mdbw-cappius-speaker presentation - enterprise_speech_analytics_v5
TRANSCRIPT
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Enterprise Speech Analytics Actionable insights from customer interactions in a Service Center
Presented by
Name: Surya Putchala
Title: Head, Big Data Analytics
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1. Customer experience: overview
2. Need for the Solution
3. Enterprise Speech Analytics Solution
4. Architecture
5. Features
6. Benefits
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Agenda
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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
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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.
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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.
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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.
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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
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Core Engine Visualization
Call Conversation
Voice
Expression
Audio Extract from Video
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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
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Speech Analyzer in Action
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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
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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
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Thank You
Contact us,
www.cappius.com