wed-04_mwa11_customer_experience_analytics_v0.6 (1).pdf

7/27/2019 Wed-04_MWA11_Customer_Experience_Analytics_v0.6 (1).pdf

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© 2011 TeleManagement Forum | 1 www.tmforum.orgv2011.1

v2011.1

Customer Experience Analytics

MWD12




KPI Alphabet Soup

KAI – Key Attitude indicators

KBI – Key Business indicators

KCI – Key Customer indicators

KDI – Key Driver index

KEI – Key Experience indicators

KFI – Key Financial indicators

KGI – Key Goal indicators

KHI – Key Health indicators

KII – Key Improvement indicator

KJI - Key Jurisdiction indices

KLI - Key Lifestyle indicatorsKMI – Knowledge Management index

KNI - Key Navigation indicator

KOI – a Fish or Key Operations Indicator

KPI - Key Performance Indicator

KQI – Key Quality indicator

KRI – Key Revenue Indicator

KSI – Key Success Indicator

KTI - Key Trending indicator

KUI – Key User indicator

KVI – Key Volume indicator

KWI – Key Wealth Indicator

KXI – any key metric for measuring status

KZI – Key Zoning indicator




Analytics-What If

A system could identify that a high ARPUcustomer had just terminated their service

for no apparent reason…and

The system could identify the next twenty

customers with twin Customer

Profiles…and A system that could look outside the firewall

to capture what your customers are really

saying about your products and services

Do you think your Marketing Departmentmay be interested in this data?




Business Problem

CSP Annual reports all list customer experience (NPS®/CDI Indices) as

central to business success

The factors influencing the customer’s

experience are many & diverse, ranging

from point of sale service to tariff plans

to data throughput

With the explosion in mobile data usage

the factors influencing Customer’s

Experience are growing

CSP’s that measure & manage the

Customer’s experience continuously will

be the most successful

NPS a registered name by Satmetrix




Solution

Managing the customer’s experience requires Accurate measures of customer

experience for each interaction with the

CSP

Collation of these measures into a

Customer Experience Management Index(CEMI)

An ability to drill-down from the CEMI to

the factors influencing the experience

Volumes & complexity of data generated in

networks made analyzing customer

experience a challenge but advances in data

integration, storage & analytics now make it

possible




Solution

This catalyst program proposes a Customer Experience

(CEM) model & Customer Experience Index (CEI) tosurface & collate the Customer’s Experience

It proposes a logical multi-tiered

decomposition of the CEI into it’s

multiple components which alignswith Frameworx

This enables the surfacing of

customer issues into an operational

executive dashboard, with drill-down supported to identify the root

cause of problems




Service Operations Center

Service & Network

Surveillance

(Real time

measurements)

Trend Analysis

&

Service Quality Management

Reporting

Business Strategic Areas :

Service & Network

Surveillance

(Real time

measurements)

Service & Network

Surveillance

(Real time

measurements)

Service & Network

Surveillance

&Troubleshooting

•Real Time Measurements

•KPI surfacing •Post Processing

•KPI KQI

Phase 1 Phase 2




•Deep visibility for real time IT systems performing services related to the provided network quality

•Define and activate Improvement actions for the most critical systems

•Monitoring customer experience for provided services

•Tuning che customer profile for each service

Expected benefits

•Deep visibility for real time IT systems performing services related to the provided network quality

•Define and activate Improvement actions for the most critical systems

•Monitoring and improving Customer Experience for provided services

•Tuning the customer profile for each service

Benefits

•Executive level (e.g. Customer Experience Index)

•Operational level

•Department / engineering level (e.g. Software & systems Quality )

• Customer level

KPI & KQI

Service Operations Center Concept




Technology

Implementing this logical framework

requires that the following

challenges are addressed

Accurate measurement of QoE

Analysis of massive volumes of

complex data

Collation of data from sources of

disparate ownership

An architecture is proposed to

address these technical challenges

leveraging recent advances in OSS

& BSS technologies




Big Data

Big data and information integration capabilities make it possible to

generate insight from vast quantities of data—fundamentallychanging the way organizations use information. It means:

Filtering petabytes of data per second from almost any

connected device

Analyzing the data while still in motion, deciding what, if any,

data must be stored,

Using analytics tools to virtually integrate the data with data

stored in traditional warehouses.




Description of Demonstration

The demonstration focuses on thecontribution to the CEI of the Network

Quality and Social Media

It traces how a customer impacted by

a quality issue is surfaced in the CEMConsole and is subsequently

analyzed and resolved by traversing

the multi-tiered CEM Model for KXI

Surfacing Customer impacting issues arising

from the other components of the

CEM Model can be analysed in an

analogous manner




Benefits

CSP’s have identified customer experience as being

important because happy customers Use more services

Promote the CSP to friends

Churn less

By optimising the customer’s experience the CSP will grow

revenue, reduce churn & increase market share..and find

those next ten customers!

This project proposes a model &

reference architecture to measure

& optimise the Customer

Experience in an operational

manner




At a Glance




Flashboard




Customer Experience Management Index detail




CEMI Trend




Catalyst Team Members

Robert Segat IBM/Netezza [email protected]

Prof. Paul Morrissey Ventraq [email protected]

Dan O’Donnell

Stewart Howe

Network

Critical

[email protected]

Simona La Rosa Telecom Italia [email protected]

Jing Shang China Mobile [email protected]

Ted Stuchberry Genband [email protected]

Steve Koudelis Ventraq [email protected]

C t S ti t A l ti



© 2011 TeleManagement Forum | 19 www tmforum org

Customer Sentiment Analytics

List of the KPIs that are for the sentiment analysis

Ventraq & IBM apply analytics to the social media feed.

Currently we are conducting three measurements.

Brand Sentiment Index This is a combination of the twoscores below.

Brand Sentiment Score This measures the level of positive and

negative statements

Brand Intensity Score This measures how strong a position thecustomer is taking in their positive or negative a statements

Supported languages from the social media analytic e.g.

Twitter, Facebook

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