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Why Your Customers Want a Cognitive Call Center


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Customers increasingly expect to engage with brands through self-service channels and not with tedious and frustrating traditional call centers that use IVR. They want the convenience and timely, streamlined interactions that a virtual agent offers.

More than 50% of enterprises have invested in virtual agents for customer service, and it’s estimated that by 2020 approximately 85% will manage the customer relationship with no human interaction at all.

But not all virtual agents are created equal. IBM Watson harnesses the power of natural language processing, machine learning, and cognitive computing to deliver an exceptional virtual agent experience.

Perficient and IBM took a closer look at intelligent virtual agents, including:

-The benefits of intelligent virtual agents
-Considerations when selecting a virtual agent
-IBM Watson Assistant introduction and demonstration
-Practical ways to get started with Watson

Published in: Technology
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Why Your Customers Want a Cognitive Call Center

  1. 1. Cognitive Virtual Agents Proof-of-Technology August 2018
  2. 2. 2 About Perficient Perficient is the leading digital transformation consulting firm serving Global 2000 and enterprise customers throughout North America. With unparalleled information technology, management consulting, and creative capabilities, Perficient and its Perficient Digital agency deliver vision, execution, and value with outstanding digital experience, business optimization, and industry solutions.
  3. 3. 3 Perficient Profile • Founded in 1997 • Public, NASDAQ: PRFT • 2017 revenue $485 million • Major market locations: Allentown, Atlanta, Ann Arbor, Boston, Charlotte, Chicago, Cincinnati, Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Lafayette, Milwaukee, Minneapolis, New York City, Northern California, Oxford (UK), Phoenix, Seattle, Southern California, St. Louis, Toronto, Washington, D.C. • Global delivery centers in China, India and Mexico • 3,000+ colleagues • Dedicated solution practices • ~95% repeat business rate • Alliance partnerships with major technology vendors • Multiple vendor/industry technology and growth awards
  4. 4. 4 • Practice Overview • Virtual Agents Trends and Forecast • Cognitive Virtual Agent Review ⎼ Conversational Agents ⎼ Conceptual Architecture • Training Approach • PoT Execution ⎼ Sprint Plan ⎼ Assumptions • Perficient Case Studies Agenda
  5. 5. 5 • Over 30 delivery professionals • Leveraging experience in Analytics, Big Data, Unstructured Content Management, Enterprise Search, Digital Experience and Business Optimization • IBM Watson Talent Partner • IBM Watson • Microsoft Azure • Google Cloud Platform • Amazon • Open Source (R, Python, etc.) • Platform Selection Engagements • Cognitive Readiness Evaluations • Solution Business Case Development • Cognitive Search Implementations • Text and Content Analytics Solutions • Virtual Agents and Chatbots • Predictive Modeling • Machine Learning Models • Decision Support Solutions Practice Overview Platform Support Offerings and Services 2017 Beacon Award Winner for an Outstanding Watson Cognitive Solution Artificial Intelligence Practice Overview
  6. 6. 6 Clients Served
  7. 7. 7 Looking Forward by 2022 25% of customer service and support operations will integrate virtual agent technology across engagement 40% of customer-facing employees and government workers will consult daily an AI virtual support agent for decision support over 50% of organizations have already invested in VAs for customer service, as they realize the advantages of automated self-service 20% of brands will abandon their mobile apps in favor of building presence in consumer messaging apps, such as Facebook Messenger 85% of the enterprise relationship to a customer will be managed without human interaction 30% of all B2B companies will employ artificial intelligence (AI) to augment at least one of their primary sales processes. by 2019 in 2018 by 2020
  8. 8. 8 Self-Service Channels are Key to Winning the Future of Customer Service
  9. 9. 9 The volume, variety and veracity of data – 80% of it unstructured – is growing at a rate impossible to keep up with. Customers have a wider range of choices than ever before and are expecting innovative, relevant and personalized engagement. Why is Cognitive Important? Companies must engage customers on their terms - in a consistent, natural, and intuitive way. Cognitive is the new competitive advantage for enterprises focused on enhancing the customer experience.
  10. 10. 10 Column Value Patient Joe Brown Date of Birth 02/13/1972 Date Admitted 02/05/2014 Structured Data High Degree of organization, such as a relational database “The patient came in complaining of chest pain, shortness of breath, and lingering headaches…smokes 2 packs a day… family history of heart disease…has been experiencing similar symptoms for the past 12 hours….” Unstructured Data Information that is difficult to organize using traditional mechanisms Structured vs. Unstructured Data
  11. 11. 11 explorer India In May 1898 India In May celebrated anniversary in Portugal In May, Gary arrived in India after he celebrated his anniversary in Portugal Portugal 400th anniversary celebrated Gary In May 1898 Portugal celebrated the 400th anniversary of this explorer’s arrival in India This evidence suggests “Gary” is the answer BUT the system must learn that keyword matching may be weak relative to other types of evidence arrived in arrival in Legend Keyword “Hit” Reference Text Answer Weak evidenceRed Text Answering complex natural language questions requires more than keyword evidence Analyzing Unstructured Content
  12. 12. 12 27th May 1498 Vasco da Gama landed in arrival in explorer India Para- phrases Geo- KB Date Match Stronger evidence can be much harder to find and score … … and the evidence is still not 100% certain  Search far and wide  Explore many hypotheses  Find judge evidence  Many inference algorithms On the 27th of May 1498, Vasco da Gama landed in Kappad Beach 400th anniversary Portugal May 1898 celebrated In May 1898 Portugal celebrated the 400th anniversary of this explorer’s arrival in India. Kappad Beach Legend Temporal Reasoning Reference Text Answer Statistical Paraphrasing GeoSpatial Reasoning Leverage Multiple Algorithms The Watson Difference:
  13. 13. Cognitive Virtual Agent Review
  14. 14. 14 Scripted vs. Cognitive Conversations • Driven by a pre-defined conversation flow • Expects key phrases or words • Functions best on structured data • Best for short and simple tasks • Relatively quick to implement Scripted Conversations • Driven by conversational intents rather than expected flow • Trained to understand natural language • Operates on both structured and unstructured data • Learns over time • Capable of a wide range of tasks • Training time varies by complexity Cognitive Conversations
  15. 15. 15 Conceptual Virtual Agent Architecture
  16. 16. 16 Virtual Agent Knowledge Base Frequency Complexity High complexity, answer depends on a number of variables (knowing the intent is not enough to answer), requires Deep QA search. Short Tail Long Tail Proof-of-Technology Phase1 Phase2 Phase 3 Low complexity, easy to answer derived using context of the question itself Phase 4 Phase 5
  17. 17. 17 Forrester Wave Q2 2018 Conversational Computing Platforms
  18. 18. Training Approach
  19. 19. 19 Virtual Agent Vocabulary I need to add my daughter to my auto policy. utterance entity entity intent: addDriver verb noun
  20. 20. 20 Intent Training I need to add my daughter to my auto policy. Training Set: intent: addDriver My son just turned 16 and I need to add him to my policy. I have to update my policy to include my nanny. Make sure my account covers my twins also. Test Set Please add my son.
  21. 21. 21 Entity Training I need to add my daughter to my auto policy. Training Set: entity: PolicyType - auto My son just turned 16 and I need to add him to my policy. What does my automotive insurance cover? My twins are new drivers please add them to my policy. Test Set Does my car insurance cover theft? requires inference
  22. 22. Watson Assistant
  23. 23. 23 IBMWatson’sAI capabilities organized into 6 categories and available as API’s on IBM Cloud © 2018 IBM Corporation Knowledge Natural Language Classifier Language Translator Speech Text to SpeechSpeech to Text Empathy Tone Analyzer Personality Insights Language Natural Language Understanding Discovery incl Element Classification Discovery News Vision Visual Recognition Watson Knowledge Studio AI Assistants & Chatbots Watson Assistant Watson sees, hears, speaks, feels, converses, translates, finds 2
  24. 24. 24 3 Primary Watson Assistant Use Cases Customer Care Through the Watson Assistant, IBM can decrease call center operations cost, while improving the customer experience and developing new revenue streams Conversational Commerce Provide guided buying experience for prospective customers to purchase goods and services through the mobile or messaging channel of their choice Employee Productivity Simplify access to common questions and tasks through enterprise channels © 2018 IBM Corporation
  25. 25. 25 Contextual Entities Enable entities to be contextually aware and expand value Recently Released Features • Dialog Folders Stay organized as you scale your bot. • Digressions Dynamically answer questions in the midst of a business process • Rich Response Types Provide buttons, images, videos, pauses, etc. into the response to the end user Set Context in the Dialog UI Avoid having to set context in the advanced JSON editor. Conflict Detection (Premium) Find conflicts between intents and resolve them 6 Entity Synonym Recommendations Disambiguation (Premium) Prompt user for clarification on which intent was intended 7 8 Separate Log Files Separate workspace from your log file, allowing you to improve a bot while in production. 9 Based on a particular value, recommend other synonyms for the user
  26. 26. Case Studies
  27. 27. 27 A Digital Concierge  Reshaped the User Experience  Autonomously Handles Tier-1 Requests (60% Upon Initial Release)  Supports Software Activation and Maintenance Tasks  300% Increase in Web Traffic 90% 99% lower support costs shorter resolution times North American Software Provider
  28. 28. 28 63%reduced AHT Interactive Agent for Healthcare Providers  Cognitive Agent Converses with Providers to Verify Benefits  Seamlessly Manages Member Information Inquiries  Transformed a Tedious IVR System  Drastic Reduction in Live Agent Requests  Call Time Reduced from 8 to 3 Minutes live agent requests Major Health Insurer
  29. 29. 29 Bradesco is one of the biggest and fastest growing banking and financial services companies in Brazil. The bank recognized that international expansion could provide some growth opportunities but saw the need to improve service to existing customers as a top priority. Working with Watson, Bradesco, created a virtual customer service solution to provide support for call center agents. The agents, who answered branch agent queries, now have an AI system that recognizes, understands and answers these questions with a high level of accuracy. 283k+ questions is answered by Watson in Portuguese every month 95% Watson is answering questions at a 95% accuracy rate, with only 5% requiring calls for further assistance 62 products Watson has been trained on 62 different Bradesco products use Watson to better serve Bradesco’s 65 million customers 5200 branches 2 © 2018 IBM Corporation
  30. 30. 30 In an age when elegant technology interactions have become key factors in many consumer decisions, financial institutions must strive to digitally differentiate themselves from the competition. RBS recognized that although its customer service representatives were crucial to a customer’s journey, they spent too much time handling problems that are easily resolved, increasing wait times and negatively affecting satisfaction ratings. RBS used the IBM Watson Conversation Service to build a conversational solution called Cora. The chatbot weaves automated assistance seamlessly with human intervention, creating a hybrid solution that serves as a virtual assistant. Cora has reduced the length of agent/customer conversations by 20% 200+ question topics per brand within Cora’s knowledge base, which has more than doubled since 50% of customer questions Cora can answer after just a few months 85% of customer inquiries are managed by Cora 2x The average contact center agent can now spend up to twice as much time on the more complex problems and questions that matter most to customers 3 © 2018 IBM Corporation
  31. 31. Questions Type your question into the chat box
  32. 32. Thank You