MediaPrint Case Study: 24% better Data Quality

• Rapid implementation together with partners TDI & Tilores with minimal operational effort.
• The identification of unique individuals was improved by over 24%.
• Foundation laid for reliable advanced analytics, AI, and automation use cases.

During the development of the new data platform at MediaPrint, it became clear early on that the quality of the underlying data would play a decisive role in the success of future use cases. Together with our technology partner Tilores, a Berlin-based start-up specializing in identity resolution, we therefore recommended addressing the issues of duplicate checking and data standardization on the new platform in a timely manner.

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To validate the approach, we first started with a proof of concept (PoC), which delivered very convincing results in a short period of time. After successful completion and subsequent purchase by MediaPrint, the project was gradually transferred to operational use and integrated into the existing data platform.

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The challenge was clearly defined: Some of the individual source systems already had solid duplicate checks in place, but there was no cross-system ID. Merging the data sources from the three organizational units—MediaPrint, Krone, and Kurier—resulted in multiple person records, which made it difficult to use the data consistently for analytics or marketing. Together with Tilores and input from the specialist departments, a solution was implemented that automatically checks, cleanses, and merges all personal and customer data on the data platform.

Tilores uses intelligent matching algorithms to identify similar spellings, detect duplicates, and create a unique personal ID that will serve as a connecting element across all systems in the future. Another key success factor was the ability to feed this ID back into selected source systems—a step that ensures data quality is improved early on in the process rather than only at the end of the data flow. This means that not only analysis and campaign tools benefit from higher data quality, but also operational systems such as CRM and others.

The results are impressive: the unique identification of individuals has been improved by over 24% – a significant improvement in the database for future use cases. The solution runs largely automatically and requires minimal maintenance. The successful completion of this project marks another important milestone on the path to becoming a data-driven organization.

The improved data quality creates trust in the data and forms the necessary basis for advanced analytics and AI applications – for example, in the areas of churn prediction or customer lifetime value (CLV) forecasts, which are already being implemented.

Challenges & lessons learned

Technical integration with greater depth of detail than initially assumed: Connecting Tilores to the existing data platform required several iteration loops. In particular, the return of the personal ID increased the coordination effort due to detailed questions about the interfaces.

The 7 Success Factors from the MediaPrint Case Study

• ‍Clear Business Case: Concrete use cases (churn prediction, CLV) defined goal and ROI
• ‍Right Partner Selection: Combination of TDI (strategy, change) and Tilores (technology specialist) brought complementary expertise
• ‍Phased Rollout: PoC → Piloting → Scaling reduced risks and enabled early learning
• ‍Close Collaboration: Weekly alignments between all partners ensured fast problem resolution
• ‍Business Unit Involvement: Data Stewards from business units ensured matching rules were technically correct
• ‍Transparent Communication: Openness about challenges and delays built trust
• ‍Long-term Focus: Investment in low-maintenance, scalable solution instead of quick fix

Conclusion: The MediaPrint Case Study as Blueprint

The MediaPrint Identity Resolution Case Study impressively demonstrates: data quality is not a "nice-to-have" but a strategic success factor. The +24% improved person identification is not just an impressive number – it's the foundation for Advanced Analytics, AI use cases, and a truly data-driven organization.

The core insights from this case study:

✅ Technology + Methodology = Success: TDI Framework (Culture, Organization, Architecture) + Tilores technology

✅ Phased Rollout reduces risks: PoC → Piloting → Scaling enables early learning

✅ Change Management is success-critical: Without cultural acceptance, best technology fizzles

✅ ROI is measurable: Concrete KPIs instead of vague promises

✅ Partnership approach works: MediaPrint-TDI-Tilores as example of complementary expertise

Your Takeaways from this Case Study:

Ask yourself:

• How many of your analytics projects fail due to inconsistent data?
• What costs arise from duplicate outreach, manual cleansing, or wrong decisions?
• Is your data ready for the AI use cases you're planning?

At The Data Institute, we've supported over 15 data platform projects – from media companies like MediaPrint and HAAS to e-commerce players like babymarkt.de to retail chains like Parfümerie Pieper. Our conclusion: the most successful organizations treat data quality as a strategic priority from the start.

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