Data Platform

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Integration is the 'glue' that links the Sports Alliance Data Platform to other 3rd party systems or applications. Integration brings together supporter, transactional and behavioural data across all touchpoints within the club, including ticketing, access, merchandise, web registration, hospitality and web applications in to the Data Platform.

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Analytical models provide a data-driven basis for enhanced personalisation and targeted supporter marketing in Sport.

Many of the key revenue or commercial products sold by Sports Clubs are seasonal or subscription based, and have enabled Clubs to form a significant level of affiliation over time with individual supporters.

We have 5 years of commercial and data experience in developing classification models to help identify key 'predicted' behaviours such as a supporter’s likelihood to renew or purchase a season ticket or membership. Every Club is different. We 'share' experience between model approaches but the underlying data is specific to an individual Club across seasons.

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The Supporter API is a resource-based RESTful web service, built on ASP.NET Web API and MS SQL Server technologies. It provides a secure and effective interface for 3rd party applications to access data and functionality relating to the full Supporter profile. It provides a single, standardised and consistent point of contact for applications for all aspects of the Supporter data profile – ticketing, retail, demographics, marketing, analytics and more.

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Built in Microsoft SQL Server, the Data Warehouse stores and processes data from all Club and 3rd party sources, providing a single reference for supporter data profile for all consuming applications, services or processes.

  • Data is retrieved or consumed from transactional source systems via Integration processes specific to each supplier, system or application
  • Schema mapping from source to generic across hundreds of supplier systems
  • Within the Data Warehouse hundreds of modules, functions and processes for implementing relevant business rules / logic work to cleanse, validate and de-duplicate data
  • Data validation and normalisation based on internal and external reference data
  • Individual supporter deduplication