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Discover how Actowiz Solutions tackles ride-hailing price scraping challenges for Bolt & Uber, ensuring scalable, accurate, and undetectable data extraction.
Ride-hailing platforms like Bolt and Uber have become essential for urban mobility, offering dynamic pricing based on demand, location, and other factors. Businesses tracking these price variations require real-time data to make informed decisions. However, extracting data from ride-hailing apps presents challenges such as IP bans, CAPTCHA restrictions, and frequent API changes. This case study explores how Actowiz Solutions effectively extracts ride-hailing price data while overcoming these challenges.
A leading mobility analytics company approached Actowiz Solutions to scrape price data from Bolt and Uber across multiple locations. Their key requirements included:
- High-volume data extraction – 25,000 searches per week, scalable up to 500,000.
- Comprehensive data collection – All fare details, surge pricing, estimated wait times, and ride types.
- Minimal detection risks – Avoiding bans and CAPTCHAs.
- Scalability and reliability – Ensuring uninterrupted data flow.
Extracting ride-hailing price data comes with multiple hurdles:
1. Dynamic Pricing Models – Prices fluctuate based on demand, making frequent updates necessary.
2. IP Blocking & CAPTCHA Restrictions – Platforms implement security measures to prevent automated scraping.
3. Data Encryption & API Restrictions – Ride-hailing apps often use encryption and restrict unauthorized API access.
4. Geolocation-Based Pricing – Fare estimates depend on location, requiring proxies or VPN solutions for accurate data.
Actowiz Solutions implemented residential and mobile proxy networks to bypass IP bans and accurately simulate searches from various locations. This ensured:
- Undetectable requests by mimicking human-like behavior.
- Geo-targeted data collection for city-specific fare insights.
Using headless browsers and fingerprinting techniques, Actowiz Solutions ensured the scraping system mimicked real-user activity, reducing detection risks. Benefits included:
- Avoiding bot detection algorithms by imitating human interactions.
- Handling dynamic elements like fare pop-ups and surge pricing.
To tackle CAPTCHA challenges, Actowiz Solutions integrated machine learning-based solvers, enabling automated bypassing without human intervention.
After extraction, raw data was cleaned, structured, and delivered in various formats via custom APIs and cloud-based databases for seamless integration.
- 99.5% uptime and uninterrupted data flow across all locations.
- 500,000+ weekly searches processed seamlessly.
- 20% cost reduction for the client by automating ride-hailing price monitoring.
- Enhanced market intelligence for dynamic pricing strategies.
Actowiz Solutions has demonstrated expertise in overcoming ride-hailing data extraction challenges, ensuring accurate, large-scale price monitoring for Bolt and Uber. By leveraging advanced automation, proxy management, and AI-driven solutions, Actowiz Solutions provides businesses with critical pricing insights while maintaining compliance and efficiency.