© 2013, HSI
DATA GOVERNANCE
Peg Kuman, CIPM
Vice Chairman, Relevate
Gina Scala
Vice President Education, The DMA
© 2013, HSI
What is Data
Governance?
© 2013, HSI
Data Governance encompasses:
• Privacy
• Security
• Data Stewardship
• Data Provenance (Rights Management)
• Data Privacy
Management
implementing
processes, roles,
controls - all of which
treat information as an
asset that needs
...
• Data Security
protecting your
data against
damage, loss,
danger, and
crime.
Security
© 2013, HSI
Data Stewardship
• The intentional collaboration of all the
data stakeholders to insure accurate,
safe, and re...
Data Provenance
• Data Provenance
–Ownership,
–Access,
–Use,
–Rights
Management
© 2013, HSI
Benefits of Marketing Data
Governance:
• Let’s you set the corporate tone for your brand
[Social media has rob...
© 2013, HSI
Data Governance Drivers:
• Scale
• Global
• Innovation
• Profit
• Regulation
• The Media
© 2013, HSI
Today and Tomorrow
• Part 1: The Big Data Landscape- Light speed-150 minutes of
where we came from and where w...
© 2013, HSI
Peg’s Promise
• 4 revenue producing ideas that will drive new
growth by the end of Q1 2014
PROFIT
GROWTH
INNOV...
© 2013, HSI
A few insights from a
BIG fan of BIG DATA
Introducing
Christy UherFerguson
Director,
Communications
Strategy
at Teradata
© 2013, HSI
Big and Speed get Attention
© 2013, HSI Source: edCetra, 2012
© 2013, HSI Source: edCetra, 2012
© 2013, HSI Source: edCetra, 2012
© 2013, HSI Source: edCetra, 2012
© 2013, HSI Source: edCetra, 2012
© 2013, HSI Source: edCetra, 2012
© 2013, HSI Source: edCetra, 2012
THAT’S ENOUGH INFORMATION TO FILL
135.7 BILLION 64 GIG iPADS
Source: edCetra, 2012
© 2013, HSI
How did we get here?
• America leads the information revolution!
• USPS established by the Continental Congres...
© 2013, HSI
1744 - Addresses and Lists
• Oh, what to sell?
• In 1744 Benjamin Franklin published a catalog which sold
scie...
© 2013, HSI
1848 – HammacherSchlemmer
• In 1848 Alfred Hammacher created a
mail-order business, Hammacher
Schlemmer, in Ne...
© 2013, HSI
1856 - Orvis
New England Fishing Catalog
1872 – Montgomery Ward
• Aaron Montgomery
Ward is credited with
mass mailing the first
mail-order catalog in
1872 for Mont...
1888 – Sears, Roebuck
• RW Sears sold
watches and jeweler
through self-mailers
in 1888.
• The first Sears and
Roebuck cata...
© 2013, HSI
The Survivors and the Vanished
• All but MW have innovated their brands and
today have migrated to a gentle pu...
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
And today:
© 2013, HSI
Marketing Data…
is the key driver to revenue and profits
across ALL brands,
Both B2C and B2B
© 2013, HSI
Data Driven Marketing
Has Leverage
• 8.7% GDP
• $168 Billion Spend
• $2.05 Trillion Sales
• 9.2 Million Jobs
© 2013, HSI
Revolutionary Changes
“The growing ability to collect and analyze
massive sets of information, known as Big
Da...
© 2013, HSI
Effective Government
“From election campaigning to setting
NASA's budget to prepping for the next big
natural ...
THIS CHANGE IS BEING
LOOKED AT BY:
THE MEDIA
REGULATORS
CONSUMERS
©2012 Heart Safety, Inc.
Threats Are Growing Every Day
• Congressis investigating data-driven marketers and fundraisers for
basic marketing practic...
© 2013, HSI
We are in a time of
DRASTIC CHANGE
“We are migrating from a PUSH marketing
world to a PULL marketing world, an...
PUSH
• Creating DEMAND -
where the marketer
controls the message
and the type of
response
PULL
• Creating demand where
the responder controls
the message and the
decision how and by
which means to
respond.
• With...
© 2013, HSI
What age are we in?
40’s, 50’s,
60’s
Brand
Creation and
Expansion
Mass Advertising - National Coverage
Interne...
© 2013, HSI
Where are we in terms of
usability?
Available
Usable
© 2013, HSI
How much OFFLINE data is there?
• Offline - we have over 100 years of knowledge & data.
• Finite…
© 2013, HSI
How much ONLINE data is there?
• Online & Emerging Channels - we have ~ 40 years of
knowledge and ~ 19 years o...
© 2013, HSI
So, The Rules of the Road for
Offline Data are …
• Are pretty well established
• Possess behaviors that are ea...
© 2013, HSI
But, then Online comes along…
•ARPANET
1969
•First
email
sent
1971
• BBS Bulletin
Board System
1978
•Usenet
go...
© 2013, HSI
And THEN ‘social’ explodes…
• 2002 Friendster
-(3M users first 3 months)
• 2002 LinkedIn
• 2003 MySpace
• 2004...
© 2013, HSI
Explosive Statistics
• One out of every seven minutes spent online is on Facebook
• 340 million tweets are sen...
© 2013, HSI
Estimated Monthly Unique Visitors
to SNS in August, 2013:
•1,000,000,000 - You Tube
• 750,000,000 – Facebook
•...
© 2013, HSI
Social Sites To Watch in 2013
• Pheed- pay as you go access to celebs
• Thumb - personal crowdsourcing
(thumbs...
Translation:
• Control by PUSH is
GONE!
• Social KILLED it.
• We are learning
how to PULL the
buyer into the
conversation
© 2013, HSI
Our SOCIAL world is a
BIG Data world
We Live in BIG Data…
• One out of every seven minutes
spent online is on Facebook
• 340 million tweets are sent each and
e...
© 2013, HSI
What Consumers Do:
Sources: Infographic Digital Buzz Blog,
• Instagram- By May of 2012, 56 photo’s
and a new u...
© 2013, HSI
Dataportunity?
What will we do?
• Where are the opportunities?
• Where are the pitfalls?
• And where can you h...
Oreo dunked a
timely moment during
the Super Bowl’s
unexpected power
outage.
• Oreos tapped into a timely moment
at the Su...
© 2013, HSI
© 2013, HSI
Social Media Enables Targeted Marketing Responses at Individual
Touch Points along the Consumer Decision Journ...
© 2013, HSI
Confluence of Multiple Media, Channels, and
Touches
• Pushes all of us into new opportunities
• Experimentatio...
© 2013, HSI
Cases in Point
• Let’s look at this confluence of multiple touch
points and influences…
• To set the stage - s...
© 2013, HSI
P O T T E R Y B A R N
© 2013, HSI
Pottery Barn
• 1949 - Began in Lower Manhattan
• 1986 - 21 PB stores bought by Williams-Sonoma, Inc.
• 1987 - ...
© 2013, HSI
PB Multi-Channel Growth - Great PUSH
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
PB Multi-Channel Growth
• 196 Stores nationwide
• 150 million+ catalogs a year
• Targeted Daily Online Web Off...
© 2013, HSI
Let’s Look at Mobile
© 2013, HSI
Mobile is PUSH
• All 100% opt-in
• Mobile marketers call ‘PUSH’
a new channel for brands to
better socialize w...
© 2013, HSI
App Happy…
• iPhone has over 900K Apps
• Google claims 800K+ for
Android…
• Each App, collects data and
each a...
2013 Top Mobile Apps
• Google Maps
• Facebook
• YouTube
• Google+
• Weixin/WeChat
• Twitter
• Skype
Source: Mashable. 8/20...
© 2013, HSI
58 Mobile Minutes….
© 2013, HSI
Time and Privacy
• Smartphone owners spend more time today – 58
minutes, than in 2012- 39 minutes, and 2011- 3...
© 2013, HSI
Mobile is getting bigger…
© 2013, HSI
M-Commerce
• The 2012 eMarketer report shows that the
growth in m-commerce sales will be as
follows:
+$11.6 Bi...
© 2013, HSI
And Bigger….
• Mobile web adoption is 8 times faster today than
web adoption in the late 1990’s/early 2000’s.
...
© 2013, HSI
By the end of 2013:
• Mobile commerce from iPhones =
5% of retail sales
• 56% of mobile users in the US now
us...
© 2013, HSI
And by the end of 2013
There will be more mobile
devices on Earth than
people.
Source: Cisco, 2013
9 out of 10 Mobile Searches Lead to
Action
and over half
lead to a
purchase
Source: Search Engine Land
But what happens to the data
and information that can be
scraped?
Mobile is 100% Opt-in
© 2013, HSI
HOW traditional
brands use media to build
“e” responders, accelerate
mobile and engage with
social
© 2013, HSI
Data ROI - Social
Nike/Facebook Video
Nike
© 2013, HSI
LBM- Location Based Marketing
• Opt-in Mobile
• Meat Pack- Hijack
LBM- shoes…..
• SMS, MMS
• Sweeps for $10K Scholarship
• Plus 5 $1K winners
• Buzz, Participation and excitement leading up
to last Frid...
Marketers are embracing the
Mobile channel with
Innovation and Experimentation-
Driving Media and Regulators to
Amplify Th...
© 2013, HSI
Geo—Navigational + Social
• WAZE : GOOGLE
• Company: Waze
• Website: waze.com
• Launch Date:2007
• Funding:
• ...
© 2013, HSI
Google buys Waze- up to 50M users by June
© 2013, HSI
Q1 2013
• A rise in active engagement across all social platforms
with Twitter the fastest growing
• Local soc...
© 2013, HSI
Q1 2013
• Older internet users are also driving social platforms
growth globally
• Google+ remains the number ...
© 2013, HSI
• On Twitter the 55-64 year age bracket is the fastest
growing demographic with 79% growth rate since
2012.
• ...
© 2013, HSI
As Audiences Get Older Trust is
a Key Factor
© 2013, HSI
Trusting Social Media
• Social media engagement requires trust, authenticity and transparency
Nielsen Global T...
© 2013, HSI
1. AMEX
2. HP
3. AMAZON
4. IBM
5. USPS
6. P&G
7. USAA
8. NATIONWIDE
9. eBAY
10. INTUIT
11. VERIZON
12. J&J/ FED EX
13. WEB...
© 2013, HSI
Why are they trusted?
• Privacy Features on Transactional Sites
• Substantial Security Protections were identi...
© 2013, HSI
What Consumers Fear Most
• Losing Control of Personal Information. Only 35
percent of consumers feel they have...
© 2013, HSI
Fear and Trust =
A formula for Regulatory and
Congressional Review– even
though the Government is the
number 1...
© 2013, HSI
And so: The FTC Tackles Mobile
• Should’s for Mobile Platforms
• Should’s for App Developers
• Should’s for Ad...
© 2013, HSI
Mobile Platforms Should:
• Provide just-in-time disclosures to
consumers and obtain their
affirmative express ...
© 2013, HSI
Mobile Platforms Should:
• Consider providing just-in-time
disclosures and obtaining
affirmative express conse...
© 2013, HSI
Mobile Platforms Should:
• Consider developing a one-stop
“dashboard” approach to allow
consumers to review th...
© 2013, HSI
Mobile Platforms Should:
• Consider developing icons to depict the
transmission of user data;
• Promote app de...
© 2013, HSI
Mobile Platforms Should:
• Consider providing consumers with
clear disclosures about the extent to
which platf...
© 2013, HSI
Mobile Platforms Should:
• Consider offering a Do Not Track (DNT)
mechanism for smartphone users. A
mobile DNT...
And Congress is Full of Ideas
In the 113th Congress, legislators
in both the House and Senate
rushed to “make their marks”...
© 2013, HSI
Good, Big and Ugly
Whether you think Snowden is
a whistle-blower or a traitor, no
matter. But know that very
b...
© 2013, HSI
© 2013, HSI
Data Loss Incidents 2003-
2013
Source: Open Security Foundation, DataLossDB
0
200
400
600
800
1000
1200
1400
1...
Incidents By Loca on- 2003-2013
Government- 18%
Medical- 15%
Educa on- 15%
Businesses-52%
Source: Open Security Foundation...
Incidents By Type- 2012-2013 YTD
Hack- 56%
Fraud- 9%
Web- 5%
Stolen Laptop- 7%
Stolen Docs- 3%
Email- 2%
Virus- 2%
Stolen ...
Top Target Countries for Hackers
© 2013, HSI
Who Tracks This?
• The Open Security Foundation (OSF) is a 501(c)(3)
non-profit public organization founded an...
© 2013, HSI
Customer View and Marketing
Fear, Theft, Breach, Bad behavior dial
up the need for consolidated Data
Governanc...
© 2013, HSI
Criminal Data Breach Video
Anti Sec I
© 2013, HSI
Unintentional Data Loss Video
Toy Story 2
© 2013, HSI
DATA GOVERNANCE
Peg Kuman, CIPM
Vice Chairman, Relevate
Gina Scala
Vice President Education, The DMA
© 2013, HSI
© 2013, HSI
WHAT WE KNOW:
• Marketing use is still evolving…and will continue to do
so
• What works and why - we remain in...
© 2013, HSI
Sourcing, Typing and Classifying
Control
Minimize
Risk
Insight and
Growth
© 2013, HSI
Data is a collection of facts – such as
values or measurements - it can be:
 Numbers
 Words
 Measurements
...
© 2013, HSI
Classifying Data-
• Data is either:
• Quantitative,
• Qualitative,
• Or a blend of both.
• Quantitative Data -...
© 2013, HSI
What is Marketing Data?
• Marketing Data - is a collection of facts that when
looked at together becomes infor...
© 2013, HSI
Where does it all come from?
Marketing data comes from –
• your prospects
• your customers
• your partners
• t...
© 2013, HSI
Where does it all come from?
Marketing data comes from all corners of your brand
- your marketing initiatives
...
© 2013, HSI
Where does it all come from?
• Marketing data also comes in the form of:
• Brand mentions from Facebook and Tw...
© 2013, HSI
What does it look like?
• The customers and prospects information
may include:
• names
• email addresses
• phy...
© 2013, HSI
What does it look like?
• The customers and prospects information
may also include:
• attitudes
• sentiments
•...
© 2013, HSI
Sourced Through:
• Customer transactions
• 3rd Party Data [demo’s, psycho's, firmo’s]
• 1st Party Data [demo’s...
© 2013, HSI
Sources for Marketing Data
• Examples:
Customer Transactions
 Inquiry, Request for Info, Survey
 Order Place...
© 2013, HSI
First Party Data - The ‘Owner’
• In the Offline world -
• The company that owns the data -
customer files, cus...
© 2013, HSI
Third Party Data
• In the Offline world -
• Data that is compiled, aggregated, assembled from
public or propri...
© 2013, HSI
Third Party Data
• Be Informed:
• Know who the providers are, know their
privacy and information policies and
...
© 2013, HSI
Online Third Party Data
• Third Party Data Collection
• Defined by Companies that collect either PII
or non-pe...
© 2013, HSI
Online Third Party Data
• Third Party Data Collection
• The Company uses a Domain to collect the
information t...
© 2013, HSI
Online Third Party Data
» There are different types of Third Party Data Collectors
not all of which collect da...
© 2013, HSI
Third Party Data
• Not all Third Party Data Collectors collect data for the
purposes of marketing but provide ...
© 2013, HSI
Types of Marketing Data
1. PII and Sensitive Data
2. Public
3. Private/IP
4. Anonymized
© 2013, HSI
1. PII - Personally Identifiable
Information
• PII is Personally Identifiable Information
• Information that c...
© 2013, HSI
DMA: PII
• Marketers should be sensitive to the
issue of consumer privacy and should
only
collect, combine, re...
© 2013, HSI
Examples of PII
Health Related PII-
 Illnesses or conditions
 Treatments for those illnesses or conditions, ...
© 2013, HSI
Sensitive or Intimate
Information
• Data and selection criteria that by reasonable
standards may be considered...
© 2013, HSI
PII – Credit Card Numbers
• Credit card numbers, checking account
numbers, and debit account numbers are
consi...
© 2013, HSI
PII – SS Numbers
• Social Security numbers are also considered
to be personal.
• Social Security numbers, howe...
© 2013, HSI
Linked Information
• Information about an individual that
is linked or linkable to one of the PII
attributes
(...
© 2013, HSI
Even in Digital Marketing
• ALL information that can be
linked back to an individual is
considered PII
© 2013, HSI
Context
• Identifiability. Organizations should evaluate how easily PII
can be used to identify specific indiv...
© 2013, HSI
Context
• Data Field Sensitivity. Organizations should
evaluate the sensitivity of each individual PII
data fi...
© 2013, HSI
Context of Use
• Context of Use. Organizations should evaluate the context of
use—the purpose for which the PI...
© 2013, HSI
Non-PII
Context
PII
Can be linked
To an individual
Sensitive PII
SSN
Health Related Info
Account Information
D...
© 2013, HSI
PII Summary - Marketing
• Name linked to Address
• Email Address linked to N/A
• Name linked to Phone
© 2013, HSI
PII Summary- Sensitive
• Medical Records
• Biometric Information
• Place of Birth
• SSN
• Personnel Records
• ...
© 2013, HSI
Protecting PII
1. Required by Law
1. Prevents Identity Theft
2. Best Practice
© 2013, HSI
2. Public Data
• Data and information that is in the
public domain. Not private.
Examples:
• Public Directorie...
© 2013, HSI
© 2013, HSI
3. Private/IP- can be PII or
Non-PII
• Data that is private:
• Data not shared and unique to the company
based...
© 2013, HSI
Private/IP cont’d
Examples:
• Customer Transactional Data
• Contractual
• Customer/Share of Wallet
• Customer ...
© 2013, HSI
4. Anonymized Data
» Anonymous data is defined in numerous ways
depending on the data type, collection method ...
© 2013, HSI
4. Anonymized Data
» Using cookies to anonymize data:
• Cookies are machine specific and work in
a name/value ...
© 2013, HSI
Cookie Shortfalls
• Cookies get erased
• People use multiple machines
• People often share a machine
• Cookies...
© 2013, HSI
Cookie Benefits
• Improved user experience
• Ad serving and re-marketing completely
anonymous
• No PII and no ...
© 2013, HSI
Unpacking AnonymizedData
• Can you truly anonymize data?
• PII conversion to cookies using IP and email addres...
© 2013, HSI
What’s After Cookies?
“The Web Cookie Is Dying. Here's The Creepier
Technology That Comes Next”
Source: Forbes...
© 2013, HSI
Why Fingerprinting?
© 2013, HSI
It Eliminates Cookies Flaws
• Fingerprinting allows a web site to look at the
characteristics of a computer su...
© 2013, HSI
And- Cookies don’t work on mobile
© 2013, HSI
Scale
• The Electronic Frontier Foundation has found
that 94% of browsers that use Flash or Java –
which enabl...
© 2013, HSI
My browser has
21.67 bits of uniquity
© 2013, HSI
Panopticlick
https://panopticlick.eff.org
© 2013, HSI
The Marketing Data Eco System
Transactional
Data
Sensitive
Data
Marketing
Data
Credit Data
Summarized
Credit D...
© 2013, HSI
Data Use is Complex!
• Where does it reside?
• How is it classified?
• How is it defined?
• Who uses it?
• Who...
© 2013, HSI
Connecting Use to Where
Data Resides
1. List all of the locations your data resides (that
you are aware of).
2...
© 2013, HSI
Data Use
Show of hands:
•How many of you have ever sent data via email?
•Unencrypted?
•Unzipped?
Photo Ref: ht...
© 2013, HSI
Data Use
Does Data Have a Life-cycle?
• Data comes from
inception, aggregation, compilation, licen
se…
• But d...
© 2013, HSI
Life-cycle Determinants –
Keep forever or Kill
» Frequency of updates
» Changes in the data itself
• (deceased...
Controlling Data Use
–Physical Controls
–Virtual Controls
–Contractual
Controls
–Audit Rights
Who has access?
Who controls...
© 2013, HSI
Vulnerabilities
for Use and Misuse
© 2013, HSI
Removable Media
• How many times have you used a
thumb drive… and how do you control
among those who have data...
© 2013, HSI
ACCESS
• What do your employees have?
• What do they know, what do they see?
• Contact Lists
• NDA’s, Contract...
© 2013, HSI
How Do You Handle
Media Disposal?
End of life policies for data:
• Do your business contracts address
this?
• ...
© 2013, HSI
Wireless Networking
• Are you and your colleagues trained on
the basics? [i.e. turn off sharing, enable
firewa...
© 2013, HSI
Electronic Messaging
IM and SMS – limited use?
• Gchat
• Skype
• AIM
• Facebook
• Twitter
© 2013, HSI
Mobile Devices and
Acceptable Use
• Laptops, PDA’s, and Remote Access
• What should mobile users know?
© 2013, HSI
Best Practices for
Managing Use and Access
•Know your inventory:
•By Application
•By Location
•Know your users...
© 2013, HSI
Best Practices for
Managing Use and Access
• Communicate access rules to all
• Create Policies, Processes, and...
© 2013, HSI
Data Provenance
• Who owns the data?
© 2013, HSI
So, Who owns the data?
•The primary source?
•The aggregator/compiler?
•The enhancer?
•The consumer?
Thoughts?
© 2013, HSI
Who owns the data & data agreements?
• Rental
• License
• Co-op’s
• Shared
• Exchanged
At what point in time d...
© 2013, HSI
Defining Data Ownership is Difficult
• We share, friend, check in and tweet our every move.
• We log on, log i...
© 2013, HSI
Why Data Ownership is Difficult
• Our laws have focused on physical ownership or assets
that couldn’t be easil...
© 2013, HSI
It’s What We As Marketers Do With Data…
• The important question isn’t who owns the
data. Ultimately, we all d...
© 2013, HSI
We Are All Data Stewards
• Accurate, Safe, Responsible
Use of the Data
• We will view the impact of
monetizing...
© 2013, HSI
DATA GOVERNANCE
Peg Kuman, CIPM
Vice Chairman, Relevate
Gina Scala
Vice President Education, The DMA
© 2013, HSI
© 2013, HSI
Circling Back
Putting the Data to Work:
© 2013, HSI
Cracking the Code-
A work in progress
© 2013, HSI
Getting to Attribution
ROIOffline
Data
Ecomm
Data
Digital
Data
Social
Data
Enhanced
Data
Behavioral
Data
Multi...
© 2013, HSI
Discovery
• What are you doing to drive response today?
• What will you be adding?
• How are you caching the r...
© 2013, HSI
Where Does The Customer
Interface Occur?
• Social
• Digital
• On-line
• Off-line
• Where are the locators?
• W...
© 2013, HSI
Who is your customer?
• Transactional and Behavioral
• Building persona’s
• Implementing the Models
• Test and...
What is Your Spending By Channel?
• Print
• Broadcast
• Direct Mail
• In Store / Face-to-Face
• E-mail
• Social
– Blog
– T...
What is Your Spending By…
• SKU? • Segment?
© 2013, HSI
Tracking Frequency of Response
• To understand how channel performs
• To identify channel preferences
• To fig...
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
© 2013, HSI
Finding the Bright Lines
• Unknowns
• Market Oppy- opportunity segments, channels
• Staged approach
• Keep wha...
© 2013, HSI
Big Data / Changing Structure
Analytics
Attribution
Marketing
Intelligence
and Insight
© 2013, HSI
Structure Changes When
Looking at the Data Ecosystem
Holistically-
• Shared
• Not Shared
• Anonymized
© 2013, HSI
Death by Silo
© 2013, HSI
Old Data Governance
© 2013, HSI
Old Data Governance
© 2013, HSI
New Data Governance
• Positioning and integrating allbusiness
functionsinto your data governance mix
throughou...
© 2013, HSI
New Data Governance
© 2013, HSI
DATA GOVERNANCE
Peg Kuman, CIPM
Vice Chairman, Relevate
Gina Scala
Vice President Education, The DMA
© 2013, HSI
© 2013, HSI
Business Cases –
Success and Failure:
• Case Study: Global Differences
• Case Study: Gold Standard of Consent
...
The Stakeholders
• InfoSec
• Sales/Biz Dev
• Marketing
• C-Suite
• IT/Technology and Infrastructure
• HR
• Vendors/Partner...
© 2013, HSI
Why We Need Best Practice:
Data as The Regulators See It:
Pizza Pie Order
© 2013, HSI
Best Practices
Marketing Data Governance
© 2013, HSI
Key Safe Harbor Principles
1. Notice
2. Choice and Opt-out
3. Onward Transfer
4. Access
5. Security
6. Data In...
© 2013, HSI
Notice – Defined
Providing notification to your customers
and prospects how you collect and use
information ab...
© 2013, HSI
Examples of Notice
Google, Facebook, Apple and most major
brands tell the customer that their use of
data is t...
© 2013, HSI
Choice and Opt-Out
Give consumers the opportunity to
choose whether their PI will be disclosed
to a third part...
© 2013, HSI
Disney
• Provides for Categorical Opt-Out.
• They clearly state how information is used and provide
clear lang...
© 2013, HSI
Onward Transfer
The act of notifying the individual
customer prior to disclosing PI to a third
party and allow...
Onward Transfer Examples
• If it is necessary to
respond to a
subpoena, court
order, or legal
process, or to exercise
your...
© 2013, HSI
Access
• Allowing the individual consumer the ability
to access their PI and allow the individual to
correct, ...
© 2013, HSI
Data Security
• Taking reasonable steps to protect your data
and information from loss, misuse and
unauthorize...
© 2013, HSI
Data Integrity
• When processing PII, it should be done
in a way that is compatible with, and
relevant to the ...
© 2013, HSI
Data Integrity Examples
• Business Rules for Standardization
• Clean and Updated
• Capture Customer Driven Cha...
Advocacy/Enforcement
Employ a self-assessment
approach to assure
compliance with your
privacy policy and
periodically veri...
© 2013, HSI
What It Takes
The process is ongoing and should be ever-changing as you innovate and add new
data capabilities...
© 2013, HSI
In Closing
Marketing Data, big or small, is just a piece to a
much larger puzzle. Striking a balance between
m...
© 2013, HSI
Want More Info?
Contact Us!
• Peg Kuman:
pkuman@relevategroup
.com
• Gina Scala:
gscala@the-dma.org
Join Us!
www.dmadatago...
DATA GOVERNANCE
DATA GOVERNANCE
DATA GOVERNANCE
DATA GOVERNANCE
Upcoming SlideShare
Loading in …5
×

DATA GOVERNANCE

1,616 views
1,564 views

Published on

Published in: Business, Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,616
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
106
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide
  • Assumption: DATA is a corporate asset (Peg talk to this!!)
  • Some refer to data rights as digityal rights and that touches on copyrightAnd patter of access and IP. That is NOT what we mean here. Tom Tom Incident
  • Assumption: DATA is a corporate asset (Peg talk to this!!)
  • 1 SEXTILLION BYTES
  • Based on the British Royal Mail which was opened to the public in 1635 by Charles the First (before he lost his head)
  • Direct marketing this year accounted for 8.7 percent of the total US gross domestic product. And data-driven marketers -- both commercial and nonprofit -- will spend $168 billion dollars on marketing. That accounts for 52.7 percent of all ad expenditures in the US. Measured against total US sales, these advertising expenditures will generate over $2 Trillion dollars in incremental sales.Marketers and the sales efforts they support account for 9.2 million US jobs.
  • MOVE TO NEXT SLIDE AT PRESS…..
  • Biz Stone anecdote
  • Meta, Giga, Tera, Peta
  • And If we want relevant audiences to scale you need insights collected over time. The value of Offline Data in reaching larger, more qualified audiences. The value of Online data is in reaching time-specific in-market behaviorsAnd if you want more nuanced analytic insights, then blending offline and online data is the only way.OFFLINE Data = 4,000 data points FOR EVERYONE IN THE COUNTRYUltimately the online community needs to bring more of the offline data into the ad serving equation in order to generate more scale
  • And If we want relevant audiences to scale you need insights collected over time. The value of Offline Data in reaching larger, more qualified audiences. The value of Online data is in reaching time-specific in-market behaviorsAnd if you want more nuanced analytic insights, then blending offline and online data is the only way.OFFLINE Data = 4,000 data points FOR EVERYONE IN THE COUNTRYUltimately the online community needs to bring more of the offline data into the ad serving equation in order to generate more scale
  • Duke U Truscott and Ellis- first onl ine BBIRC Unix- not a lot of folks had avail- but precursor to IM
  • Duke U Truscott and Ellis- first onl ine BBIRC Unix- not a lot of folks had avail- but precursor to IM
  • http://www.thinkoutsidein.com/blog/2012/01/grouped-chapter2/
  • But then how do they behave…
  • One of my favorite brands that has embraces all of the channels to drive brand, relations ship and following
  • We are going to do a deep dive into Mobile data governance and best practice tomorrow- but let’s tee what’s driving the givernance discussions today
  • May 28 Experian-Simmons Research
  • Imagine if you could drive 520 miles per hour on the freeway, 8 times the current speed limit of 65mph. Imagine if a flight from New York to London took 1 hour, 1/8th the current travel time of 8 hours. Life would be drastically different in both cases — at 8 times its current speed.
  • http://www.youtube.com/watch?v=D2YXsk3Ey00
  • Second only to Toy Story $110M
  • http://socialcommercetoday.com/word-of-mouth-still-most-trusted-resource-says-nielsen-implications-for-social-commerce/
  • Let’s look froward at the US safe harbor framework as a starting place– peg to next slide
  • Assumption: DATA is a corporate asset (Peg talk to this!!)
  • Discuss
  • Discuss
  • Local Shared Objects commonly called flash cookies
  • Now we have sourced it, lets define it
  • discussion
  • discussion
  • Discussionbehaviors that a renot anaymous
  • How many of you do use ananymous data
  • How many of you do use ananymous data
  • How many of you do use ananymous data
  • How many of you do use ananymous data
  • discussion
  • Ghostery and Abine
  • discussion
  • What do you do with old data?
  • Examples and Discussion
  • Examples and Discussion
  • Do you carry thumb drives in your briefcase, how many and what is on them? Have you even done a data download using a thumb drive?
  • Training? Contact lists, tiers from incidence response, access, mail stops
  • Training? Contact lists, tiers from incidence response, access, mail stops
  • Training? Contact lists, tiers from incidence response, access, mail stops
  • Policies, devices, company v personal
  • Mobile/cellular phones Laptop/notebook/tablet computers Smartphones and PDA’s Any mobile device capable of storing corporate data and connecting to an unmanaged network
  • Examples and Discussion
  • Examples and Discussion
  • Alistair Croll and PK
  • We have been discussing use and value across multiple channels, let’s discuss this as it relates to data ownership, as that is what fires the debate…
  • Alistair Croll
  • You add to the list- but just for fun let’s see who’s pushing the envelope of both good and bad behavior
  • Not for every one- international borders yes- us domestic, maybe not concept of ombudsman acts
  • You will want to include some, but perhaps not all depending on what you do, to whom you market and where you market
  • Some examples on the next several slides– and it shouldn’t be relegated to only online communications- include in your mailers
  • This is a safe harbor requirement, and one that is not embraced by many US based businesses
  • Use Bank/Credit example
  • Use Bank/Credit example
  • DATA GOVERNANCE

    1. 1. © 2013, HSI DATA GOVERNANCE Peg Kuman, CIPM Vice Chairman, Relevate Gina Scala Vice President Education, The DMA
    2. 2. © 2013, HSI What is Data Governance?
    3. 3. © 2013, HSI Data Governance encompasses: • Privacy • Security • Data Stewardship • Data Provenance (Rights Management)
    4. 4. • Data Privacy Management implementing processes, roles, controls - all of which treat information as an asset that needs protection. Privacy
    5. 5. • Data Security protecting your data against damage, loss, danger, and crime. Security
    6. 6. © 2013, HSI Data Stewardship • The intentional collaboration of all the data stakeholders to insure accurate, safe, and responsible use of the data and to insure the longer term sustainability of both compliance behavior and business strategy in a sea of changing technology, laws, and regulations.
    7. 7. Data Provenance • Data Provenance –Ownership, –Access, –Use, –Rights Management
    8. 8. © 2013, HSI Benefits of Marketing Data Governance: • Let’s you set the corporate tone for your brand [Social media has robbed us of the ability to spin the message] • Engage all stakeholders • Let’s your company and brand set the gold standard for best practices and compliance • Gets you to attribution ROI faster
    9. 9. © 2013, HSI Data Governance Drivers: • Scale • Global • Innovation • Profit • Regulation • The Media
    10. 10. © 2013, HSI Today and Tomorrow • Part 1: The Big Data Landscape- Light speed-150 minutes of where we came from and where we are going. • Part 2: Sourcing, Users, Ownership- things you may not know, questions you may not have asked, and how to optimize data use. • Part 3: Putting the Data to Work - Enhance, enrich, analyze and model. • Part 4: Tying It All Together- Use cases on attributions, and digital successes.
    11. 11. © 2013, HSI Peg’s Promise • 4 revenue producing ideas that will drive new growth by the end of Q1 2014 PROFIT GROWTH INNOVATION ATTRIBUTION INSIGHT
    12. 12. © 2013, HSI
    13. 13. A few insights from a BIG fan of BIG DATA Introducing Christy UherFerguson Director, Communications Strategy at Teradata
    14. 14. © 2013, HSI Big and Speed get Attention
    15. 15. © 2013, HSI Source: edCetra, 2012
    16. 16. © 2013, HSI Source: edCetra, 2012
    17. 17. © 2013, HSI Source: edCetra, 2012
    18. 18. © 2013, HSI Source: edCetra, 2012
    19. 19. © 2013, HSI Source: edCetra, 2012
    20. 20. © 2013, HSI Source: edCetra, 2012
    21. 21. © 2013, HSI Source: edCetra, 2012
    22. 22. THAT’S ENOUGH INFORMATION TO FILL 135.7 BILLION 64 GIG iPADS Source: edCetra, 2012
    23. 23. © 2013, HSI How did we get here? • America leads the information revolution! • USPS established by the Continental Congress in 1775 naming Ben Franklin as the first Post Master General.
    24. 24. © 2013, HSI 1744 - Addresses and Lists • Oh, what to sell? • In 1744 Benjamin Franklin published a catalog which sold scientific and academic books by mail and even came with the world's first mail-order guarantee: "Those persons who live remote, by sending their orders and money to B. Franklin may depend on the same justice as if present.”
    25. 25. © 2013, HSI 1848 – HammacherSchlemmer • In 1848 Alfred Hammacher created a mail-order business, Hammacher Schlemmer, in New York City, which sold tools and hardware.
    26. 26. © 2013, HSI 1856 - Orvis New England Fishing Catalog
    27. 27. 1872 – Montgomery Ward • Aaron Montgomery Ward is credited with mass mailing the first mail-order catalog in 1872 for Montgomery Ward, his new mail order business. • His business grew and soon his catalog was a whopping 500+ pages of shopping delight.
    28. 28. 1888 – Sears, Roebuck • RW Sears sold watches and jeweler through self-mailers in 1888. • The first Sears and Roebuck catalog was in 1894.
    29. 29. © 2013, HSI The Survivors and the Vanished • All but MW have innovated their brands and today have migrated to a gentle push to their best customers…
    30. 30. © 2013, HSI
    31. 31. © 2013, HSI
    32. 32. © 2013, HSI
    33. 33. © 2013, HSI
    34. 34. © 2013, HSI And today:
    35. 35. © 2013, HSI Marketing Data… is the key driver to revenue and profits across ALL brands, Both B2C and B2B
    36. 36. © 2013, HSI
    37. 37. Data Driven Marketing Has Leverage • 8.7% GDP • $168 Billion Spend • $2.05 Trillion Sales • 9.2 Million Jobs
    38. 38. © 2013, HSI Revolutionary Changes “The growing ability to collect and analyze massive sets of information, known as Big Data, could lead to revolutionary changes in business, political and social enterprises.” - Pew Internet and American Life Project


    39. 39. © 2013, HSI Effective Government “From election campaigning to setting NASA's budget to prepping for the next big natural disaster, the information derived from analysis of large data sets is being used to make governmentmore effective.” -- The Atlantic
    40. 40. THIS CHANGE IS BEING LOOKED AT BY: THE MEDIA REGULATORS CONSUMERS ©2012 Heart Safety, Inc.
    41. 41. Threats Are Growing Every Day • Congressis investigating data-driven marketers and fundraisers for basic marketing practices. • The Federal Trade Commission is telling tall tales about marketing practices – that a consumer who buys a deep fryer online will be denied health insurance...and looking to bring nonprofits under its regulatory reach. • Consumer activists are using scare tactics – saying that “consumers are being pinned like insects to a pinboard” by marketers. • The Pressis slanting the story – reporting that data-driven marketers and fundraisers are worse than the FBI or the IRS…chipping away at the trust consumers and donors place in your organizations.
    42. 42. © 2013, HSI We are in a time of DRASTIC CHANGE “We are migrating from a PUSH marketing world to a PULL marketing world, and as that happens forces and factors will create NEW INNOVATIVE opportunities for marketers, and NEW, MORE RESTRICTIVE points of view from regulators.” - Peg Kuman, 2013
    43. 43. PUSH • Creating DEMAND - where the marketer controls the message and the type of response
    44. 44. PULL • Creating demand where the responder controls the message and the decision how and by which means to respond. • With social media - PULL allows you to influence the decision makers…
    45. 45. © 2013, HSI What age are we in? 40’s, 50’s, 60’s Brand Creation and Expansion Mass Advertising - National Coverage Internet and e-Commerce Digital-Social
    46. 46. © 2013, HSI Where are we in terms of usability? Available Usable
    47. 47. © 2013, HSI How much OFFLINE data is there? • Offline - we have over 100 years of knowledge & data. • Finite…
    48. 48. © 2013, HSI How much ONLINE data is there? • Online & Emerging Channels - we have ~ 40 years of knowledge and ~ 19 years of data. • Infinite…
    49. 49. © 2013, HSI So, The Rules of the Road for Offline Data are … • Are pretty well established • Possess behaviors that are easy to monitor • Complicated but, not complex
    50. 50. © 2013, HSI But, then Online comes along… •ARPANET 1969 •First email sent 1971 • BBS Bulletin Board System 1978 •Usenet goes online 1979 •IRC (Internet Relay Chat) 1988 • 1st Social Site - Geocities 1994 • The Globe 1995 •AOL launches IM 1997 •Sixdegrees.com 1997
    51. 51. © 2013, HSI And THEN ‘social’ explodes… • 2002 Friendster -(3M users first 3 months) • 2002 LinkedIn • 2003 MySpace • 2004 Facebook • 2006 Twitter • 2007 Tumblr • 2009 Foursquare • 2010 Instagram • 2012 Pinterest • More to come…
    52. 52. © 2013, HSI Explosive Statistics • One out of every seven minutes spent online is on Facebook • 340 million tweets are sent each and every day • Pinterest is the social network that skews most heavily towards female users, whilst Google+ is predominately used by men • 300 million pictures are uploaded to Facebook every day via Instagram • 61 percent of LinkedIn members use it as their primary professional networking site Source: Infographic, .2013
    53. 53. © 2013, HSI Estimated Monthly Unique Visitors to SNS in August, 2013: •1,000,000,000 - You Tube • 750,000,000 – Facebook • 250,000,000 – Twitter • 110,000,000 – LinkedIn • 85,500,000 – Pinterest • 65,000,000 – Google + Source:EbizMBA.com Source: eBizMBA.8.8.2013
    54. 54. © 2013, HSI Social Sites To Watch in 2013 • Pheed- pay as you go access to celebs • Thumb - personal crowdsourcing (thumbs up/down) • Medium - by invitation only- creators limited, everyone can view (Twitter) • Chirpify - social conversation platform for multi-channel campaigns--buying power with 1 tweet [5% to the payee]
    55. 55. Translation: • Control by PUSH is GONE! • Social KILLED it. • We are learning how to PULL the buyer into the conversation
    56. 56. © 2013, HSI Our SOCIAL world is a BIG Data world
    57. 57. We Live in BIG Data… • One out of every seven minutes spent online is on Facebook • 340 million tweets are sent each and every day • Pinterest is the social network that skews most heavily towards female users, whilst Google+ is predominately used by men • 300 million pictures are uploaded to Facebook every day via Instagram • 61 percent of LinkedIn members use it as their primary professional networking site Source: Infographic, 2013
    58. 58. © 2013, HSI What Consumers Do: Sources: Infographic Digital Buzz Blog, • Instagram- By May of 2012, 56 photo’s and a new user was being gained every second • 12,000 tweets per second during the Super Bowl on February 3rd
    59. 59. © 2013, HSI Dataportunity? What will we do? • Where are the opportunities? • Where are the pitfalls? • And where can you have the most profitable impact?
    60. 60. Oreo dunked a timely moment during the Super Bowl’s unexpected power outage. • Oreos tapped into a timely moment at the Super Bowl during the unexpected power outage. • They understood what people are likely to share. • Leveraged excellent design &copywriting. • Posted across all channels to increase distribution. • The real boon was the amount of PR that was created from a single image • This doesn’t just “happen”. Oreo had copywriters, designers, marketing pros & lawyers all together in a war room which enabled them to create this slam dunk
    61. 61. © 2013, HSI
    62. 62. © 2013, HSI Social Media Enables Targeted Marketing Responses at Individual Touch Points along the Consumer Decision Journey 2. Respond To consumers comments 3. Amplify Current positive activity/tone 4. Lead Changes in sentiment or behavior Consider Brand Monitoring Crisis Management Referrals and recommendations Brand content awareness Evaluate Product launches Buy Targeted deals, offers Experience Customer Service Fostering Communities Customer input Advocate Brand Advocacy Bond 1. Monitor social channels for trends, insights Stepsintheconsumerdecisionjourney Source: McKinsey Social Media Study, 2012
    63. 63. © 2013, HSI Confluence of Multiple Media, Channels, and Touches • Pushes all of us into new opportunities • Experimentation and Testing without obligation… • On, on-demand, all the time • Scale is overwhelming • Data Governance requires a new roadmap
    64. 64. © 2013, HSI Cases in Point • Let’s look at this confluence of multiple touch points and influences… • To set the stage - some good examples of multi-channel touch • How we profit and use the data… • And where the data governance pieces begin to fit.
    65. 65. © 2013, HSI P O T T E R Y B A R N
    66. 66. © 2013, HSI Pottery Barn • 1949 - Began in Lower Manhattan • 1986 - 21 PB stores bought by Williams-Sonoma, Inc. • 1987 - First mailing of the Pottery Barn catalog • 1995 - PB gift registry is launched • 1999 - Launched Pottery Barn Kids *Source: Pottery Barn MP Web story
    67. 67. © 2013, HSI PB Multi-Channel Growth - Great PUSH
    68. 68. © 2013, HSI
    69. 69. © 2013, HSI
    70. 70. © 2013, HSI
    71. 71. © 2013, HSI
    72. 72. © 2013, HSI PB Multi-Channel Growth • 196 Stores nationwide • 150 million+ catalogs a year • Targeted Daily Online Web Offers • 2012 William-Sonoma, Inc revenues exceeded $4.0 billion [$1.7B -42% PB] • DTC Grew 14.5% driven by PB and WE. *Source: 4/4/2013 Market Watch
    73. 73. © 2013, HSI Let’s Look at Mobile
    74. 74. © 2013, HSI Mobile is PUSH • All 100% opt-in • Mobile marketers call ‘PUSH’ a new channel for brands to better socialize with their BEST customers
    75. 75. © 2013, HSI App Happy… • iPhone has over 900K Apps • Google claims 800K+ for Android… • Each App, collects data and each app has a data-driven solution…
    76. 76. 2013 Top Mobile Apps • Google Maps • Facebook • YouTube • Google+ • Weixin/WeChat • Twitter • Skype Source: Mashable. 8/2013
    77. 77. © 2013, HSI 58 Mobile Minutes….
    78. 78. © 2013, HSI Time and Privacy • Smartphone owners spend more time today – 58 minutes, than in 2012- 39 minutes, and 2011- 37 minutes. • A vast majority of SP users (70% in 2011 and 73% in 2012) expressed concern over personal data collection and 55% wary of sharing information about their location via smartphone apps. Source: NielsenWire
    79. 79. © 2013, HSI Mobile is getting bigger…
    80. 80. © 2013, HSI M-Commerce • The 2012 eMarketer report shows that the growth in m-commerce sales will be as follows: +$11.6 Billion in 2012 +$17.2 Billion in 2013 +$23.7 Billion in 2014 +$31 Billion in 2015 Source: eMarketer 2012 Mobile Commerce Study
    81. 81. © 2013, HSI And Bigger…. • Mobile web adoption is 8 times faster today than web adoption in the late 1990’s/early 2000’s. • Speed matters and influences our decisions, our lives, and our ideas about what’s possible in the world. • We are currently on pace to outnumber ‘us’ with 3 times as many smart-phones activated every minute as there are human births.
    82. 82. © 2013, HSI By the end of 2013: • Mobile commerce from iPhones = 5% of retail sales • 56% of mobile users in the US now use smart phones • Mobile shopping up • Social shopping in decline Source: 1/13/2013 IBM Mobile Report, Pew 2013 Mobile Study,
    83. 83. © 2013, HSI And by the end of 2013 There will be more mobile devices on Earth than people. Source: Cisco, 2013
    84. 84. 9 out of 10 Mobile Searches Lead to Action and over half lead to a purchase Source: Search Engine Land
    85. 85. But what happens to the data and information that can be scraped? Mobile is 100% Opt-in
    86. 86. © 2013, HSI HOW traditional brands use media to build “e” responders, accelerate mobile and engage with social
    87. 87. © 2013, HSI Data ROI - Social Nike/Facebook Video Nike
    88. 88. © 2013, HSI LBM- Location Based Marketing • Opt-in Mobile • Meat Pack- Hijack LBM- shoes…..
    89. 89. • SMS, MMS • Sweeps for $10K Scholarship • Plus 5 $1K winners • Buzz, Participation and excitement leading up to last Friday’s launch…. • The first weekend numbers were: $82MM Smart Puffs, Disney and Mobile
    90. 90. Marketers are embracing the Mobile channel with Innovation and Experimentation- Driving Media and Regulators to Amplify Their Review
    91. 91. © 2013, HSI Geo—Navigational + Social • WAZE : GOOGLE • Company: Waze • Website: waze.com • Launch Date:2007 • Funding: • $67M
    92. 92. © 2013, HSI Google buys Waze- up to 50M users by June
    93. 93. © 2013, HSI Q1 2013 • A rise in active engagement across all social platforms with Twitter the fastest growing • Local social platforms continue their decline around the world with the exception of China and Russia • Mobile is playing a massive role in driving real-time active usage of social platforms in all markets Source: Global Web Index, Stream Social Report Q1 2013
    94. 94. © 2013, HSI Q1 2013 • Older internet users are also driving social platforms growth globally • Google+ remains the number 2 social platform in the world with 359 million monthly active users, Facebook is number 1 Source: Global Web Index, Stream Social Report Q1 2013
    95. 95. © 2013, HSI • On Twitter the 55-64 year age bracket is the fastest growing demographic with 79% growth rate since 2012. • The fastest growing demographic on Facebook’s and Google+’s networks are the 45 to 54 year age bracket at 46% and 56% respectively. Source: Global Web Index, Stream Social Report Q1 2013 Q1 2013
    96. 96. © 2013, HSI As Audiences Get Older Trust is a Key Factor
    97. 97. © 2013, HSI Trusting Social Media • Social media engagement requires trust, authenticity and transparency Nielsen Global Trust in Advertising 2012
    98. 98. © 2013, HSI
    99. 99. 1. AMEX 2. HP 3. AMAZON 4. IBM 5. USPS 6. P&G 7. USAA 8. NATIONWIDE 9. eBAY 10. INTUIT 11. VERIZON 12. J&J/ FED EX 13. WEB MD 14. WEIGHT WATCHERS 15. US BANK 16. DISNEY 17. MICROSOFT/UNITED HC 18. VISA 19. AT&T 20. MOZILLA Most Trusted Brands Ponemon Research Institute Annual Privacy Study, 2012
    100. 100. © 2013, HSI Why are they trusted? • Privacy Features on Transactional Sites • Substantial Security Protections were identified as a trust asset by 60 percent of consumers. • Accurate Data Collection and Use were cited by 53% as a trust asset. • Limits on the Collection of Personal Information and Online Anonymity were cited as key trust assets. Ponemon Research Institute Annual Privacy Study, 2012
    101. 101. © 2013, HSI What Consumers Fear Most • Losing Control of Personal Information. Only 35 percent of consumers feel they have control over their personal information, down from 41% last year and an overall drop from 56 percent in 2006. • Identity theft. 61% percent of consumers said fear of identity theft was a major factor in brand trust diminishment, and 73 percent said notice of a data breach was a factor. • Abuse of Civil Liberties. Ponemon Research Institute Annual Privacy Study, 2012
    102. 102. © 2013, HSI Fear and Trust = A formula for Regulatory and Congressional Review– even though the Government is the number 1 least trusted organization by consumers.
    103. 103. © 2013, HSI And so: The FTC Tackles Mobile • Should’s for Mobile Platforms • Should’s for App Developers • Should’s for Ad Networks and 3rd Parties • Can’s for Trade Associations, Researchers, Privacy Experts
    104. 104. © 2013, HSI Mobile Platforms Should: • Provide just-in-time disclosures to consumers and obtain their affirmative express consent before allowing apps to access sensitive content like geolocation;
    105. 105. © 2013, HSI Mobile Platforms Should: • Consider providing just-in-time disclosures and obtaining affirmative express consent for other content that consumers would find sensitive in many contexts, such as contacts, photos, calendar entries, or the recording of audio or video content;
    106. 106. © 2013, HSI Mobile Platforms Should: • Consider developing a one-stop “dashboard” approach to allow consumers to review the types of content accessed by the apps they have downloaded;
    107. 107. © 2013, HSI Mobile Platforms Should: • Consider developing icons to depict the transmission of user data; • Promote app developer best practices. For example, platforms can require developers to make privacy disclosures, reasonably enforce these requirements, and educate app developers;
    108. 108. © 2013, HSI Mobile Platforms Should: • Consider providing consumers with clear disclosures about the extent to which platforms review apps prior to making them available for download in the app stores and conduct compliance checks after the apps have been placed in the app stores; and
    109. 109. © 2013, HSI Mobile Platforms Should: • Consider offering a Do Not Track (DNT) mechanism for smartphone users. A mobile DNT mechanism, which a majority of the Commission has endorsed, would allow consumers to choose to prevent tracking by ad networks or other third parties as they navigate among apps on their phones.
    110. 110. And Congress is Full of Ideas In the 113th Congress, legislators in both the House and Senate rushed to “make their marks” on the privacy and data security debates by introducing bills focusing on various issues… - Data “Brokers” - “Comprehensive” privacy - “Do Not Track” - Kids privacy - Geo-locational privacy - Data security/data breach
    111. 111. © 2013, HSI Good, Big and Ugly Whether you think Snowden is a whistle-blower or a traitor, no matter. But know that very bad, ugly mean individuals and organizations are trying to disrupt the social order by theft, hack and breach.
    112. 112. © 2013, HSI
    113. 113. © 2013, HSI Data Loss Incidents 2003- 2013 Source: Open Security Foundation, DataLossDB 0 200 400 600 800 1000 1200 1400 1600 2003 2006 2010 2011 2012 2013=692 as of Sept.
    114. 114. Incidents By Loca on- 2003-2013 Government- 18% Medical- 15% Educa on- 15% Businesses-52% Source: Open Security Foundation, DataLossDB
    115. 115. Incidents By Type- 2012-2013 YTD Hack- 56% Fraud- 9% Web- 5% Stolen Laptop- 7% Stolen Docs- 3% Email- 2% Virus- 2% Stolen Drive- 2% Unknown- 13% Postal Mail- 3% Source: Open Security Foundation, DataLossDB Incidents By Type 2012-2013 YTD
    116. 116. Top Target Countries for Hackers
    117. 117. © 2013, HSI Who Tracks This? • The Open Security Foundation (OSF) is a 501(c)(3) non-profit public organization founded and operated by information security enthusiasts, formed to empower all types of organizations by providing knowledge and resources so that they may properly detect, protect, and mitigate information security risks. • The Foundation established the DataLoss Database, a free and open resource for the collection and dissemination of data loss incident-related information.
    118. 118. © 2013, HSI Customer View and Marketing Fear, Theft, Breach, Bad behavior dial up the need for consolidated Data Governance that must include Marketing Data.
    119. 119. © 2013, HSI Criminal Data Breach Video Anti Sec I
    120. 120. © 2013, HSI Unintentional Data Loss Video Toy Story 2
    121. 121. © 2013, HSI DATA GOVERNANCE Peg Kuman, CIPM Vice Chairman, Relevate Gina Scala Vice President Education, The DMA
    122. 122. © 2013, HSI
    123. 123. © 2013, HSI WHAT WE KNOW: • Marketing use is still evolving…and will continue to do so • What works and why - we remain in the test, re- test, and “Lemming” phase • Everyone has access, everyone has data, it remains unclear still what works and why - and importantly if we (the marketers) do not define the rules of the road, the regulators will.
    124. 124. © 2013, HSI Sourcing, Typing and Classifying Control Minimize Risk Insight and Growth
    125. 125. © 2013, HSI Data is a collection of facts – such as values or measurements - it can be:  Numbers  Words  Measurements  Observations  Descriptions  Actions
    126. 126. © 2013, HSI Classifying Data- • Data is either: • Quantitative, • Qualitative, • Or a blend of both. • Quantitative Data - DEFINES • The HH has 2 children • Qualitative Data - DESCRIBES • The HH buys online
    127. 127. © 2013, HSI What is Marketing Data? • Marketing Data - is a collection of facts that when looked at together becomes information that can be acted upon to inform, sell, service…
    128. 128. © 2013, HSI Where does it all come from? Marketing data comes from – • your prospects • your customers • your partners • third party data providers MARKETING DATA DEFINES YOUR AUDIENCE
    129. 129. © 2013, HSI Where does it all come from? Marketing data comes from all corners of your brand - your marketing initiatives - retail spaces - websites - social media - customer service reps - your sales team - surveys
    130. 130. © 2013, HSI Where does it all come from? • Marketing data also comes in the form of: • Brand mentions from Facebook and Twitter • From collected social conversations around a much more basic topic. • From website analytics in the form of tracking conversions, clicks, bounce rates, search keywords and more… Where else can you think of?
    131. 131. © 2013, HSI What does it look like? • The customers and prospects information may include: • names • email addresses • physical addresses • telephone numbers • categorical interest • and more…
    132. 132. © 2013, HSI What does it look like? • The customers and prospects information may also include: • attitudes • sentiments • opinions • locations • relationships • click-throughs’ & browsing • and more…
    133. 133. © 2013, HSI Sourced Through: • Customer transactions • 3rd Party Data [demo’s, psycho's, firmo’s] • 1st Party Data [demo’s, psycho's, firmo’s] • Publicly Available Data • Public Records Data • Traded or Exchanged Data • Scraped, Compiled, or Aggregated Data • Modeled/Behavioral Data • Online • Offline
    134. 134. © 2013, HSI Sources for Marketing Data • Examples: Customer Transactions  Inquiry, Request for Info, Survey  Order Placement/Purchase  Application for: • credit • insurance • loan • mortgage • college • employment • refund…
    135. 135. © 2013, HSI First Party Data - The ‘Owner’ • In the Offline world - • The company that owns the data - customer files, customer transactions, survey responders, inquiries • In the Online world - • The entity that owns and controls the domain
    136. 136. © 2013, HSI Third Party Data • In the Offline world - • Data that is compiled, aggregated, assembled from public or proprietary (1st Party) Sources about consumers or businesses • In the Online world - • An entity that is not reasonably affiliated or not affiliated at all with the consumers or businesses • Company(ies) classified as a third party data collector which collects data through Domains it does not own
    137. 137. © 2013, HSI Third Party Data • Be Informed: • Know who the providers are, know their privacy and information policies and practices • Know where their data comes from • Know its accuracy • Know its currency
    138. 138. © 2013, HSI Online Third Party Data • Third Party Data Collection • Defined by Companies that collect either PII or non-personally identifiable data about individuals, usually without the individual's knowledge, over a period time through a Domain or network of Domains not owned by that Company.
    139. 139. © 2013, HSI Online Third Party Data • Third Party Data Collection • The Company uses a Domain to collect the information that is different from the Domain(s) upon where the data is being collected. The data is collected using technologies such as HTTP cookies, web beacons, tracking JavaScripts, or Flash LSOs. [Local Shared Objects] This differs from First Party collection of data where typically the collection of data is restricted to a Domain that is owned by the First Party.
    140. 140. © 2013, HSI Online Third Party Data » There are different types of Third Party Data Collectors not all of which collect data for marketing purposes. » Typically those that use data for marketing purposes include: • Advertisers • Ad Exchanges • Ad Networks • Ad Platforms • Data Aggregators/Exchanges • Market Research companies, and the like
    141. 141. © 2013, HSI Third Party Data • Not all Third Party Data Collectors collect data for the purposes of marketing but provide a fundamental service for the functioning of websites. » Some of these types of Third Party Data Collectors include: • Publishers, • Service Providers, • Web Analytics Providers, and • Widget Providers.
    142. 142. © 2013, HSI Types of Marketing Data 1. PII and Sensitive Data 2. Public 3. Private/IP 4. Anonymized
    143. 143. © 2013, HSI 1. PII - Personally Identifiable Information • PII is Personally Identifiable Information • Information that can be used to distinguish or trace someone’s identity. • In other words: Any information that is linked or linkable to a specified individual. • Source OMB/2007
    144. 144. © 2013, HSI DMA: PII • Marketers should be sensitive to the issue of consumer privacy and should only collect, combine, rent, sell, exchange, or use marketing data. • Marketing data should be used only for marketing purposes.
    145. 145. © 2013, HSI Examples of PII Health Related PII-  Illnesses or conditions  Treatments for those illnesses or conditions, such as prescription drugs, medical procedures, devices or supplies  Or Treatments received from doctors (or other healthcare providers), at hospitals, at clinics, or at other medical treatment facilities
    146. 146. © 2013, HSI Sensitive or Intimate Information • Data and selection criteria that by reasonable standards may be considered sensitive and/or intimate should not be disclosed, be displayed, or provide the basis for lists made available for rental, sale or exchange when there is a reasonable expectation by the consumer that the information will be kept confidential.
    147. 147. © 2013, HSI PII – Credit Card Numbers • Credit card numbers, checking account numbers, and debit account numbers are considered to be personal information. • Therefore these should not be transferred, rented, sold, or exchanged when there is a reasonable expectation by the consumer that the information will be kept confidential….or otherwise made public by direct marketers.
    148. 148. © 2013, HSI PII – SS Numbers • Social Security numbers are also considered to be personal. • Social Security numbers, however, are used by direct marketers as part of the process of extending credit to consumers or for matching or verification purposes.
    149. 149. © 2013, HSI Linked Information • Information about an individual that is linked or linkable to one of the PII attributes (e.g., date of birth, place of birth, race, religion, weight, activities, geographical indicators, employment information, medical information, education information, financial information).
    150. 150. © 2013, HSI Even in Digital Marketing • ALL information that can be linked back to an individual is considered PII
    151. 151. © 2013, HSI Context • Identifiability. Organizations should evaluate how easily PII can be used to identify specific individuals. For example, a SSN uniquely and directly identifies an individual, whereas a telephone area code identifies a set of people. • Quantity of PII. Organizations should consider how many individuals can be identified from the PII. Breaches of 25 records and 25 million records may have different impacts. The PII confidentiality impact level should only be raised and not lowered based on this factor.
    152. 152. © 2013, HSI Context • Data Field Sensitivity. Organizations should evaluate the sensitivity of each individual PII data field. • For example, an individual‘s SSN or financial account number is generally more sensitive than an individual‘s phone number or ZIP Code. Organizations should also evaluate the sensitivity of the PII data fields when combined.
    153. 153. © 2013, HSI Context of Use • Context of Use. Organizations should evaluate the context of use—the purpose for which the PII is collected, stored, used, processed, disclosed, or disseminated. The context of use may cause the same PII data elements to be assigned different PII confidentiality impact levels based on their use. • For example, suppose that an organization has two lists that contain the same PII data fields (e.g., name, address, phone number). The first list is people who subscribe to a general- interest newsletter produced by the organization, and the second list is people who work undercover in law enforcement. If the confidentiality of the lists is breached, the potential impacts to the affected individuals and to the organization are significantly different for each list.
    154. 154. © 2013, HSI Non-PII Context PII Can be linked To an individual Sensitive PII SSN Health Related Info Account Information DOB Race Religion Cannot be linked to an individual
    155. 155. © 2013, HSI PII Summary - Marketing • Name linked to Address • Email Address linked to N/A • Name linked to Phone
    156. 156. © 2013, HSI PII Summary- Sensitive • Medical Records • Biometric Information • Place of Birth • SSN • Personnel Records • Cite CA SC Decision
    157. 157. © 2013, HSI Protecting PII 1. Required by Law 1. Prevents Identity Theft 2. Best Practice
    158. 158. © 2013, HSI 2. Public Data • Data and information that is in the public domain. Not private. Examples: • Public Directories • Public Filings (Deeds, UCC) • Census Data • Government Subsidized Data
    159. 159. © 2013, HSI
    160. 160. © 2013, HSI 3. Private/IP- can be PII or Non-PII • Data that is private: • Data not shared and unique to the company based on non-shared information from customers, clients, vendors. • Data that is deemed company intellectual property.
    161. 161. © 2013, HSI Private/IP cont’d Examples: • Customer Transactional Data • Contractual • Customer/Share of Wallet • Customer Provided Information • Confluence of Company Data Points
    162. 162. © 2013, HSI 4. Anonymized Data » Anonymous data is defined in numerous ways depending on the data type, collection method and use. For example: Data that by virtue of the method of collection can never reasonably be connected with the person providing them. Data that is anonymized using de-anonymizing data identifiers such as dynamic cookies - used in the aggregate for ad serving.
    163. 163. © 2013, HSI 4. Anonymized Data » Using cookies to anonymize data: • Cookies are machine specific and work in a name/value pair. • They are data, not a program and cannot ‘do’ anything.
    164. 164. © 2013, HSI Cookie Shortfalls • Cookies get erased • People use multiple machines • People often share a machine • Cookies have a shelf-life
    165. 165. © 2013, HSI Cookie Benefits • Improved user experience • Ad serving and re-marketing completely anonymous • No PII and no chance to re-engineer
    166. 166. © 2013, HSI Unpacking AnonymizedData • Can you truly anonymize data? • PII conversion to cookies using IP and email addresses • Eliminating any individual identifiable data (HIPPA) • Encoding, Encrypting • Re-identification Thoughts?
    167. 167. © 2013, HSI What’s After Cookies? “The Web Cookie Is Dying. Here's The Creepier Technology That Comes Next” Source: Forbes.com 06/17/2013 Photo Credit: COPA
    168. 168. © 2013, HSI Why Fingerprinting?
    169. 169. © 2013, HSI It Eliminates Cookies Flaws • Fingerprinting allows a web site to look at the characteristics of a computer such as what plugins and software you have installed, the size of the screen, the time zone, fonts and other features of any particular machine. These form a unique signature just like random skin patterns on a finger.
    170. 170. © 2013, HSI And- Cookies don’t work on mobile
    171. 171. © 2013, HSI Scale • The Electronic Frontier Foundation has found that 94% of browsers that use Flash or Java – which enable key features in Internet browsing – had unique identities. • That’s a higher percentage than cookie matches- which range from 40-60%...
    172. 172. © 2013, HSI My browser has 21.67 bits of uniquity
    173. 173. © 2013, HSI Panopticlick https://panopticlick.eff.org
    174. 174. © 2013, HSI The Marketing Data Eco System Transactional Data Sensitive Data Marketing Data Credit Data Summarized Credit Data Anonymized Data Modeled Data Analytics/ Insight
    175. 175. © 2013, HSI Data Use is Complex! • Where does it reside? • How is it classified? • How is it defined? • Who uses it? • Who needs access? • How is it accessed, transmitted, shared, enhanced, and destroyed (or not)?
    176. 176. © 2013, HSI Connecting Use to Where Data Resides 1. List all of the locations your data resides (that you are aware of). 2. How is that data classified? 3. Who has access? 4. How do they access it?
    177. 177. © 2013, HSI Data Use Show of hands: •How many of you have ever sent data via email? •Unencrypted? •Unzipped? Photo Ref: http://www.maximumpc.com/article/news/aol_raise_your_hand_if_you_want_lose_your_job
    178. 178. © 2013, HSI Data Use Does Data Have a Life-cycle? • Data comes from inception, aggregation, compilation, licen se… • But does data ever retire, and when should it, or should it ever, be destroyed?
    179. 179. © 2013, HSI Life-cycle Determinants – Keep forever or Kill » Frequency of updates » Changes in the data itself • (deceased, moved, preference changes, marital status) » Compulsory
    180. 180. Controlling Data Use –Physical Controls –Virtual Controls –Contractual Controls –Audit Rights Who has access? Who controls access?
    181. 181. © 2013, HSI Vulnerabilities for Use and Misuse
    182. 182. © 2013, HSI Removable Media • How many times have you used a thumb drive… and how do you control among those who have data access? • Is is part of policy and does every employee have sign off?
    183. 183. © 2013, HSI ACCESS • What do your employees have? • What do they know, what do they see? • Contact Lists • NDA’s, Contracts, Policies – Training • Affidavit of Compliance • Staff with remote access – controls and monitors
    184. 184. © 2013, HSI How Do You Handle Media Disposal? End of life policies for data: • Do your business contracts address this? • Does you consumer data policy inform and address? • Should you address at all?
    185. 185. © 2013, HSI Wireless Networking • Are you and your colleagues trained on the basics? [i.e. turn off sharing, enable firewalls etc.] • Do you have and require a VPN? • Do you restrict remote data access?
    186. 186. © 2013, HSI Electronic Messaging IM and SMS – limited use? • Gchat • Skype • AIM • Facebook • Twitter
    187. 187. © 2013, HSI Mobile Devices and Acceptable Use • Laptops, PDA’s, and Remote Access • What should mobile users know?
    188. 188. © 2013, HSI Best Practices for Managing Use and Access •Know your inventory: •By Application •By Location •Know your users: •Internal •External
    189. 189. © 2013, HSI Best Practices for Managing Use and Access • Communicate access rules to all • Create Policies, Processes, and Procedures • Communicate necessary policies to all stakeholders, including customers, vendors, partners, and employees • Regularly review and update/change
    190. 190. © 2013, HSI Data Provenance • Who owns the data?
    191. 191. © 2013, HSI So, Who owns the data? •The primary source? •The aggregator/compiler? •The enhancer? •The consumer? Thoughts?
    192. 192. © 2013, HSI Who owns the data & data agreements? • Rental • License • Co-op’s • Shared • Exchanged At what point in time does ownership change hands? Thoughts?
    193. 193. © 2013, HSI Defining Data Ownership is Difficult • We share, friend, check in and tweet our every move. • We log on, log in, and browse. • We swipe loyalty cards and enter frequent flyer numbers. • We leave a trail of digital breadcrumbs in our wake. • But, as we use the Internet for “free”, we have to remember that if we’re not paying for something, we’re not the customer. We are in fact, a product. A data set.
    194. 194. © 2013, HSI Why Data Ownership is Difficult • Our laws have focused on physical ownership or assets that couldn’t be easily duplicated. • Technology, from copying devices to recording devices have changed the thinking. • BUT - it’s not just our ability to replicate that makes data different - it is how it is used that defines its value.
    195. 195. © 2013, HSI It’s What We As Marketers Do With Data… • The important question isn’t who owns the data. Ultimately, we all do. A better question is, who owns the means of analysis? Because that’s how you get the right information in the right place. • The discussion shouldn’t be about who owns data — it should focus on who can put the data to work.
    196. 196. © 2013, HSI We Are All Data Stewards • Accurate, Safe, Responsible Use of the Data • We will view the impact of monetizing the data asset on DG
    197. 197. © 2013, HSI DATA GOVERNANCE Peg Kuman, CIPM Vice Chairman, Relevate Gina Scala Vice President Education, The DMA
    198. 198. © 2013, HSI
    199. 199. © 2013, HSI Circling Back Putting the Data to Work:
    200. 200. © 2013, HSI Cracking the Code- A work in progress
    201. 201. © 2013, HSI Getting to Attribution ROIOffline Data Ecomm Data Digital Data Social Data Enhanced Data Behavioral Data Multi Touch Tracking
    202. 202. © 2013, HSI Discovery • What are you doing to drive response today? • What will you be adding? • How are you caching the responses? • Are you tracking multi-channel touches? • Are you tracking multi-channel response? • Is it important?
    203. 203. © 2013, HSI Where Does The Customer Interface Occur? • Social • Digital • On-line • Off-line • Where are the locators? • Where are the problems? (POS, Call Center)
    204. 204. © 2013, HSI Who is your customer? • Transactional and Behavioral • Building persona’s • Implementing the Models • Test and test and refine and test
    205. 205. What is Your Spending By Channel? • Print • Broadcast • Direct Mail • In Store / Face-to-Face • E-mail • Social – Blog – Tweets – Likes • Digital – E-commerce – Display • Search • Mobile – SMS – Web – Commerce
    206. 206. What is Your Spending By… • SKU? • Segment?
    207. 207. © 2013, HSI Tracking Frequency of Response • To understand how channel performs • To identify channel preferences • To figure out best campaign frequency • To understand a segment’s patterns
    208. 208. © 2013, HSI
    209. 209. © 2013, HSI
    210. 210. © 2013, HSI
    211. 211. © 2013, HSI
    212. 212. © 2013, HSI
    213. 213. © 2013, HSI
    214. 214. © 2013, HSI
    215. 215. © 2013, HSI
    216. 216. © 2013, HSI
    217. 217. © 2013, HSI
    218. 218. © 2013, HSI
    219. 219. © 2013, HSI
    220. 220. © 2013, HSI Finding the Bright Lines • Unknowns • Market Oppy- opportunity segments, channels • Staged approach • Keep what’s working while you build insight
    221. 221. © 2013, HSI Big Data / Changing Structure Analytics Attribution Marketing Intelligence and Insight
    222. 222. © 2013, HSI Structure Changes When Looking at the Data Ecosystem Holistically- • Shared • Not Shared • Anonymized
    223. 223. © 2013, HSI Death by Silo
    224. 224. © 2013, HSI Old Data Governance
    225. 225. © 2013, HSI Old Data Governance
    226. 226. © 2013, HSI New Data Governance • Positioning and integrating allbusiness functionsinto your data governance mix throughout your organization- and across all of your brands • Focus on collaboration
    227. 227. © 2013, HSI New Data Governance
    228. 228. © 2013, HSI DATA GOVERNANCE Peg Kuman, CIPM Vice Chairman, Relevate Gina Scala Vice President Education, The DMA
    229. 229. © 2013, HSI
    230. 230. © 2013, HSI Business Cases – Success and Failure: • Case Study: Global Differences • Case Study: Gold Standard of Consent • Case Study: Dysfunctional Family
    231. 231. The Stakeholders • InfoSec • Sales/Biz Dev • Marketing • C-Suite • IT/Technology and Infrastructure • HR • Vendors/Partners • Customers • KYC • Who else can you think of?
    232. 232. © 2013, HSI Why We Need Best Practice: Data as The Regulators See It: Pizza Pie Order
    233. 233. © 2013, HSI Best Practices Marketing Data Governance
    234. 234. © 2013, HSI Key Safe Harbor Principles 1. Notice 2. Choice and Opt-out 3. Onward Transfer 4. Access 5. Security 6. Data Integrity 7. Advocacy/Enforcement * Adapted from the DOC US/Swiss Safe Harbor Framework
    235. 235. © 2013, HSI Notice – Defined Providing notification to your customers and prospects how you collect and use information about them. This should include points of contact internally, and third party disclosures and limits of use, or not.
    236. 236. © 2013, HSI Examples of Notice Google, Facebook, Apple and most major brands tell the customer that their use of data is to help them help you focus on your user experience….
    237. 237. © 2013, HSI Choice and Opt-Out Give consumers the opportunity to choose whether their PI will be disclosed to a third party for a different use than which it was intended, and for sensitive information give an affirmative (explicit) opt-out.
    238. 238. © 2013, HSI Disney • Provides for Categorical Opt-Out. • They clearly state how information is used and provide clear language on personal control and choice including quick links. • http://corporate.disney.go.com/corporate/pp.html#DIMG%20Q uestion%205
    239. 239. © 2013, HSI Onward Transfer The act of notifying the individual customer prior to disclosing PI to a third party and allowing the individual the choice to opt-out.
    240. 240. Onward Transfer Examples • If it is necessary to respond to a subpoena, court order, or legal process, or to exercise your rights to defend against legal claims.
    241. 241. © 2013, HSI Access • Allowing the individual consumer the ability to access their PI and allow the individual to correct, amend, or delete inaccurate information – except where the burden or expense of providing access would be disproportionate to the privacy risks of the individual, or where the rights of persons other than the individual would be violated. • This is a controversial hot button topic!
    242. 242. © 2013, HSI Data Security • Taking reasonable steps to protect your data and information from loss, misuse and unauthorized access, disclosure, alteration, and destruction. That you have in place physical, electronic, and managerial procedures to do same. And, note that you cannot guarantee the security of information on or transmitted via the internet.
    243. 243. © 2013, HSI Data Integrity • When processing PII, it should be done in a way that is compatible with, and relevant to the purpose for which it was collected or authorized by the individual consumer. You should take steps to insure that all PI is accurate, complete, current, and reliable for its intended use.
    244. 244. © 2013, HSI Data Integrity Examples • Business Rules for Standardization • Clean and Updated • Capture Customer Driven Changes [COA’s, Nixies, POS corrections] • Siloed PI/Marketing Data
    245. 245. Advocacy/Enforcement Employ a self-assessment approach to assure compliance with your privacy policy and periodically verify that the policy is accurate, comprehensive, prominently displayed, complete, and accessible.
    246. 246. © 2013, HSI What It Takes The process is ongoing and should be ever-changing as you innovate and add new data capabilities, new data, new devices, new services, and even new brands. Balance, Budget, and Buy-in. Data Provenance Data Stewardship Security Privacy Ideal MDG
    247. 247. © 2013, HSI In Closing Marketing Data, big or small, is just a piece to a much larger puzzle. Striking a balance between marketing innovation and best practices will afford our businesses the opportunity to experiment, create, and grow freely and without fear of regulation. ~Peg Kuman, 2013
    248. 248. © 2013, HSI
    249. 249. Want More Info? Contact Us! • Peg Kuman: pkuman@relevategroup .com • Gina Scala: gscala@the-dma.org Join Us! www.dmadatagovernance.org Data Matters: Governance & Best Practice December 12-13th - New York March 31- April 1 – Chicago

    ×