As businesses, we know the importance of correct, complete, and integrated data to drive our marketing performance. Learn what the experts recommend, what a high-performing data management program looks like, and three steps to get there.
The basics of data ownership, rights, and who’s in charge of maintenance
The fundamentals of data governance and essential tools for data hygiene
Real-world examples of common data integration and data quality pitfalls that we see every day, and tips for how to avoid them
How CRM integration and high-quality data powers your marketing automation
Fueling your growth with accurate data and smart data management
1. FUELING YOUR GROWTH
WITH ACCURATE DATA AND
SMART DATA MANAGEMENT:
LEARN HOW TO COLLECT, CLEAN, ENGAGE AND
LEVERAGE YOUR DATA
2. FUN
FACTS
90% of all data has been created in the last two years.
https://public.dhe.ibm.com/common/ssi/ecm/wr/en/wrl12345usen/watson-
customer-engagement-watson-marketing-wr-other-papers-and-reports-
wrl12345usen-20170719.pdf
Today it would take a person approximately 181 million
years to download all the data from the internet with an
average download speed of 44Mbps.
http://www.physics.org/thankphysics/internet/
2012 only 22% of all the data had the potential for
analysis from sources such as surveillance,
entertainment and social media, etc.
By 2020, the percentage of useful data, i.e., the
information that has the potential for analysis, is
predicted to jump to 37%.
3. THERE IS A
LOT OF
DATA OUT
THERE
https://www.visualcapitalist.com/what-happens-in-an-internet-minute-
4. AGENDA
• Basics of Data Ownership and
Data Governance
• Importance of Data Quality
• Tools for Maintaining Your
Data
• Tips for CRM Integration;
Using Data to power Your
Marketing Automation
• Bringing it All Together
5. DATA
OWNERSHIP
What does Data Ownership mean?
• Definition - Data ownership is the act of
having legal rights and complete control over
a single piece or set of data elements. It
defines and provides information about the
rightful owner of data assets and the
acquisition, use and distribution policy
implemented by the data owner.
• Data ownership also defines the data owner’s
ability to assign, share or surrender all of
these privileges to a third party. This concept
is generally implemented in medium to large
enterprises with huge repositories of
6. DATA
SOURCES
Where does it come from?
• Your customer database – Automatic
Ownership
• Third Party data (Vendor/ Partner) –
Licensed Ownership
7. UNDERSTAND YOUR DATA SOURCES• Identify your data sources – do you know where your data
is from?
• If using third party provider – do you know the frequency
that they update their data? Are you scheduled to receive
data refreshes?
• Is all data created equal? A one-time conference list
should be ranked differently than a trusted data partner
In an enterprise setting, the term ‘ownership’ generally
assigns a level of accountability and responsibility for
specific datasets.
8. FUNDAMENTALS OF DATA GOVERNANCE
DEFINITION -
DATA
GOVERNANCE
REFERS TO
THE GENERAL
MANAGEMENT
OF THE
INTEGRITY,
USABILITY,
SECURITY,
AND
AVAILABILITY
CAN BE A
CROSS-
DEPARTMENTAL
TEAM
INCLUDING
VOICES FROM
VARIED USERS
CREATE
FUNCTIONAL
DATA FLOWS
BETWEEN
APPLICATIONS
9. COMMON
PITFALLS IN
MAINTAININ
G YOUR
DATA
• Lack of data ownership
• Focusing only on new data and/or
Fear of removing or inactivating
data
• Data overlay – when data differs,
how do you know what data to keep
• Not understanding all data sources
• Duplication
10. DATA
QUALITY
ISSUES
• For example, if an employee hits the A key instead of the
I key when entering an address in Washington, IL, you
might end up sending marketing material to an address in
the ghost town of Washington, AL instead of the livelier
town of Washington, IL.
Inaccurate
Address Data
• If you operate internationally, having numbers that
are as complete as possible is likely to be important.
Incomplete
Phone
Numbers
• While you can’t (typically) force users to enter data
that they don’t want to enter, you can at least use data-
quality tools to identify fields within a database that are
missing, or appear likely to be inaccurate.
Missing Data
Entries
14. DATA HYGIENE
• Merge Purge: Utilize partners to
merge records from one or multiple
data sources to eliminate duplicate
records. The result is one unique
record containing all of the valuable
data.
• Data Refresh: Updating records with
current information; Adds, changes,
deletes
15. EMAIL
HYGIENE
What is email hygiene?
Email hygiene/ verification is
defined as the process of
verifying or removing invalid
email addresses from an email
list
• Increase deliverability
• Saves money
• Increased conversion rates
• Increased email ROI
16. DATA
APPENDS
Data append is taking known customer data (first
name, last name, and postal address) and matching
it against a database to obtain new information
Demographic/ Firmographic append:
Appending variable(s) to a customer file
Email append: Utilizes a postal address to
provide customers with an email address
Reverse append: Uses an email address to
provide customers with a postal address
What is a Data Append?
18. IMPORTANT CHALLENGES OF DATA
INTEGRATION
Defining Data
Integration - What
are you integrating?
1
Formatting of data
sources – How are
you integrating it?
2
Defining KPIs of the
Data – Why are you
integrating it?
3
Do you have the
infrastructure to
support the
integration?
4
What are the costs
involved in the
integration?
5
Data integration can pose multiple challenges during the
implementation process if you do not approach it the right way.
Successful data integration requires knowledge and thorough
planning.
19. DATA
INTEGRATIO
N
SOLUTIONS
Understand all your data sources and
repositories and the workflows between them
Understand
Identify key fields that can link source data to
your existing data
Identify
Seek outside assistance with data mapping
tools to update existing and new records
Seek
