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Data Ownership in Digital marketing

$299.00
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Self-paced • Lifetime updates
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Course access is prepared after purchase and delivered via email
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Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
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This curriculum spans the breadth of a multi-workshop legal and operational advisory program, addressing data ownership challenges across global marketing ecosystems with the granularity seen in enterprise data governance implementations.

Module 1: Defining Data Ownership Across Digital Marketing Ecosystems

  • Determine legal ownership of first-party data collected via multiple touchpoints (website, CRM, offline events) when data flows through third-party platforms.
  • Establish contractual clauses with agencies and ad tech vendors to clarify data rights, usage limitations, and reversion upon contract termination.
  • Resolve conflicts between joint controllership under GDPR and unilateral data monetization strategies in co-branded campaigns.
  • Classify data assets by ownership tier (owned, shared, licensed) to inform retention, access, and compliance protocols.
  • Negotiate data rights in media buying agreements where audience data is generated on publisher-owned platforms.
  • Implement metadata tagging to track data lineage and assert provenance across fragmented marketing technology stacks.
  • Address discrepancies between IT data governance policies and marketing team data collection practices in decentralized organizations.

Module 2: Legal and Regulatory Frameworks for Marketing Data

  • Map data processing activities across ad servers, CDPs, and email platforms to fulfill GDPR Article 30 record-keeping requirements.
  • Assess lawful basis for processing in B2B marketing when relying on legitimate interest versus consent for email outreach.
  • Implement data subject request (DSR) workflows that span multiple SaaS platforms without creating data silos or compliance gaps.
  • Adapt data retention schedules based on jurisdiction-specific regulations (e.g., CCPA, LGPD) when operating in global markets.
  • Conduct DPIAs for cross-device tracking initiatives involving probabilistic matching and device graph construction.
  • Manage data transfer mechanisms (e.g., SCCs, UK Addendums) when marketing data is processed in non-adequate jurisdictions.
  • Respond to regulatory inquiries by producing audit trails that demonstrate data minimization in audience segmentation.

Module 4: Data Governance and Stewardship in Marketing Operations

  • Assign data steward roles within marketing teams to enforce classification, access controls, and usage policies for customer data.
  • Develop data quality scorecards to monitor completeness, accuracy, and freshness of CRM data used in lifecycle campaigns.
  • Implement role-based access controls (RBAC) in marketing automation platforms to restrict data export and segmentation capabilities.
  • Standardize data naming conventions and taxonomy across teams to reduce duplication and misattribution in reporting.
  • Integrate data governance workflows into campaign launch checklists to ensure compliance before deployment.
  • Conduct quarterly data inventory audits to identify shadow marketing databases and unauthorized data sharing.
  • Establish escalation paths for data ownership disputes between marketing, sales, and customer service departments.

Module 5: Third-Party Data Partnerships and Vendor Management

  • Negotiate data licensing terms with DMPs and data co-ops to prevent downstream resale or repurposing of enriched segments.
  • Perform vendor risk assessments on email service providers to evaluate sub-processor transparency and breach notification timelines.
  • Define permissible use cases in contracts with audience data suppliers to avoid regulatory exposure from inferred categories.
  • Implement data processing agreements (DPAs) with all third-party tags deployed on owned digital properties.
  • Monitor vendor compliance with data deletion requests across cloud-based analytics and personalization platforms.
  • Assess data provenance in lookalike modeling services to ensure source audiences were collected under compliant consent frameworks.
  • Enforce data minimization in API integrations by limiting field-level access to only necessary customer attributes.

Module 6: Consent Management and Preference Enforcement

  • Configure consent management platforms (CMPs) to synchronize opt-in status across web, mobile app, and email channels.
  • Design fallback strategies for personalization engines when consent is withdrawn or not obtained.
  • Integrate preference center updates with downstream systems (e.g., ESPs, CRMs) to enforce real-time suppression.
  • Validate CMP compliance with IAB TCF v2.2 specifications for header bidding and programmatic advertising.
  • Test consent signal propagation across server-side tagging and client-side SDKs in hybrid tracking environments.
  • Document legal basis transitions (e.g., from consent to contract) for transactional email workflows.
  • Reconcile discrepancies between declared consent and observed tracking behavior during internal audits.

Module 7: Identity Resolution and Cross-Channel Data Linking

  • Select identity resolution methods (deterministic vs. probabilistic) based on data availability, accuracy requirements, and privacy risk tolerance.
  • Implement identity graphs with expiration policies to prevent indefinite linkage of pseudonymous identifiers.
  • Design fallback identity strategies for post-cookie environments using authenticated sessions and modeled identifiers.
  • Limit cross-device profiling to explicit opt-in audiences in regions with strict privacy laws.
  • Audit match rates and overlap between onboarded CRM data and platform-specific identifiers (e.g., Apple ID, Google GAID).
  • Balance personalization efficacy with privacy by suppressing low-confidence identity matches in campaign targeting.
  • Document data linkage logic for regulatory inspections and internal transparency.

Module 8: Data Monetization and Strategic Use Rights

  • Assess contractual permissibility of using first-party data for audience modeling offered to partners or advertisers.
  • Structure data clean rooms for joint campaign measurement while preventing raw data extraction by counterparties.
  • Quantify data asset value based on recency, coverage, and predictive power before entering data-sharing agreements.
  • Implement watermarking or differential privacy techniques to deter unauthorized redistribution of shared audience segments.
  • Define revenue-sharing models tied to data contribution levels in co-op marketing initiatives.
  • Restrict access to high-value data sets (e.g., high-LTV customer profiles) to pre-approved use cases and personnel.
  • Conduct legal reviews before repurposing campaign performance data for product development or M&A due diligence.

Module 9: Incident Response and Data Rights Enforcement

  • Activate data breach protocols when unauthorized access to marketing databases is detected, including notification timelines and regulatory reporting.
  • Trace data exfiltration paths in cloud marketing platforms using audit logs and access monitoring tools.
  • Coordinate with legal teams to respond to data subject complaints about unexpected targeting or profiling.
  • Freeze data sharing pipelines during vendor security incidents until risk assessment is complete.
  • Recover data rights after employee offboarding by revoking platform access and auditing recent export activity.
  • Conduct post-incident reviews to update data minimization policies based on exposure analysis.
  • Enforce data deletion across distributed systems (e.g., backups, data lakes) following formal erasure requests.