quantifying customer experience - presented at customer experience design 2013
DESCRIPTION
Big data customer experience net promoter score nps analytics service design conference presentation greg stewart SMS four eras of analyticsTRANSCRIPT
1
Quantifying
greg Stewart SMS Management & Technology www.smsmt.com @clarityrules #CX13 6 may 2013
of customer
analytics
questions
A CX LEADER’S CHALLENGE
and
to
try and make a difference?
If I do, will it be
CFO
They count . They want .
customer analytics practices
1.0 2.0 3.0 4.0
four eras
Thurston Howell
Crystal Ball
Trip Fall
1.0 2.0 3.0
4.0
1.0 2.0 3.0 4.0
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
1.0
out inside
1.0
era 1.0 – inside out
1.0
main symptom of 1.0:
A is just the
of each business unit.
he isn’t.
to get from your
What Questions
How you explore data
2.0
in outside
era 2.0 – outside in
:
Customer’s Point of View
entity identification
top process owners
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 permission View 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 based Linear 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
Transformation Business Case
Experiences have a life cycle
19
Experiences have a life cycle
20
Want Consider Evaluate Buy Experience Advocate Bond
Social media monitoring
IMAGE – TWITTER, FACEBOOK Sentiment analysis
23
BI Reports
top process owners entity identification customer journey mapping Customer decision journey Social media monitoring Chief Customer Officer Customer satisfaction
:
Customer’s Point of View
2.0 analytics activities Measuring
Tick
Generating showing
performance and stats by
business unit/product etc…
Tick
oh dear…
a little knowledge is a dangerous thing
good idea, bad execution
all the kit, but still pretty s#&t
some
some
Why Q
A Answers not correlated with revenue
customer
delighting
exceeding expectations
Excellence
Recall
Question: Strong correlation to growth?
4%
Source: Satmetrix: The Power behind a single number,
chasing
funding
he isn’t.
he is asking questions
answers are and in fixed structures
What Questions
How you explore data
to get from your
something
3.0
in – but better
outside
no insights false insights explored insights predicted insights insights you didn’t know to ask for
era 3.0 – business outcomes
no insights false insights explored insights predicted insights insights you didn’t know to ask for
Better Question
to get from your
you are using
What Questions
A CX LEADER’S CHALLENGE
and
to
try and make a difference?
If I do, will it be
of CX measure no insights false insights explored insights predicted insights insights you didn’t know to ask for To Get actionable insight: 1.0 You’re not even asking 2.0 you can ask questions of the wrong data but you’re asking bad questions and the answers are slow in coming 3.0 You can ask much better questions about what happened, and the answers are instant, and you can ask follow up questions 3.5 You can ask good questions about what might happen next? 4.0 you don’t have to ask questions -
Quantitative
Qualitative
Outcome
(what happened to the customer?)
(how did they feel about it?
(What will they do as a result?)
Net Promoter Score
Probably the most measure of customer intention
Open Source Simple Surprisingly Robust and versatile
Legitimising investment in customer experience
Question: Strong correlation to growth?
80% 4%
Source: Satmetrix: The Power behind a single number,
what’s it
what’s the of loyalty?
from a to a ?
by 10 points?
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.
NPS Gives TEETH to customer metrics
1.0 1.0 1.0
NPS Gives TEETH to customer metrics
1.0 1.0 1.0
wallet share
NPS Gives TEETH to customer metrics
1.0 1.0 1.0
retention
wallet share
NPS Gives TEETH to customer metrics
1.0 1.0 1.0
referrals
retention
wallet share
NPS Gives TEETH to customer metrics
bad-mouthing
cost to serve
wallet share
1.0 1.0 1.0
referrals
retention
wallet share
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
1.0
1.9
0.65
NPS Gives TEETH to customer metrics
Some examples
Cautionary tales no insights false insights explored insights predicted insights insights you didn’t know to ask for
“NPS is , but it’s .
There are lots of things you have to do to and make it .
cautionary tale - sampling
Promoters 45%
Neutrals 22%
Detractors 33%
cautionary tale - sampling
Promoters 45%
Neutrals 22%
Detractors 33%
Promoters 20%
Neutrals 29%
Detractors 51%
64
“ ” Our NPS is 20 A guy from (a well-known Australian Brand), two months ago
cautionary tale – oversimplifying
What’s good?
Segment – with a two tier system no insights false insights explored insights predicted insights insights you didn’t know to ask for
Tier one
Overall
Tier two
Discrete details
Associate
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
Use NPS to prototype service
it creates a
for leaders
to get from your
you are using
What Questions
to get from your
you are using
What Questions
you can ask questions
and answers are returned
How you explore data
data disco- very
73
Analytic
Extensive data modeling to
respond
Works within
Issues with traditional BI
reporting isn’t good enough no insights false insights explored insights predicted insights insights you didn’t know to ask for
“ is
so last year.”
exploring beats reporting no insights false insights explored insights predicted insights insights you didn’t know to ask for
“link .”
76
BI Reports
BI Reports Business discovery
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
Let me show you
Source: our technology partner: Qlikview
Why is NPS low?
ask a question of your
dear data:
What Questions
dear data:
predictive analytics
to see
patterns
enough
data
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
...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
it’s about likelihood no insights false insights explored insights predicted insights insights you didn’t know to ask for
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
Source: Getty Images
it’s about
better decisions
NBO
NBA
NBA and NBO better customer decisions, in real time
Source: our technology partner: ibm spss
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
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
it’s about likelihood Based on
is quite a lot
segmentation
no more sampling
Insure the box
A CMO will have
available to filter for insights than will be produced by the
array
era 4.0 – rocket surgery
era 4.0 – pre hypothesis analysis
what if you
where to look?
with data..
what if you don’t have to?
4.0 topological analysis
abduction and
topological data analysis
Explore
without an hypothesis
It finds similar nodes
It folds the data set together
Shapes reveal the relationships
You explore for meaning and action image: ayasdi.com
create
using shape and colour image: ayasdi.com
Basketball
Image: HD Wallpapers
image: ayasdi.com
image: ayasdi.com
image: ayasdi.com
image: ayasdi.com
just think what could you do with
analytics everything we listed in
segmentation unexpected discoveries in
refinement customer-specific or staff specific
marketing uber
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
1.0 insights
2.0 insights
3.0 insights insights
4.0 insights you
What Questions
How you explore data
A CX LEADER’S CHALLENGE
and
to
try and make a difference?
If I do, will it be
113
thank you
greg Stewart SMS management & Technology www.smsmt.com [email protected] @clarityrules #CX13