Speech Analytics Speech Analytics –– Gaining Gaining Insights from the "Voice of Insights from the "Voice of the Customer" the Customer"

Introducing…

Karl Walder– VP – Solutions, Noble Systems

Mike Hutchinson– VP – Professional Services, Nexidia

Agenda

What is Speech Analytics?

Demonstration of Technology

Speech Analytics Case Studies

Question & Answers

Glossary

SA – Speech Analytics

WFO – Workforce Optimization

WFM – Workforce Management

LVCSR – Large-Vocabulary Continuous Speech Recognition

TOP – Technology & Operations Profilegy p

What is Speech Analytics?

The Six Components of WFO

ScoreCards

WFMRecording

S

CardsWFO

RealScreenCaptureSpeech

Analytics

TimeMonitors

Analytics

What’s Missing?What s Missing?

Key Process Indicators (KPI) for TOP Analysis− Liquidity, Costs, Compliance, Training

Questions:– Are collectors, sales, and customer service agent using best practices

in their conversations?in their conversations?– Are they having The “RIGHT” Conversation? – Adequate Training?– Are bad habits forming?Are bad habits forming?– Compliance?

WFO Answers:– Score CardsScore Cards– Recording and Screen Capture– Listening, Monitoring, Coaching

The problemp– Bandwidth

What is Speech Analytics?

Speech Analytics (aka audio mining) is the process of leveraging large volumes of recorded conversations toleveraging large volumes of recorded conversations to gain actionable business intelligence to:− Automatically analyze the structure of conversations− Find hidden insights into collector, sales, or customer service skills − Assure call dispositions are accurate− Identify inefficiencies in call processing and handlingIdentify inefficiencies in call processing and handling− Compliance − Assure customer service level compliance

S h A l ti T h l Speech Analytics Technology Phonetic vs. LVCSRPHONETIC

Washington

PHONETICPhonetic Search

WashingtonResults =436 instances of

LVCSR

..PAT files ‘w aa sh ih ng t ah n’

436 instances ofWashington

W t h hiLVCSR Watch his son

Dictionary Word Lattice Grammar

Repeat process to add new search term(s)

Speech Analytics Technology

Demonstration

Speech Analytics C SCase Studies

C ll tiCollections

B i O t it Id tif i ffi i t ll h dli t l i b t ll tiBusiness Opportunity: Identify inefficient call handling, not applying best collections practices to enhance collected revenue, and areas of non-compliance

Applied: 1 Indexed 6 279 First Party calls

Findings: 1 60% of Right Party Contacts

Action: Pinpointed training opportunities1. Indexed 6,279 First Party calls

and 4,504 Contingency calls Represents 145 hours of First Party audio and 99 hours of Contingency audio.

1. 60% of Right Party Contacts were not asking for payment.2. Non- adherence to negotiation and call flow increased call handle time by 5%.3 N t t t d t

Pinpointed training opportunities by book of business down to the agent level that require additional training.

2. Developed 3 categories for each and 30 queries over 7 days.

3. Analyzed results:Equivalent manual effort saved

3. Non-contact events passed to collector had an average of 20 seconds of silence.4. 60% of calls did not comply to FDCPA RPC compliance standardsequals 3.52 man-years*. standards.

Economic Benefit:Estimated net revenue increase of $772,000 dollars annuallyDecrease in AHT by 5% decreasing costs by $240,000 dollars annually

© 2008 Nexidia, Inc. CONFIDENTIAL. DO NOT DISTRIBUTE

B i O t it I b id tif i th ll

Hospitality

Business Opportunity: Increase revenue by identifying the reasons callers do not confirm a stay.

Applied: 1 Identified Room Confirmations

Findings: 1 Non confirmations at 46%

Action: 1. Identified Room Confirmations and Non-confirmations in 3,886 calls.

2. Isolate reasons for Non-confirmations.

1. Non-confirmations at 46%.

2. Reasons for Non-confirmation include restricted reservations, advance purchases, and Sold Outs.

Increase alternative offers, track and measure down to the agent level.

3. Pinpoint Sold Out opportunities to sell an alternative property.

3. Alternative properties were offered when primary request was sold out only 5% of the time.

Economic Benefit:Economic Benefit:Increase revenue capture of an estimated $20M annually lost by non-confirmations.

© 2008 Nexidia, Inc. CONFIDENTIAL. DO NOT DISTRIBUTE

C dit C d P idCredit Card Provider

B i O t it A di i i h b t ki t ll Id tif hBusiness Opportunity: A new division has begun taking customer calls. Identify why customers call.

Applied: 1 Call Drivers Analyzed for 89 000

Findings: 1 Call Drivers typically

Action: Client uses SA to gain insight1. Call Drivers Analyzed for 89,000

calls.

2. Call Drivers analyzed for interdependencies.

1. Call Drivers typically summarized to:

- Changes to terms- I have a problem

2 All ll th

Client uses SA to gain insight into issues before they grow.

They also use SA to fill a void in the customer feedback loop.

3. Average handle time for long calls analyzed by call driver.

2. All calls more than one standard deviation from the mean AHT provide opportunity for process improvement.

Economic Benefit: $1.2M annually in productivity gains from implementing SA-Economic Benefit: $1.2M annually in productivity gains from implementing SAreducing cost per call, improving agent effectiveness, reducing misrouted calls.

© 2008 Nexidia, Inc. CONFIDENTIAL. DO NOT DISTRIBUTE

Fi i l S iFinancial Services

B i O t it Hi h t f b t t i ffi i dBusiness Opportunity: High transfers between queues represents inefficiency and waste. Identify transfers, where customers are transferred, and why.

Applied: 1 Identified transfer calls out

Findings: 1 Online banking and credit cards

Action: Pinpointed training opportunities1. Identified transfer calls out

of 21,000 calls.2. Identified locations to which calls were transferred.3. Determined why the call was t f d

1. Online banking and credit cards generate ~46% transfers.

2. Access to systems or info was the primary reason for appropriate transfers ~77%.

Pinpointed training opportunities by line of business down to the agent level that will reduce Inappropriate Transfers.

transferred.4. Pinpointed whether the transfer was appropriate.5. Developed change recommendations to eliminate i i f

%

3. Agent knowledge was the primary driver of inappropriate transfers.

inappropriate transfers.

Economic Benefit:Estimated net savings of $1.4M annuallyIdentification of potential call steering defects

© 2008 Nexidia, Inc. CONFIDENTIAL. DO NOT DISTRIBUTE

Speech Analytics Solutions

No of Agents Solution Messaging

< 100 agents AudioFinder Improved opportunity targetingg p pp y g g

Sampled Recording

Manual file extraction and indexing

100 to 200 agents

ESI Discovery

Improved opportunity targeting

Analyze 100% of recorded calls

Automated file extraction and indexingAutomated file extraction and indexing

200+ agents ESI Collections

Provide interactive reports

Detailed agent analytics using Noble metadata

Analyze 100% of recorded calls

Summary

Speech Analytics available to all Customers/Platforms –Noble Enterprise Noble CCS TouchStar and TDINoble Enterprise, Noble CCS, TouchStar and TDI

To get a more in-depth demonstration contact info@noblesys.com or your Noble Account team.

QQ A&A