Comprehensive historical and current event data from Ticketmaster's platform covering millions of concerts, sports games, and entertainment shows. Access structured datasets with pricing trends, venue information, and attendance patterns across North America and beyond.
Leverage years of ticketing data to uncover market insights, seasonal trends, and consumer behavior patterns. Our dataset includes detailed event metadata, pricing histories, and venue analytics for advanced business intelligence.
Pre-processed and enriched Ticketmaster data ready for immediate analysis and integration. Ideal for machine learning models, market research, and competitive intelligence in the live entertainment industry.
Analyze touring revenues and venue performance to inform investment decisions. Track artist earning potential and venue profitability across different markets.
Demand Forecasting for Artists
Predict ticket demand for upcoming tours based on historical performance data. Optimize tour routing and venue selection to maximize revenue.
Dynamic Pricing Strategy Development
Study pricing patterns across similar events to develop optimal pricing models. Identify price elasticity factors and peak demand periods for different event types.
Tourism and Economic Impact Studies
Measure the economic impact of major events on local economies. Correlate event schedules with hotel bookings and restaurant traffic for urban planning.
Ticketmaster Dataset New Entries
The graph below contains real data based on our scraping operations. Latest update was 9 hours ago.
Advanced Ticketmaster Web Scraper Available Now!
Get real-time Ticketmaster data with custom processing to perfectly fit your data pipelines.
Access ready-to-use data instantly instead of waiting weeks or months to build your own data collection pipeline.
Structured & Clean Data
All datasets are thoroughly processed, normalized, and validated to ensure high-quality, consistent information.
Zero Maintenance
We handle all updates and data freshness, allowing you to focus on using the data rather than collecting it.
Cost Efficiency
Save thousands in development and infrastructure costs by leveraging our pre-built dataset instead of creating your own.
Our datasets
Discover our comprehensive datasets for efficient web data collection. Our datasets are regularly updated, thoroughly validated for accuracy, and ready for immediate use in your applications. Each dataset comes with complete documentation and sample implementations to get you started quickly.
Extract millions of property listings with prices, amenities, neighborhood insights, school ratings, and market trends from Trulia's real estate platform
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Our specialized team focuses exclusively on crafting bespoke data solutions for organizations with specific intelligence requirements.
Receive your first custom dataset sample within one week - engineered to your exact specifications and business logic.
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Yes, Rebrowser Datasets are designed for seamless integration with your existing data infrastructure. We offer various integration options including direct API connections, compatible data formats, and customizable delivery methods to ensure smooth incorporation into your data ecosystem.
Yes. During checkout, you can specify your preferred data freshness requirements. We offer options ranging from historical data to near real-time updates depending on your specific use case and requirements.
We employ a multi-layered validation process including automated checks, statistical anomaly detection, and human review for critical datasets. Our quality control team continuously monitors data quality metrics to ensure all information meets our rigorous standards before delivery to customers.
Absolutely. We understand that each project has unique requirements, which is why we offer extensive customization options. You can tailor datasets according to specific timeframes, geographic regions, data fields, or other parameters to ensure the data perfectly aligns with your project objectives.
Absolutely. We offer specialized datasets specifically optimized for LLM training and fine-tuning. These datasets feature diverse, high-quality content with appropriate metadata and context, making them ideal for improving model performance across various domains and reducing bias.