How to construct a Data Identity moat — John Velcamp // Capgemini

Show Notes

• 01:44
  Johns background and role as Identity and Data Strategy Lead at Capgemini

  John spent a significant part of his career at Axiom, focused on data management and identity solutions. At Capgemini, he leverages this expertise to help organizations understand their data sources and turn data into a strategic advantage for their brand.
• 02:23
  The concept of a data identity moat and its relevance today

  As the adtech and martech landscape evolves, a data identity moat means achieving self-sufficiency with your data to maintain control amidst ecosystem changes. Ultimately, it safeguards your brand's data from potential impacts of the evolving ecosystem.
• 03:35
  The compatibility of a data identity moat with data management outsourcing

  Building a data identity moat is compatible with outsourcing data management. It's about the brand's control, which can be extended to partners and service providers to bolster your data against the ecosystem.
• 04:10
  Safeguarding privacy and compliance with a data identity moat

  The data identity moat safeguards against privacy and compliance risks in the context of evolving legislation like GDPR and domestic privacy policies. Its core purpose is to prevent incidents that could lead to negative publicity or legal consequences, ensuring responsible data handling.
• 05:05
  Balancing data protection and quality with a data identity moat

  The concept of a data identity moat serves a dual purpose. It involves protecting data from leaking out, especially when sharing personally identifiable information, and also ensuring the quality and relevance of incoming data to maintain efficiency in data analysis and utilization.
• 07:10
  The significance of evaluating the quality and the sources of the data you buy

  Intent data can be misleading if not carefully assessed for quality, relevance, and source. Evaluating data sources, relevancy, and distinguishing between modeled and actual data is crucial to avoid wasting resources on irrelevant or poorly sourced datasets.
• 09:33
  Establishing data moats for informed data ingestion and decision making

  A data moat simplifies data ingestion decisions by prioritizing performance-based assessments over sources and attributes. Evaluating whether a dataset improves outcomes is crucial, and advanced tools like generative AI can aid in this process to ensure data's relevance to the right audience.
• 11:28
  The changing landscape of customer data

  The cost of finding new customers is increasing due to diminishing data availability in the face of GDPR, changes by Apple, etc. Rising customer expectations for personalized experiences make it crucial to rebuild customer identification methods in the evolving ecosystem.
• 15:27
  Navigating data protection and utilization in the modern landscape

  It's crucial to create a moat around both first-party and expanded data ecosystems formed through strategic third-party partnerships. Ethical data practices, smart utilization, and customer trust, enhance data's value and your ability to serve customers effectively.
• 19:50
  Leveraging cleanrooms for safe data collaborations

  Capgemini helps clients establish data cleanrooms, even within the same brand, when business silos have differing privacy policies or permissions. Alternative on-premise data joining solutions like InfoSum, provide secure, encrypted data integration without the need to transfer data externally.
• 21:34
  Data protection in cleanroom environments

  When data leaves the cleanroom environment, it's not the raw data but a securely encoded representation of it, providing protection against interception. Solutions vary from on-premise software installations to cloud-based options, providing flexibility to suit different security and compliance needs.
• 22:48
  Cleanroom solutions for brand collaborations

  Data collaboration scenarios range from partnerships where brands share customer lists to asymmetrical collaborations between large retailers and other companies. Tools like LiveRamp enable secure, anonymous data access in aggregate and integration with platforms like Google.
• 24:49
  Assessing customer needs for CDPs and data cleanrooms

  Clients approach Capgemini with diverse requirements related to CDPs. They analyze their identity management, customer journey objectives, and data integration needs to determine if a cleanroom solution suits their goals, offering tailored solutions through platform combination.
• 28:00
  Choosing the right tools and solutions for enhanced effectiveness

  Capgeminis role is to help clients choose the right tools and solutions tailored to their specific needs. They focus on enhancing what's already in place and building for the future, ensuring efficient, effective outcomes without unnecessary overhaul.