1. April 14, 2015
Elliott Lowe
Dir, Marketing Ops
@elliottlowe
Institute for Integrative
Nutrition
Inga Romanoff
President/CEO
@ingaroma
Romanoff Consulting
Data Quality Bootcamp
Why Dirty Data = Low ROI, & What You Can Do About It
2. Page 2
Inga Romanoff
President, Romanoff Consulting
Elliott Lowe
Director, Marketing Operations,
Institute for Integrative Nutrition
With over 15 years of marketing experience in the
U.S., Russia, and EMEA, Inga is no stranger to
Marketing Automation. Inga is a Principal of a
boutique marketing automation consultancy. She
is passionate about helping clients implement and
optimize Marketo, recruit talent, and get
exceptional results. She is an award-winning
Certified Marketo Expert & a multi-year Marketo
Champion, and leads Marketo User Group in New
York.
With over 30 years of experience at startups and
large public companies, Elliott Lowe specializes in
building solid operations foundations for rapidly
growing companies. Presently, Elliott heads up
Marketing Operations at the Institute for
Integrative Nutrition, the world's largest nutrition
school. He is a Marketo-Certified Expert, a multi-
year Marketo Champion and a co-leader of the
Marketo New York User Group.
3. Page 3
Agenda #DataQuality
Why Should I Care
About Data Quality?
Where Dirty Data
Comes From
Your 6-Step Program
to Clean Data
Data Quality Saves Tips and Tricks
4. Page 4
Why Should I Care About Data Quality?
“25 percent of the average
B2B marketer’s database is
inaccurate and 60 percent of
companies have an overall
data health of ‘unreliable’.”
- SiriusDecisions study
COMPANIES DO NOT HAVE A SOPHISTICATED
APPROACH TO DATA QUALITY1
74%
MARKETERS SAY DATA QUALITY IS THE BIGGEST
OBSTACLE TO MARKETING AUTOMATION SUCCESS3
36%
COMPANIES WITH CENTRAL DATA MGTMT
HAD A SIGNIFICANT INCREASE IN PROFITS1
53%
RECORDS ANALYZED WERE LACKING
FIRMOGRAPHIC DATA2
88%
1 2015 Experian The data quality benchmark report
2 2014 Netprospex Annual Marketing Data Benchmark Report
3 Ascend2 Marketing Automation Benchmark Survey, July 2014
#DataQuality Facts
7. Page 7
6-Step Program to Clean Data
1. Perform data
audit
2. Perform systems
audit
3. Revise data capture
processes
4. Correct data
errors
5. Implement email
alerts and reports
6. Manage data quality
across the organization
8. Page 8
Where Dirty Data Comes From
Systems
• Flawed setup
• Poorly designed integrations
People and Process
• Manual input
• Lack of a data quality strategy
51%
48%
44%
32%
0%
10%
20%
30%
40%
50%
60%
Most common data errors1
1 2015 Experian The data quality benchmark report
10. Page 10
Progressive Profiling - Almost
• Successful launch of
progressive profiling
• High fillout rate except
Business Name
• Field: Company Name
• New custom field and smart
campaign with logic to
substitute “N/A” values
11. Page 11
Duplication Prevention - Not
• Dupe app matched on First Name +
Last Name + Email Address
• Most new leads from forms have
only a First Name and Email Address
• [Not Provided] added if Last Name
field is empty (for sync with SFDC)
• Dupe app almost never detected a
match, yet we had thousands of
email duplicates
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External Data Capture
• Marketo forms, Server-Side Form
Post, SOAP, REST
• Restricting form field inputs
• Form field pre-population
• Form field validation
• List import
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External Data Capture
• Marketo forms, Server-Side Form
Post, SOAP, REST
• Restricting form field inputs
• Form field pre-population
• Form field validation
• List import
15. Page 15
External Data Capture
• Marketo forms, Server-Side Form
Post, SOAP, REST
• Restricting form field inputs
• Form field pre-population
• Form field validation
• List import
16. Page 16
Sales Inputs
• Capture fields needed for marketing
• Prevent duplicate creation
• Marketing attribution for Sales leads
• [mktUnknown] created from
Outlook/Google MSI plug-in
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Sales Inputs
• Capture fields needed for marketing
• Prevent duplicate creation
• Marketing attribution for Sales leads
• [mktUnknown] created from
Outlook/Google MSI plug-in
18. Page 18
CRM Sync
• Deleted Leads / Contacts
• Leads without email address
• Sync performance
• Field visibility
• Syncing to SFDC campaigns
21. Page 21
Duplicate Records
• Email notifications and weekly
reports
• Merging is evil
• Retain values during merge
based on priority
• Mass merging with Marketo
Easy Merge
22. Page 22
Duplicate Records - Alerts
• Email notifications and weekly
reports
• Merging is evil
• Retain values during merge
based on priority
• Mass merging with Marketo
Easy Merge
23. Page 23
Duplicate Records
• Email notifications and weekly
reports
• Merging is evil
• Retain values during merge
based on priority
• Mass merging with Marketo
Easy Merge
24. Page 24
Data Normalization
• Normalization smart campaigns
• Phone and email validation
• Capitalization of the First and Last
Name in SFDC
