data quality bootcamp
TRANSCRIPT
April 14, 2015
Elliott LoweDir, Marketing Ops@elliottloweInstitute for Integrative Nutrition
Inga RomanoffPresident/CEO@ingaromaRomanoff Consulting
Data Quality BootcampWhy Dirty Data = Low ROI, & What You Can Do About It
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Inga RomanoffPresident, Romanoff Consulting
Elliott LoweDirector, 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.
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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
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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 report2 2014 Netprospex Annual Marketing Data Benchmark Report 3 Ascend2 Marketing Automation Benchmark Survey, July 2014
#DataQuality Facts
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6-Step Program to Clean Data
1. Perform dataaudit
2. Perform systemsaudit
3. Revise data capture processes
4. Correct dataerrors
5. Implement emailalerts and reports
6. Manage data quality across the
organization
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Where Dirty Data Comes From
Systems• Flawed setup• Poorly designed integrations
People and Process• Manual input• Lack of a data quality strategy
Incom
plete
Outdate
d
Inacc
urate
Dupli
cates
0%
10%
20%
30%
40%
50%
60%51% 48%
44%
32%
Most common data errors1
1 2015 Experian The data quality benchmark report
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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
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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
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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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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
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CRM Sync• Deleted Leads / Contacts• Leads without email address• Sync performance• Field visibility• Syncing to SFDC campaigns
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Duplicate Records• Email notifications and
weekly reports• Merging is evil • Retain values during
merge based on priority• Mass merging with
Marketo Easy Merge
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Duplicate Records - Alerts• Email notifications and
weekly reports• Merging is evil • Retain values during
merge based on priority• Mass merging with
Marketo Easy Merge
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Duplicate Records• Email notifications and
weekly reports• Merging is evil • Retain values during
merge based on priority• Mass merging with
Marketo Easy Merge
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Data Normalization • Normalization smart
campaigns • Phone and email
validation• Capitalization of the First
and Last Name in SFDC