1. The Technology that Drives the
Modern Marketing Department
Thursday, February 13th 2014
#B2BBrains

2. Topics for Today’s Session
● How has the role of marketing changed in the
past 10 years? How will it change in the future?
● Traditional “data-think” will not be adequate to
prepare for the future of marketing
● How marketers can leverage new technologies
to engage in conversational marketing with
prospects & customers
● How to develop processes, personas and
messages that resonate with your target
prospects.
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3. The
Modern
Marketer
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4. Prepare for the coming revolution!
Phase 1: Inspect and Correct
your Foundation: Put Data First!
Phase 2: Develop your Processes,
Personas and Message.
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5. About the Speakers
Justin Gray
CEO & Chief Marketing
Evangelist, LeadMD
@jgraymatter
Donato Diorio
CEO, RingLead
@idonato
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6. The Data decision: It starts with a clear vision
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7. Turn left or turn right?
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8. Left
1 contact with:
• company name
• name
• title
• email
• phone
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Right
Multiple contacts with:
• company name
• name
• title
• title level
• department
• email
• verified email
• phone
• company sector
• company description
• bio

9. 1 flavor
●
●
●
●
Generic campaign
List fatigue
High unsubscribes
No segmentation
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Multiple
•
•
•
•
Targeted campaign
Fresh data
Growing interest
Ability to segment

10. The 3 P’s and the Foundations of Data
● Data Planning - what are my goals?
● Data Potential - what is possible?
● Data Philosophy - how to achieve it?
Data powers your CRM and marketing automation platform
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11. Upgrade your
Data-Think
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12. How do I build a
great database?
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13. The Foundations of Data Execution
Without…
Clean
Protect
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Enhance
Enhanc
e

14. The Foundation: Good Campaign Data
Without…
Clean
Protect
Without
performing a
comprehensive
data cleanse, the
foundation is weak
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Poor
foundation
Enhance
Enhanc
e

15. The Foundation: Good Campaign Data
Without a
protection
Without…
strategy, your data
will continually
decay
Clean
Decaying
data
Protect
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Enhance
Enhanc
e

16. The Foundation: Good Campaign Data
Without enhancing
your existing data
you limit your
“data potential”
Without…
Clean
Limited
potential
Protect
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Enhance
Enhanc
e

17. Is it OK to delete
data?
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18. Never delete CRM data - Score it Instead!
Notes:
11/21/13:
06/15/13:
04/10/13:
03/19/11:
#B2BBrains
Donato is the decision maker for CRM Add ons
Dan went to Kansas State, played football
April is Donato’s assistant
Matt Smith is the new Doctor, Donato is Dr. Who fan

19. Scoring Data: Focus on Good Data
Notes:
11/21/13:
06/15/13:
04/10/13:
03/19/11:
#B2BBrains
Donato is the decision maker for CRM Add ons
Dan went to Kansas State, played football
April is Donato’s assistant
Matt Smith is the new Doctor, Donato is Dr. Who fan

20. 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!
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21. How can I enforce
data quality best
practices?
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22. Both Carrot and Stick work
• 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
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23. Can training help
enforce data
standards?
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24. #B2BBrains

25. Enforcing Data Standards is Optimal
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26. How complete is
my data?
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27. My Data is Fairly Complete
• Superstition or fact? Find out!
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28. My Data is Fairly Complete
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29. Shouldn’t I buy as
much data as I can
all at once?
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30. Data decay happens
• Change in title, promotion
• Change of department
• Change in working location
• Change of area code
• Change of phone number
• Change of email format
• Add mobile phone number
• Merger or acquisition
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31. #B2BBrains

32. Isn’t bad data
IT’s problem?
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33. Company Based
Changes
Decade
Multi year
Year
Contact based Event & Activity Based
Quarter
Month
Day
Static
Data types
Acquisition
method
URL
Database
merging +
algorithm
Update
strategy
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Hour
Dynamic
Corp Name
City
State
Address
Zip
Phone
Competitors
Editorial &
Aggregation
Revenue
Employees
Products
Services
Financials
Editorial + SEC
spidering
Static, compiled and
online databases
Names
Titles
Emails address
Phone
Biographies
Social Network Links
Real time
content
spidering
News
Email content
Blogs
Net links
social networks
newsgroups
Tweet
Check-In’s
Proximity
Website visits
Email reads
Semantic
monitoring
services
Real time
API’s
Real time

34. How good is my
vendor’s data?
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35. Data industry processes
•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
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36. Buying data...why, how and gotchas
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%
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37. Buying data...why, how and gotchas
86.5%
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59.5%

38. 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
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39. How good is
my data?
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40. CRM Data Quality
Points
4
3
2
1
Fresh
<30 days
<60 days
<90 days
<180 days
Accurate
95.00%
80% +
70% +
60% +
Multi-venue
All
available
Basic + 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
Scored
Custom
rules
Accessible
rules
white box
scoring
black box
scoring
Factors
Total data quality score:
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Your
score

41. CRM Competitive Advantage
Points
4
3
2
1
target by self
description
hand built
keywords
SIC code
built on-demand
mashed from
many sources
pulled from
larger sample
Complete
95%+
80.0%
60.0%
40.0%
Exclusive
no competitors
limited access
anyone can buy
access
free
Sources
transparent
sources known
sources
available
By a person
Marketing
automation
email
Factors
Targeted
Custom
Transparent
Verified
Total competitive advantage score:
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Your
score

42. Where is your CRM data?
Competitive
Advantage
24
12
0
12
Data Quality
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24

43. What is your data potential?
Qualitative /
Event-Driven
Qualitative
Cyclic
Quantitative /
Cyclic
Quantitative/
commodity
Competitive Advantage
Quadrant Key
24
Influence
Relationship
m
o
a
12
ng
ti
ke
ar
ut
a
on
ti
CRM+
90 days
CRM+
180
m
CRM+ days
360
days
Cold Call
0
new
CRM
lead
Warm call
12
Data Quality
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24

44. Can I Prevent Duplicate
Records Based
on Email Address?
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45. Prevent duplicate based on email?
● No. Email addresses are not social security numbers
● I have five current email addresses
■ ddiorio@broadlook.com
■ dd@broadlook.com
■ donato@broadlook.com
■ dd@ringlead.com
■ donato.diorio@gmail.com
● I get duplicate emails to (four) emails.
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46. Does my marketing
team know
what they need?
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47. The Evolution of Marketing Desire
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
Data
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Information
Knowledge
Process

48. So What’s the Next Step in That Evolution?
CONVERSATION
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49. Science shifts to Art
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50. Demographics
• The Building Blocks
Standardize
Normalize
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“Buyerize”

51. Firmographics
• The Blueprint
– Revenue Bands
– Purchasing Profiles
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52. Psychographics
• Buyer Personas
– Need
– Pain
– Motivation
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53. The Result
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54. Behaviors
• The Craft
– Behavior is 60% of the equation
– “Lead” and the fallacy of data
– If you wield it, they will come
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55. The Conversation is Born
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56. Apply the Science to make Art
• Inputs
• Processes
• Revenue Path
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57. Buyer Personas
• Think of Data as Conversation Queues
• Route “leads” based on commonality
• Communicate based on:
– Recency
– Felt Need
– Pain
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58. Engage with Process!
• Bring everything together
• Build a success path
• Measure
success
– Time
– Progression
– Result
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59. Watch Out Though
• Automation increases the probability of
– Mistakes
– Duplicates
– Rogue messages
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60. #B2BBrains

61. Pitfalls to Avoid
• Overwriting Key Data
– Lead Source
– Original Search Terms
• Channel Fatigue
• Data Maintenance & Purge
• Record Types
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62. How Does Success Look?
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63. Le
ar
n
M
or
e!
How can data quality create a
competitive advantage for you?
Download our free whitepaper, Put Data First
www.RingLead.com/putdatafirst
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64. Q&
Questions?
Need help getting your
data in order?
Contact RingLead
www.RingLead.com
sales@ringlead.com
1.888.240.8088
Need help building a worldclass revenue engine?
Contact LeadMD
www.LeadMD.com/pigsfly
1.888.294.9854
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A
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