Geometric mean of LBA, Authority and TOM. Penalises any single weak metric.
What the model believes about Lime without web search.
Frequency × prominence across organic category prompts.
Measures what GPT-5 believes about Lime 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 Lime is firmly in the model's "micro-mobility operator" 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 micro-mobility operators for cities? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| Which micro-mobility operators are the most popular right now? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the top micro-mobility operator companies? | 10 | 5/5 | 1, 1, 1, 1, 1 |
| Which micro-mobility operators are best for urban travel? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the most recommended micro-mobility operators? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| Which shared e-scooter and e-bike operators are the best? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What micro-mobility brands do people use most in cities? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| Which are the leading dockless bike and scooter operators? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the best shared mobility operators for short trips? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| Which micro-mobility operators have the best reputation? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the most reliable micro-mobility operators? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| Which micro-mobility operators are worth using? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the best e-scooter and e-bike sharing companies? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| Which micro-mobility operators are the biggest? | 0 | 5/5 | 1, 1, 1, 1, 1 |
| What are the top shared scooter operators in cities? | 0 | 5/5 | 1, 1, 1, 1, 1 |
This report focuses on Micro-Mobility Operators because that is where Lime 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.
You score 100 on recall but only 90 on retrieval (gap of +10.1). Training-data authority is outpacing your current web footprint. Publish fresh, well-cited content to keep search-augmented responses including your brand.
Close the fragility gapYour 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 Micro-Mobility Operators 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 23, 2026 at 3:43 AM
Click a prompt to expand its responses. 210 total responses across 72 prompts.