RingLead, McKnight Consulting Group and Cirro, Inc. team up to present business intelligence best practices using your biggest asset: Data.

1. #Datafabric
The New Frontier: How to Gain Insight with
Interwoven Quality Data
Webinar with Jake Dolezal, Mike Franko & Donato Diorio

2. Data as a Story
✤ Data is an asset
✤ Data tells stories
✤ Humans have used
stories as our principle
means of communication
for thousands of years
#Datafabric

3. Each system
tells a story
✤ CRM tells customer
stories
✤ ERP tells enterprise
stories
✤ Point-of-sale transactions
are vignettes of customer
purchases
#Datafabric

4. Quality matters
Tell the…
✤ Most complete
✤ Most accurate
✤ Most consistent
Story possible
#Datafabric

5. I have great quality data, so now what?
✤ Even with data of the highest quality, it still only tells a small isolated
story.
✤ An eye-witness account is biased by its limited point-of-view.
✤ It may be correct, but it is only one perspective
✤ But what about the other interactions that lead to that purchase? What
happened? Who did they talk to? What did they see or hear? What
influenced them?
✤ Don’t be shortsighted and only see part of the story
#Datafabric

6. Bringing data together…the old way
#Datafabric

7. Conventional integration cannot keep up!
#Datafabric

8. Introducing the Data Fabric…
#Datafabric

9. Single point of entry for all data
#Datafabric

10. Data Practice Evolution
#Datafabric

11. #Datafabric
• Companies
solve
the
problems
themselves
• Focus
on
symptoms
vs.
cause
• Every
project
starts
anew
• Very
little
automation
• Service
costs
are
astronomical
• Over
time
&
budget
The
first
rule
of
any
technology
used
in
a
business
is
that
automation
applied
to
an
efficient
operation
will
magnify
the
efficiency.
The
second
is
that
automation
applied
to
an
inefficient
operation
will
magnify
the
inefficiency.
-­‐Bill
Gates
Data Evolution: Do-it-yourself era

12. #Datafabric
• Focus
is
still
symptom
vs.
cause
• Product
is
reviewed
more
than
the
problem
(whether
is
it
dedupe,
data
fill,
etc
)
• Product
fit
is
the
focus
• Gaps
in
the
product-­‐solution
are
ignored
• Leads
to
partial
solutions
• Less
consultative
sales
process
The
problem
always
looks
like
a
nail
when
you
only
have
a
hammer.
Data Evolution: Product era

13. Data Evolution: Consultant era
• Consultants
are
product
specialists,
process
generalists
• Learning
on
client’s
time
• Abundance
of
“try
and
fix”
iterations
• Longer
process,
most
expensive
• More
expensive
than
doing
it
in-­‐house
• Gaps
in
the
product-­‐solution
are
ignored
• Failure
rate
is
similar
to
early
CRM
implementations
#Datafabric

14. Data Evolution: Expert era
#Datafabric
• Experts
in
product
and
process
• Quicker
process
• Less
expensive
than
doing
it
in-­‐house
• “Try
&
fix”
iterations
much
less
common
• Success
is
common,
break
downs
happen
when
advice
is
ignored

15. Data Evolution: Assessment era
#Datafabric
• Data
assessment
starts
the
process
• Decisions
based
on
data
facts
vs.
expert
hunches
• Fewer
“try
and
fix”
iterations
• Assessment
provides
better
visibility
into
solution
set
required
• Fastest
time
to
start
and
complete
project
• Once
you
assess,
ready
for
expert!

16. 9 lost secrets of Clean Data
#Datafabric

17. What is Clean Data?
Minimalist:
Only
what
you
need,
uncluttered
Integrated
:
Supportive
of
your
CRM
Complete
:
URL,
emails,
address,
points
of
contact
Expandable
:
Data
catalysts,
URL
&
social
links
#Datafabric

18. Based
on
total
record
count
across
all
silos,
choose
an
appropriate
number
of
random
records
from
silos
to
perform
a
data
test.
What
is
the
state
of
the
data?
Company
record
completeness
(url,
address,
city,
etc)
Contact
record
completeness
(name,
email,
phone,
bio,
etc)
Contact
record
depth/company
(number
of
contacts
per
company)
Secret 1: DataTest
#Datafabric

19. A
look
at
CRM,
Email
systems,
lead
databases
and
any
silos
of
information
which
drives
the
business.
The
end
goal
is
to
have
a
solid
understanding
of:
Business
process
Vendors
used
Data
flow
Known
problems
Process
gaps
Silo
interconnectivity
Silo
latency/data
age
Silo
normalization
Silo
record
count
Potential
problems
Secret 2: Silo Review (not just CRM)
#Datafabric

20. Develop
a
CRM
Data
Plan
which
is
crucial
to
the
entire
project.
The
CRM
Data
Plan
is
used
for
cleaning,
enhancing,
de-­‐duping,
and
eventually
protecting
the
CRM
from
additional
duplicates.
(Data
ShieldTM
)
Secret 3: CRM Data Plan
#Datafabric

21. Websites
are
the
future
backbone
of
company
data.
Fill
in
URLs
for
company
records.
Some
companies
have
multiple
brands
and
multiple
websites.
This
step
is
critical
to
keeping
company
and
contact
information
fresh.
URL
fill
is
critical
to
resolve
ambiguous
company
names
for
later
deduping.
Secret 4: URL fill
#Datafabric

22. Secret 5: Email Capture
A
large,
untapped
source
of
contact
information
and
connection
strength
lies
buried
in
email
archives.
Select
email
contacts
based
on
email
counts,
names,
companies
or
connection
strength.
Selected
contacts
and
companies
are
held
for
final
data
reintegration.
#Datafabric

23. Secret 6: Normalize your Data
Using
the
CRM
Data
Plan,
all
extracted
data
silos
are
normalized.
Normalized
data
is
ready
for
deduping.
Deduping
will
be
600%
more
effective
if
Normalization
is
done
first.
(6%
dupes
vs
<1%)
#Datafabric

24. Secret 7:Address correction
Provides
standard
address
correction.
This
step
can
be
done
before
or
after
the
data
load
back
into
the
CRM.
Very
large
address
appends
are
best
done
before
loading.
#Datafabric

25. Secret 8: Company Profiling
Scan
the
public
web,
in
real-­‐time
for
contacts
at
each
unique
company.
Data
returned
includes
names,
titles,
emails,
phone
numbers,
professional
bios
and
social
network
links.
#Datafabric

26. Secret 9: Market Mapping
Add
segmentation
tags
into
the
account
record
of
your
CRM.
Industry-­‐only
categorization
is
not
enough
for
the
demands
of
marketing
automation
that
requires
segmentation
for
effective
campaigning.
tags
#Datafabric

27. #Datafabric
Q&A
Free Ebook
bit.ly/CRM-Plan