Make Money with Big Data (TCELab)


Published on

Make money with big data by organizing your company around your customers. I presented this deck at the Cybera Big Data #cybersummit 2012 in Banff, Canada. In it, I talk about customer loyalty, how to use driver and linkage analysis to sort out both what's important to your customers and what will drive sustainable revenue for your business. Case studies include a SaaS software company, and U.S. Hospital patient experience data based on HCAHPS patient surveys from 4,610 health care facilities nationwide.

For More, please visit

Published in: Business, Technology
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Make Money with Big Data (TCELab)

  1. 1. MAKING MONEY WITH BIG DATA Stephen King CEO, President, @tcelab @stephdokin © 2012 TCELab LLC. All rights reserved. Unauthorized duplication or distribution is prohibited.
  2. 2. TCE Lab Some context: I am not THAT Stephen King 2 StephdokinSTRATEGIC EXECUTIVE CONSULTING Driven over $500M in revenue and participated in over 50 product and program launches / lifecycles; a combination of strategic leadership, branding/marketing, deep technical background, product and customer experience management (CEM). Then: Now: “Customer-centric, Data driven Leadership”
  3. 3. TCE Lab Disparate business data sources 1. Call  handling  ,me   2. Number  of  calls  un,l   resolu,on   3. Response  ,me   4. Sources:  phone,     email,  social   1. Revenue   2. Number  of  products   purchased   3. Customer  tenure   4. Service  contract   renewal   5. Number  of  sales   transac,ons   6. Frequency  of   purchases   1. Customer  Loyalty   2. Rela,onship   Sa,sfac,on   3. Transac,on  Sat.   4. Sen,ment   1. Employee  Loyalty   2. Sa,sfac,on  with     business  areas   Operational Partner Feedback 1. Partner  Loyalty   2. Sa,sfac,on  with   partnering     rela,onship   Customer Feedback Employee Feedback Financial 4 1. Frequency  of  use   2. Dura,on  of  use   3. Frequented  areas   4. Crash  &  bug  reports   5. Region   6. Customer  type   7. Customer  profile;   Demographics  like   gender,  age   8. SaaS  ,ers   Product Quality, Software Use, Adoption
  4. 4. … but … most big data are garbage
  5. 5. TCE Lab … so … be careful 6 “Big data doesn't inherently lead to better results … too many organizations don't quite grasp that being ‘big data-driven’ requires more qualified human judgment than cloud-enabled machine learning.”
  6. 6. Make money by organizing big data around the customer Research & Audit Surveys, Measurement & Driver Analysis Linkage Analysis & Predictive Analytics
  7. 7. RAPID LOYALTY Three dimensions of Customer Loyalty based on the three ways companies make money Business Programs Marketing Sales Service Customer Development (cross/up-sell) Firm Value Customer Lifetime Value Customer Acquisition Customer Retention Business Programs Marketing Sales Service 2. New Customers (Acquire through Advocacy Loyalty) Firm Value Customer Lifetime Value 1. Customer Renews (Retention Loyalty) 3. Customer Buys More (cross/up-sell through Purchasing loyalty) Product development Infrastructure © 2012 @TCELab Based on Dr. Bob Hayes, Ph.D. research, science and published books, articles and speaking. “Dr. Bob” is the Chief Customer Officer at @bobehayes
  8. 8. TCE Lab We combine Big Data and Voice of Customer “VOC” metrics and apply predictive analytics to identify correlates of customer loyalty and sustained revenue growth. Create brand fans. Optimize your ROI.
  9. 9. TCE Lab Financials Voice of Employee Voice of Partner Voice of Customer Product Quality Operational Metrics TCELab Customer Experience Management Roadmap 10 Sophistication of Business Intelligence CompetitiveAdvantage -  Establish VOC practices -  Establish satisfaction / loyalty measurement; typically either NPS or RAPID -  Create “Single Source of Truth” data set -  Establish Big Data technical architecture -  Customer KPI’s -  Recognize trends -  Root cause and driver analysis -  Proactive vs. Reactive (Trend Analysis) -  Customer Impact Analysis -  Risk Awareness -  New revenue growth -  Churn reduction -  Increased ARPU -  Closed loop client feedback -  Social and verbatim sentiment analysis -  Business Intelligence Dashboards -  Customer centric customer and employee goals
  10. 10. DRIVER ANALYSIS CASE STUDY SaaS #1 iPad Accounting App & Cloud Software Company CRD: Customer Relationship Diagnostic
  11. 11. Case study •  SaaS Software Company
  12. 12. TCE Lab “CRD Customer Survey” Driver Matrix 13 Impact LowHigh Key Drivers INVEST in these areas. FIX and IMPROVE these product attributes. Improvement in these areas are predicted to attract new customers (advocacy), increase purchasing behavior (purchasing) or retain customers (retention) Hidden Drivers LEVERAGE as strengths in order to keep current customers loyal ADVERTISE as strengths in marketing collateral and sales presentations in order to attract new customers (advocacy), increase purchasing behavior (purchasing) or retain customers (retention) Weak Drivers DISREGARD as lowest priority for investment. These areas have relatively low impact on improving customer loyalty Visible Drivers CONSIDER as strengths in marketing collateral and sales presentations in order to attract new customers EVALUATE as areas of potential over-investment Low High Performance Driver Matrix helps us prioritize investments 1.  Key Drivers – Fix and improve these product attributes. 2.  Hidden Drivers – Focus on these features in marketing to grow customer base. 3.  Visible Drivers – Consider features in marketing to grow customer base. 4.  Weak Drivers – Disregard as priority for investment.
  13. 13. TCE Lab Driver Chart: Predicting Retention Loyalty 14   Predic,ng  Reten,on  Loyalty   0.00 0.05 0.10 0.15 0.20 0.25 0.30 6.00 6.50 7.00 7.50 8.00 ImpactonRetentionLoyalty (correlationbetweenbusinessattributes andRetentionLoyaltyIndex) Performance on Business Attribute (Customer Rating) To improve retention loyalty, you may consider focusing on following areas: 1.  Reports 2.  Future Product / Company Direction 3.  Banking / Bank Reconciliation •  Different drivers for Advocacy and Purchasing Loyalty •  Different analysis for “Paid vs. Trial,” “Active, non-active, dormant” & “iPad, iPhone, Android, Web”, type of customer / business
  14. 14. LINKAGE ANALYSIS CASE STUDY Hospitals PXM: Patient Experience Management
  15. 15. TCE Lab What is Linkage Analysis? •  Linkage analysis between customer loyalty and disparate data sets answers the questions: –  Which operational metrics have the biggest impact on customer satisfaction/loyalty? –  Which employee/partner factors have the biggest impact on customer satisfaction/loyalty? –  Does medical spending improve patient experience? •  And, ultimately, “predictive analytics”: –  What is the $ revenue value of improving customer satisfaction/loyalty? Opera,onal   Metrics   Transac,onal   Sa,sfac,on   Rela,onship   Sa,sfac,on/   Loyalty   Financial   Business   Metrics   Cons,tuency   Sa,sfac,on/   Loyalty   16 Product,   internet  and   intranet   usage  
  16. 16. TCE Lab HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) 17 Areas with the highest Medicare spending per patient •  Patience Experience Ratings for each hospital in the U.S. from surveys over the last few years •  Starting in 2013, the higher the rating, the more Medicare $ they will receive. •  Green = Best Patience Experience Yellow = Average Patience Experience Red = Bad Patience Experience Blue = No data Interactive map available at •  U.S. CTO released 6 big data sets of 2.8M surveys from 4,610 hospitals that Dr. Bob analyzed over summer, 2012 •  Our free report can be found at hcahps.
  17. 17. TCE Lab Linkage Analysis 18 A Good Patient Experience Does Not Start With Medicare Spending More insights at: •  Valley General Hospital in Monroe, Washington has average patient satisfaction •  But, the hospital has one of the highest per patience spend of Medicare in WA •  From public financial statements, hospital lost $950K in 2010 on $47M gross revenue. •  If medical spending is not related to patient satisfaction … what is? •  Linkage analysis correlates the hospital’s customer satisfaction with operational, financial, employee, etc… big data sets to understand its unique challenges •  Outcomes: •  Focus time and $$$ on the things that matter most to patience experience •  Optimize Medicare spend per patient •  Make patient experience better •  Increase total Medicare reimbursement $$$
  18. 18. TCE Lab TCELab Products and Services 19 Research & Audit Surveys, Measurement & Driver Analysis Linkage Analysis & Predictive Analytics CEM Audit CEM Audit offers a thorough review and evaluation of your VOC program, including big data sources and organization as well survey data available and required, The CEM Audit provides a snapshot of “starting Point A,” what “Point B” could look like, and recommendations on how to get from Point A to Point B. PXM Audit For hospitals and health care facilities that participate in HCAHPS surveys, PXM Audit helps you understand the raw data produced from HCAHPS, and evaluate the current Voice of Patient program at the hospital; from both a Big Data perspective as well as Patient Experience. It will help you understand which dimensions of the patient experience have the biggest impact on HCAHPS rankings, giving your health care facility focus on the most important things that drive PX loyalty and optimize Medicare spend. CRD Customer Relationship Diagnostic is a survey providing deep insight into key areas of customer relationship: 1) Customer Loyalty (RAPID), 2) Customer Experience. 3) Driver Chart on how to best improve loyalty, 4) Competitive Benchmarking (C-PeRK). Loyalty Widget Loyalty Widget is a transactional survey; i.e. small ongoing web or mobile surveys that customers complete after an interaction with your company (purchase, service call, retail shopping experience, etc…); it provides a steady stream of VOC data used for measurement and trend analysis. QR Code for geo-location mobile surveys available. EUD End User Diagnostic survey is used to understand how the end user experience impacts their acceptance and adoption of product/software. The end user is not always the buying “customer.” PRD Partner Relationship Diagnostic survey dives into partner loyalty to optimize relationships with vendors who work with you; suppliers, sales & distribution channels. ERD Employee Relationship Diagnostic survey evaluates the employee experience to ensure you provide the right environment, tools and resources for your employees; great employees do great things for customers. PXD For hospitals that don’t participate in HCAHPS, Patient Experience Diagnostic is a great alternative to create your Voice of Patience surveys to optimize / organize patient data for key driver analysis. CEM Linkage CEM Linkage helps you build your company around your customer. Following Big Data principles, we collect, integrate and analyze disparate data sources like customer feedback, operational metrics and financial metrics. We use predictive analytics to help you improve the customer experience.
  19. 19. @tcelab @stephdokin Thanks! Questions? Thoughts?