Geometric mean of LBA, Authority and TOM. Penalises any single weak metric.
What the model believes about Apple Notes without web search.
Frequency × prominence across organic category prompts.
Measures what GPT-5 believes about Apple Notes from training alone, before any web search. We probe the model 5 times across 5 different angles and score 5 sub-signals.
High overlap with brand prompts shows Apple Notes is firmly in the model's "note-taking app" category.
Unprompted recall on 15 high-volume discovery prompts, run 5 times each in pure recall mode (no web). Brands that surface here are baked into the model's training, not borrowed from live search.
| Discovery prompt | Volume | Appeared | Positions (5 runs) |
|---|---|---|---|
| What are the best note-taking apps for everyday use? | 1,600 | 5/5 | 1, 1, 1, 1, 1 |
| What are the top note-taking apps right now? | 210 | 5/5 | 3, 5, 3, 3, 2 |
| Which note-taking apps are the most popular? | 210 | 5/5 | 3, 2, 4, 3, 3 |
| What note-taking apps are most recommended? | 0 | 5/5 | 3, 5, 1, 5, 1 |
| What are the best note-taking apps for students? | 0 | 4/5 | 7, 8, 8, 4 |
| What are the best note-taking apps for work? | 0 | 5/5 | 5, 6, 6, 6, 5 |
| What are the best note-taking apps for iPhone? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the best note-taking apps for Android? | 720 | 0/5 | — |
| What are the best note-taking apps for Windows? | 20 | 1/5 | 5 |
| What are the best note-taking apps for Mac? | 1,300 | 5/5 | 1, 1, 1, 3, 1 |
| What are the best note-taking apps for organizing notes? | 0 | 5/5 | 4, 4, 5, 4, 5 |
| What are the best note-taking apps with cloud sync? | 0 | 5/5 | 4, 4, 4, 4, 4 |
| What are the best note-taking apps with collaboration features? | 0 | 2/5 | 5, 7 |
| What are the best note-taking apps with tags and search? | 0 | 0/5 | — |
| What are the best note-taking apps for personal knowledge management? | 0 | 4/5 | 3, 3, 2, 3 |
This report focuses on Note-Taking Apps because that is where Apple Notes scores highest. The model also evaluates it against the industries below, with their own prompts and competitor sets. Click any industry for its full leaderboard.
Generated automatically from gaps and weaknesses in the analysis above, ranked by potential impact on the AI Visibility Score.
Retrieval (60) beats recall (45). Current web knows you, but training data lags. Focus on category-phrase density in authoritative sources so future training cycles pick you up.
+5 to +15 on Authority recallYour LBA is strong. Focus on maintaining authoritative coverage and ensuring new product launches get independent reviews within 12 months of release.
Maintain current LBACore TOM is strong. Watch for specific differentiators (slogans, signature products) that appear in only some iterations. Push those into training-data-crawled headlines.
Maintain / refine TOMOther brands in the Note-Taking Apps industry, ranked by overall AI Visibility Score.
Every score on this page is reproducible. Below is exactly what we ran and how we computed each number.
(LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
quality × meta × stability × share × recognition × 100. Each sub-signal is on a 0-1 scale. Read the full LBA methodology →
Analysis run on April 22, 2026 at 6:46 PM
Click a prompt to expand its responses. 210 total responses across 72 prompts.