Presented by Sheila Colclasure, Global Public Policy and Privacy, Americas Officer at the 2013 Racom IMC Roundtable. More info on this event at cadmef.org.

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BIG DATA

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Data is Gold

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Customers’ Lives Are Constantly Changing
Every hour of every day
5,769 people changed jobs
2,748 people moved
509 people were married
244 people got divorced
186 people declared bankruptcy
These people are your customers

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Traditional Data and Data Solutions
Data Application
• List Data for Customer Acquisition
• Enhancement Data for Upsell, Cross-sell, CRM
• Intense Data Analytic Driven Segmentation
• Postal Address Cleansing
• Locate, Look Up, Verify
• Customer Recognition
Direct Marketing/Addressable Media:
• Call Center
• Direct Mail
• Direct eMail
• Brick and Mortar

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Channels Are Multiplying Rapidly New Types of Data
Exploding Volume Escalating Velocity

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Data Elements in Play
Marketing Layer On and Offline – Anonymous and PII
 Shopping behavior
 Viewing Behavior (Digital TV)
 Geo-Location (Mobile Device)
 Browsing behavior
 Click stream
 Purchase behavior
 Demographics, Sociographics
 Life Stage
 Analytics and Segmentation
 Spotlights, Footlights
 Cookies
 Email behavior – click and open
 Social Network Data
 # of Networks
 # of Friends
 Likes, Interests, Mentions
 Blog Data
 Preference data
 Response data
 Pings
 Precise Geo w/n a store
 Cookie syncing
 Container tags
 Offline to online

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Marketing
Online
Mobile
Set Top
Box
Risk
Fraud
Authentication
Verification
Identity
Marketing and Risk

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BIG DATA

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Agenda
•Landscape is Changing
•Attitudes about Big Data
•Spotlight on Data Brokering and Marketing
•Implications for Data Content and Data Enablers
•Implications for Users of Data
•What is Expected of Stakeholders
•Questions
9

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Acxiom’s Privacy and Compliance Team
•Acxiom has been big data for over two decades and been at the forefront in
data protection and privacy matters
•Pioneered innovative privacy solutions, creating the foundations for what are
now standard practices in many industries.
•One of the most advanced and robust privacy programs in the world helping
clients be compliant and improve business results
•Most experienced privacy team in our industry which is regularly sought after
by clients, policy makers and regulators
•Maintain strong relationships with key policy makers and regulators in the US
and abroad.
•Provide innovative approaches to maximize the value of data while
understanding the risks involved
Privacy Permission Practices

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Privacy Permission Practices
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Acxiom’s Privacy and Compliance Team
General Counsel Jerry Jones
Global Public Policy and Privacy Executive Jennifer Glasgow
Global Compliance Risk Leader Tim Spainhour
Americas Team
Public Policy and Privacy Officer Sheila Colclasure
Compliance Legal Leader Jordan Abbott
Compliance Legal Attorney Kimberlin Cranford
Data Content Compliance Legal Attorney David Reckert
US Marketing Data Products Compliance Melisa Aebly
US Risk Products Compliance Maxlyn Wanner
US Consumer Care Advocate Alice Beaton
Kelli Chase
EU/EEC Team
EU Privacy Officer Sachiko Scheuing
UK Officer Alex Hazell
French Privacy Officer Sarah Wanquet
German Privacy Coordinator Dr. Sachiko Scheuing
Polish Privacy Officer (Data & GSC) Michal Kacxorowski
Australian and New Zealand
Privacy Attorney Julie Dennis
Officer Karina Boscolo
Asian Privacy Officer Dr. JJ Pan

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Landscape is Changing
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Law and
Regulations
versus
Expectations
Big Data = Big Compliance
Big Data = Big Security

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Landscape is Changing
•Attitudes about Big Data
•Data Minimization
•PII vs Anonymous
•Sensitive Data Evolving
•Analytics & Automated Decisions
•Accountability
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Law and
Regulations
versus
Expectations

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Attitudes about Big Data
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20 Years of Consumer Attitudes
60% Pragmatist
30% Fundamentalist
10% Unconcerned
Examples of Big Data individuals can understand…
Search is Big Data for consumers.

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Attitudes about Big Data
•Individuals
• Some concerned about commercial surveillance
• Few concerned about government surveillance
•Consumer Advocates and Policy Makers
• Business only after profits
• Protect individuals from themselves
• Need for transparency
• Concern about secondary use
• Concern about too much data
• Concern about robust analytics
15

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Data Minimization vs Big Data
•Increasing Commercial Surveillance
• Online (Search, Behavioral, etc.)
• Mobile (Location)
• Interactive TV
• Movies & Video
• Social Media (Social Networks, Blogs, Chat)
• Facial Recognition
• Apps
•International Perspective (especially EU)
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Television
Mobile
Online
Retail
Facial
Recognition
Minimize what?

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100% 0%
PII vs Anonymous – Definitions
Device
Identifiable
Information
Anonymous
Choice
Notice
X
De-Identified
Information
XPersonally
Identifiable
Information
Aggregate
Information
Pseudo-
anonymous
/
/
Personal
Pseudo-
anonymous
PII DII AGIDe-ID
SANI
ANIPII
SANI
Covered Information
Ease of Technical Re-identification

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Sensitive Data Evolving
•Historical Sensitive Commercial Data
• Identification
• Financial
• Medical
•New Categories of Sensitive Commercial Data
• Specific location
• At-risk populations (children & elderly)
– Raise the age for COPPA from under 13 to 18
• Social network information (public & non-public)
• Biometrics & Facial recognition
• Modeled Data
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Finances
Identification
Medical
Social Networks
Biometrics
At Risk
Populations
Facial
Recognition
Location

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•Effectiveness of Analytics
• Modeling
– Identifying & Justifying Predictive Data
• Application of Models
– Scope Creep & Secondary Uses
•Risks with Automated Decisions
• “Boxing in” Individuals
• Discrimination & Profiling
• EU Fear of Automated Decisions
Analytics & Automated Decisions
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Big Data = Big Analytics

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New Privacy Principle: Accountability
•Accountability Principle (CIPL Project)
• Authorize Someone to Oversee Privacy – Chief Privacy Officer
– Need some independence/authority to have credibility
• Implement Written Policies that Conform to External Criteria
• Build Privacy into Agency Processes / Systems (e.g. Privacy by Design /
Privacy Impact Assessments)
• Review Policies & Practices Periodically (Assessment or Audit)
• Provide Effective Redress to Individuals
•Adoption
• Unofficially Adopted by Regulators before Officially Required by Law
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•Behavioral Advertising
•Using Offline Data for Online Advertising
•Mobile Marketing
• Location
• Mobile IDs
•Digital TV
•Cross-border Data Flows
Self-Regulation (Co-Regulation)
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Companies must go beyond what is required by law!
Must work on and anticipate more self-regulatory
guidelines = new policies.

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•Policy Makers
• Way Behind the Times
• Reactive to Incidents
• Don’t Understand
– Technology
– Value of Data
– Protections Available
•Supreme Court and Lower Courts Engaged
•Data Broker Legislation (2-3 years?)
Legislation & Courts
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Self-regulation can set the
stage for workable
legislation.

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•House Privacy Caucus
• Congressmen Markey & Barton
•Senate Commerce Committee
• Senator Rockefeller
•Federal Trade Commission (FTC)
• Commissioner Julie Brill
• Aggressive Consent Decrees
•General Accounting Office (GAO)
•States Attorneys General
Spotlight on Data Brokers & Data Services
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Media attention high!
Client inquiries increasing.

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Implications
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•Evolve Policies and Practices
•Greater Visibility with Consumers
•Comply with All Policies
•Sustain Privacy Leadership Position
•Promote Self-Regulation
•Evolve Acxiom Policies
•Develop Compliant Products and Services
•Be Proactive with Clients
•Be Careful with Partners and Suppliers
•Be Careful about Messaging
•Promote a Compliance Culture

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•Don’t Understand 3rd Party Obligations
•New Anonymous Online Rules Prevent
Common Offline Practices
• Closed Loop Marketing
• Open Loop Marketing
•Increased Risk of Non-compliance
Implications for Users of Big Data
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Be a trusted
vendor.

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What is expected of Big Data Industry?
•Learn the rules for area/industry.
•Question what doesn’t seem to fit those rules.
• New approaches
• New products
• Short cuts / workarounds
•Help assure compliance all the time.
•Learn from media and enforcement examples
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Call privacy team if you have ANY
doubt/question.

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TRUST
Clients Policy Makers
and Regulators
Consumers
Hyper-Transparency
Future Depends on…

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Questions?