Improving the customer experience using big data customer-centric measurement and analytics

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This presentation provides an overview of some of the content of my new book, TCE: Total Customer Experience. In the presentation, I discuss customer experience management, customer loyalty, the optimal customer survey, the value of analytics and using a Big Data customer-centric approach to improve the value of all your business data. For More, please visit


  • 1. How may we help? Spring 2013 Improving the Customer Experience Using Big Data, Customer-Centric Measurement and Analytics Bob E. Hayes, PhD

2. TCE: Total Customer Experience Copyright 2013 TCELab 1. Customer Experience Management 2. Customer Loyalty 3. Optimal Customer Survey 4. Value of Analytics 5. Big Data Customer- Centric Approach For more info on book: 3. Copyright 2013 TCELab Customer Experience, Customer Experience Management and Customer Loyalty 4. Customer Experience Management (CEM) The process of understanding and managing your customers interactions with and perceptions of your brand / company Copyright 2013 TCELab 5. Copyright 2013 TCELab Optimal Customer Relationship Survey 6. Customer Relationship Surveys Copyright 2013 TCELab Solicited feedback from customers about their experience with company/brand Assess health of the customer relationship Conducted periodically (non-trivial time period) Common in CEM Programs Guide company strategy Identify causes of customer loyalty Improve customer experience Prioritize improvement efforts to maximize ROI 7. Four Parts to Customer Surveys Copyright 2013 TCELab 1. Customer Loyalty likelihood of customers engaging in positive behaviors 2. Customer Experience satisfaction with important touch points 3. Relative Performance your competitive advantage 4. Additional Questions Extra value- added questions 8. Customer Loyalty Types The degree to which customers experience positive feelings for and engage in positive behaviors toward a company/brand Emotional (Advocacy) Behavioral (Retention, Purchasing) Love, Consider, Forgive, Trust Stay, Renew, Buy, Buy more often, Expand usage Copyright 2013 TCELab 9. Customer Loyalty Measurement Framework Loyalty Types Emotional Behavioral MeasurementApproach Objective ADVOCACY Number/Percent of new customers RETENTION Churn rates Service contract renewal rates PURCHASING Usage Metrics Frequency of use/ visit, Page views Sales Records - Number of products purchased Subjective (SurveyQuestions) ADVOCACY Overall satisfaction Likelihood to recommend Likelihood to buy same product Level of trust Willing to forgive Willing to consider RETENTION Likelihood to renew service contract Likelihood to leave PURCHASING Likelihood to buy different/ additional products Likelihood to expand usage 1 Using RAPID Loyalty Approach - Overall satisfaction rated on a scale from 0 (Extremely Dissatisfied) to 10 (Extremely Satisfied). Other questions are rated on a scale from 0 (Not at all likely) to 10 (Extremely likely). * Reverse coded so lower rates of these behaviors indicates higher levels of Retention Loyalty. Copyright 2013 TCELab 10. Customer Experience Copyright 2013 TCELab Two types of customer experience questions Overall, how satisfied are you with Area General CX Questions Specific CX Questions Product 1. Product Quality 1. Reliability of product 2. Features of product 3. Ease of using the product 4. Availability of product Account Management 2. Sales / Account Management 1. Knowledge of your industry 2. Ability to coordinate resources 3. Understanding of your business issues 4. Responds quickly to my needs Technical Support 3. Technical Support 1. Timeliness of solution provided 2. Knowledge and skills of personnel 3. Effectiveness of solution provided 4. Online tools and services 0 1051 2 3 4 6 7 8 9 Extremely Dissatisfied Extremely Satisfied Neither Satisfied Nor Dissatisfied 11. Customer Experience Copyright 2013 TCELab Overall, how satisfied are you with each area? 1. Ease of doing business 2. Sales / Account Management 3. Product Quality 4. Service Quality 5. Technical Support 6. Communications from the Company 7. Future Product/Company Direction 0 1051 2 3 4 6 7 8 9 Extremely Dissatisfied Extremely Satisfied Neither Satisfied Nor Dissatisfied 12. CX Predicting Customer Loyalty Copyright 2013 TCELab 74% 42% 60% 85% 0% 4% 2% 4% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Company A Company B Company C Company D PercentofVariability(R2)inCustomer LoyaltyExplainedbyCXQuestions Specific CX Questions General CX Questions General CX items reflected areas (e.g., product quality, ease of doing business, tech support) and additional specific CX items reflected specific aspects of the general items (product reliability, tech support knowledge, account managements ability to respond quickly). R2 reflects percent of variance of customer loyalty that is explained when using general items in regression analysis . R2 reflects the additional percent of variance explained above what is explained by general items when using general items and specific items in a stepwise regression analysis. 1. General CX questions explain customer loyalty differences well. 2. Specific CX questions do not add much to our prediction of customer loyalty differences. 3. On average, each Specific CX question explains < .5% of variability in customer loyalty.7 General CX 5 General CX 6 General CX 7 General CX 0 Specific CX 14 Specific CX 27 Specific CX 34 Specific CX 13. Customer experience questions may not be enough to improve business growth You need to understand your relative performance HBR study (2011)1: Top-ranked companies receive greater share of wallet compared to bottom-ranked companies Focus on increasing purchasing loyalty (e.g., customers buy more from you) Competitive Analytics Copyright 2013 TCELab 14. Relative Performance Assessment (RPA) Ask customers to rank you relative to the competitors in their usage set What best describes our performance compared to the competitors you use? Copyright 2013 TCELab 15. RPA Predicting Customer Loyalty Copyright 2013 TCELab 69% 72% 18% 16% 14% 1% 2% 8% 7% 1% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Overall Satisfaction Recommend Purchase different/new solutions Expand usage Renew Subscription PercentofVariability(R2)inCustomer LoyaltyExplainedbyGeneralCXQuestionsand RelativePerformanceAssessment(RPA) Loyalty Questions 1 RPA Question 7 General CX Questions What best describes our performance compared to the competitors you use? 1. General CX questions explain purchasing loyalty differences well. 2. Relative Performance Assessment improved the predictability of purchasing loyalty by almost 50% 3. Improving companys ranking against the competition will improve purchasing loyalty and share of wallet 16. Understanding your Ranking Copyright 2013 TCELab 1. Correlate RPA score with customer experience measures 2. Analyze customer comments about the reasons behind their ranking Why did you think we are better/worse than the competition? Which competitors are better than us and why? What to improve? Product Quality was top driver of Relative Performance Assessment Open-ended comments by customers who gave low RPA rankings were primarily focused on making the product easier to use while adding more customizability. 17. Additional Questions Copyright 2013 TCELab Out of necessity or driven by specific business need Segmentation Questions How long have you been a customer? What is your role in purchasing decisions? What is your job level? Specific topics of interest to senior management Perceived benefits of solution (What is the % improvement in efficiency / productivity / customer satisfaction) Perceived value (How satisfied are you with the value received?) Open-ended questions for improvement areas If you were in charge of our company, what improvements, if any, would you make? 18. Summary: Your Relationship Survey Copyright 2013 TCELab 1. Measure different types of customer loyalty (N = 4-6) 2. Consider the number of customer experience questions in your survey (N = 7) General CX questions point you in the right direction. 3. Measure your relative performance (N = 3) Understand and Improve/Maintain your competitive advantage 4. Consider additional questions (N = 5) How will you use the data? 19. Copyright 2013 TCELab Big Data, Analytics and Integration 20. Big Data Big Data refers to the tools and processes of managing and utilizing large datasets. An amalgamation of different areas that help us try to get a handle on, insight from and use out of large, quickly-expanding, diverse data Copyright 2013 TCELab 21. Big Data Landscape Copyright 2013 TCELab 22. Three Big Data Approaches 1. Interactive Exploration - good for discovering real-time patterns from your data as they emerge 2. Direct Batch Reporting - good for summarizing data into pre-built, scheduled (e.g., daily, weekly) reports 3. Batch ETL (extract-transform-load) - good for analyzing historical trends or linking disparate data Copyright 2012 TCELab 23. Value from Analytics: MIT / IBM 2010 Study Top-performing organizations use analytics five times more than lower performers Copyright 2013 TCELab winter/52205/big-data-analytics-and-the-path-from- insights-to-value/ Number one obstacle to the adoption of analytics in their organizations was a lack of understanding of how to use analytics to improve the business 24. Value from Analytics: Accenture 2012 Study Copyright 2013 TCELab 1. Measure Right Customer Metrics - only 20% were very satisfied with the business outcomes of their existing analytics programs 2. Focus on Strategic Issues - only 39% said that the data they generate is "relevant to the business strategy" 3. Integrate Business Metrics - Half of the executives indicated that data integration remains a key challenge to them. 25. Disparate Sources of Business Data 1.Call handling time 2.Number of calls until resolution 3.Response time 1.Revenue 2.Number of products purchased 3.Customer tenure 4.Service contract renewal 5.Number of sales transactions 6.Frequency of purchases 1.Customer Loyalty 2.Relationship satisfaction 3.Transaction satisfaction 4.Sentiment 1.Employee Loyalty 2.Satisfaction with