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Turning Audio Search and Speech Analytics into Business Intelligence.

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Presentation on theme: "Turning Audio Search and Speech Analytics into Business Intelligence."— Presentation transcript:

1 Turning Audio Search and Speech Analytics into Business Intelligence

2 Insight from Interactions TM 2 Business Intelligence is Hidden in Customer Interactions Business Analyst Customer churn Campaign effectiveness Competitive info. Process issues Service quality Agent productivity Enterprise challenges:  Understand market and customer dynamics  Improve business processes  Enhance sales effectiveness  Increase contact center productivity ? Enterprise ? ?

3 Insight from Interactions TM 3 Adaptive Interaction Analytics: Business Impact Examples  Increased revenue by identifying missed opportunities by 10% ($2M annually )  Reduced direct-mailing inquires call volume by 30%  $200 increase in sales-per-hour per associate  Reduced total call volume by identifying calls associated with new health plan groups by 5%

4 Insight from Interactions TM 4 The Technologies of Speech Analytics  Key Word Spotting  Phonetic Indexing  Transcription (Speech to Text)  Emotion Detection  Talk Pattern

5 Insight from Interactions TM 5 Comparing the Different Technologies Technology Processing Speed (analyzed recording hours per server) Search Speed (records in one second) AccuracyStorage Word SpottingHigh (360 hours per server) Very High (> 1M) High (80-90%)Very Small Phonetics Recognition Very High (~1700 hours per server) Medium (60- 500 calls in a second) Medium- High (70-90%) Large (1-4 times the audio storage) TranscriptionVery Low (30-100 hours per server) Very high (> 0.5M) Medium (40- 50% without fine tuning) Small

6 Insight from Interactions TM 6 Going Beyond Technology Solutions – Introducing Adaptive Interaction Analytics An automated, iterative, self-learning analytics solution that leverages customer interactions to identify trends, anticipate opportunities and adjust processes to meet business objectives

7 Insight from Interactions TM 7 Adaptive Refinement Extract Insights Interaction Categorization ProcessingModeling Trends analysisMiningRoot Cause Analysis 100% Interaction Analysis  Services levels  Sales effectiveness  Productivity  Customer retention Business Insights Into Adaptive Interaction Analytics Methodology

8 Insight from Interactions TM 8 Interaction Capture Root Cause Analysis Category Manager Transcription Data Mining In-depth queries Comprehensive Reports Alerts Phonetic Indexing Emotion Detection Talk Pattern Other Technologies Adaptive Interaction Analytics Buildings Blocks

9 Insight from Interactions TM 9 Why do certain products sell more then others? 100% Interaction Analysis Processing & Mining Focus on higher selling products Interaction Categorization Product A Product B Product C Modeling & Root Cause Identify Successful sales criteria Refinement  Competitive offerings  Product features  Winning pitch

10 Insight from Interactions TM 10 Recap  There is a wealth of business intelligence contained in customer interactions  Technology point solutions are valuable tools but have limitations  Adaptive Interaction Analytics integrates the point technologies to:  Enable 100% analysis of recorded interactions  Reduce the amount of manual intervention required  Answer questions we don’t even know to ask

11 Thank You Brian Spraetz Senior Manager, NICE Systems brian.spraetz@nice.com 214-227-8592


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