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

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

  1. 1. How may we help?info@tcelab.comSpring 2013Improving the Customer ExperienceUsing Big Data, Customer-CentricMeasurement and AnalyticsBob E. Hayes, PhD
  2. 2. TCE: Total Customer ExperienceCopyright 2013 TCELab1. Customer ExperienceManagement2. Customer Loyalty3. Optimal CustomerSurvey4. Value of Analytics5. Big Data Customer-Centric ApproachFor more info on book:
  3. 3. Copyright 2013 TCELabCustomer Experience,Customer Experience Managementand Customer Loyalty
  4. 4. Customer Experience Management (CEM)The process ofunderstanding andmanaging yourcustomers’interactions withand perceptionsof your brand /companyCopyright 2013 TCELab
  5. 5. Copyright 2013 TCELabOptimal CustomerRelationship Survey
  6. 6. Customer Relationship SurveysCopyright 2013 TCELab• Solicited feedback from customers about theirexperience 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. 7. Four Parts to Customer SurveysCopyright 2013 TCELab1. Customer Loyalty – likelihood ofcustomers engaging in positive behaviors2. Customer Experience – satisfaction withimportant touch points3. Relative Performance – your competitiveadvantage4. Additional Questions – Extra value-added questions
  8. 8. Customer Loyalty TypesThe degree to which customersexperience positive feelings forand engage in positive behaviorstoward a company/brandEmotional(Advocacy)Behavioral(Retention, Purchasing)Love, Consider,Forgive, TrustStay, Renew, Buy,Buy more often,Expand usageCopyright 2013 TCELab
  9. 9. Customer Loyalty Measurement FrameworkLoyalty TypesEmotional BehavioralMeasurementApproachObjectiveADVOCACY• Number/Percent of newcustomersRETENTION• Churn rates• Service contract renewal ratesPURCHASING• Usage Metrics – Frequency ofuse/ visit, Page views• Sales Records - Number ofproducts purchasedSubjective(SurveyQuestions)ADVOCACY• Overall satisfaction• Likelihood to recommend• Likelihood to buy same product• Level of trust• Willing to forgive• Willing to considerRETENTION• Likelihood to renew service contract• Likelihood to leavePURCHASING• Likelihood to buy different/additional products• Likelihood to expand usage1 Using RAPID Loyalty Approach - Overall satisfaction rated on a scale from 0 (Extremely Dissatisfied) to 10 (Extremely Satisfied). Other questions arerated 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 RetentionLoyalty. Copyright 2013 TCELab
  10. 10. Customer ExperienceCopyright 2013 TCELab• Two types of customer experience questions• Overall, how satisfiedare you with…Area General CX Questions Specific CX QuestionsProduct 1. Product Quality1. Reliability of product2. Features of product3. Ease of using the product4. Availability of productAccountManagement2. Sales / AccountManagement1. Knowledge of your industry2. Ability to coordinate resources3. Understanding of your business issues4. Responds quickly to my needsTechnicalSupport3. Technical Support1. Timeliness of solution provided2. Knowledge and skills of personnel3. Effectiveness of solution provided4. Online tools and services0 1051 2 3 4 6 7 8 9ExtremelyDissatisfiedExtremelySatisfiedNeither SatisfiedNor Dissatisfied
  11. 11. Customer ExperienceCopyright 2013 TCELab• Overall, how satisfied are you with each area?1. Ease of doing business2. Sales / Account Management3. Product Quality4. Service Quality5. Technical Support6. Communications from the Company7. Future Product/Company Direction0 1051 2 3 4 6 7 8 9ExtremelyDissatisfiedExtremelySatisfiedNeither SatisfiedNor Dissatisfied
  12. 12. CX Predicting Customer LoyaltyCopyright 2013 TCELab74%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 DPercentofVariability(R2)inCustomerLoyaltyExplainedbyCXQuestionsSpecific CX QuestionsGeneral CX QuestionsGeneral CX items reflected areas (e.g., product quality, ease of doing business, tech support) and additional specific CX items reflected specificaspects of the general items (product reliability, tech support knowledge, account management’s 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 additionalpercent of variance explained above what is explained by general items when using general items and specific items in a stepwise regression analysis.1. General CXquestions explaincustomer loyaltydifferences well.2. Specific CXquestions do not addmuch to ourprediction of customerloyalty differences.3. On average, eachSpecific CX questionexplains < .5% ofvariability in customerloyalty.7 General CX 5 General CX 6 General CX 7 General CX0 Specific CX 14 Specific CX 27 Specific CX 34 Specific CX
  13. 13. • Customer experience questions may not beenough to improve business growth– You need to understand your relative performance• HBR study (2011)1: Top-ranked companiesreceive greater share of wallet compared tobottom-ranked companies• Focus on increasing purchasing loyalty (e.g.,customers buy more from you)Competitive AnalyticsCopyright 2013 TCELab
  14. 14. Relative Performance Assessment (RPA)• Ask customers to rank you relative to the competitorsin their usage set• What best describes our performance compared tothe competitors you use?Copyright 2013 TCELab
  15. 15. RPA Predicting Customer LoyaltyCopyright 2013 TCELab69% 72%18% 16% 14%1%2%8% 7%1%0%10%20%30%40%50%60%70%80%90%100%OverallSatisfactionRecommend Purchasedifferent/newsolutionsExpand usage RenewSubscriptionPercentofVariability(R2)inCustomerLoyaltyExplainedbyGeneralCXQuestionsandRelativePerformanceAssessment(RPA)Loyalty Questions1 RPA Question7 General CX Questions What best describes our performance compared tothe competitors you use?1. General CX questionsexplain purchasingloyalty differences well.2. Relative PerformanceAssessment improvedthe predictability ofpurchasing loyalty byalmost 50%3. Improving company’sranking against thecompetition willimprove purchasingloyalty and share ofwallet
  16. 16. Understanding your RankingCopyright 2013 TCELab1. Correlate RPA score with customer experiencemeasures2. Analyze customer comments about the reasonsbehind their ranking– Why did you think we are better/worse than thecompetition?– Which competitors are better than us and why?• What to improve?– Product Quality was top driver of Relative PerformanceAssessment– Open-ended comments by customers who gave low RPArankings were primarily focused on making the producteasier to use while adding more customizability.
  17. 17. Additional QuestionsCopyright 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 % improvementin efficiency / productivity / customer satisfaction)– Perceived value (How satisfied are you with the valuereceived?)• Open-ended questions for improvement areas– If you were in charge of our company, what improvements,if any, would you make?
  18. 18. Summary: Your Relationship SurveyCopyright 2013 TCELab1. Measure different types of customer loyalty(N = 4-6)2. Consider the number of customer experiencequestions 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 advantage4. Consider additional questions (N = 5)– How will you use the data?
  19. 19. Copyright 2013 TCELabBig Data, Analytics and Integration
  20. 20. Big Data• Big Data refers to the tools andprocesses of managing and utilizinglarge datasets.• An amalgamation of different areas thathelp us try to get a handle on, insight fromand use out of large, quickly-expanding,diverse dataCopyright 2013 TCELab
  21. 21. Big Data Landscape – bigdatalandscape.comCopyright 2013 TCELab
  22. 22. Three Big Data Approaches1. Interactive Exploration - goodfor discovering real-time patterns from yourdata as they emerge2. Direct Batch Reporting - goodfor summarizing data into pre-built,scheduled (e.g., daily, weekly) reports3. Batch ETL (extract-transform-load) -good for analyzing historical trends orlinking disparate dataCopyright 2012 TCELab
  23. 23. Value from Analytics: MIT / IBM 2010 StudyTop-performingorganizationsuse analytics fivetimes more thanlower performersCopyright 2013 TCELab one obstacle tothe adoption of analyticsin their organizations wasa lack of understandingof how to use analytics toimprove the business
  24. 24. Value from Analytics: Accenture 2012 StudyCopyright 2013 TCELab1. Measure Right Customer Metrics - only20% were very satisfied with the businessoutcomes of their existing analyticsprograms2. Focus on Strategic Issues - only 39%said that the data they generate is"relevant to the business strategy"3. Integrate Business Metrics - Half of theexecutives indicated that data integrationremains a key challenge to them.
  25. 25. Disparate Sources of Business Data1.Call handling time2.Number of calls untilresolution3.Response time1.Revenue2.Number of productspurchased3.Customer tenure4.Service contractrenewal5.Number of salestransactions6.Frequency ofpurchases1.Customer Loyalty2.Relationship satisfaction3.Transaction satisfaction4.Sentiment1.Employee Loyalty2.Satisfaction withbusiness areasOperationalPartner Feedback1.Partner Loyalty2.Satisfaction withpartnering relationshipCustomerFeedbackEmployeeFeedbackFinancialCopyright 2013 TCELab
  26. 26. Data Integration is Key to Extracting ValueCopyright 2013 TCELab
  27. 27. Linkage AnalysisOperationalMetricsTransactionalSatisfactionRelationshipSatisfaction/LoyaltyFinancialBusinessMetricsConstituencySatisfaction/LoyaltyCopyright 2013 TCELab
  28. 28. Customer Feedback Data SourcesRelationshipSurvey(satisfaction/loyalty tocompany)TransactionalSurvey(satisfaction with specifictransaction/interaction)Social Media/Communities(sentiment / shares / likes)BusinessDataSourcesFinancial(revenue, number ofsales)• Link data at customerlevel• Quality of therelationship (sat, loyalty)impacts financial metricsN/A• Link data at customer level• Quality of relationship(sentiment / likes / shares)impacts financial metricsOperational(call handling, responsetime)N/A• Link data at transactionlevel• Operational metrics impactquality of the transaction• Link data at transactionlevel• Operational metrics impactsentiment / likes/ sharesConstituency(employee / partnerfeedback)• Link data at constituencylevel• Constituency satisfactionimpacts customersatisfaction with overallrelationship• Link data at constituencylevel• Constituency satisfactionimpacts customersatisfaction with interaction• Link data at constituencylevel• Constituency satisfactionimpacts customersentiment / likes / sharesIntegrating your Business DataCopyright 2013 TCELab
  29. 29. Customer Feedback / Financial LinkageCustomer(Account) 1Customer(Account) 2Customer(Account) 3Customer(Account) 4Customer(Account) nCustomer Feedbackfor a specificcustomer (account)Financial Metricfor a specificcustomer (account)x1x3x2xnx4y1y3y2yny4yn represents the financial metric for customer n.xn represents customer feedback for customer n..........Copyright 2013 TCELab
  30. 30. Determine ROI of Increasing Customer LoyaltyDisloyal (0-5) Loyal ( 6-8) Very Loyal (9-10)PercentPurchasingAdditionalSoftwareCustomer Loyalty55%increaseCopyright 2013 TCELab
  31. 31. Operational / Customer Feedback LinkageCustomer 1InteractionCustomer 2InteractionCustomer 3InteractionCustomer 4InteractionCustomer nInteractionOperational Metricfor a specificcustomer’s interactionCustomer Feedbackfor a specificcustomer’s interactionx1x3x2xnx4y1y3y2yny4yn represents the customer feedback for customer interaction n.xn represents the operational metric for customer interaction n..........Copyright 2013 TCELab
  32. 32. Identify Operational Drivers of SatisfactionCopyright 2013 TCELab
  33. 33. Identify Operational Standards1 call 2-3 calls 4-5 calls 6-7 calls 8 or more callsSatwithSRNumber of Calls to Resolve SR1 change 2 changes 3 changes 4 changes 5+ changesSatwithSRNumber of SR Ownership ChangesCopyright 2013 TCELab
  34. 34. 3 Implications of Big Data in CEM1. Ask/Answer bigger questions2. Build company around the customer3. Predict real customer loyalty behaviorsCopyright 2012 TCELab
  35. 35. may we help?info@tcelab.comSpring 2013Improving the Customer ExperienceUsing Big Data, Customer-CentricMeasurement and AnalyticsBob E. Hayes, PhDFor more info on book:
  36. 36. RAPID Loyalty MeasurementIndex Definition Survey QuestionsRetentionLoyaltyIndex (RLI)The degree to which customers willremain as a customer/not leave tocompetitor (0 – low loyalty to 10 –high loyalty)Likelihood to switch to another company*Likelihood to purchase from competitor*Likelihood to stop purchasing*AdvocacyLoyaltyIndex (ALI)The degree to which customers feelpositively toward/will advocate yourproduct/service/brand (0 – low loyaltyto 10 – high loyalty)Overall satisfactionLikelihood to choose again for first timeLikelihood to recommend (NPS)Likelihood to purchase same product/servicePurchasingLoyaltyIndex (PLI)The degree to which customers willincrease their purchasing behavior (0 –low loyalty to 10 – high loyalty)Likelihood to purchase different products/servicesLikelihood to expand usage throughout companyLikelihood to upgrade1 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.• Assesses three components of customer loyaltyCopyright 2013 TCELab
  37. 37. Financial Metrics / Real Loyalty Behaviors• Linkage analysis helps us determine if ourcustomer feedback metrics predict real andmeasurable business outcomes• Retention– Customer tenure– Customer defection rate– Service contract renewal• Advocacy– Number of new customers– Revenue• Purchasing• Number of productspurchased• Number of salestransactions• Frequency of purchasesRelationshipSatisfaction/LoyaltyFinancialBusinessMetricsCopyright 2013 TCELab
  38. 38. Operational Metrics• Linkage analysis helps us determine/identify theoperational factors that influence customersatisfaction/loyalty• Support Metrics– First Call Resolution (FCR)– Number of calls until resolution– Call handling time– Response time– Abandon rate– Average talk time– Adherence & Shrinkage– Average speed of answer (ASA)Copyright 2013 TCELabOperationalMetricsTransactionalSatisfaction