Using analytics and automation to create personalised customer journeys

Nilanjan Sarkar

General Manager – Brand & Communications

Vodafone Hutchison Australia

Agenda

• Identify nature and needs of customers, and act on them

• Use data to improve customer satisfaction, and drive growth

• How SAS helps to do this at scale

2

A new operating model

3

6 week Reaction Sub-Second Reaction

Sending Listening, Responding

Single Channel Multiple Channels

Moment in Time Spans Time

Direct to CustomerInfluence the Influencer

Vodafone in 2012 Vodafone Today

• We have learnt to

Listen and Respond

– Customised marketing

and service interaction

– Faster, more

contextual, and at

scale

4

• Customer Satisfaction

has improved

– 30 point NPS

improvement in 18

months

– Customer retention

among the best in the

industry – halved churn

in 18 months

– Complaint rates halved

in 12 months

Contract customers go through a variety of experiences over time

We listen for experiences over time. We have the ability to respond appropriately

The lifecycle framework allows balancing customer and commercial objectives

Welcome

Consolidate

At Risk

Loyalty

This is done with a combination of three capabilities

7

Identifying

Stage

Knowing

what to look for

Acting

on the Insight

Welcome

Consolidate

At Risk

Loyalty

• Scoring life

stage

• Static and

Dynamic

Decision

variables

• Events

• Triggers

• Usage patterns

• Feed into

service systems

• Regular usage

patterns

• Abnormal

changes in

pattern

• Predicted impact

on experience

• Events

impacting

experience

• Triggers known

to impact

experience

• Proactive

intervention

• Reactive actions

• Making it easy

for customers

• Staff training and

monitoring

• Making it easy

for Customer

Service

Stage

Alerts in Action

• Customise alerts based

on behaviour

• Contextual presentation

of data packs

• On the phone

• At call centre

• Easy to get

• Suited to your needs

8

Not all relationships have a predictable life span. So we need other surrogates. Usage is one.

9

DAYS INACTIVE

RE

TE

NT

ION

RA

TE

Prediction of usage helps us serve customers better

We can use a variety of data points to identify these natures and needs

10

Time of day

Length of call

Destination

Data Vol/ Speed

Day Caller

Weekend

Work

Content

Identifying Nature

Knowing what to look for

Acting on theInsight

Predicting nature and needs gives us over 10% improvement in outcomes

11

90 DAYS

RE

TE

NT

ION

RA

TE

Control Contact

10%

• Tracking events, usage, and underlying patterns helps serve

customers better

• Continuous, at scale, and with granularity

• Not selling, but listening and responding, for better outcomes

Key Learnings

Insert Confidentiality Level in slide footer 12

SAS ® helps us

• Build complex frameworks to scale. Understand our customer needs better

• Organise data for decision making, across many scenarios

• Use the data in real-time across a variety of channels, to improve customer

experience

• Improved customer satisfaction and experience

Thank you