Data sovereignty in marketing: How Schaeffler relies on internal data management

Speakers: Antonia Benz (Schaeffler), Christian Henne (MDI)

Talking points

• Schaeffler to rely on internal data processing and use for analytics and insights in future
• All external data is migrated or synchronized internally, harmonized and made available there
• The entire data management and automation runs in Microsoft Azure Cloud, including data visualization in Power BI
• “Data on demand” is planned for the future via chatbot and AI applications. Basis: AI-ready data.
• Such a project consists of 50% IT and must be planned accordingly in terms of time and resources
• Project was launched with external support from the MUNICH DIGITAL INSTITUTE (MDI) and is currently being further developed

Explanation

Data storage is of fundamental importance for Data & Insights. The presentations are therefore archived in a standardized way in order to bundle the knowledge and be able to use it later in different formats.

Brief description of the presentation

Schaeffler Marketing will rely on internal data management in the future. The background to this fundamental decision is to gain greater control and direct access to marketing and communication data and to ensure appropriate data protection. This must also be seen in terms of data intelligence outside of reporting dashboards. AI development is changing the way data is used. Schaeffler expects that data and analytics will have to answer much more specific questions in the future, provide insights and thus also gain value for the management of campaigns and marketing as a whole.

Findings

(1) Internal data management creates insights.

• Insights: External solutions often meant that Schaeffler could only access data in the form of dashboards. In future, it will be possible to access all data and thus further process it internally according to specific requirements and use cases.
• Cross-Channel. The quality of the analyses increases significantly as data from different sources can be combined, making cross-channel and journey evaluation possible.

(2) Data becomes future-proof for AI.

• AI applications. Cleanly structured data tables are a prerequisite for evaluations using AI with LLMs.
• Harmonization. These data tables must be harmonized
• Data access. Internal AI applications need access to this data. This is only possible with internal data storage

(3) Analytics becomes scalable.

• Flexibility. A key aspect of data-driven marketing is scalability within the organization. Internal data management creates the prerequisite for being able to react flexibly and quickly to a wide range of questions and analysis requests.
• Automation and costs. With regard to AI, it can also be assumed that the effort and therefore the costs for analytics will decrease in the future. Automation can at least achieve significantly greater data penetration in the organization without increasing costs.