welcome [tc18.tableau.com] · agenda intro –who we are think big: business problem –sales...
TRANSCRIPT
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Welcome
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Leveraging Analytics & Data Science to Empower Sales & Marketing: A Viz for the Biz
# T C 1 8
Stefanie Dombek
Sr Mgr Marketing Operations and Analytics
Cloudera
Michael Stephenson
Senior Data Architect
Cloudera
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Agenda
Intro – Who we are
Think Big: Business Problem – Sales lacked integrated information to make educated decisions
The solution: Create a sales recommendation engine
Start Smart: Intent data
Iterate Often
Solution - V0
Solution – V1
Solution – V2
Solution – V3
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Introduction
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Stefanie Dombek, Sr. Mgr. Marketing Ops & Analytics
Homesteader and supermom by nightData nerd by day
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Michael Stephenson, Senior Data Architect
Data nerd by nightData nerd by day
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Think big – The business problem
Sales lacks integrated information to make educated business decisions.
Who do we target with what message?
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Solution: Create a sales recommendation engine
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Intent Data tells you what
businesses are interested in
Through the observation of business users’ content consumption, Intent data
identifies the increased interest and research activity that takes place prior to
purchase. Thus indicating potential ‘intent’ to take an action.
Start smart – Intent data
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V0: The Excel Spreadsheet
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V0: Create a sales recommendation engine
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V0: The Excel Spreadsheet
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EDH
SO, we put the data into our EDH
DailyProcessing
Structured
Day 1
Day 2
Day 3
Day N
... BomboraDatabase
SFDCDatabase
HourlyProcessing
cloudera.comintent data
Op
tim
izat
ion
s
all otherintent data
Raw
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V1: Create a sales recommendation engine
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V1: View 1
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V1: View 2
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Solution: Create a sales recommendation engine
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ITERATEV2: Trending
Stef and Michael review
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ITERATEV3: The butterfly chart
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ITERATE V4 – Sales Recommendation Engine
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ANALYTICS
CORE
Always on Advertising
ANALYTICS
COMPETITOR
CLOUD
OTHER
MACHINE LEARNING
(CORE, CYBER, IOT)
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Current work:think even BIGGER ...
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Propensity Modeling in the EDH
Picking better customers via machine learning
Which companies have
high-yield potential?
Which potential high-yield
companies are likely to buy soon?
What is the probability of
winning a given opportunity in the pipeline?
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Conclusion
What made this successful?
• The shift or mindset change to view this really cool data set through a sales lens
and serving it up as they view the world daily (based on SFDC)
Tips for marketers who want to move this way
• Think big – Be bold and solve a big question
• Start smart – Find your differentiated data set
• Iterate often – Get a minimum viable product out the door
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Thank you!
#TC18
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