Transforming Customer Engagement with IBM Watson


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Transforming Customer Engagement with IBM Watson

  1. 1. Transforming Customer Engagement with IBM Watson Vince Padua, Director, IBM Watson Rahul Garg, Product Manager, IBM Watson
  2. 2. The interactions customers want Examples of cognitive computing The role of cognitive computing
  3. 3. The information is available today but the systems can’t use it effectively Information is unstructured •  Structured data from CRM systems and ERP systems provide a small portion of the information needed Information is spread across many systems •  Product Manuals •  FAQs •  Knowledgebases •  Call notes •  Forums •  Reviews •  Blogs
  4. 4. Mobile: •  Customers demand great experiences on their mobile devices across their relationship with you Personal: •  Customers expect you to know them across channels and personalize your interaction Self - Service: •  Customers are embracing self-service options 75% 75% of customers prefer some form of self-service for simple inquiries 91% 91% of Smartphone users say they would use an online knowledgebase if it was tailored to their needs Customers want this type of interaction
  5. 5. Today the Customer Service department manually brings the information together Lower customer satisfaction $300B Organizations spend over $300B annually on contact center labor 42% % of service agents unable to efficiently resolve customer issues due to disconnected systems, archaic user interfaces, and multiple applications 11% Average amount of time agents spend looking for information needed to manage customer interactions Fewer deflected calls Lower first call resolutions Higher average handle times COSTS SERVICE
  6. 6. The effects of poor service ripple beyond the Contact Center to Marketing 6-7X It is 6-7 times more costly to attract a new customer than to retain an existing one 4X Customers are 4 times more likely to buy from a competitor if the problem is service related vs. price or product Poor service •  Increases customer churn •  Reduces loyalty and share of wallet •  Reduces word of mouth advocacy and net promoter scores •  Drives up marketing costs 66% Percent of customers willing to spend more with a company they feel provides excellent customer service (on average 13% more)
  7. 7. The effects also ripple to Sales 45% % of US consumers that abandon an online transaction if their questions or concerns are not addressed quickly 55% % of consumers that have intended to conduct a business transaction or make a purchase, but decided not to based on a poor service experience Poor service •  Reduces sales revenue •  Increases cart abandonment 83% of consumers require some degree of customer support while making an online purchase
  8. 8. The interactions customers want Examples of cognitive computing The role of cognitive computing
  9. 9. Perceiving: Watson understands the world as we do: it interprets sensory input beyond traditional data • Understands  natural  language   • Reads  manuals,  social  data,  blogs,  consumer  reviews,  etc. Reasoning: Watson thinks through complex problems: it deepens our analysis and inspires creativity • Makes  inferences     • Evaluates  pros  and  cons   • Finds  rela=onships  between  terms  and  concepts Relating: Watson understands how we communicate, and personalizes its interactions with each of us • Responds  in  natural  language   • Personalizes  the  interac=on  and  provides  reasons   Learning: Watson learns from every interaction, scaling our ability to build experience • Trains  with  experts  and  improves  with  feedback Watson  is  a  learning  system  that  augments   human  cogni2on;  scaling  people’s  abili2es  to   perceive,  reason  and  relate
  10. 10. Decision Maker Decision Maker Search Engine Finds Documents Containing Keywords Delivers Documents Based on Popularity Has Question Distills to 2-3 Keywords Reads Documents, Finds Answers Finds & Analyzes Evidence Watson Understands Question Produces Possible Answers & Evidence Delivers Response, Evidence & Confidence Analyzes Evidence, Computes Confidence Asks NL Question Considers Answer & Evidence Decision Maker Cognitive conforms the technology to the user; Keywords force the user to conform “My husband hardly ever uses his phone, which plan is right for him? “I need a window covering for my dining room. I want the natural light, but in the morning the sun shines in low and I have to close the shades.”
  11. 11. The interactions customers want Examples of cognitive computing The role of cognitive computing
  12. 12. Watson Engagement Advisor 1 2 © 2014 International Business Machines Corporation
  13. 13. 13 The core of Watson is a learning system that works by understanding both customers and knowledge Multiple interpretations Hundreds of answer sources •  Primary search •  Candidate answer generation Tens of thousands of evidence sources and scores •  Answer scoring •  Evidence retrieval •  Deep evidence scoring Learned models •  Combine and weigh evidence Inquiry analysis Decomposition Hypothesis generation Synthesis Hypothesis and evidence scoring Final confidence merging and ranking Question Answer ? ! © 2014 International Business Machines Corporation
  14. 14. 14 Gary This evidence suggests “Gary” is the answer BUT the system must learn that keyword matching may be weak relative to other types of evidence In May 1898 Portugal celebrated the 400th anniversary of this explorer’s arrival in India. Legend Key word hit “Reference text” Answer Question: In May, Gary arrived in India after he celebrated his anniversary in Portugal. Supporting evidence: Answering complex questions requires more than keyword evidence “explorer” “India” “In May 1898” “India” “In May” “celebrated” “anniversary” “in Portugal” “Portugal” “400th anniversary” “celebrated” “arrived in” “arrival in” “Weak evidence” © 2014 International Business Machines Corporation
  15. 15. 15 “27th May 1498” Vasco da Gama “landed in” “arrival in” “explorer” “India” Paraphrases Geo-KB Stronger evidence can be much harder to find and score… §  Search far and wide §  Explore many hypotheses §  Find judge evidence §  Many inference algorithms “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 Question: On the 27th of May 1498, Vasco da Gama landed in Kappad Beach. Supporting evidence: Date Match Watson leverages multiple algorithms to perform deeper analysis © 2014 International Business Machines Corporation
  16. 16. 16 Watson Engagement Advisor delivers the next wave of customer engagement through cognitive computing © 2014 International Business Machines Corporation 16 •  Automates customer interaction to increase customer engagement in sales and service •  Transforms customer engagement by knowing, engaging and empowering clients •  Develops customer relationships through a transformative user experience What it does •  Provides answers not links and webpages •  Answers with evidence not guesses •  Not restricted to a predefined question- answer set •  Learns from every interaction How it does it
  17. 17. 17© 2014 International Business Machines Corporation New agents need to get up to speed quickly and demonstrate value Customers (Millennials): Customer demographics and expectations are shifting, creating challenges with traditional service environments Agents: Expect instant responses that understand them Goal is to take action immediately Increase in mobile use reduces reviewable information Customer insight is lost as many don’t call and transactions are separated Issues: Promotions can be overlooked decreasing customer lifetime value
  18. 18. 18© 2014 International Business Machines Corporation Watson helps new agents become productive quickly Watson helps Millennials get instant answers across devices Watson integrates processes to enable action Watson reads information to net it out for customers on mobile screens Watson captures interactions over time for identification of new insights Watson surfaces promotions in discussion, increasing visibility Customers (Millennials): Watson enables transformational customer engagement improving the customer experience and business value Agents:Solutions:
  19. 19. 19 A mobile phone provider plans to use Watson to differentiate the company with personalized service and support. Needs 1.  Meet changing expectations 2.  Reduce churn 3.  Beat competition Solutions 1.  Omni-channel self- service 2.  Guide through processes Benefits 1.  Increase loyalty 2.  Decrease churn 3.  Grow customer base ©2014InternationalBusinessMachinesCorporation 19
  20. 20. 20 Self-service User Experience Here is what you are looking for. Here it is. Shall I complete the task for you? Here it is, complete. Also, this new info might be helpful. How did it go? Can I assist with these next steps? Knowledge Expert Empowered Assistant Personal Advisor Ask a question Get answers Ask a questionGet answers Get action Ask a question Get answers Get action Get suggestions Get follow-up Recommended(AnalyticEngine) 2 0 Value Customer Satisfaction
  21. 21. 2121© 2014 International Business Machines Corporation Shannon is… the unconfident agent □ A new employee □ Wants what’s best for customers □ Spends too much time searching for answers □ Feels inferior when asking for guidance from peers IBM Watson is… the Cognitive Agent Advisor ■ Provides answers from trusted information ■ Uses natural language ■ Offers more visibility of customer needs ■ Tailors proactive service to each individual ■ Decreases need for supervision ■ Creates efficiencies
  22. 22. 2222© 2014 International Business Machines Corporation Jim is… the busy, capable customer □ A multi-line customer for years □ Busy, rarely available during normal business hours □ Prefers self-service □ Calling into a contact center will instantly put him in a bad mood IBM Watson is… the Empowered Virtual Agent ■ Transforms customer self-serve with the ability to answer questions ■ Can complete transactions ■ Provides personalized and proactive recommendations ■ Uses an intuitive text/voice interface ■ Continues learning from prior interactions
  23. 23. 23 To add mobile hotspot to your iPhone, simply launch setting, cellular and select mobile hotspot. You may have to restart your phone once added. You can also order online by logging in to your account. Watson helps Shannon and Jim © 2014 International Business Machines Corporation Knowledge Expert Empowered Assistant Personal Advisor 23 How expensive is it for a customer to add a new line to their account? It should be 9.99 for customers already in a family plan. How do I upgrade my customer to the latest device? 1)  On the NPC screen, select Prices and Promotions. 2)  From the Sales Offer Mode (SOM), select Upgrade > Waive Activation if appropriate How do I add Mobile Hotspot to my iPhone? I see you have a family plan with 4 lines. You also have 2GB of data per line. We have a new family share plan that you are eligible for, $160 / Month includes Unlimited Text, Unlimited Talk and 10GB of shared data. My bill is too high. I’d like to learn more about the new shared family plan. Ok. Let me connect you with an agent to provide you more information on plan eligibility. Hi Jim. This is Shannon. I see you’re interested in learning more about the new shared family plan… Hi Jim, I’ve noticed you’ve been spending more on international roaming recently Did you know that we offer an international roaming package that is available to you for only $46 extra per month which can be turned on and off at any time. Would you like to add the international roaming packages? Yes, please add the international roaming packages to my account. I’ll make that change now. Give me a moment to add International roaming… I added international roaming package, and backdated the addition so you save $30 on your last month bill I notice you’ve had some late charges. Can I help you avoid future charges by setting up AutoPay or changing your bill date? Yes, I’d like to set up AutoPay....
  24. 24. 2424© 2014 International Business Machines Corporation Watson on Watson Demo