it is to rank for the chosen phrase.
📝 Step 5 — Prompt Listing
CitationMapper then generates a structured list of prompts, including:
- Short-tail, medium-tail, and long-tail variations.
- Which entities currently occupy visibility space.
- Opportunities where competition is weaker (quick wins).
📂 Step 6 — Dashboard Storage
All tested prompts and results are stored in the user’s personal CitationMapper dashboard, making it easy to:
- Track changes over time.
- Compare different prompts.
- Identify new opportunities to improve AI visibility.
Figure 3. CitationMapper workflow — user inserts a target prompt; CitationMapper searches Tier-1 sources, extracts entities, calculates a competition score, lists prompt variants, and stores all results in the dashboard.
Explore CitationMapper: bit.ly/cm-atom1-chatgpt
Provenance
Deposited by AIVO Mesh Lab (2025). This record is part of a structured publishing pilot.