8. 8
CUSTOMER INSIGHTS
AND ANALYTICSC U STO MER
ST R AT EG Y
D ATA D R IVEN
MAR KET IN G
C U STO MER
IN T ER AC T IO N
MAN AG EMEN T
WE ARE NOW PROVIDING THIS CAPABILITY AS
A SERVICE TO OTHER ORGANISATIONS
R ESU LT S AN D
BU SIN ESS
R EPO RT IN G
10. Business models
evolving
10
SOURCES OF COMPETITIVE ADVANTAGE ARE CHANGING
Barriers
to entry decreasing
Industry convergence
NEW ENTRANTS ACCESS
LOWER COST AND
MORE AGILITY
Scale has historically
been a key advantage
Implications for INCUMBENTS
Now becoming one of its
biggest weaknesses
11. 11
HOW DOES AN INCUMBENT COMPETE
Customer
interactions
Brand
Customer
knowledge
12. KEY PRINCIPLES FOR USING BIG DATA
12
MUST BE YOUR PERVASIVE
MANAGEMENT APPROACH
333 444
555
222
111
ORGANISATIONAL
BEHAVIOUR
AND STRUCTURE
EXTRACTING
THE VALUE
DATAENRICHMENT
OPERATIONALISE
& EXECUTION
13. 13
IT IS NOT JUST ABOUT THE DATA & INFRASTRUCTURE
WHERE THE
INSIGHTS
COULD BE USED
CREATION
OF INSIGHTS
DELIVERY
OF INSIGHTS
Sales and
marketing
Strategy
formulation
Product
design
Capital allocation
Planning and
forecasting
Pricing
and yield
management
Loyalty Customer
service
MeasurementPrediction
Test & learn
Insights requests
Management
Insights “automation”
Customer interactions
THE
CUSTOMERS
THE CONSUMER
14. KEY PRINCIPLES FOR USING BIG DATA
14
MUST BE YOUR PERVASIVE
MANAGEMENT APPROACH
333 444
555
111
EXTRACTING
THE VALUE
DATAENRICHMENT
OPERATIONALISE
& EXECUTION
222
ORGANISATIONAL
BEHAVIOUR
AND STRUCTURE
15. IT’S NOT ABOUT DATA
IT’S ABOUT CREATING CHANGE
DATA WON’T CREATE CHANGE
Customer analytics should create change across all
departments in the organisation
15
Ensure the organisation can keep up with the rate of
change – and wants to
17. KEY PRINCIPLES FOR USING BIG DATA
17
MUST BE YOUR PERVASIVE
MANAGEMENT APPROACH
444
555
111
DATAENRICHMENT
OPERATIONALISE
& EXECUTION
222
ORGANISATIONAL
BEHAVIOUR
AND STRUCTURE
333
EXTRACTING
THE VALUE
18. COMMERCIAL INVOLVEMENT IN DECISION MAKING
Decision complexity level
Low High
Management
Decision
owner
Common
perception
Best practice
approach
18
System
19. ARTICULATE RESULTS
IN A WAY THE BUSINESS
CAN UNDERSTAND
EXTRACTING
19
THE VALUE
HAVE HIGHLY SKILLED
COMMERCIAL LEADERSHIP
DRIVE ANALYTICS
20. KEY PRINCIPLES FOR USING BIG DATA
20
MUST BE YOUR PERVASIVE
MANAGEMENT APPROACH
555
111
OPERATIONALISE
& EXECUTION
222
ORGANISATIONAL
BEHAVIOUR
AND STRUCTURE
333
EXTRACTING
THE VALUE
444
DATAENRICHMENT
21. Dan
38
Bronze
1 int. flight with Qantas last year
No other icon usage
John
38
Bronze
1 int. flight with Qantas last year
No other icon usage
21
KNOWLEDGE OF THE INDIVIDUAL CUSTOMER IS CRITICAL
22. 38
Bronze
1 int. flight with Qantas last year
No other icon usage
38
Bronze
1 int. flight with Qantas last year
No other icon usage
22
KNOWLEDGE OF THE INDIVIDUAL CUSTOMER IS CRITICAL
John
4 kids
Ideal reward is voucher
Interested in family friendly activities
Took his only flight with us
Stay at home Dad
QFF promoter
Optus user
Dan
Ideal reward is upgrade
Single
Loves food & wine
Platinum with other FFP
Owns his own company
QFF detractor
Frequent user of hotels & hire cars
23. Qantas Frequent Flyer Predicting Flight Behaviour
Fitted
Observed
Customer ranking model percentile
Actual
probability of
flying with
Qantas
ENHANCED DATA WILL GENERATE FAR SUPERIOR RESULTS
0 10 20 30 40 50 60 70 80 90 100
23
24. KEY PRINCIPLES FOR USING BIG DATA
24
MUST BE YOUR PERVASIVE
MANAGEMENT APPROACH111
222
ORGANISATIONAL
BEHAVIOUR
AND STRUCTURE
333
EXTRACTING
THE VALUE
444
DATAENRICHMENT
555 OPERATIONALISE
& EXECUTION