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Arena Racing - Bringing the Single Customer View to Life

This IDC Market Note highlights Arena Racing Company's transition to a new data management suite based on Experian Aperture Data Studio to support its initiative for a single customer view (SCV). IDC interviewed Niall Kempson, Group Customer Relationship Management (CRM) Data and Insights Analyst at Arena Racing Company, to understand why and how the company transitioned to a new data management suite, as well as its experiences and the issues it faced along the way.

Key Takeaways

  • Arena Racing Company owns 16 U.K. horse race courses and two greyhound tracks. It hosts around 35% of annual U.K. horseracing fixtures across a mix of flat, jump, and all-weather tracks.
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  • Building a single view of the customer is critical to Arena's marketing efforts as it provides the company a deeper understanding of customer behavior and habits, as well as a better view of the performance of its sponsors and sponsorship packages.
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  • Arena Racing Company engaged in the beta test program for Experian Aperture Data Studio before moving to the production version of the data management suite. Arena is suing the suite's self-service capabilities for address and email verification, fuzzy matching, and access to curated Mosaic and third-party data sets.

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IDC's Point of View

Building a trustworthy, consistent, and single view of the customer is critical to Arena's marketing efforts since it provides the company a deeper understanding of customer behavior and habits and obtain a better view of the performance of its sponsors and sponsorships packages. The benefits for Arena of employing from such an approach include improved customer service levels, better customer retention, higher conversion rates and arguably an improved customer lifetime value.

Participating in Aperture Data Studio's Beta Test Program

While Arena is not new to the concept of building an SCV, it was forced to move from its previous data quality solution, Experian Pandora, because the PCs running it had become corrupt. Given that Arena was already an existing Experian customer, the company made the decision to kickstart its SCV work by trialing Experian Aperture Data Studio — Experian's new data management suite — and becoming a beta test customer.

Aperture Data Studio incorporates much of Pandora's functionality, but brings this together with enhanced data quality functionality on a more better-performing and browser-based platform. The main developmental thrust of Aperture Data Studio is to enable self-service data quality for nontechnical users such as business users, data stewards, and analysts, enabling them to service their own requirements without help from IT. Aperture Data Studio has been designed with a drag-and-drop visual workflow interface and easy access to curated data sets. It is specifically targeted at individuals in charge of data projects that want to leverage and manipulate the data they have for their own purposes.

Arena is using the following features and functionality of Aperture Data Studio:

  • Data workflows. The company develops data pipelines in a drag-and-drop workflow to profile, validate, and transform data.
  • Address and email verification. Arena cleanses its data by cross referencing and verifying the accuracy of its data against U.K. addresses and emails via Data Studio integration to Experian Batch.
  • Fuzzy matching. The ability to identify duplicates, score data, and de-duplicate data based on customized business rules was a main focus for Arena.
  • Data enrichment. Arena has access to Experian Mosaic and third-party data sets from Experian within Aperture Data Studio. This enables the company to append information to the customer record within its CRM system. The longer-term aim is to integrate Mosaic fully within its new CRM system, so information is validated during the data entry process.

As part of its beta test program, Experian held an initial training session with Arena, so that Kempson was "up and running" with the product, although no further training was scheduled. Kempson was mainly self-taught, demonstrating that the tool was essentially self-directing and doesn't require the expertise of an IT specialist.

Critical to Arena's SCV efforts was the ability to cross-reference customer data with Mosaic data sets. These curated data sets provide a detailed view of U.K. consumers based on the latest consumer and societal trends. The data set contains around 850 million pieces of information across 450 different data points to identify 15 summary groups and 66 detailed types. Arena is actively using this information to gain a better understanding of its customers, so it can communicate with them more effectively.

Progressing Toward Production

Working with a beta version of the product enabled Kempson to familiarize himself with the tool and its new interface, but the ultimate aim was to move to Aperture's production version. This was an arduous process at times, since not all the functionality was readily available in the beta version when needed (such as access to Mosaic data sets).

Kempson's experience on working with Experian and Aperture Data Studio was broadly positive, despite (as is often found) setbacks along the way. Key learnings included:

  • The user interface was very intuitive, with easy-to-understand rules and workflows. All the transformations needed were available and easy to find.
  • Building data workflows provided a steep learning curve, so additional training and guidance was needed. This proved particularly complex since Arena's source transactional systems were often misused. For example, the system didn't have a gender field, so specialist rules were needed to reformat and extract information from the source data.
  • There was a lack of an Aperture Data Studio user community or user forum at the time to provide additional support and guidance.
  • Additional training was a consideration. Kempson was aware he was not leveraging the full potential of the tool, but without sufficient direction, he was unable to identify how he could benefit from using certain features, such as Aperture Data Studio's integration with Python tools.
  • Aperture Data Studio proved useful for Arena's General Data Protection Regulation (GDPR) compliance efforts by helping validate contact details for privacy updates and helping protect its reputation.

Conclusion

Customer data is the lifeblood of most businesses; the same is true for Arena as it builds a SCV to underpin its marketing communications efforts. Among the biggest problems faced by the company was duplicate customer records, a problem that manifested itself within its CRM system, which wasn't intelligent enough to recognize if contact information for a customer record already existed. Aperture Data Studio proved critical in helping the company identify duplicates and match them correctly. Likewise, Aperture Data Studio was responsible for identifying data quality issues that the company was not aware of. For example, by profiling data, Arena discovered that address fields contained unmappable characters. It then used Aperture Data Studio to export data, so it could remove the characters and re-import a corrected version.

While these issues were not insurmountable, the ability to improve the performance and efficiency of marketing campaigns was seen as a significant gain for the company. Duplicate records can create real business issues such as wasted budgets, the risk of a flawed reputation, and inability to get a clear and consistent view of customers and their behavior. Without a single customer view, it would be much harder to build meaningful segments that support targeted marketing campaigns with effective and relevant communications and offers.

Data quality best practices also dictate that issues with quality are best resolved at the source; it is best to trap and fix issues before they permeate downstream systems. Arena recently completed a software review and is in the process of implementing Salesforce Cloud Lightning and Marketing Cloud. Experian Aperture Data Studio will form an integral part of the data migration project and ongoing cleansing for the new CRM. In addition, Arena's ability to implement aspects of Aperture Data Studio to screen and validate customer information on entry will significantly improve data quality and reduce the presence of duplicates in the longer term.

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