DoubleData
DoubleData is a specialized provider of enterprise-grade data scraping services and data matching solutions. We empower global organizations with clean, structured, and deduplicated data for strategic competitive intelligence.
Location:
Poland
Active since:
2018
Tech
Services
Enterprise Scraping
Scraping Consultancy
Custom Scrapers
Data Scraping
Market Research
Leads Data
Marketing Data
Travel Data
E-commerce Data
Use Cases
Food Delivery
Real-Time New Lead Generation: We identify new restaurants (e.g., appearing on maps) before they are listed on competitor apps, providing sales teams with exclusive "first-mover" leads.
Accurate TAM & Market Share Analysis: Utilizing our proprietary matching engine to deduplicate venues (e.g., merging "Joe's Pizza" and "Pizza by Joe"), giving Strategy teams a truthful view of Total Addressable Market and market saturation.
Total "Checkout Price" Monitoring: Tracking not just menu prices, but all hidden cost components including delivery fees, service fees, small order fees, and bad weather fees to prevent revenue leakage.
QCommerce & FMCG
"The 7 PM Rule" (Out-of-Stock Monitoring): Real-time alerts for product availability during peak hours to prevent lost revenue when products go out-of-stock while competitors remain available.
KVI (Key Value Item) Basket Tracking: Monitoring the total price of a defined basket of goods (e.g., 28 essential items) across competitors to manage price perception and competitiveness.
Digital Shelf & Search Visibility: Tracking product ranking within retailer apps (e.g., "Page 1 vs. Page 3") and Share of Shelf to ensure products are visible where 90% of sales occur.
Airlines
Total Flight Price & Ancillaries: Going beyond basic ticket prices to track the full cost including baggage fees, seat selection, and upgrades, ensuring accurate competitive fare analysis.
Strategic Network Capacity & Time Bands: Analyzing "seat capacity" (not just flight frequency) and dominance in specific "time bands" (e.g., morning business rush) for superior network planning.
Artificial Intelligence (AI)
Model-Ready Datasets for LLM Training: Delivering clean, structured, and toxicity-filtered datasets, removing "garbage" (ads, boilerplate) so Data Scientists can focus on architecture rather than cleaning.
Real-Time RAG Data Feeds: Providing live-web data feeds to power Retrieval-Augmented Generation systems, allowing AI models to answer queries with current information (e.g., today's stock price or news).
