This document discusses the evolution of customer analytics from Eras 1.0 to 4.0. Era 1.0 focused on internal metrics by business unit. Era 2.0 adopted a customer point of view and used metrics like NPS. Era 3.0 linked metrics like NPS to business outcomes. Era 4.0 uses advanced analytics and topological data analysis to generate insights without predefined questions, allowing unexpected discoveries. The document advocates moving from basic reporting to exploring data interactively to generate insights that improve customer experience and business performance.

1. 1
Quantifying
greg Stewart
SMS Management & Technology
www.smsmt.com
@clarityrules
#CX13
6 may 2013
of customer
analytics

2. questions

3. A CX LEADER’S CHALLENGE
and
to
try and make a difference?
If I do, will it be

4. CFO
They count . They want .

5. customer analytics practices

6. 1.0 2.0 3.0 4.0
four eras

7. Thurston Howell
Crystal Ball
Trip
Fall
1.0 2.0 3.0
4.0

8. 1.0 2.0 3.0 4.0

9. to get from your
you are using
What
Questions
things that you can
ask
you can ask questions
and answers are returned
How you
explore
data

10. 1.0
out
inside

11. 1.0
era 1.0 – inside out

12. 1.0
main symptom of 1.0:
A is just
the
of each business unit.

13. he isn’t.
to get from your
What
Questions
How you
explore
data

14. 2.0
in
outside

15. era 2.0 – outside in

16. :
Customer’s Point of View
entity identification
top process owners

18. Guiding Principles
Customer Journey
Opportunities
SMS Services
RIGHT VISION
STAGES
ACTIVITIES
DOING
THINKING
FEELING
Trip Initiation Enrolment Finalise Trip Post-Trip
College e-Enabled Field Trip Experience Map
• Where should I organise the trip?
• When is a good time to go?
• What processes do I need to follow?
• I’m excited about this trip!
• I’m worried it won’t get approval from the Principal
Obtain approval Schedule resources Give permissionView itinerary
Go paperless &
move towards
online processes
Adopt automated
workflow where
possible
Introduce “cloud”
spaces for remote
collaboration
Develop web forms,
portals, and apps
Build platforms to
push notifications to
SMSs & emails
• Do we have enough information about this trip?
• How much will this cost?
• Who else is going?
• Can we pay online?
• Happy that Wesley College allowed us to nominate the preferred
communications channel
• Wish we are able to see other parents’ responses
• I need to have an up-to-date view of the responses to
help me finalise arrangements
• What do I do if there is not enough responses?
• Stressed that this is taking longer than expected
• Worried about getting things wrong
RIGHT INVESTMENT RIGHT INFORMATION RIGHT INTEGRATION RIGHT OUTCOMES
Submit internal
trip request form
Mr. Smith
(History
Teacher)
Receive trip
approval
Organise volunteers,
buses, etc.
Mr & Mrs
Lincoln
(Parents)
View trip
itinerary
Receive trip
details
Submit permission slips
Make payment
Mr. Smith
(History
Teacher)
Monitor
responses
Answer
questions
Confirm
arrangements
Notify parents
Receive
confirmation
For queries / difficulties encountered
Consolidate responses Schedule resources Gather feedback Share experience
Mr. Smith
(History
Teacher)
Mr & Mrs
Lincoln
(Parents)
Sarah
(Student)
Share photos
• I need to know if the students enjoyed themselves
• Next time, I will need to plan more carefully
• Excited to share photos with students and parents
Organise payment
Discuss
experience
Get
trip
ratings
Allow knowledge
re-use and
discovery
Encourage sharing
& participations
through online
communities
Build-in intelligence
to merge & report
information from
disparate sources
Trip
Trip
occurs
Participate
For unexpected
changes
Continuous, non linear Non linear, but time basedLinear Processes
Business Performance Improvement (BPI)
Information & Data Management (IDM)
Systems Integration (SI)
Program & Project Services (PPS)Project Management
System Architecture Social Media Integration
Business Intelligence
Customer Experience Improvement
Workflow Automation
TransformationBusiness Case

19. Experiences have a life cycle
19

20. Experiences have a life cycle
20
Want Consider Evaluate Buy Experience Advocate Bond

21. Social media monitoring

22. IMAGE – TWITTER, FACEBOOKSentiment analysis

23. 23
BI Reports

24. top process owners
entity identification
customer journey mapping
Customer decision journey
Social media monitoring
Chief Customer Officer
Customer satisfaction
:
Customer’s Point of View

25. 2.0 analytics activities
Measuring
Tick
Generating
showing
performance and
stats by
business unit/product
etc…
Tick

26. oh dear…
a little knowledge is a
dangerous thing
good idea,
bad execution
all the kit, but
still pretty s#&t

27. some

28. some

29. some

30. some

31. some

32. WhyQ
A
Answers not
correlated with
revenue

33. customer
delighting
exceeding expectations
Excellence

34. Recall

35. Question: Strong correlation to
growth?
4%
Source: Satmetrix: The Power behind a single number,

36. chasing

37. funding

38. he isn’t.
he is asking questions
answers are and in fixed structures
What
Questions
How you
explore
data
to get from your

39. something

40. 3.0
in –
but better
outside

41. era 3.0 – business outcomes

42. Better
Question

43. to get from your
you are using
What
Questions

44. A CX LEADER’S CHALLENGE
and
to
try and make a difference?
If I do, will it be

45. of CX measure
Quantitative
Qualitative
Outcome
(what happened to the customer?)
(how did they feel about it?
(What will they do as a result?)

47. The high priest of Loyalty research

48. Net Promoter Score
Probably the most measure of customer intention
Open Source Simple
Surprisingly Robust
and versatile

49. Legitimising investment in
customer experience

50. Question: Strong correlation to
growth?
80% 4%
Source: Satmetrix: The Power behind a single number,

51. what’s it
what’s the of loyalty?
from a to a ?
by 10 points?

52. Value estimate the of the
average customer in each segment
1.
Look at the
between , and
2.
Hypotheses – find in your
experience design that affect NPS
3.
Work on those
4.

53. NPS Gives TEETH to customer
metrics
1.0 1.0 1.0

54. NPS Gives TEETH to customer
metrics
1.0 1.0 1.0
wallet share

55. NPS Gives TEETH to customer
metrics
1.0 1.0 1.0
retention
wallet share

56. NPS Gives TEETH to customer
metrics
1.0 1.0 1.0
referrals
retention
wallet share

57. NPS Gives TEETH to customer
metrics
bad-mouthing
cost to serve
wallet share
1.0 1.0 1.0
referrals
retention
wallet share

58. Your industry’s & YOURS
7.6x
referrals
cost to serve
wallet share
bad-mouthing
cost to serve
wallet share
1.0 1.0 1.0

59. 1.0
1.9
0.65
NPS Gives TEETH to customer metrics

60. Some examples

61. Cautionary tales
“NPS is , but it’s .
There are lots of things you
have to do to and
make it .

62. cautionary tale - sampling
Promoters
45%
Neutrals 22%
Detractors
33%

63. cautionary tale - sampling
Promoters
45%
Neutrals 22%
Detractors
33%
Promoters
20%
Neutrals 29%
Detractors
51%

64. 64
“ ”Our NPS is 20
A guy from (a well-known Australian Brand), two months ago
cautionary tale – oversimplifying

65. What’s good?

66. Segment – with a two tier system
Tier one
Overall
Tier two
Discrete
details

67. Associate

68. Actionable insight
0.56499
lorem
0.56499
lorem
0.56499
ipsum
0.56499
ipsum
Related to a
Related to
Related to
Related to a
Related to a

69. Use NPS to prototype service
it creates a
for leaders

70. to get from your
you are using
What
Questions

71. to get from your
you are using
What
Questions
you can ask questions
and answers are returned
How you
explore
data

72. data
disco-
very

73. 73
Analytic
Extensive data modeling
to
respond
Works within
Issues with traditional BI

74. reporting isn’t good enough
“ is
so last year.”

75. exploring beats reporting
“link
.”

76. 76
BI Reports

77. BI ReportsBusiness discovery

78. Business DISCOVERY over Business
Intelligence
NPS Data
CRM Data
Segmentation
Data
Services Owned
Data
Billing info
Churn
IVR Data - #calls,
route, scripts
Financial Data
Usage data
Service outages
Provisioning info
ASSOCIATED IN INSIGHT
ENGINE
YOUR DATA EXPLORE & DISCOVER
THAT POSES A
QUESTION
LEADS TO A
THOUGHT
IDEA
LEADING TO
INSIGHT

79. 79
Let me show you
Source: our technology partner: Qlikview

80. Why is NPS low?

81. ask a question of your
dear data:
What
Questions
dear data:

82. predictive
analytics

83. to see
patterns
enough
data

84. Take Business DISCOVERY…
NPS Data
CRM Data
Segmentation
Data
Services Owned
Data
Billing info
Churn
IVR Data - #calls,
route, scripts
Financial Data
Usage data
Service outages
Provisioning info
ASSOCIATED IN INSIGHT
ENGINE
YOUR DATA EXPLORE & DISCOVER
THAT POSES A
QUESTION
LEADS TO A
THOUGHT
IDEA
LEADING TO
INSIGHT

85. ...and add in a layer of analytics
NPS Data
CRM Data
Segmentation
Data
Services Owned
Data
Billing info
Churn
IVR Data - #calls,
route, scripts
Financial Data
Usage data
Service outages
Provisioning info
ASSOCIATED IN INSIGHT
ENGINE
YOUR DATA EXPLORE & DISCOVER
THAT POSES A
QUESTION
LEADS TO A
THOUGHT
IDEA
LEADING TO
INSIGHT

86. it’s about likelihood
Based on
risk of
risk of
likely to
likely to
likely to
likely to
likelihood of
what do you want to find out?
likely to

87. Source: Getty Images
it’s about

88. better decisions
NBO
NBA

89. NBA and NBO
better customer decisions, in real time
Source: our technology partner: ibm spss

90. what’s it
better
8.4x
Simon Taranto - Amex
marketing campaign
increase
100% ibm
to target profitable
customers
33% ibm
on predictive analytics
250% independent

91. he isn’t.
he is asking questions
answers are and in fixed structures
she is asking questions
she can get answers about
she can ask questions about what’s
What
Questions
How you
explore
data
to get from your

92. it’s about likelihood
Based on
is quite a lot

93. segmentation

94. no more sampling

95. Insure the box

96. A CMO will have
available to filter for
insights than will be
produced by the
array

97. era 4.0 – rocket surgery

98. era 4.0 – pre hypothesis analysis
what if you
where to look?
with data..

99. what if you
don’t have to?

100. 4.0
topological
analysis
abduction and

101. topological
data analysis
Explore
without an hypothesis

102. It finds similar nodes
It folds the data set together
Shapes reveal the relationships
You explore for meaning and action
image: ayasdi.com

103. create
using shape and colour
image: ayasdi.com

104. Basketball
Image: HD Wallpapers

105. image: ayasdi.com

106. image: ayasdi.com

107. image: ayasdi.com

108. image: ayasdi.com

109. just think
what could you do with
analytics
everything we listed in
segmentation
unexpected discoveries in
refinement
customer-specific or staff specific
marketing
uber

110. he isn’t.
he is asking questions
answers are and in fixed structures
she is asking questions
she can get answers about
she can ask questions about what’s
he
What
Questions
How you
explore
data
to get from your

111. 1.0 insights
2.0 insights
3.0 insights
insights
4.0insights you
What
Questions
How you
explore
data

112. A CX LEADER’S CHALLENGE
and
to
try and make a difference?
If I do, will it be

113. 113
thank you
greg Stewart
SMS management & Technology
www.smsmt.com
greg.stewart@smsmt.com
@clarityrules
#CX13