11

Customer Experience Monitoring

May 2010

• End to End Customer Experience

• Challenges and Case study

�Robert BeckChief Executive, CR-Xrobert.beck@cr-x.com

2

The Cost of Poor Customer Service:The Economic Impact of the Customer Experience and Engagement

• Survey of 16 countries shows poor customer service costs $338.5

billion per year in lost business

• Hardest hit industries across all countries:

− financial services

− cable and satellite TV providers

− telecommunications companies

• Average value of each lost relationship across all countries surveyed is

$243 per year

• Losses to a competitor (63% of the total)

• Transaction abandoned entirely (37% of the total)

Source: Data monitor/Ovum & Alcatel-Lucent (November 2009)

3

The Customers Viewpoint

• Understanding the entire customer engagement cycle:

− High quality customer self-service

− Reduced customer churn

− Long term loyalty

• Billions are spent worldwide on internal KPI and SLA

measurement

• If only one moving part fails, the customer sees overall failure

• Business intelligence in silos will not highlight this failure

• Operators must see from the customer’s view point:

− re-assembling all the moving parts into a single view

− allows you to monitor total customer experience

4

Customer Experience Monitoring

• Operational data that requires real-time or ready for next day

processing is not an optimal candidate for Enterprise Data

Warehouses (EDW)

• Customer intelligence can be derived from many different sources:

− Call Centre interactions

− Web activity

− Shop visit, Kiosks & ATM

− Online Commerce activity

− Service usage and fault to restore activity

− Customer surveys

5

Customer Experience Monitoring

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Operational Data Store (ODS) versus EDW

Enterprise Data Warehouse

Operational Data

Store

Data Warehouse (EDW) Issues

• Traditional Enterprise Data Warehouse (EDW) systems are excellent at collecting historical data, that can be normalised and indexed – can be slow and inflexible

• Typical data warehouse projects will require companies to spend 80% of their time loading and cleaning data

• While cleaning the data can be complicated, extracting it can be

even more challenging

Operational Data Store (ODS)

• Used for integrating disparate data from multiple sources

• Business operations, analysis and reporting can be carried out while business operations are occurring (on-line/real-time)

• The place where most of the data used in current operations is housed

• Transferred to the enterprise data warehouse for longer term storage or archiving

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Must see from the customer’s view point

• Re-assembling all the moving parts into a single view

• Stitching the data together into a contiguous stream of events

• Requires collecting on-line or real-time operational data

• Need to employ ODS temporary storage

• Requires intra-day or next day reporting

• Highlight individual events (triggers – exceptions)

• Aggregate activity that breaches acceptable thresholds

• Allows you to monitor total customer experience

• Provides opportunity for continuous process and behaviour

improvement

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The Telecommunications Carrier Case Study

• Customer Experience Monitoring

• Key objectives of the “movers” end-to-end experience

• Map end-to-end (E2E) customer experience from first customer contact “through” to service activation

• Identification of key experience metrics through the end-to-end process

• Enablement of a continuous improvement cycle

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Customer E2E experience overview

• The following slides provide a detailed view of 1 customer experience and the key insights we were able develop based on joining data from 1ST call through the IT systems until the Move order was completed and the service was active.

• Mrs Beverley Smith contacted the Telco to “Move” her 1 PSTN service.

• Beverley:

• Made 8 phone calls

• Visited 1 the Telco store

• Made a complaint

• For the Proof of Concept (PoC) we defined the Moves E2E experience as:

1st Call Service Active

Start Experience End Experience

• the Telco:

• Initiated 17 actions to meet the customer requirements

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Mrs Smith made 9 contacts to move a single PSTN

phone service, 17 Telco actions resulted…

23 Sep 24 Sep 25 Sep 26 Sep 27 Sep 28 Sep 29 Sep 30 Sep

Inbound Calls

Shop/Web

Call Centre

Outbound

Orders

BOH

Field Services

9:42 am

9:58 am

5:20 pm

3:00 pm

3:29 pm

10:17 am

10:37 am

12:58 pm

8:00 am

Customer

(Shop visit)

Telco

11:00 am

(Foxtel Mktg)

5:28 pm

5:32 pm

X:XX am (TR: Act tel line)

O1: 10:37 am

O2: 11:53 am

O3: 1:08 pm

X:XX am

(Schedule TR)

1:26 pm (Activation failed)

O4: 5:27 pm O5: 9:59 am

TD: 1:16 pm

FU: 1:16 pm

(Schedule TR)9:42 am (Cancel TR)

X:XX am

10:25 am

1:26 pm

(Call terminated in IVR)

(Failed attempts to notify customer after creation of 1st ADD Order)

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Key insights through Mrs Smith’s experience..

• Customers new address unknown by customer & unconfirmed• 3 days Telco system processing time to confirm new address

1. Address

Confirmation

Failure

• the Telco agent called Beverley for a Foxtel up-sell as part of an outbound campaign

2. Inappropriate

Outbound

Marketing

• Move order was cancelled twice prior to provisioning• Third attempt failed due to malformed order. An order that had been sitting in pending for 3 days

3. Cancellation/Rejec

tion of orders prior

to provisioning

• Assess quality of adbor data by comparison with a national address db & cleanse, subject to findings• Review confirmation business process:• collapse timeframe• positively confirm adbor address

• Upgrade systems for real-time address update

• Tighten Siebel order entry data validation and business rules to ensure orders are complete and able to be provisioned once submitted. (e.g. 3 day pending order was incorrectly

created and was not picked

until submitted and order

failure)

• Up-sell Outbound campaigns to be subject to Siebel customer status order status and matching to Customer experience metric / threshold score (e.g. Customer had a good experience and up-sell

opportunity exists)• Outbound campaigns to address customer concerns post poor Moves experience

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Key insights through Mrs Smith’s experience..

Agent D296199 told customer’s daughter to tell her mother to call either to discuss the problem herself or to authorize the daughter on the account

4. Lack of Process

Ownership - Account

Authorization

• Agent D364486 “…contacted product connect to connect the line. Tel line at new address is now active.”(Incorrect)

5. Status Information

Incorrect / Unavailable

Information

• Call with Adelaide agent on 30 Sep dropped out after 20 mins. the Telco Call-back was routed to a new / different agent in Qld

7. Call Drop-out

Recovery

• Siebel Order of 28 Sep resulted in appointment: 2 Oct – 4 days later• If a technician was required why were there 2 utilised• Line was connected without a technician

6. Criteria and Timeframe

for On-Site Tech

Appointments

• Change business process for account authorization to require agent to contact customer when an authorization is required (e.g. Priority call back if it is clear to the

consultant that the

customer is unhappy

with experience)

• Provide provisioning progress information back to Siebel to support accurate, timely agent-to-customer interaction

• Telco to use CLI to call back the customer at time of “drop out”• Train and require agents immediately to call back• If 1st call-back is unsuccessful, schedule to dialler for retry until successful.

• Review business process & resourcing for Move related appointments and set SLA for responsiveness

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E2E “Move” MetricsAggregate like events

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Time: Total talk + hold time (min)

Contacts: # of inbound contacts

Queue: Longest hold time (min)

Transfers: Most per call

Repeat Calls: Max calls/day

Agent: Lowest Csat (1-5)

25

8

3.2

1

3

2

Telco Commitment

Date Met?

Customer Request

Date Met?

1st Order to Final

Order (SLA = 0 minutes)

Final Order to Full

Activation (SLA = 4 days)

1st Call to 1st Order (SLA = 30 minutes)

2% 2% 1%

3% 2%

Contacts/Call Center

Failed Actions: # of failed actions

Orders: # of orders created

Actions: # of actions initiated

Time: Duration of longest TD/FU

3

5

3.3

Orders/BOH

0.8

Missed: # of appts missed

Appointments: # of appointments

Late: # of appts late

Time: Customer time required (hr)

0.4

1.6

5.6

Field Services

Time: Customer time wasted (m) 47

Completed Last Week Open Moves

0 1-3 4-6 7-9 10+>0

Days late vs. Commitment Date

4-6 7-9 10-1213-15 16+0-3

Days open

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High level tactical solution

CR-X completes daily processing of required data in BSS/OSS environment and store data locally on server

CR-X constructs a history of the E2E Customer

Experience comprising multiple Call Records, Siebel Interaction Records and

Siebel Order Records, and calculate metrics on the Call and Interaction Records

Metrics on Provisioning and CR-X metrics on Calls and Interactions are merged for construction of the Moves

Scorecard

Scorecard

Survey Customer Lists

Analytical Dataset

Refine scorecard weightings based on

Analysis and Survey Results

Outputs

Resolution Actions

Improvement Team

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Summary

• Operators must see from the customer’s view point:

− re-assembling all the moving parts into a single view

− allows you to monitor total customer experience

• Operational data that requires real-time or ready for next day

processing is not an optimal candidate for Enterprise Data

Warehouses

• Understanding the entire customer engagement cycle drives:

− High quality customer self-service

− Reduced customer churn

− Long term loyalty

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Postscript

• is a real-time data integration and

transformation engine

• collects and transforms data at the rate of over

100,000 transactions per second

• operates on low cost commodity grade Intel

based hardware

• does not rely on relational d/base technology

and runs on open source operating systems

• can be contacted at www.cr-x.com