Sharad Mathur from SBI General Insurance spoke at the Digital Insurance in Africa Summit in 2015 on the single view of the customer

1. Single
Customer
View
6th
August
2015
Sharad
Mathur
Senior
Vice
President
&
Na?onal
Head
–
Agency,
Digital
&
Alternate
Channel
SBI
General
Insurance
Company
Limited,
India

2. Overview
2
Innova?ve
Techniques
to
Track,
Monitor
&
Analyse
Customer
Behaviour
Across
Mul?-­‐Channel
Touch
points
for
a
Coherent,
Single
Customer
View
• Analyzing
the
en,re
customer
journey
across
all
digital
pla7orms
for
a
joined-­‐up,
single
view
of
the
customer
• Knowing
customer’s
expecta,ons
and
how
they
are
changing
towards
devices
and
channels
offline
and
online
–
to
feed
analysis
back
and
improve
the
customer
journey
• Enhancing
sales
throughout
the
purchase
cycle
by
gaining
a
comprehensive
overview
of
customer
interac,on
and
conversions
• Harnessing
the
power
of
big
data
and
CRM
systems
to
generate
leads
and
link
data
for
an
integrated,
cross-­‐channel
view
of
the
customer

3. General
Insurance
Landscape
• Insurance
is
largely
a
push
product
than
a
pull
• General
Insurance
policy
period
is
small,
an
annual
contract
• Churning
of
Insurers
during
renewal
is
prevalent
• Low
loyalty
and
high
transac,onal
price
driven
rela,onship
exists
between
Insurer
and
Insured
• Products
like
Health
insurance
are
sought
when
a
health
related
incident
occurs
in
family
or
with
friends
• Customers
seek
help
from
advisors
as
most
do
not
understand
the
wordings
or
the
coverage
or
benefits
offered
• Brand
selec,on
and
buying
decisions
are
highly
influenced
by
experiences
shared
in
social
circles
3

4. Consumer
changing
behavior
and
expecta,ons
• Dwindling
boundaries
between
Online
and
Offline
space
• Customers
exhibi,ng
mul,-­‐channel
behavior
– 60-­‐70%
of
online
users
conduct
digital
research
before
purchasing
a
financial
product
– 66%
customers
change
the
product
or
Brand
aTer
researching
online
• Consumer
awareness
and
involvement
has
increased
due
to
high
penetra,on
of
internet
and
mobile.
Self
ini,ated
Renewals
have
significantly
improved
in
last
5
years
• Customers
have
varied
needs
and
expecta,ons
which
demand
a
higher
customer
centric
and
solu,on
oriented
approach
4

5. Customer
interac,ons
across
different
channels
5
Mul?ple
channels
of
Customer
Interac?ons
Call
Centre
Social
Media
Internet
Web
Chat
ATM
/
Kiosk
Branch
SMS
Email
Le[er
Apps

6. Mul,-­‐channels
commonly
used
by
Customers
• Receives
an
email
about
a
product
offering
• Visits
the
website
for
details
and
generates
a
quote
• Calls
the
Call
Centre
to
get
some
clarifica?on
• Visits
the
branch
and
takes
a
policy
6

7. Mul,-­‐Channel
customer
expecta,ons
• 50%
of
customers
today
are
mul,-­‐
channel
shoppers
which
is
a
mix
of
Social,
Mobile
or
Tradi,onal
modes
• Customers
demand
flexible,
real-­‐,me
personalized
experience
• Customers
expect
consistent
and
immediately
iden,fiable
appearance
across
all
sales
channels
• Customer
interac,ons
are
sca[ered
but
experience
expected
is
unified
7

8. Need
for
Single
Customer
View
• Single
Customer
View
is
needed
to:
– Create
a
360
degree
view
of
the
customer
interac,ons
and
preferences
– Combine
customer
informa,on
– Have
a
be[er
knowledge
and
understanding
of
customer
needs
and
preferences
– Conduct
effec,ve
and
efficient
Marke,ng
ac,vi,es
– Offer
higher
level
of
service
through
be[er
customer
understanding
– Achieve
higher
return
on
investment
– Achieve
higher
customer
sa,sfac,on
– Build
durable
customer
rela,onships
8
Single
Customer
View
is
an
aggregated,
consistent
and
holis,c
representa,on
of
the
customer
data

9.
SCV
builds
a
base
to
drive
ini,a,ves
&
innova,on
• Build
dis?nc?ve
granular
customer
insights
to
capture
high
poten?al
growth
opportuni?es
and
enhance
engagement
across
the
customer
lifecycle
ƒ
• Upgrade
to
next
genera,on
technical
capabili,es
(claims,
underwri?ng,
analy?cs,
and
actuarial
capabili?es)
ƒ
• Build
world
class
opera,ng
models
to
achieve
gains
in
efficiency
while
strengthening
the
human
capital
9

10. Cross
Channel
Customer
Centric
approach
• Unified
communica,on
approach
in
CRM
– All
Customer
interac,ons
with
the
company
can
be
tagged
together
based
on
the
unique
customer
iden,fier
– This
can
include
all
modes
(email,
sms,
call,
le[er)
and
channels
(website,
branch,
agent)
of
customer
interac?ons
– This
can
even
include
communica,on
done
by
the
Company
– It
can
also
consolidate
the
mul,ple
accounts
and
various
rela,onships
the
user
has
with
the
insurer
– This
can
also
include
data
from
other
backend
systems
– CRM
can
store
all
the
interac,on
data
for
appropriate
ac,on
• Rules
can
be
triggered
to
handle
the
customer
appropriately
10

11. Predic,ve
data
analy?cs
• Historic
and
Current
data
coupled
with
Predic,ve
Data
analy,cs
can
help
Intelligent
cross-­‐sell
and
up-­‐sell
• Dynamically
predict,
based
on
feedback
to
con?nuously
improve
results
11
Historic
data
+
Current
data
Predic,ve
Data
Analy,cs
Intelligent
cross-­‐sell
&
up-­‐sell

12. Customer
journey
based
on
interac,on
insights
• Example
1:
– Customer
visited
the
insurer’s
website
– Computes
premium
for
a
Motor
Insurance
– Does
not
proceed
with
Policy
• This
Customer
interac,on
is
captured
in
Website
and
stored
in
CRM
• In
CRM,
an
ac,vity
is
created
as
a
‘Poten,al
Customer’
• Email
related
to
Motor
Insurance
product
is
triggered
to
customer
• An
outcall
is
done
from
the
Call
Centre
to
assist
him
further
to
purchase
a
motor
insurance
policy
12

13. Customer
journey
based
on
interac?on
insights
Contd..
• Example
2:
– Customer
calls
Call
Centre
and
complains
about
non
receipt
of
insurance
policy
document
– With
the
available
dispatch
details,
the
Execu,ve
informs
the
courier
details
and
the
exact
reason
for
non
delivery
of
the
document
– Emails
the
policy
document
to
customers
available
email
id
• Due
to
the
seamless
integra,on
of
the
system,
the
updated
informa,on
of
the
policy
dispatch
is
available.
This
enables
the
Execu,ve
to
handle
the
customer
aptly
13

14. Big
Data
• Big
data
refers
to
a
very
large
and
complex
data
sets
that
are
sourced
but
can
not
be
processed
using
tradi,onal
applica,ons
• It
helps
businesses
build
long-­‐term
rela,onships,
realize
value
and
incorporate
all
sources
of
data,
thereby
changing
the
way
they
interact
with
customers
14

15. Customer
Disposi?on
15
•
Customer
Disposi?on
defines
the
essence
of
who
a
customer
is
The
relevance
of
Insurer’s
interac,ons
with
the
customer
is
directly
related
to
its
understanding
of
customer
disposi?on
and
needs

16. Big
Data
&
CRM
• To
create
value
for
customers,
internal
data
mining
and
predic,ve
data
analy,cs
form
the
base
• Understanding
internal
customers
using
CRM
is
essen,al
and
fundamental
to
ge_ng
customer
insights
• Integra,ng
the
two
insights
–
internal
customer
data
and
external
Big
data
create
be[er
understanding
of
customers
and
enables
the
business
to
provide
superior
personalized
experience
16

17. Leverage
CRM
&
Big
Data
17
• Assess
life,me
value
of
a
customer
– Through
internal
data
mining
of
exis?ng
customers,
iden,fy
the
a[ributes
of
the
current
profitable
and
high-­‐value
customers
eg:
Motor
Insurance
customer
having
a
specific
segment
of
vehicle,
in
a
par?cular
loca,on
and
of
a
par?cular
age
group
– Target
similar
users
to
acquire
new
business
– Customized
offers
could
be
made
throughout
the
customer
lifecycle.
Like
an
offer
for
his
2nd
vehicle
or
a
personal
accident
insurance
– Mode
of
communica,on
could
be
chosen
depending
the
frequency
eg:
user
connects
over
the
website
or
over
web
chat
indicates,
he
would
be
recep,ve
to
a
mobile
responsive
e-­‐mailer
– Helps
reduce
resource
drain
on
low
value
customers
– Keep
a
check
of
the
low
value
customers
to
control
nega,ve
profitability
and
improve
reten,on
rates

18. Leverage
CRM
&
Big
Data
Contd…
18
• Improve
accuracy
and
response
to
marke,ng
campaigns
• Reduce
cost
of
Acquiring
new
customers
Example:
– Users
who
have
expressed
preference
for
health
ar,cles
or
have
subscribed
for
health
magazines
– Health
campaign
to
acquire
new
business
would
work
be[er
for
this
targeted
set
of
users
– A/B
Tes,ng
of
targeted
campaigns
would
determine
which
campaign
worked
best
for
customer
acquisi,on

19. Leverage
CRM
&
Big
Data
Contd…
19
• Iden,fy
behavioural
anomalies
across
channels
indica?ng
risk
of
losing
customer
Example:
– Receiving
mul,ple
calls,
emails
or
web
chats
about
service
issues
– Nega,ve
response
on
a
survey
or
feedback
– Access
Website
FAQ
pages
to
understand
policy
cancella?on
process
This
is
a
high
alert
to
retain
the
customer
by
offering
personalized
be[er
and
tailor
made
offer