Actionable Intelligence via Speech Analytics Dr Ofer Shochet

Actionable Intelligence via Speech Analytics Dr. Ofer Shochet SVP Verint Systems July 2008 IBM Speech Technologies Seminar

Speech analytics transforms recorded customer interactions from idle data to actionable intelligence

Three Levels of Speech Analytics BUSINESS VALUE ROOT CAUSE ANALYTICS Find out what you do not know to look for Analyze impact on known issues CONTENT CATEGORIZATION (lower false alarms) Find isolated calls of interest (high false alarms) KEYWORD SPOTTING INTELLIGENCE Spot 20 -200 defined words Transcribe and index entire call and extract concepts Mine categorized calls and suggest root cause

Another way of looking at it: Word Spotting, Categorization, Root Cause Word Spotting Categorization Root Cause Analytics Technician did not show Customer complaints Received wrong information Did not receive credit Large sample of customer interactions Interactions about new product offering Offer not clear to customers Interactions involving competition Perceived as better value Product does not work well Product is too expensive Product quality driving churn Price attracting customers

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 Contact Center Sales Back Office Marketing R&D Intelligence from Customer Interactions Compliance Fraud Collections Risk Management

Verint Analytics Addresses Key Business Issues Why are Customers Calling? Customer Complaints First Contact Resolution Sales Effectiveness Customer Retention Vendor Management • Identify contact drivers • Uncover trends and customer needs • Increase usage and effectiveness of self service channels • Reduce customer defections • Reduce costly escalations • Improve first contact resolution • Pinpoint best (and worst) selling circumstances and behaviors • Improve up-selling/cross-selling capabilities • Increase closing rates • Increase customer loyalty • Reduce churn • Evaluate performance of business partners

Customer Case Study First Contact Resolution • Improve First Contact Resolution 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 First Contact Resolution How it works Classifieskey callsreasons via automated speechissues recognition andresolved categorization technology Identifies why customer were not Success (65%) Resolved Calls (60%) Unresolved Calls (40%)

Customer Case Study First Contact Resolution How it works Surfaces root cause of first callindicating resolutionroot issues Terms automatically surfaced cause Agent Knowledge “I don’t know” Gaps Resolved Calls (60%) “Check with Lack of Agent my Empowerment supervisor” ! “calling back Processing about. Issues my claim” Unresolved Calls (40%) “waiting for a Missing claim form” Paperwork

Customer Case Study Solutions First Contact Resolution • 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 Unresolved Calls 25% increase in First Call Resolution!

Customer Case Study Additional Results First Contact Resolution • 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

Speech Analytics Delivers the Power of Why Root cause of why my results are poor/excellent? What am I analyzing? • First contact resolution What Why • Agent knowledge • Agent empowerment • Outdated policies • Confusing claim forms Execute How Execute a Plan How can I improve performance? • Increase first call resolution by 25% • Review outdated policies • Empower agents • Revise claim forms • Improve frontline processing

Customer Case Study Sales Effectiveness • Pinpoint best (and worst) selling circumstances and behaviors • Improve up-selling/cross-selling capabilities • Increase closing rates 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 Sales Effectiveness How it works Classifies calls via effective automated speech recognition categorization technology Identifies the most approaches for agentsand when selling to customers Success (65%) Other calls (50%) Sales Opportunities (50%)

Customer Case Study Sales Effectiveness How it works Automatically detects sales success and failures based on key phrases and metadata Success (65%) Other calls (50%) Sales Opportunities (50%) Failure (35%)

Customer Case Study Sales Effectiveness How it works Surfaces root cause of negative sales performance Terms automatically surfaced indicating root cause “Are you. Agent interested in Presented the choices I All Options presented? ” Success (65%) “I’m Customer confused” Confusion “I am not sure that Agents Acted we offer that…” Simply as Order Takers ! Failure (35%)

Customer Case Study Sales Effectiveness How it works Surfaces root cause of positiveindicating sales performance Terms automatically surfaced rootbehaviors cause are corrected Positive behaviors are reinforced, negative “May I ask you a Presented few. Qualifying questions? ” Questions Agent Presented All Options Success (65%) Customer Confusion Agents Acted Simply as Order Takers ! “the best deal Offered for you. Most is…” Relevant Option “this is a better Conducted offer Research on because…” Competitive Offers

Customer Case Study Solutions Sales Effectiveness • 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 Sales Conversion Rates 19% increase in conversions!

Speech Analytics Delivers the Power of Why Root cause of why my results are poor/excellent? What am I analyzing? • The factors that drive success or failure in sales calls What Why • Agent knowledge • Probing questions • Simplicity of offers Execute a Plan • Increase closing rates by 19% How can I improve performance? • Train agents to qualify • Create simple marketing offers

Speech Analytics Delivers Quantifiable ROI Communications Provider Past Performance three months after Verint deployment Quality Scores 70% 81. 20% Revenue Per Call $0. 33 $0. 67 First Call Resolution 76. 8% 79. 1% +3% Improvement 8700 @ $82 Countless occasions to be proactive Potential saving of $713 K 1 -2 call evaluations/month 5 -6 call evaluations/month Analysis underway KPI Customer Satisfaction /Executive Complaints Manager Productivity Customer Churn Impact +16% Improvement +103% Improvement +300% Improvement 25% reduction

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