Actionable Intelligence via Speech Analytics

Dr. Ofer ShochetSVP

Verint Systems

July 2008

IBM Speech Technologies Seminar

Speech analytics transforms recorded customer interactions from idle data to

actionable intelligence

CONTENT CATEGORIZATION

Transcribe and index entire call and extract

concepts

Analyze impact on known issues

(lower false alarms)

Three Levels of Speech Analytics

KEYWORD SPOTTING

Spot 20-200 defined words

Find isolated calls of interest

(high false alarms)

BUSINESS VALUE

INTELLIGENCE

ROOT CAUSE ANALYTICS

Mine categorized calls and suggest root cause

Find out what you do not know to look for

Word Spotting Categorization Root Cause Analytics

Technician did not show

Received wrong information

Did not receive credit

Offer not clear to customers

Product does not work well

Product is too expensive

Perceived as better value

Product quality driving churn

Price attracting customers

Large sample of customer interactions

Customer complaints

Interactions about new product offering

Interactions involving competition

Another way of looking at it: Word Spotting, Categorization, Root Cause

The Value of Speech Analytics

• Delivers value from the “voice of the customer” – “Focus groups on demand” with a more complete

view of the customer experience

• Enhances Quality Monitoring– Evaluate calls that represent

“what matters most” to you

• Connects the contact center and the enterprise

SalesSales

Back OfficeBack Office

FraudFraud

CollectionsCollections Risk Management

Risk Management

ComplianceCompliance

R&DR&D

MarketingMarketing

ContactCenter

ContactCenter

Intelligence from Customer

Interactions

Intelligence from Customer

Interactions

Verint Analytics Addresses Key Business Issues

Customer Details

• Fortune 500 Insurance provider with over 4 million customers

• First call resolution at 60%

• Abandonment rate of 28%

• Customer service rating of “Poor”

• No clear insight into why customer issues not resolved

Customer Case Study

• Improve First Contact ResolutionFirst Contact Resolution

Classifies calls via automated speech recognition and categorization technologyIdentifies key reasons why customer issues were not resolved

Customer Case Study

How it works First Contact Resolution

Success(65%)

Terms automatically surfaced indicating root causeSurfaces root cause of first call resolution issues

Customer Case Study

How it works

“calling back about my claim”

“calling back about my claim”

“Check with my

supervisor”

“Check with my

supervisor”

“I don’t know”“I don’t know”

First Contact Resolution

“waiting for a claim form”

“waiting for a claim form”

Solutions

• Outdated policies reviewed and changed and agents were trained to fully understand them

• Agents empowered to solve customer issue on first call

• Integration of frontline transaction processing

• Clarification of timelines on claim forms

Customer Case Study

First Contact Resolution

Results

Customer Case Study

0%

20%

40%

40%30%

Before Speech Analytics After Speech Analytics

Unresolved Calls

25% increase

in First Call Resolution!

First Contact Resolution

Additional Results

• 83% improvement in average speed of answer

• 68% improvement in their service level (% of calls answered in 30 seconds)

• 25% improvement in abandonment

• 20% reduction in average handle time

• 15% reduction in seasonal call volumes

• eliminated the need to hire 22 additional agents

• greatly improved staff morale

Customer Case Study

First Contact Resolution

Speech Analytics Delivers the Power of Why

How can I improve performance?• Review outdated policies

• Empower agents

• Revise claim forms

• Improve frontline processing

What am I analyzing?• First contact resolution

Root cause of why my results are poor/excellent?• Agent knowledge

• Agent empowerment

• Outdated policies

• Confusing claim forms

Execute a Plan• Increase first call resolution by 25%

Customer Details

• Credit card provider

• Historical record of converting 65% of inbound customer inquires

• Sales conversion rate stagnating in previous three years

• Marketing currently testing new offers

Customer Case Study

• Pinpoint best (and worst) selling circumstances and behaviors• Improve up-selling/cross-selling capabilities• Increase closing rates

Sales Effectiveness

Identifies the most effective approaches for agents when selling to customersClassifies calls via automated speech recognition and categorization technology

Customer Case Study

How it works Sales Effectiveness

Success(65%)

Automatically detects sales success and failures based on key phrases and metadata

Customer Case Study

How it works Sales Effectiveness

Surfaces root cause of negative sales performanceTerms automatically surfaced indicating root cause

Customer Case Study

How it works

“I am not sure that we offer that…”

“I am not sure that we offer that…”

“I’m confused”

“I’m confused”

“Are you interested in the choices I

presented?”

“Are you interested in the choices I

presented?”

Sales Effectiveness

Terms automatically surfaced indicating root causePositive behaviors are reinforced, negative behaviors are correctedSurfaces root cause of positive sales performance

Customer Case Study

How it works

“May I ask you a few

questions?”

“May I ask you a few

questions?”

“the best deal for you is…”

“the best deal for you is…”

“this is a betteroffer

because…”

“this is a betteroffer

because…”

Sales Effectiveness

Solutions

• Agents trained to engage in conversation to uncover what customer values

• Agents trained in presenting offers appropriately

• Marketing began providing competitive data to agents prior to campaign launch

• Marketing revised offers based on findings

Customer Case Study

Sales Effectiveness

Results

Customer Case Study

50%

60%

70%

80%

65%77%

Before Speech Analytics After Speech Analytics

Sales Conversion Rates

19% increase

in conversions!

Sales Effectiveness

Speech Analytics Delivers the Power of Why

How can I improve performance?•Train agents to qualify

•Create simple marketing offers

What am I analyzing?•The factors that drive success or

failure in sales calls

Root cause of why my results are poor/excellent?

• Agent knowledge

• Probing questions

• Simplicity of offers

Execute a Plan• Increase closing rates by 19%

KPIPast

Performance

Performance three months after Verint

deployment Impact

Quality Scores 70% 81.20%+16%

Improvement

Revenue Per Call $0.33 $0.67+103%

Improvement

First Call Resolution 76.8% 79.1% +3%

Improvement

Customer Satisfaction /Executive Complaints

8700 @ $82Countless occasions to be

proactivePotential saving

of $713K

Manager Productivity 1-2 call evaluations/month 5-6 call evaluations/month +300%

Improvement

Customer Churn Analysis underway Analysis underway 25% reduction

Speech Analytics Delivers Quantifiable ROI

Communications Provider

Analyst Praise for Verint Analytics

“Saddletree Research views the Verint approach

to speech analytics managed services as the most comprehensive and efficient offering on the

market today…Verint has set the competitive bar”

Paul Stockford - Saddletree Research

Why Verint Speech Analytics?

• Automated root-cause – Delivers the Power of WHY

• Integrated recording and QM platforms– Lower TCO and future proof

• #1 Market Leader in Speech Analytics – Market proven ROI

– Expert turnkey service offering