Superior customer experiences are the real coin: relevance drives results - Rene Van Der Laan
- 2. Copyright
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2016,
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How
to
get
there?
Agenda
What’s
Required?
Real-‐life
Examples
Context:
the
key
to
value
Customer
Experience
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Interac,ons
based
on
context
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2016,
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rights
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Interac,ons
based
on
context
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©
2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Interac,ons
based
on
context
- 6. Copyright
©
2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Interac,ons
based
on
context
- 7. Copyright
©
2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Interac,ons
based
on
context
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2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Interac,ons
based
on
context
- 9. Copyright
©
2016,
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Ins6tute
Inc.
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rights
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Interac,ons
based
on
context
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2016,
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Interac,ons
based
on
context
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Interac,ons
based
on
context
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2016,
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Interac,ons
based
on
context
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2016,
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Interac,ons
based
on
context
- 14. Copyright
©
2016,
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Ins6tute
Inc.
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rights
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Interac,ons
based
on
context
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2016,
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Ins6tute
Inc.
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rights
reserved.
Interac,ons
based
on
context
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2016,
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rights
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Interac,ons
based
on
context
- 17. Copyright
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2016,
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rights
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Marke,ng
Today
–
room
for
improvement
KPMG:
2014,
2015
- 18. Copyright
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2016,
SAS
Ins6tute
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rights
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What
are
we
talking
about?
It
sounds
simple…
the
right
thing
for
the
right
customer
at
the
right
6me
in
the
right
place
Doing
exactly
- 20. Copyright
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2016,
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rights
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So,
how
should
you
respond?
Relevance
Convenience
Acceptance
+
=
- 21. Copyright
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2016,
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rights
reserved.
What
makes
up
context?
Customer
Rela,onship
Context
Real-‐Time
Context
-‐
Situa,on
Personal
Context
Relevance
- 22. Copyright
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rights
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Contextual
Marke,ng
-‐
defini,on
Context
Event
Insights
360º
Customer
View
Analy6cs
Situa6on,
Channel
Data,
Behavior
Customer
All
relevant
informa6on
for
the
op6mal
decision
- 23. Copyright
©
2016,
SAS
Ins6tute
Inc.
All
rights
reserved.
Contextual
Marke,ng
-‐
defini,on
Context
Event
Insights
360º
Customer
View
Analy6cs
Situa6on,
Channel
Data,
Behavior
Customer
All
relevant
informa6on
for
the
op6mal
decision
Twice a
year weekly
Travel
InsuranceOliver Rene Nothing
?
- 24. Copyright
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rights
reserved.
*
21M
Ac6ve
Customers,
50K
TPS
Take
Ac6on
Understand
S1
S2
Listen
So
why
do
it?
A
real
world
example*
Real-‐6me
behavioral
triggers
Limited
contextual
data
Rules-‐driven
next
best
offer
Real-‐6me
delivery
Poorly-‐defined
offer
Delayed
behavioral
triggers
Broad
contextual
data
Analy6cs-‐driven
next
best
offer
Delayed
delivery
Sophis6cated
offer
Real-‐6me
behavioral
triggers
Broad
contextual
data
Personalized
offer
driven
by
real-‐6me
analy6cs
Real-‐6me
delivery
Sophis6cated
offer
5%
û
ü
Relevance
Confidence
Max.
Take
Rate
5%
û
ü
Relevance
Confidence
Max.
Take
Rate
24%
ü
ü
Relevance
Confidence
Max.
Take
Rate
Incremental
Revenue
Increase
€10M
Payback
MONTHS
Take
Rate
5x
Business
As
Usual
24%
- 25. Copyright
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2016,
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rights
reserved.
What
Macy’s
needs
to
understand
RFM
segmenta,on
Response
history
Propensity
models
CLTV
modeling
Brand
advocacy
segmenta,on
• Who are my customers?
• How are my customers different from one another?
• What similarities do my customers share?
• What/when/where do my customers buy?
• How do customers engage with me?
• How do customers feel about my brand/product?
• In the coming seasons, what should I recommend them?
• How do they respond to our special offers
"With the extra time, the team has moved from being
reactionary to proactive, …spend more time analyzing it and
become internal consultants who provide more of the insight
behind the data.”
Kerem Tomak
Vice
President
of
Analy2cs
- 26. Copyright
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How
Macy’s
plans
to
take
ac,on
Melanie
receives
op6mized
email
‘Friday
in-‐store
shopping
promo’.
1
1
Melanie
enters
the
store
on
Friday
2
Melanie
con6nues
to
shop
–
con6nues
to
receive
tailored
offers
based
on
beacon
loca6on.
7
Macy’s
detects
store
entry
(based
on
beacon
&
cell
phone)
3
4
Customer
Hub
Full
360
View
of
Melanie
Accessed
in
Real6me
6
SMS
or
App
push
offer
is
made
–
right
product,
great
discount
5
Contextual
Engagement
technologies
combine
to
determine
the
best
offer
to
promote
Op6miza6on
Real-‐Time
Right
offers,
delivered
how
Melanie
wants
them
-‐
not
too
many.
All
contextually
based,
priced
and
personalised
to
Melanie
- 27. Copyright
©
2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Pung
it
all
together
CUSTOMER
DECISION
HUB
Marke6ng
Campaigns
Service
Analy6cs
Sales
Programs
Ad-‐hoc
Ac6ons
Regular
Communica6ons
Contact
strategies
Priori6es
Strategic
Decisions
Contact
Rules
Contracts
Channel
restric6ons
Budget
Limits
Contact
Permissions
Transac6onal
data
Analy6cal
models
Events
Context
Scores
Risk
Poten6als
History
- 28. Copyright
©
2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Rules
Decision
Logic
Real-‐Time
Analy,cs
Request
Reply
Next-‐Best
Ac,on
Customer
Decision
Hub
Specific
Refinement
Campaign
Orchestra,on
Pung
it
all
together
- 29. Copyright
©
2016,
SAS
Ins6tute
Inc.
All
rights
reserved.
Start
with
the
easiest
scenarios
Check
and
integrate
available
data
Integrate
analy,cs
and
channels
incrementally
Deliver
incremental
value
and
build
the
expansion
case
Modular,
Roadmap-‐driven
Evolu,on
- 30. Copyright
©
2016,
SAS
Ins6tute
Inc.
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rights
reserved.
Start
with
the
easiest
scenarios