crm data myths
TRANSCRIPT
#DataMyths
Dispelling CRM Data Myths
Donato DiorioFounder & CEOBroadlook Technologieswww.broadlook.com
Michael FarringtonChief Product OfficerRingLeadwww.ringlead.com
#DataMyths
Collaborative selling
CloudBig data & sales
intelligence
Mobile
Key trends in CRM
Social
Analytics
Metrics/ Dashboards
Empowered Users
#DataMyths
Enhance
Clean
Protect Enhance
Without…
The Foundation: Good CRM Data
#DataMyths
Enhance
Clean
Protect Enhance
Without…
Poorfoundation
Without performing a
comprehensive data cleanse, the
foundation is weak
The Foundation: Good CRM Data
#DataMyths
Enhance
Clean
Protect Enhance
Without…
Decaying data
Without a protection
strategy, your data will continually
decay
The Foundation: Good CRM Data
#DataMyths
Enhance
Clean
Protect Enhance
Without…
Limited
potential
Without enhancing your existing data
you limit your “data potential”
The Foundation: Good CRM Data
#DataMyths
It’s ok to delete data
MYTH
#DataMyths
Never delete CRM data - Score it Instead!
11/21/13: Donato is the decision maker for CRM Add ons06/15/13: Dan went to Kansas State, played football04/10/13: April is Donato’s assistant03/19/11: Matt Smith is the new Doctor, Donato is Dr. Who fan
Notes:
#DataMyths
Scoring Data: Focus on Good Data
11/21/13: Donato is the decision maker for CRM Add ons06/15/13: Dan went to Kansas State, played football04/10/13: April is Donato’s assistant03/19/11: Matt Smith is the new Doctor, Donato is Dr. Who fan
Notes:
#DataMyths
What can we learn/derive from the existing data?
• Domain is broadlook.com• Email pattern in first-initial(.)last-name• April reports to Donato• On broadlook.com, there are 15 additional contacts• Notes on Donato are 1 month old• Notes on April are 8 months old• Natalie is no longer at the company• “The Doctor” is a fictional character• Natalie is now a VP at another company - and an
additional prospect!
#DataMyths
MYTH
Using the stick works:make all fields required!
#DataMyths
Using the stick works
• Determine carrot and/or stick on field basis, not object
• Educate users on the importance of everything you ask of them (focus on selfish reasons)
• Don’t ask what they don’t know
#DataMyths
Training works to enforce data standards
MYTH
#DataMyths
#DataMyths
Enforcing Data Standards is Optimal
#DataMyths
My Data is Fairly Complete
MYTH
#DataMyths
My Data is Fairly Complete
• Superstition or fact? Find out!
#DataMyths
My Data is Fairly Complete
#DataMyths
Buy as much data as you can, all at once
(because it’s cheaper)
MYTH
#DataMyths
Data decay happens
• Change in title, promotion
• Change in working location
• Change of phone number
• Add mobile phone number
• Change of department
• Change of area code
• Change of email format
• Merger or acquisition
#DataMyths
#DataMyths
Bad Data is IT’s Problem
MYTH
#DataMyths
Bad Data is IT’s Problem
• He who reporteth upon it...
• Treat it like a project
• Choose Data Quality applications that don’t require a PhD in Computer Physiology
#DataMyths
The company’s name is more important than
the website address
MYTH
#DataMyths
Contact based
Month
NamesTitles
Emails addressPhone
BiographiesSocial Network Links
Real time content
spidering
Event & Activity Based
Day Hour
Dynamic
NewsEmail content
BlogsNet links
social networksnewsgroups
TweetCheck-In’sProximity
Website visitsEmail reads
Semantic monitoring
services
Real time API’s
Company Based
Decade Multi year Year Quarter
Static
URL Corp Name
CityState
AddressZip
PhoneCompetitors
RevenueEmployeesProductsServices
Financials
Database merging + algorithm
Editorial & Aggregation
Editorial + SEC spidering
Changes
Data types
Acquisition
method
Static, compiled and online databases Real timeUpdate
strategy
#DataMyths
I know how to search for duplicates
MYTH
#DataMyths
I know how to search for duplicates
• It gets messy
• Users may not have access
• Even if you do, is that a good use of your
(user’s) time?
#DataMyths
My vendor’s data is better than mine(they are the specialists right?)
MYTH
#DataMyths
•Buy data from multiple sources•Refresh top companies with editors •6 month cycle (top 10K companies)•6-12 month (next 40K companies)•24 month cycle on the next 2 million•Nothing past the top 2 million•Add social data (good for top 10%)•Add news feeds (good for top 5%)•Mob source
Data industry processes
#DataMyths
How recent is the list as whole? How quickly was the list produced? Different from record freshness. Contact data degrades 3% per month (5% in a stressed economy). A list of 1000 records can be built over 60 days. In the case below, the first 500 records are 8 weeks old (5.68% inaccurate) upon list delivery.
96.8%
Buying data...why, how and gotchas
#DataMyths
86.5%
59.5%
Buying data...why, how and gotchas
#DataMyths
Your data vs. your vendor’s
• Your data is less complete
• Your data has a better competitive
advantage
• Use their data to fill in your data
#DataMyths
My data is awesome!
MYTH
#DataMyths
Points Your scoreFactors 4 3 2 1
Fresh <30 days <60 days <90 days <180 days
Accurate 95.00% 80% + 70% + 60% +
Multi-venueAll
availableBasic + 2 social Basic + 1 social
Basic(email+phone)
Built fast <14 days < 60 days < 90 days < 180 days
Normalized Enforced Plan + culture Has plan no
ScoredCustom
rulesAccessible
ruleswhite box
scoringblack box
scoring
Total data quality score:
CRM Data Quality
#DataMyths
Points Your scoreFactors 4 3 2 1
Targetedtarget by self description
hand built keywords SIC code
Custom built on-demandmashed from many sources
pulled from larger sample
Complete 95%+ 80.0% 60.0% 40.0%
Exclusive no competitors limited accessanyone can buy
accessfree
TransparentSources
transparentsources known
sourcesavailable
Verified By a personMarketing
automationemail
Total competitive advantage score:
CRM Competitive Advantage
#DataMyths
12
24
0 12 24
Data Quality
Co
mp
etit
ive
Ad
van
tage
Where is your CRM data?
#DataMyths
12
24
0 12 24
Quadrant Key
Data Quality
Co
mp
etit
ive
Ad
van
tage
Qualitative /Event-Driven
Influence
Quantitative/commodity
Cold Call
newCRMlead
Quantitative /Cyclic
Warm call
QualitativeCyclic
Relationship
CRM+90 days
CRM+180 daysCRM+
360 days
What is your data potential?
marketing automatio
n
#DataMyths
Preventing Duplicate Records Based on Email is Sufficient
MYTH
#DataMyths
Preventing Duplicate Records Based on Email is Sufficient
● No. Not even for sending emails.● Email addresses are not social security
numbers● True story: I had four email addresses at one
company
#DataMyths
My sales team lets me know what they need
MYTH
#DataMyths
Data Information Knowledge Process
I want...More data (lists)I want... Better selection (databases)
I want... More contacts per company (zoom)I want... Fresher contacts(Jigsaw)
I want... More information (LinkedIn)I want... More knowledge (many sources)
I want... More process (crm)I want... Sustainable process
The Evolution of Sales Desire
#DataMyths
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