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

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 ...

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 http://www.tcelab.com

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

    • How may we help? info@tcelab.com Spring 2013 Improving the Customer Experience Using Big Data, Customer-Centric Measurement and Analytics Bob E. Hayes, PhD
    • 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: http://bit.ly/tcebook
    • Copyright 2013 TCELab Customer Experience, Customer Experience Management and Customer Loyalty
    • Customer Experience Management (CEM) The process of understanding and managing your customers’ interactions with and perceptions of your brand / company Copyright 2013 TCELab
    • Copyright 2013 TCELab Optimal Customer Relationship Survey
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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 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 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
    • • 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
    • 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
    • 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 company’s ranking against the competition will improve purchasing loyalty and share of wallet
    • 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.
    • 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?
    • 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?
    • Copyright 2013 TCELab Big Data, Analytics and Integration
    • 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
    • Big Data Landscape – bigdatalandscape.com Copyright 2013 TCELab
    • 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
    • Value from Analytics: MIT / IBM 2010 Study Top-performing organizations use analytics five times more than lower performers Copyright 2013 TCELab http://sloanreview.mit.edu/the-magazine/2011- 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
    • 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.
    • 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 business areas Operational Partner Feedback 1.Partner Loyalty 2.Satisfaction with partnering relationship Customer Feedback Employee Feedback Financial Copyright 2013 TCELab
    • Data Integration is Key to Extracting Value Copyright 2013 TCELab
    • Linkage Analysis Operational Metrics Transactional Satisfaction Relationship Satisfaction/ Loyalty Financial Business Metrics Constituency Satisfaction/ Loyalty Copyright 2013 TCELab
    • Customer Feedback Data Sources Relationship Survey (satisfaction/loyalty to company) Transactional Survey (satisfaction with specific transaction/interaction) Social Media/ Communities (sentiment / shares / likes) BusinessDataSources Financial (revenue, number of sales) • Link data at customer level • Quality of the relationship (sat, loyalty) impacts financial metrics N/A • Link data at customer level • Quality of relationship (sentiment / likes / shares) impacts financial metrics Operational (call handling, response time) N/A • Link data at transaction level • Operational metrics impact quality of the transaction • Link data at transaction level • Operational metrics impact sentiment / likes/ shares Constituency (employee / partner feedback) • Link data at constituency level • Constituency satisfaction impacts customer satisfaction with overall relationship • Link data at constituency level • Constituency satisfaction impacts customer satisfaction with interaction • Link data at constituency level • Constituency satisfaction impacts customer sentiment / likes / shares Integrating your Business Data Copyright 2013 TCELab
    • Customer Feedback / Financial Linkage Customer (Account) 1 Customer (Account) 2 Customer (Account) 3 Customer (Account) 4 Customer (Account) n Customer Feedback for a specific customer (account) Financial Metric for a specific customer (account) x1 x3 x2 xn x4 y1 y3 y2 yn y4 yn represents the financial metric for customer n. xn represents customer feedback for customer n. . . . . . . . . . Copyright 2013 TCELab
    • Determine ROI of Increasing Customer Loyalty Disloyal (0-5) Loyal ( 6-8) Very Loyal (9-10) PercentPurchasing AdditionalSoftware Customer Loyalty 55% increase Copyright 2013 TCELab
    • Operational / Customer Feedback Linkage Customer 1 Interaction Customer 2 Interaction Customer 3 Interaction Customer 4 Interaction Customer n Interaction Operational Metric for a specific customer’s interaction Customer Feedback for a specific customer’s interaction x1 x3 x2 xn x4 y1 y3 y2 yn y4 yn represents the customer feedback for customer interaction n. xn represents the operational metric for customer interaction n. . . . . . . . . . Copyright 2013 TCELab
    • Identify Operational Drivers of Satisfaction Copyright 2013 TCELab
    • Identify Operational Standards 1 call 2-3 calls 4-5 calls 6-7 calls 8 or more calls SatwithSR Number of Calls to Resolve SR 1 change 2 changes 3 changes 4 changes 5+ changes SatwithSR Number of SR Ownership Changes Copyright 2013 TCELab
    • 3 Implications of Big Data in CEM 1. Ask/Answer bigger questions 2. Build company around the customer 3. Predict real customer loyalty behaviors Copyright 2012 TCELab
    • bob@tcelab.com @bobehayes businessoverbroadway.com/blog How may we help? info@tcelab.com Spring 2013 Improving the Customer Experience Using Big Data, Customer-Centric Measurement and Analytics Bob E. Hayes, PhD For more info on book: http://bit.ly/tcebook
    • RAPID Loyalty Measurement Index Definition Survey Questions Retention Loyalty Index (RLI) The degree to which customers will remain as a customer/not leave to competitor (0 – low loyalty to 10 – high loyalty) Likelihood to switch to another company* Likelihood to purchase from competitor* Likelihood to stop purchasing* Advocacy Loyalty Index (ALI) The degree to which customers feel positively toward/will advocate your product/service/brand (0 – low loyalty to 10 – high loyalty) Overall satisfaction Likelihood to choose again for first time Likelihood to recommend (NPS) Likelihood to purchase same product/service Purchasing Loyalty Index (PLI) The degree to which customers will increase their purchasing behavior (0 – low loyalty to 10 – high loyalty) Likelihood to purchase different products/services Likelihood to expand usage throughout company Likelihood to upgrade 1 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 loyalty Copyright 2013 TCELab
    • Financial Metrics / Real Loyalty Behaviors • Linkage analysis helps us determine if our customer feedback metrics predict real and measurable business outcomes • Retention – Customer tenure – Customer defection rate – Service contract renewal • Advocacy – Number of new customers – Revenue • Purchasing • Number of products purchased • Number of sales transactions • Frequency of purchases Relationship Satisfaction/ Loyalty Financial Business Metrics Copyright 2013 TCELab
    • Operational Metrics • Linkage analysis helps us determine/identify the operational factors that influence customer satisfaction/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 TCELab Operational Metrics Transactional Satisfaction