make money with big data (tcelab)

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MAKING MONEY WITH BIG DATA Stephen King CEO, TCELab.com President, Stephdokin.com @tcelab @stephdokin © 2012 TCELab LLC. All rights reserved. Unauthorized duplication or distribution is prohibited.

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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 http://www.tcelab.com

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Page 1: Make Money with Big Data (TCELab)

MAKING MONEY WITH BIG DATA Stephen King CEO, TCELab.com President, Stephdokin.com @tcelab @stephdokin

© 2012 TCELab LLC. All rights reserved. Unauthorized duplication or distribution is prohibited.

Page 2: Make Money with Big Data (TCELab)

TCELabSome 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”

Page 3: Make Money with Big Data (TCELab)
Page 4: Make Money with Big Data (TCELab)

TCELabDisparate 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

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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

Page 5: Make Money with Big Data (TCELab)

… but … most big data are garbage

Page 6: Make Money with Big Data (TCELab)

TCELab… so … be careful

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“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.”

http://blogs.hbr.org/schrage/2012/09/what-executives-dont-understan.html

Page 7: Make Money with Big Data (TCELab)

Make money by organizing big data around the customer

Research & Audit

Surveys, Measurement & Driver Analysis

Linkage Analysis & Predictive Analytics

Page 8: Make Money with Big Data (TCELab)

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.com @TCELab

Based on Dr. Bob Hayes, Ph.D. research, science and published books, articles and speaking. “Dr. Bob” is the Chief Customer Officer at TCELab.com @bobehayes www.businessoverbroadway.com

Page 9: Make Money with Big Data (TCELab)

TCELab

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.

Page 10: Make Money with Big Data (TCELab)

TCELab

Financials

Voice of Employee

Voice of Partner

Voice of Customer

Product Quality

Operational Metrics

TCELab Customer Experience Management Roadmap 10

1 11

Sophistication of Business Intelligence

Com

petit

ive

Adv

anta

ge

-  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

Page 11: Make Money with Big Data (TCELab)

DRIVER ANALYSIS CASE STUDY

SaaS #1 iPad Accounting App & Cloud Software Company CRD: Customer Relationship Diagnostic

Page 12: Make Money with Big Data (TCELab)

Case study

•  SaaS Software Company

Page 13: Make Money with Big Data (TCELab)

TCELab“CRD Customer Survey” Driver Matrix

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Imp

act

Low

Hig

h

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.

Page 14: Make Money with Big Data (TCELab)

TCELabDriver Chart: Predicting Retention Loyalty

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 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

Impa

ct o

n R

eten

tion

Loya

lty

(cor

rela

tion

betw

een

busi

ness

attr

ibut

es

and

Ret

entio

n Lo

yalty

Inde

x)

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

Page 15: Make Money with Big Data (TCELab)

LINKAGE ANALYSIS CASE STUDY

Hospitals PXM: Patient Experience Management

Page 16: Make Money with Big Data (TCELab)

TCELabWhat 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  

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Product,  internet  and  intranet  usage  

Page 17: Make Money with Big Data (TCELab)

TCELabHCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems)

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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 http://bit.ly/S5kK1H

•  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 www.tcelab.com/hcahps.

Page 18: Make Money with Big Data (TCELab)

TCELabLinkage Analysis

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A Good Patient Experience Does Not Start With Medicare Spending

More insights at: http://businessoverbroadway.com/big-data-provides-big-insights-for-u-s-hospitals

•  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

$$$

Page 19: Make Money with Big Data (TCELab)

TCELabTCELab Products and Services

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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.

Page 20: Make Money with Big Data (TCELab)

[email protected] [email protected] @tcelab @stephdokin

Thanks! Questions? Thoughts?