Data & Advanced Analytics: Executive Track by ZIFF winners of the Big Mountain Data Competition ziff.io & @ziffio

1. Data & Advanced
Analytics
Executive Track
by
ZIFF
winners of the Big Mountain Data Competition
ziff.io & @ziffio
Sponsors

3. Agenda
1. Competing with data & analytics
2. Identify where best to test a POC in your
enterprise
3. Identify requirements for a POC
4. Wrap up
5. Lunch (sponsored by: ___ )

4. Upfront Contract
YES
Business value
Specific to your needs
Getting started and next
steps
Well formed problem
Collaboration
NO
Me-too
Latest hotness
What the big guys are doing
Unrealistic/overly complex
Long lectures

5. introductions
what you hope to gain

7. Data Products
Data Aggregation
Analytics
Recommended Action
Activity

8. Product Innovation/
Product Leadership
Customer
Relationships/
Customer Intimacy
Infrastructure Mgmt/
Operational
Excellence
Economics Early market entry enables
charging premium prices and
acquiring large market
share; speed is key
High cost of customer
acquisition makes it
imperative to gain large
wallet share; economies of
scope are key
High fixed costs make large
volumes essential to achieve
low unit costs; economies of
scale are key
Competition Battle for talent; low barriers
to entry; many small players
thrive
Battle for scope; rapid
consolidation; a few big
players dominate
Battle for scale; rapid
consolidation; a few big
players dominate
Culture Employee centered; coddling
the creative stars
Highly service oriented;
customer-comes-first
mentality
Cost focused; stresses
standardization,
predictability, and efficiency
Business Core Competencies
Business Model Generation

9. Product Customer Operations
==MARKETING==
Who are your potential
customers?
What do they want?
Brand loyalty?
What’s next?
e.g
Customer seg/profile
Market analysis
Sentiment
==SALES==
What motivates
customers?
Which channels work
best?
What else do they
need?
e.g.
Engagement
Churn
Conversion
Offers
Channel attribution
==OPS==
How long will X
function?
How much product?
waste?
Will Y be cheaper?
e.g.
Yield optimization
Failure rates
Futures
Competing on analytics

10. Key
Partnerships
Key Activities
PLATFORM MGMT
MANAGING
SERVICES
EXPANDING REACH
Value
Propositions
TARGETED ADS
FREE SEARCH
MONETIZING
CONTENT
Customer
Relationships
Customer
Segments
ADVERTISERS
WEB SURFERS
CONTENT
CREATORS
Key Resources
SEARCH
PLATFORM
Channels
Cost Structure
PLATFORM COSTS
Revenue Structure
KEYWORD AUCTIONS
FREE
Business Model Canvas: Google
Business Model Generation

11. Gain, Pain, & Google
You
GainGain
Creators
Pain
Relievers
Pain
JobsProducts &
Services
FIND STUFF
TOO MANY THINGS
OFF TOPIC
SAVE TIME
PERSONALIZED
CAPACITY
TARGETING
SIMPLE UI
MAGIC
WEB SEARCH

12. Skullcandy

13. Key
Partnerships
Key Activities Value
Propositions
Customer
Relationships
Customer
Segments
Key Resources Channels
Cost Structure Revenue Structure
Your Business Model Canvas
Business Model Generation
12

14. Product Customer Operations
==MARKETING==
Who are your potential
customers?
What do they want?
Brand loyalty?
What’s next?
e.g
Customer seg/profile
Market analysis
Sentiment
==SALES==
What motivates
customers?
Which channels work
best?
What else do they
need?
e.g.
Engagement
Churn
Conversion
Offers
Channel attribution
==OPS==
How long will X
function?
How much product?
waste?
Will Y be cheaper?
e.g.
Yield optimization
Failure rates
Futures
Competing on analytics

15. Gain, Pain, & Customer/Revenue-side Analytics
You
GainGain
Creators
Pain
Relievers
Pain
JobsProducts &
Services

16. Gain, Pain, & Partner/Cost-side Analytics
Partner/
Vendor
GainGain
Creators
Pain
Relievers
Pain
JobsProducts &
Services
You

17. Skullcandy
Focus: Get more customers with online channel
Know
● Who
● vs Competition
Be able to
● Target
● Get in front
Profile
● muses & personas

18. What must be true?
What must be true in order to
detect/identify/catch ___________________?
● know
● be able to
● profile (story)

19. Inputs
twitter followers:
Skullcandy & Competitors
Facebook page “likers”:
page post likes & some profile
information
Reviews:
Skullcandy & Competitors;
by store, brand, product
Insights
Segments
(e.g. geo,
“snowboarders”,
bought, influential, etc.)
Sentiment
/Reasons
(e.g. good/bad, quality,
innovation, birthday,
back-to-school, etc.)
Clusters
(predictive e.g.
personas, buyers,
users, switchers, loyal,
etc.)
Recommended
Actions
(alerts, “mailing” lists,
offers, etc.)
these are al la carte data points even within
source
insights are cumulative (e.g. clusters are built from segments and/or reasons)
but need not be comprehensive (e.g. a single datapoint can be the basis of
recommended actions)

20. … in order to get the info
● people
● data points
● resources

21. … in order to use it
● metric(s) or key results
● tools
● technology
● expertise

22. Wrap up
Hope
You & your organization will incorporate
advanced analytics as part of your competitive
strategy in your market.

23. Wrap up
Belief
Data & Advanced Analytics can be key in better
aligning your business with strategic objectives
and can be ideal for helping to measure key
results in the course of meeting those
objectives.

24. Wrap up
Dare to dream
● Innovation as accepted norm in your enterprise
● Employees feel greater autonomy, mastery, purpose
● Shared, well defined, measurable vision and objectives
● Leaner, more productive organizations
● Delight customers

25. Thank You!
info@ziff.io
@ziffio
Sponsors