Uber Eats Scraper
With Outscraper’s Uber Eats Scraper, you can unlock valuable data from one of the world’s leading food delivery platforms. Gather detailed information on restaurants, menus, pricing, delivery zones, customer reviews, and more.
Why Scrape Uber Eats with Outscraper?
Extensive Coverage
Access data from thousands of restaurants across Uber Eats in multiple regions worldwide.
Cost-Effective & Reliable
Enterprise-grade scraping at competitive rates, supported by strong uptime and dedicated support.
High Accuracy
Clean, structured, and deduplicated data ensures reliable insights with minimal preprocessing.
Scalable & Fast
From hundreds to millions of records, our infrastructure handles requests at scale with low latency.
Customizable Output
Choose fields, formats, and delivery methods (CSV, JSON, API integration) tailored to your workflow.
Always Up-to-Date
Get fresh data with configurable scraping filters.
Planes de precios
Pague por uso con facturación mensual por uso medido.
Nivel gratuito
Usage before 100 items- Price per one item for the usage from 1 to 100 items
- WEBP/PNG/JPEG image extension
- Acceso a la API
Nivel medio
Usage after 100 items- Price per 1k items for the usage from 100 to 100,000 items
- WEBP/PNG/JPEG image extension
- Acceso a la API
Nivel de negocio
Usage after 100,000 items- Price per 1k products for the usage after 100,000 items
- WEBP/PNG/JPEG image extension
- Acceso a la API
API Docs
Utiliza los datos de tu app. Echa un vistazo a API Docs para ver ejemplos de código.
¿Qué dicen los clientes?
¡Tu reseña motivará mucho a nuestro equipo! Utiliza Facebook, Product Hunt, Trustpilot, o Capterra para publicarla.
Nuestros clientes
La confianza de miles de clientes satisfechos en todo el mundo.
Preguntas más frecuentes
Preguntas y respuestas más frecuentes
You can extract restaurant information, menu details, pricing, reviews, delivery zones, and more.
Absolutely. Our scraper supports regional targeting across different countries and cities where Uber Eats is available.
Yes. Outscraper only collects publicly available information and complies with applicable data regulations.
restaurant and menu information, you can create location-specific landing pages that rank for local searches such as “best pizza near me” or “top restaurants in [city].” By publishing detailed pages with names, addresses, categories, and menu items, you increase your chances of appearing in searches from users who are actively looking for food delivery or dining options.
Menu data is also a rich source of long-tail keywords. Each dish name, cuisine type, or special offer can become a keyword opportunity. Competitors often fail to optimize for these terms, which means you can capture niche but highly targeted traffic by integrating them into your content strategy.
Frequent updates are another major advantage. By refreshing menus, prices, and reviews on a regular basis, your website sends strong signals to search engines that your content is fresh and relevant. This improves rankings and helps you stay visible even in highly competitive food delivery markets.
Structured data plays a key role in improving click-through rates. With Uber Eats data, you can implement schema markup for ratings, pricing, and availability. This allows your search listings to show rich snippets, which not only stand out visually but also build trust with potential customers before they even click.
In addition, analyzing restaurant categories and customer reviews provides valuable competitive intelligence. By studying which restaurants perform well and which dishes are trending, you can refine your SEO targeting, adjust your content themes, and focus on the keywords that actually convert.