Case Study: Custom Solution for Ticket Data Scraping


A prominent corporation in the ticketing industry approached us with an intricate task. The objective was to automate the process of scraping and matching data from numerous ticketing platforms and marketplaces. The challenges lay not only in the enormous volume of data but also in the sophisticated anti-bot measures employed by these platforms.

The objective was to get enormous data whilst maintaining an exceptional accuracy rate. They aimed to leverage this extensive data to make informed, rapid decisions and respond more effectively to market changes.

However, they faced several significant hurdles:

  • The necessity to scrape ticketing platforms and marketplaces, matching all available events and their respective ticket listings against each other, needed specifically developed algorithms.
  • The task of harmonizing different event titles, normalizing and cleaning addresses, and calculating distances between locations for match validation.
  • The process of matching ticket listings for the same events by cleaning and analyzing data such as section and row names, ticket listing quantities, etc.
  • Dealing with the constant check and validation of event matches using Lat/Long coordinates of each venue, a task that required precise proximity identification.
  • The requirement of maintaining a high degree of accuracy in matching events, titles, addresses, performers, venues, sections, rows, quantities, and other applicable elements in events and tickets.

By having access to comprehensive, up-to-date, and accurate data about events and ticket listings across multiple platforms, they could provide their customers with the most competitive ticket prices and availabilities.

Events Listings Daily

Tickets Listings Daily


Data Matching Accuracy


The implementation of our advanced data scraping and matching algorithm led to a substantial transformation in the client’s business operations. A remarkable boost in operational efficiency up to 46% was achieved, driving the client’s ability to make faster, data-informed decisions.

This drastically reduced the need for manual data processing eliminating potential errors and bottlenecks associated with it. Our solution directly led to noticeable business results, including an estimated 6.2% increase in the client’s revenue, according to the price management team.

By aiding the processing of over 30 million ticket listings and delivering reliable, real-time data, our solution significantly augmented the client’s return on investment. Our approach enhanced the client’s capacity to respond swiftly to market fluctuations. Consequently, this led up to a 18% increase in customer satisfaction. 

With access to more accurate and up-to-date ticket availability and pricing information for over 250,000 events, we strengthened the client’s market positioning and bolstered customer loyalty. Furthermore, the client’s reputation in the market was significantly boosted. Not only did the solution’s accuracy rate of 98.5% exceed the client’s expectations, but it also set a new industry standard for data matching.

As a result, the client observed up to 48% increase in customer retention and approximately 22% rise in new customer acquisition, attributed to its enhanced market credibility.

Web Scraping Pipeline

Challenges & Solutions


Advanced Anti-Bot Measures

These sophisticated mechanisms were one of the significant barriers, necessitating innovative approaches to access the required data. These are intricate systems deployed by online platforms to differentiate and block automated bots.


Advanced Data Acquisition

To combat the sophisticated anti-bot systems employed by data sources, we developed a bespoke scraper. This system is equipped with mechanisms designed to ethically and successfully bypass such anti-bot protections.


Data Accessibility and Complexity

The diversity in the data ecosystems meant that the information was scattered and embedded in distinct configurations, leading to elevated levels of complexity in extraction and subsequent management. 


Custom Algorithm

Due to the diversity in data ecosystems we engineered a custom algorithm. It was meticulously developed to cope with the substantial variations in event addresses, titles, and other intricate details.


Data Inconsistency

Event addresses, titles, and other information varied substantially between sources, and each platform featured its own unique data structure and format, making access and standardization a significant challenge.


Geocoding API

The challenge of dealing with raw addresses scattered across various platforms, each with its unique structure and format, was handled by implementing a solution for address normalization, leveraging Geocoding APIs.


Locations Validation

Addressing the variability and diversity in event locations was pivotal, as it was crucial to validate that the events listed corresponded to the right venues. 


Leveraging Latitude/Longitude Coordinates

Utilizing Latitude/Longitude coordinates, we were able to calculate distances between event locations, thereby validating the matches and ensuring high-volume processing.


Dynamic Data Structures

The frequently changing data structures on source websites could potentially disrupt the data scraping process. This variability necessitated a solution equipped with the agility to adapt to evolving structures to maintain data integrity and reliability.


Automated Reporting and Alerting System

We countered this by implementing an automated reporting and alerting system. This system monitored the solution’s performance, providing critical insights into error rates, mismatch rates, and system downtimes, thereby ensuring resilience against such changes.


Legal and Compliance Issues

The task of ensuring strict adherence to relevant US data privacy laws, including the California Consumer Privacy Act (CCPA) and other federal and state-specific regulations, was a significant challenge.


Compliance Protocol

The challenge of ensuring strict adherence to relevant US data privacy laws, including the California Consumer Privacy Act (CCPA) and other federal and state-specific regulations, was met with stringent compliance protocols.

Key Takeaways

Scalability and Performance

Our systems are fundamentally scalable, allowing effortless handling of increasing data volumes and adapting swiftly to market dynamics, delivering robust performance and a significant competitive edge to clients.

Innovative Data Handling

We’ve engineered custom systems that achieve an industry-leading 98.5% data-matching accuracy rate. This innovative approach to data handling not only ensures the reliability of decisions but also significantly contributes to our client’s success.

Reliable Data Delivery

Ensuring integrity and consistency is the key. Our efforts, such as leveraging Geocoding API for address normalization and using Lat/Long coordinates for location verification, ensure that our clients receive clean, consistent, and reliable data.

Ethical Data Acquisition and Legal Compliance

We’ve developed advanced data acquisition technique, ensuring that data extraction process is both ethical and effective. Further, we prioritize compliance with all relevant data privacy laws, including the California Consumer Privacy Act (CCPA).

Ticketing Websites Scraping


Our advanced system demonstrated exceptional scalability and adaptability, enabling the processing of up to 250,000 events and 30 million ticket listings daily. This substantial increase in data handling capacity allowed the client to gather comprehensive and up-to-date insights, fueling their decision-making processes.

These cutting-edge techniques, combined with our solution’s robust infrastructure, delivered a remarkable matching accuracy rate of 98.5%. This level of precision allowed the client to provide their customers with highly reliable and tailored ticketing options.

This granted client the possibility to offer more precise ticket availability and pricing to their customers. Our web scrapers, built with scalability and adaptability at their core, were well-equipped to anticipate future growth in data volume and changes in market trends.

Overall, our collaboration with the leading ticketing corporation exemplifies our commitment to providing tailored solutions that address complex data challenges.

By leveraging automation, scalability, and adaptability, we empowered the client to achieve around 40% reduction in error rates, up to 48% increase in customer retention, approximately 22% rise in new customer acquisition, process vast amounts of data, and optimize their decision-making efforts.

With our advanced solution, the client is well-equipped to navigate the dynamic ticketing industry, leveraging data as a strategic asset for long-term success.

Duke University

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