Enhance Inbound and Outbound Marketing with a Trusted Single View of the Customer

Book description

IBM Campaign® and IBM Interact are critical components in an Enterprise Marketing Management (EMM) platform. They are the foundation for optimizing your marketing campaign effectiveness, marketing operations, and multi-channel marketing execution. However, the effectiveness of the marketing campaigns is highly dependent on the quality, accuracy, and completeness of the underlying customer information used by the EMM platform. IBM InfoSphere Master Data Management (MDM) is a trusted source of that complete, accurate, customer information. Using your master data as the basis for running marketing campaigns provides the best information available for the best possible return-on-investment for your marketing operations.

This IBM Redbooks® publication describes how master data about customers is extracted from an MDM hub and delivered through an "information supply chain" to your marketing data repository. This information supply chain includes capabilities such as data integration, metadata management, industry data models, and workload-optimized analytics appliance. The intent of this book is to give marketing organizations (both the business and IT functions for marketing) a blueprint for how to architect your EMM solution in a way that best takes advantage of your trusted master data.

Table of contents

  1. Front cover
  2. Notices
    1. Trademarks
  3. Preface
    1. Authors
    2. Now you can become a published author, too!
    3. Comments welcome
    4. Stay connected to IBM Redbooks
  4. Chapter 1. Introduction
    1. 1.1 Establishing a trusted 360-degree customer view
    2. 1.2 Acting on the trusted 360-degree customer view
    3. 1.3 Combining trusted information and Enterprise Marketing Management
    4. 1.4 Mapping IBM software to the solution
    5. 1.5 Example marketing scenarios
  5. Chapter 2. Using IBM Industry Models for marketing
    1. 2.1 Two approaches to creating the marketing repository
      1. 2.1.1 Approach 1: Stand-alone data mart
      2. 2.1.2 Approach 2: Enterprise Data Warehouse (EDW)
    2. 2.2 Using IBM Industry Models to design the marketing repository
      1. 2.2.1 IBM Industry Models value proposition
      2. 2.2.2 Using IBM Industry Models to accelerate implementation
    3. 2.3 Requirements for the marketing repository
    4. 2.4 Data requirements analysis
      1. 2.4.1 Review and prepare the data requirements
      2. 2.4.2 IBM InfoSphere Business Glossary for business requirements
    5. 2.5 Use the BDW to model your data requirements
      1. 2.5.1 Extend the EDW logical model
      2. 2.5.2 Create the marketing repository logical data model
      3. 2.5.3 Create the physical models and Data Definition Language
    6. 2.6 Export your logical and physical models to Metadata Workbench
    7. 2.7 Chapter summary
  6. Chapter 3. Configuring MDM with marketing-relevant attributes
    1. 3.1 The value of a customer master
      1. 3.1.1 Person identifiers
      2. 3.1.2 Increasing confidence in your customer data
    2. 3.2 Open Service Gateway initiative (OSGi)
    3. 3.3 Business Process Management (BPM)
    4. 3.4 IBM InfoSphere MDM V11 installation on Windows
      1. 3.4.1 Planning the installation
      2. 3.4.2 Installing InfoSphere Master Data Management
    5. 3.5 Adding marketing attributes to MDM
    6. 3.6 Enhance inbound marketing with MDM
      1. 3.6.1 Creating an MDM Service Tailoring project
    7. 3.7 Deploying and Testing your web services.
      1. 3.7.1 Deploying a CBA
      2. 3.7.2 Testing an MDM web service
    8. 3.8 Summary
  7. Chapter 4. PureData for Analytics: The marketing data repository
    1. 4.1 The architecture blueprint
    2. 4.2 Roles and personas
    3. 4.3 Data integration
    4. 4.4 Metadata
      1. 4.4.1 Physical metadata
      2. 4.4.2 Lineage metadata
    5. 4.5 Data Click
      1. 4.5.1 Preparing the Data Click execution
      2. 4.5.2 Executing a Data Click activity
    6. 4.6 DataStage
      1. 4.6.1 Preparing the DataStage job execution
      2. 4.6.2 Executing the DataStage job
    7. 4.7 Summary
  8. Chapter 5. From Master Data Management to PureData for Analytics
    1. 5.1 Governance
      1. 5.1.1 Stewardship
      2. 5.1.2 Business
      3. 5.1.3 Policy
      4. 5.1.4 Quality
    2. 5.2 Automation
    3. 5.3 Summary
  9. Chapter 6. Leveraging Customer Data within IBM Campaign
    1. 6.1 EMM Omni-Channel Customer Engagement
    2. 6.2 IBM Campaign: Introduction
    3. 6.3 IBM Campaign: Concepts
      1. 6.3.1 Flowcharts
      2. 6.3.2 Processes
      3. 6.3.3 Offers
      4. 6.3.4 Cells
    4. 6.4 IBM Campaign: Process
      1. 6.4.1 Before creating campaigns
      2. 6.4.2 Example: A Customer Winback campaign
      3. 6.4.3 Mapping to customer and other data for IBM campaign
      4. 6.4.4 Defining campaign logic and configuring processes in flowcharts
      5. 6.4.5 Creating queries to identify contacts
      6. 6.4.6 Creating and managing offers
      7. 6.4.7 Assigning offers to cells in a flowchart
      8. 6.4.8 Maintaining contact history
      9. 6.4.9 Contact history and audience levels
      10. 6.4.10 Tracking responses to campaigns
      11. 6.4.11 Reports
    5. 6.5 Summary
  10. Chapter 7. Leveraging Customer Data within IBM Interact
    1. 7.1 IBM Interact overview
    2. 7.2 IBM Interact: Baseline understanding
    3. 7.3 IBM Interact: Architectural overview
    4. 7.4 IBM Interact: Process components
      1. 7.4.1 Design environment
      2. 7.4.2 Interactive channels
      3. 7.4.3 Interactive flowcharts
      4. 7.4.4 Interaction points
      5. 7.4.5 Events
      6. 7.4.6 Profiles
      7. 7.4.7 Runtime environment
      8. 7.4.8 Runtime sessions
      9. 7.4.9 Smart segments
      10. 7.4.10 Touchpoints
      11. 7.4.11 Treatment rules
      12. 7.4.12 Interact API
      13. 7.4.13 Zones
    5. 7.5 IBM Interact: User workflow
      1. 7.5.1 Design
      2. 7.5.2 Configuration and development
      3. 7.5.3 Testing
    6. 7.6 IBM Interact: Mapping tables
    7. 7.7 IBM Interact: Profile Data Services
      1. 7.7.1 Add a data source for use with Profile Data Services
    8. 7.8 Conclusion
  11. Chapter 8. Where do you go from here
    1. 8.1 Managing your information
      1. 8.1.1 Big Data
      2. 8.1.2 Multi-domain MDM
      3. 8.1.3 Information governance
      4. 8.1.4 Information virtualization and data lakes
    2. 8.2 IBM Smarter Commerce
    3. 8.3 Embracing analytics
      1. 8.3.1 Descriptive analytics
      2. 8.3.2 Predictive analytics
      3. 8.3.3 Prescriptive analytics
      4. 8.3.4 Cognitive analytics
    4. 8.4 Next best action
    5. 8.5 Summary
  12. Related publications
    1. IBM Redbooks
    2. Other publications
    3. Online resources
    4. Help from IBM
  13. Back cover

Product information

  • Title: Enhance Inbound and Outbound Marketing with a Trusted Single View of the Customer
  • Author(s): Chuck Ballard, Jon Case, Deirdre Clyne, Brett Hildreth, Holger Kache, David Radley
  • Release date: March 2014
  • Publisher(s): IBM Redbooks
  • ISBN: None