SlideShare a Scribd company logo
CUSTOMER JOURNEY ANALYTICS
From a focus on products to a focus on relationships-
How adopting customer journey analytics and using
the correct data/insights have helped improve
customer experience
DATABEERS DUBLIN – 19TH JANUARY 2017
KRITHIKA RAMANARAYANAN
DATA & INSIGHTS MANAGER, DAVY
@krithikaram
SPOT THE PATTERN…..
NEXT GEN CLIENT - iGENERATION
http://www.customerexperienceexchangefs.com/what-is-customer-experience-ftp-iframe
https://www.youtube.com/watch?v=JRFrpr4W7cc
And how do you manage it?.....
 Companies need to move from a ‘pull’ approach, of providing information after the
customer requests it, to a ‘push’ approach, of proactively sending them the right
content at the right time.
 The push approach requires deep contextual understanding of the customer and
powerful predictive algorithms so that a meaningful, personalised customer
experience can be produced.
CUSTOMER JOURNEYS
“Everyone’s talking about
customer experience and
design, but to produce
better ROI it’s time to turn
to the data. Design is as
much science as it is art, and
to see more focus on results-
driven design using data,
insights and analytics is
crucial”
FINANCIAL SERVICES & CX
DATA GENTRIFICATION
Dynamic industry
ecosystem - Fine-tunes
capabilities and
performance of people,
processes and
technologies, with data
at its core
TRANSFORMING CUSTOMER JOURNEYS
It took a year-long cross-functional effort to embed this new approach, but it paid off. Customer
satisfaction scores increased from below average to the top quartile, and the new strategy covered
its costs in less than three months
EXAMPLE RETAIL BANK - FRAUD MANAGEMENT AS CUSTOMER
SERVICE ENABLER !?
Mapped
entire
lifecycleof
aretail
banking
customer
Measured
contact
frequency
Analysed
Satisfaction&
Dissatisfaction
Fraud&
Transaction
verification
Re-design
fraud
control
process
Newdata-
streams
established:Cell-
phonelocation
datacollectedto
triggeralertsto
thefraud
investigator
NewAnalytical
models:
Segmented
customer
sensitivityto
fraud
Redefined
contact
frequency
norms
Org.
readiness
(staffing,
training
etc..)

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Databeers Dub #1 - Krithika Ram - Customer Journey Analytics

  • 1. CUSTOMER JOURNEY ANALYTICS From a focus on products to a focus on relationships- How adopting customer journey analytics and using the correct data/insights have helped improve customer experience DATABEERS DUBLIN – 19TH JANUARY 2017 KRITHIKA RAMANARAYANAN DATA & INSIGHTS MANAGER, DAVY @krithikaram
  • 3. NEXT GEN CLIENT - iGENERATION
  • 4. http://www.customerexperienceexchangefs.com/what-is-customer-experience-ftp-iframe https://www.youtube.com/watch?v=JRFrpr4W7cc And how do you manage it?.....  Companies need to move from a ‘pull’ approach, of providing information after the customer requests it, to a ‘push’ approach, of proactively sending them the right content at the right time.  The push approach requires deep contextual understanding of the customer and powerful predictive algorithms so that a meaningful, personalised customer experience can be produced. CUSTOMER JOURNEYS
  • 5. “Everyone’s talking about customer experience and design, but to produce better ROI it’s time to turn to the data. Design is as much science as it is art, and to see more focus on results- driven design using data, insights and analytics is crucial” FINANCIAL SERVICES & CX
  • 7. Dynamic industry ecosystem - Fine-tunes capabilities and performance of people, processes and technologies, with data at its core TRANSFORMING CUSTOMER JOURNEYS
  • 8. It took a year-long cross-functional effort to embed this new approach, but it paid off. Customer satisfaction scores increased from below average to the top quartile, and the new strategy covered its costs in less than three months EXAMPLE RETAIL BANK - FRAUD MANAGEMENT AS CUSTOMER SERVICE ENABLER !? Mapped entire lifecycleof aretail banking customer Measured contact frequency Analysed Satisfaction& Dissatisfaction Fraud& Transaction verification Re-design fraud control process Newdata- streams established:Cell- phonelocation datacollectedto triggeralertsto thefraud investigator NewAnalytical models: Segmented customer sensitivityto fraud Redefined contact frequency norms Org. readiness (staffing, training etc..)