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Robert Moberg, Prediktiv Analysexpert, IBM Sverige
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Prediktiv analys och kundlojalitet
1.
2. Prediktiv analys och
kundlojalitet
Robert Moberg
Predictive Analytics Solutions Architect
3. Let me start with a few of qoutes...
§ ”In the factory we manufacture lipstick, in
the store we sell hope”
– Charles Revson
– 1906 – 1975
– Creater of Revlon
§ ”People don't want to buy a quarter-inch
drill, they want a quarter-inch hole.”
– Theodore Levitt
– 1925 – 2006
– Harvard Professor
§ ”We don’t sell an analytics platform – we
provide happy, loyal and prospering
customers”
– Robert Moberg
– 1969 –
– PASA at IBM
4. It is not the
strongest of the
species that
survive, nor the
most intelligent,
but the one most
responsive to
Charles Darwin change.
5. A Sample of A Universe of Things That Generate
Data Data
?
6. A Universe of A Predictive
Data Model
Attributes
•Married, 2 kids
•Home owner in Liseberg,
Älvsjö
•Has a house in Gotland
•Owns a car
•41 years old
•Enjoys fine wines and
champagne
•Plays golf
Predicted Attributes
•Likes Beastie boys
•Likes Gotland
•Works long hours
•Commutes
•Middle Income
Predicted Behavior
•Dines in descent restaurants
•Consumes a lot of electricity
•Buys green fees
•Family vacations
7. An Overwhelming Amount of Data to Process
High-value, dynamic
Social Media - source of competitive differentiation Open-Ended
(networks) Surveys
Interaction data Attitudinal
- E-Mail / chat data
transcripts - Opinions
- Call center notes - Preferences
- Web Click-streams 360 degree - Needs &
- In person dialogues Desires
Customer View
Descriptive data Behavioral
- Attributes data
- Characteristics - Orders
- Self-declared info - Transactions
CRM - - Payment Operational
Systems (Geo)demographic history Systems
s “Traditional - Usage history
”
IBM confidential
8. Evolutionary Solutions for Customer Intimacy
Differentiating Breakaway Foundational Competitive
Insight for
Decision Makers
The Next Best Action
9. Define the Strategy Run the Business
Year Month Week Day Hour No
s s s s s w
Time to Business Impact
Improve senior management Improve policy makers’ Help individual
visibility with decisions with contributors take the
Key Performance Predictors Forecasts and Optimization Next Best Action
Strategic Tactica Operational
l
11. Customer Analytics
One to One
Research &
Purchase
Purcha Product
Advoc
se
ate
More
Produ
ct
Get Use
Customer Prod
The Broad Brush
Service uct
12. Operational Analytics
Agile
Develop
ment
Procure
ment
Availab
Distributi
ility
on
Long term planning
13. Risk Analytics
Proactive Defin
e
Allow
Monito
Preven r
t
Corrective Detec
t
14. Darwinism according to me: It is not the
vData is key strongest of the
vUnderstanding data is one thing knowing what to do with it
is another species that
vIt’s easier to give people what they want if you know the
survive, nor what
that is most intelligent,
vCustomer analytics, a prerequisite to but the one your
be relevant to most
customers
responsive to
vCustomer analytics and insights provide decision support
Charles Darwin change.
vDecisions will be reliable, because they are based on facts
not on speculation
Predictive Customer Analytics will make your
company responsive to change!!!