To view the full webinar, please visit:
http://www.mintigo.com/how-to-be-a-data-driven-marketing-powerhouse-with-predictive-analytics-big-data/
Description:
How is it that b-to-b marketers have more data sources than ever before, but many are still in the dark about how to reach more of the right prospects? Sometimes the sheer volume of data can seem overwhelming, but it doesn’t have to be. In fact, with the right processes, skills and tools, many companies are transforming their approach to demand creation and letting data do the work for them.
Marketers need to make decisions in a data-rich environment, where vast amounts of customer data are flowing not only from the company’s internal systems such as CRM, marketing automation and web analytics, but also from external sources such as social, mobile, and other sources that can be found all over the web. But how do you separate the good data that signify buying signals from the noise found in the rest of the data? And what new skills and processes bring them to life?
In this dynamic session, we’ll hear from thought leaders from LinkedIn, SiriusDecisions and Mintigo on the best strategies for taking a data-driven approach to marketing. They will address key considerations and best practices to answer essential questions around:
-How the explosion of big data and emerging predictive technologies is transforming the marketing discipline
-Examples of marketers at leading companies are effectively utilizing big data & predictive analytics
-Recommendations for preparing your marketing team to become a data-driven organization
The Speakers:
- Russ Glass, Head of Products at LinkedIn
- Megan Heuer, VP & Group Director, Data-Driven Marketing at SiriusDecisions
- John Bara, President & CMO at Mintigo
10. “Big data is the most
disruptive business force
there is. Big data is the stuff
that is really moving
economic power from one
group to another.”
Geoffrey Moore, Crossing the Chasm and Inside the Tornado
10
16. THE BIG QUESTION
ABOUT BIG DATA:
How do I implement big
data principles in my
own business?
PRINCIPLE NO. 1
Determine what you know
(and want to know) about
your customer.
16
17. THE BIG QUESTION
ABOUT BIG DATA:
How do I implement big
data principles in my
own business?
17
PRINCIPLE NO. 2
Start small by thinking,
‘Big data, little triggers.’
18. THE BIG QUESTION
ABOUT BIG DATA:
How do I implement big
data principles in my
own business?
18
PRINCIPLE NO. 3
Be prudent but not shy about
investing in technology: CRM
systems are a must, marketing
automation is becoming so, and
analytics tools are a no-brainer.
19. THE BIG QUESTION
ABOUT BIG DATA:
How do I implement big
data principles in my
own business?
19
PRINCIPLE NO. 4
Hire the right people. Marketers
must hire data-oriented people,
math majors, and left-brained
thinkers.
20. THE BIG QUESTION
ABOUT BIG DATA:
How do I implement big
data principles in my
own business?
20
PRINCIPLE NO. 5
Test, test, test, measure,
measure, measure. Ideally,
measure your contribution to
revenue: It is the way to prove
marketing’s value.
24. MQL
SAL
66%
SQO
32%
Won
7%
“
T
h
e
C
l
i
f
f
“
There
is
no
leverage
in
today’s
demand
gen
process
2.89
wins
per
1,000
inquiries*
93%
Loss Rate
AN INEFFICIENT PROCESS
25. 60%
to
80%
Data
is
bad
or
has
no
chance
of
closing
40%
to
50%
Wrong
nurture
track
/
inability
to
see
stage
4x
to
10x
Top
line
growth
leU
on
the
table
Process
relies
on
data
shared
by
the
customer
with
liWle
augmentaXon
MARKETING
AUTOMATION
Campaigns
List
buys
Whitepapers
Webinars
Tradeshows
DEMAND
ACTIVITY
MARKETING
FUNNEL
Nurture
Score
Analyze
MQL
SAL
SQL
DEMAND GEN PROCESS
26.
Cost
per
Win
Outstrips
ROI
in
Most
Cases
AN EXPENSIVE PROCESS
2.89
wins
per
1,000
inquiries
@
average
$43
per
inquiry
27. Leverage
vast
amounts
of
data
and
science
to
predict
which
markeXng
acXons
have
a
high
probability
to
succeed
and
which
ones
will
probably
fail.
DEFINITION: PREDICTIVE MARKETING
30. Technologies
• API
Provider
• Saas
product
• Databases:
MySQL
User,
MS
SQL
Server,
Oracle
DB
• Mobile
Developers:
iOS
Developers
• VMWare
User
&
VirtualizaXon
Experts
• Oracle
User
• Cloud
Compu6ng
Tech:
AWS
• Cloud
Compu6ng
Tech:
Azure
• Data
Center
User
Apps
&
Tools
• Email
Service:
MS
Exchange
Online
• MS
Office
365
User
• MS
SharePoint
User
• CollaboraXon
Tools
User:
Jive,
Yammer,
ChaWer
• Atlassian
&
Jira
Users
• Hiring
Enterprise
Content
Mgmt
Expert
Web
Technologies
• DNS:
Neustar,
GoDaddy,
Dyn,
MadeEasy,
Amazon
• CDN
Technology:
Akamai,
Amazon
• CMS
Technologies:
SiteCore,
Joomla,
WordPress,
Drupal
• Web
Analy6cs
Technologies:
WebTrends,
OpXmizely,
CoreMetrics,
Adobe
Omniture,
Website
Technology:
Ad
Services,
Live
Chat
Company
• Growing
Company:
Hiring
>250
Employees
• Has
MulXple
LocaXons
• Company
Employs
Field
WorkForce
• Mobile:
BYOD
IniXaXve
• Mobile:
MDM/MAM
Technology
• Alexa
Ranking
• PPC
Budget
Spend
• Company
has
Call
Center
• Compliance:
SOX,
HIPAA,
FINRA/FISMA
• AdverXsing
Technologies:
Atlas,
Google
Adroll,
Google
Adwords,
DoubleClick
for
AdverXsers
DATA: Mintigo’s Marketing Indicators
31. IDENTIFY THE CUSTOMERDNA™
Ideal
Prospect
150-‐250
MIs
Customers
Prospects
Fit
score
&
appended
Leads
2,500+
MI’s
10
MM
Companies
150
MM
Contacts
Data
as
is
.
.
.
Enriched
Validated
Appended
33. • Who are my ideal prospects ? Discover your CustomerDNATM
• How should I communicate to them ? Use Marketing Indicators to create
micro-segmentations
• What should I say to them ? Predict best content to segment fit
• Where do I put my resources & focus ? Create scoring models
Decisions: Making the Right Marketing Decision
34. LEAD PRIORITIZATION
• IdenXfy
leads
most
like
to
convert
• Pass
high
scores
directly
to
sales
• Nurture
B
leads
• Scale
for
capacity
• Leverage
MI’s
to
assign
nurture
Lead
Enrichment
&
PrioriXzaXon
Telesales
ProducXon
38. Loosen
Status
Quo
Commit
to
Change
Exploring
SoluXons
Commit
to
SoluXon
JusXfy
Decision
Make
Decision
COVERING THE BUYER’S JOURNEY
Discovery Consideration Decision
Fit
Analysis
-‐
Journey
Relevance
Inside the Funnel Outside the Funnel
Mintigo Data Customer Data
SiriusDecisions, Buyers Journey Model
Intent
Analysis
-‐
Journey
Relevance
Behavior
Analysis
-‐
Journey
Relevance
39. PREDICTIVE IS MORE THAN A SCORE
Target
Accounts
Air Traffic
Control
Customer
Lifetime Value
Campaign
Design
Segmentation
Cross
Sell
Lead Enrichment
& Prioritization
Telesales production
Nurture
Design
Customer focused
Contentfocused
ValueFocused
Higher
ASP
Data Validation
& Enrichment
Insights Up
Sell
Customer
Retention
Partner
cDNA
Net New Focused
List
Buys
Incentivized
Content
Syndication
ABC
Real-Time
New
Accounts