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Emotion Engineering: Root-Cause Analysis for Customer Satisfaction (Dan Somers, Warwick Analytics)

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Presentation by Dan Somers, Warwick Analytics, at the 20 June 2019 CX Emotion conference (http://cx-emotion.com)

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Emotion Engineering: Root-Cause Analysis for Customer Satisfaction (Dan Somers, Warwick Analytics)

  1. 1. Emotion Engineering: Root cause analysis for customer satisfaction 20 June 2019
  2. 2. The Problem
  3. 3. ! Source: SurveyMonkey; 5 ways to get the survey data you want
  4. 4. All ML Models are not created equally! Keywords NLP/Basic ML Complex, Specific ML milk soup@Tesco why have u added milk to a perfectly nice soup???? Just to save a few pennies I am DISGUSTID. Cheapskates u have really let me down. @santanderukhelp cheers, thanks for withholding my cheque for extra days without letting me know you would. Love the clarity you have with your bankers. Good to see I’m just a number and not valued. I’m off. clarity cheque soup Ingredient change very unhappy lack of info withholding cheque very unhappy churn positive positive not picked up wrong (sarcasm) wrong (misattribution) irrelevant irrelevant subtle, key intent concepts, not keywords
  5. 5. 100% 90% 80% 70% 60% 50% 40% Accuracy Optimized Learning: minimal effort, maximum performance (represents amount of human training/classification) Conventional ML Optimized Learning
  6. 6. Case Study
  7. 7. 0 500 1000 1500 2000 2500 3000 3500 4000 4500 0 500 1000 1500 2000 2500 3000 3500 4000 4500 1. Topic model: increased accuracy with reduced ACW All Level1 Cats (Original) All Level1 Cats (New) Incorrect and “Bucket” categories AFTER STRICTLY PRIVATE AND CONFIDENTIAL BEFORE
  8. 8. 2. Sentiment Model: understand how 100% of the conversations went Sentiment at interaction Position (Actual) Sentiment at interaction Position (%) STRICTLY PRIVATE AND CONFIDENTIAL
  9. 9. 3. Emotional Intent Model: Actionable root causes Percentages (of total conversations) STRICTLY PRIVATE AND CONFIDENTIAL Neutral Positive Negative Disappointed No Intent Resolved Not Resolved Clarification/Didn't Understand Repeat Problem Bad Previous Advice Long Time Waiting Last Agent Disappeared Insecurities/Possible Error Don't Recommend Looking to Leave Recommend Broken Promise Difficulty in Purchase Difficulty in Self-Serve Grand Total anonymised Non-FCR Churn & Advocacy Customer Effort Resolution
  10. 10. Easy, rapid impact KPI1 Initial ‘Booster Pack’ Phase II CX Improvements Phase III CX Improvements PrediCX software live • 4 weeks • Pick initial KPI(s) • Quick wins/high impact KPI2 Improvements: CSat 18%, AHT 8% … AHT 35%
  11. 11. Thank You! How did we do?

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