The technical implementation was done in C# and is based on a modular architecture with multiple interfaces to external ticketing systems. Tickets and associated metadata are automatically retrieved via these interfaces and normalized in a multi-stage process. A central component of the solution is the systematic detection of duplicates as well as the correction of inconsistencies and data quality issues that can arise from different ticket sources, data models, and status logics. This ensures that the processed data is consistent, traceable, and comparable.
Electric Love Festival - ELF - Tickethelper platform
As part of the Electric Love Festival, a powerful integration and portal platform called "Tickethelper" was implemented, enabling centralized processing and consolidation of ticket data from a variety of external ticket providers. The project's goal was to transfer distributed and heterogeneous ticket information into a uniform, reliable data basis, thereby creating the foundation for consistent evaluations, analyses, and operational decisions. The consolidated data is then centrally stored in Google BigQuery, where queries and analyses are performed directly on the unified data basis.
Project advantages at a glance
- Overview of ticket sales
- Data Anomaly Detection
- BI reporting for management decisions
Details
- Client: Electric Love Festival
- Project: Custom development
- Technology: C#, Google Cloud BigQuery
- Hosting: Microsoft Azure
Increase data quality
Custom Portal
Complementing the automated processing, an internal web portal was developed that allows authorized users to access special cases. Through this portal, deviations such as incorrect customer data, unclear status assignments, or inconsistent ticket information can be manually reviewed and corrected. This combination of automated data preparation and targeted manual post-processing ensures that even complex or exceptional cases can be resolved in a controlled manner without compromising the overall quality of the data base.
With Tickethelper, we have for the first time a central and consistent view of our ticket data – regardless of which provider sold them. The solution has enabled us to significantly improve data quality, transparency, and evaluability and to create a reliable basis for reporting and operational decisions.
Jürgen Kornmüller
/ CEO
Business Intelligence
After processing is complete, the consolidated and cleaned ticket datasets are transferred to Google BigQuery. This provides a central data platform where uniform evaluations, business intelligence reports, and operational analyses across all ticket sources are possible. The solution thus creates a reliable basis for data-driven decisions and supports both operational and strategic requirements in the ticketing and event environment.
Numbers that make an impact!
Reach, team size, and project duration at a glance – compact, comprehensible, measurable.
920000
Tickets processed
200
Days of project duration
24
Festivals organized
Head of Business Development
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The platform supports visitors with all ticket-related questions – from navigating the ticket jungle to quick problem solving – and thus significantly relieves the festival's support team.
You receive clear, immediately available information, can independently resolve typical questions, and avoid long waiting times for support. The platform simplifies the entire ticket process before, during, and after the event.
Recurring support requests are automatically intercepted. This significantly reduces the volume of inquiries and allows the team to focus on more complex issues. At the same time, the service quality is improved.
Yes, the solution is modularly designed and can easily be extended with new features, additional ticket categories, or extra communication content.
Yes, it uses interfaces to the festival's ticket-relevant systems to provide current information consistently and reliably. This ensures that content is always synchronized with the official ticket shop.
To the customer
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