Matt Dimond, Solutions Consultant, BlueVenn discusses the process of creating the Golden Record and use cases for media organizations to use a Customer Data Platform for maximizing and optimizing subscriptions and the retention timeline

1. October 14th 2018
Creating and using the ‘Golden
Record’

2. Analyze &
Report
Segment
& Target
Journey
Orchestration
Communicate
& Engage
Interact
Collect
Cleanse &
Consolidate
Enhance
& Present
CDP
Process
SCVReal-time
Behavioral
Triggers
Customers
3rd Party Data
ID Resolution
DMP
Marketing

3. The Golden Record
Rebecca Ann Johns
Ms R A Johns
Becky Johns
Rebecca Moor
Rebecca Johns

4. Single Customer ViewCustomer Data Platform
Customer Data Platform

5. Single Customer ViewCustomer Data Platform
Customer Data Platform

6. Single Customer Viewata Platform Channel
Title
Customer Data Platform
Business
Specific
Project
Specific
Platform
Specific
Prospect
Subs.
Status

7. Identify Source Systems
• Identify operational systems that contain customer data
• e.g. base customer data, registrations, ERP, transactions,
communication history, responses, website clickstream etc.
• Data could come from anywhere
• Data typically will be in multiple locations

8. Getting the Source Data
• Do you currently have access to the source data?
• How will you receive the data?
• e.g. FTP, secure FTP, API, direct ODBC connection, emailed?
• How frequently do you require/can you obtain it?
• What format(s) will it arrive in?

9. Extract, Transform and Load Source Data
• Load data from the operational source or feed
• Verify the data and make use of threshold checking
• Use audit logs to maintain records
• What happens if the data doesn’t arrive?
• What happens if safe thresholds are breached?

10. Source Data Storage
• Maintain a source-coherent structure
• Store source data in an auditable format
• Date stamp incremental data loads
• Think data traceability

11. Conditioning and Validation
• Condition data, parsing it and standardizing it
• e.g. date formats, currencies, address formats etc.
• Validate and clean contact information
• Use third-party reference files where appropriate
• Name, address, business addresses, telephone, email address
• Clean data improves match rates later
• Additional processing, e.g. salacious data screening
• What happens if safe thresholds are breached?

12. Finalise Source Staging
• Final staging of source data
• Clean, auditable, traceable copy of operational source
• Maintain historical record of changes at source level
• Schema designed as a ‘stepping stone’

13. Match, Merge and Deduplicate
• For each record, match the record against the ‘master’
• Match thresholds should be iteratively improved
• Use business rules to decide matching priority
• Deduplicate records, maintaining full audit trails
• Consolidate records preventing orphaned data
• Data survivorship rules and trust thresholds
• What happens if safe thresholds are breached?

14. Consolidated Data Sources
• Single customer view base schema
• Master record for each customer
• Schema designed to support many ‘views’ of the data
• Maintain change history
• Ensure each element has traceability and field ancestry

15. Enhancement, Auditing and Governance
• Apply third-party enhancements
• Apply data suppressions
• Full audit reporting, ‘subject access request’ capable
• Full governance of all data processing and source
• Legislative compliancy (current and future)

16. Validate Data Links, Cross-Source Validation
• Cross-source links to promote
• Data normalization
• Complex calculations
• Specific views

17. Structured Single Source of the Truth
• Consolidated, clean single record for each customer
• Single Customer View for any department
• Presentation layer underpins analytics, campaign
management, selections, targeting and modelling
• Single Source of the Truth

18. Creating the Single Source of Truth
• All processing steps customized for each data source
• Sources will arrive at different frequencies
• Assumes that all data may change
• Risk-mitigated, governance-based, persistent record

19. Single Customer ViewDataCustomer Data PlatformData
Ownership is Key
• Your Customer Data Platform underpins performance,
measurement, iterative improvement and is your asset
• Critically we ensure it belongs to you

20. Rebecca Ann Johns
Ms R A Johns
Becky Johns
Rebecca Moor
Rebecca Johns
Using the Single Customer View
• Consolidated data view
• Solves data quality issues
• Solid data foundation
• Powers better insight
• Enables advanced segmentation and analysis
• Retention/renewal
• Cross sell
• Upsell
• Acquisition
• Enhanced personalisation of Customer Journey
• Multi-department benefits

21. Intuitive browser-based application to empower
marketers to understand and engage the
omnichannel customer at real-time
• Browser-based
• Intuitively & visually plan
customer journeys
• Omnichannel
• Real-time capable
• Automated segmentation
• Built-in machine learning to
predict customer behaviour
• GDPR compliant
Marketing Automation & Customer Analytics

22. Thank You