Dataset: New Uber Eats restaurants in Taiwan
- Verified Uber Eats restaurant profiles
- Complete Taiwan geographic market coverage
- Daily refreshed venue contact details
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Daily venue feed
What the new Uber Eats restaurants in Taiwan dataset contains
Each record provides normalized contact details, cuisine classifications, and precise coordinates for every recent public restaurant addition on the platform. Your strategy team can immediately ingest this structured feed to map out supply gaps across Taiwanese cities without doing any manual research.
| Venue Name | Store Format | Neighborhood | GMaps Rating | Detected | ... |
|---|---|---|---|---|---|
| Din Tai Fung (Xinyi A4) | Physical Store | Xinyi District | 4.8 / 5 | 12min ago | •••••• |
| Just Kitchen (Zhongshan) | Cloud Kitchen | Zhongshan District | 4.2 / 5 | 2hr 38min ago | •••••• |
| Tiger Sugar (Fengjia) | Physical Store | Xitun District | 4.6 / 5 | today 09:14 | •••••• |
| Bento Boss (Virtual) | Virtual Brand | Da'an District | 3.9 / 5 | today 14:22 | •••••• |
| Ah Chung Rice Noodles | Physical Store | Wanhua District | 4.9 / 5 | yesterday | •••••• |
100%
Public Uber Eats coverage
We map every active neighborhood across Taiwan to ensure complete geographic visibility. You get a true picture of total addressable market without missing any emerging suburbs.
24h
Refresh cycle for updates
Our infrastructure detects public platform additions continuously and delivers structured updates daily. Your sales representatives act on fresh leads before rival platforms even realize a venue exists.
99%
Data normalization accuracy rate
Every raw input from the delivery platform translates into a clean, standardized data model. Data engineering teams save hundreds of hours by skipping manual cleaning and matching tasks.
360°
Enriched venue profile context
We match public platform listings with external sources like Google Maps to build complete profiles. You receive actionable contact details right out of the box.
FAQ
Questions we get from strategy leaders
Here are the most common questions decision-makers ask before acquiring this local intelligence.
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