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MDBW-Cappius-Speaker Presentation - Enterprise_Speech_Analytics_v5


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MDBW-Cappius-Speaker Presentation - Enterprise_Speech_Analytics_v5

  1. 1. Confidential Information Enterprise Speech Analytics Actionable insights from customer interactions in a Service Center Presented by Name: Surya Putchala Title: Head, Big Data Analytics
  2. 2. Confidential Information 1. Customer experience: overview 2. Need for the Solution 3. Enterprise Speech Analytics Solution 4. Architecture 5. Features 6. Benefits 2 Agenda
  3. 3. Confidential Information 3 Customer experience: overview Business Intelligence CRM Intelligence Social Media Intelligence Market Intelligence Enhanced Consumer Experience Transactional Intelligence Customer Demographics Market/Product Trends, Recalls, Feedback Consumer Sentiment Customer Insights With big data and analytics you can combine all information to extract insight in real-time and create an actionable view of each customer to craft an exceptional experience  Need to integrate multi-Intelligence data  Increasingly, more intelligence data is unstructured in text formats, video and audio. Traditional Approach Enhanced Approach Service call In store, in person touch points Moments of truth
  4. 4. Confidential Information 4 Why Speech Analysis? In a Service Call center, the audio call data is archived for reference and not mined for customer interactions and extract value from them. It is exhausting to hear the tapes, hence this source of rich data is routinely ignored. Often this data is never accessed, unless there is a special situation such as an escalation or a dispute. Most information is hidden and should be mustered from the customer call data. Since, it is Audio, many Enterprises give it the least preference. The efficiencies will further improve by knowing the trending call center enquiries and deploying the right person for answering the right issue. Customer service will enhance tremendously by knowing the moods of the customer and intensity of conversation which will allows taking necessary actions to provide better service for the customer. 1 2
  5. 5. Confidential Information Archival Analysis This Solution is applicable in cases such as : 1. identification of the trending inquiries 2. identifying common pain points and improve understanding of a customer behavior. These levers could pre-empt actions that will result in preventing customer dissatisfaction and increase customer delight; achieving a superior contact center performance. 5 Enterprise Speech Analytics Solution Synchronous Analysis The process : 1. Capture the voice stream by applying various text and audio processing techniques 2. Understand the sentiments as well as mood of the conversation for a customer service call. This is accomplished real-time and continuously monitored and tracked; which allows the service center the ability to provide superior customer engagement, handle situations at the right time to mitigate attrition and escalations.
  6. 6. Confidential Information Solution Architecture Google Web Speech API Transcript Polarity Trends Ticker Mood  Voice data/ Analysis  Transcripted text/Summary Beyond Verbal API Streaming  Data Collection  Data Processing NLP  Sentiment  Mood Real time Call Signal Archived Audio Apache Storm Machine Learning Real- time Mood Transcripted Text Analytics Scoring  Service Rep Scoring  Outlier detection  Session benchmarking  Trending Topics  Floor Analysis  Problem Resolution Analysis  NPS – Net Promoter Score  Customer Traffic Analysis Persist real-time data as well as run predictive Analytics Customer Sentiment tracking at pre-configured intervals (default 15 sec) Knowledgebase 6 Core Engine Visualization Call Conversation Voice Expression Audio Extract from Video
  7. 7. Confidential Information Features Interprets voice to text (on the fly or from the archives)  Accent aware speech to text conversion  Summary and Conclusions of Call sessions Polarity Deciphering the Feelings and Meaning of a conversation Mood Analysis Analyze mood of the customer in real-time Knowledgebase  Two-way voice data (Customer and Support Executive)  Results of voice analysis (quantitative and qualitative)  Transcripted Text  Polarity, Sentiment, Word clout  Summary and conclusions data needed for Analytics Service Rep Scoring Evaluation Score how well executive handled with customer  Call Forwarding to most appropriate Staff  Help to Identified Most Efficient Employee to take up the calls Effective Handling  Real-time suggestions for customer executive  Optimization of the responses in Real-time  Trending issues, best relevant answer  Audio sniffer with configurable “key“ words (used for escalations) Transcription 7
  8. 8. Confidential Information Speech Analyzer in Action 8
  9. 9. Confidential Information Analytic Dashboards Service Rep Scoring Customer Call Analysis Topic mining and trending Average Response Time Top 10 Customer Service Representatives Top 100 Customers by # Inbound Calls Average Number of Outbound Calls to Sell a Product Change in Customer Satisfaction Rating Variance in Call Volume by Customer Segment Forecasted Call Volume Average Call Length Call Type (Sales, Service) as % of Total Inquiries Session Benchmarking Floor Analysis Customer Experience Customer Segmentation Customer Mood, Sentiment, Satisfaction Net Promoter Score Identification of Common Concerns Trending Topics Queuing Analysis Statistical Analysis Ranking and Scoring Document Similarity Anomaly Detection Customer Segmentation Anomaly Detection Analytical Themes
  10. 10. Confidential Information  Improve the customer experience  Improve service quality  Reduce operating expenses and save money  Revenue enhancement with up-sell and cross-sell  Reduce Customer Attrition Benefits 10
  11. 11. Confidential Information Thank You Contact us,