Big Data Meets Customer Profitability Analytics
 

Big Data Meets Customer Profitability Analytics

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    Big Data Meets Customer Profitability Analytics Big Data Meets Customer Profitability Analytics Presentation Transcript

    • Big Data MeetsCustomer Profitability AnalyticsJaime Fitzgerald, Founder and President,Fitzgerald AnalyticsApril 17, 2012 Architects of Fact-Based Decisions™
    • Table of Contents Introduction: 1. Big Data… Big Results? 2. Customer Profitability Analysis 3. Implications of Big Data 4. Conclusion and QuestionsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 2
    • Nice to Meet You! Data to Dollars™ specialist. To do this, created a structured methodology and toolkit to accomplish this. Will share at EDW12! • Key Mission is to Find & unlock opportunities via data, technology, people, + processes. Principles: Jaime Fitzgerald @jfitzgerald “Begin with the End in Mind” (Covey) “Quality is Free” (McGregor)Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 3
    • From to Data to Dollars It’s a journey… 1 2 Small Data Big Data Product of Alberta 3 Really Big Data Product of everywhereBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 4
    • My Perspective Towards “Big Data” Skeptical (of the hype)… ….yet Cautiously Optimistic! Big Data Product of AlbertaBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 5
    • Big Data Hype – Does is Cause a Problem? “Data is the New Oil” – World Economic Forum ReportBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 6
    • The Potential is Real…It’s Just Not Easy to GetBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 7
    • And Something Old, Essential, & Profitable “There is only one valid definition of a business purpose: to create a customer.” (The Practice of Management, ‘54).Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 8
    • Table of Contents Introduction 1. Big Data… Big Results? 2. Customer Profitability Analysis 3. Implications of Big Data 4. Conclusion and QuestionsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 9
    • Will Big Data Unlock Big Results? It depends… ...on the principles you work by. Stephen CoveyBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 10
    • The Word’s Most Successful Data Professionals… #B W T E I M! What is Covey was a data professional today? Stephen CoveyBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 11
    • Beginning with the End in Mind 1. Your Goal 2. Insight You Need 3. Analytic Methods 4. Data You Need 5. Tools, Platforms, Technology, People, and ProcessesBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 12
    • “A Journey of a Thousand Miles….” 2 1 Fitzgerald Analytics: Converting Data to Dollars™ Better Data Better Analysis Better Results 3 Worth The Trip!Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 13
    • Key Steps in the Journey to Results 1. Data 2. Analytics 3. Results  Data Governance  Better Decisions Analysis Insight  Data Management  Better Processes  Data Quality  More Customers  New Data Source  Happier Customers AcquisitionBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 14
    • Data Management: Especially Important in the Big Data EraBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 15
    • Table of Contents Introduction 1. Big Data… Big Results? 2. Customer Profitability Analysis 3. Implications of Big Data 4. Conclusion and QuestionsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 16
    • Definition Customer Profitability Analysis is: 1) Measuring the contribution each customer makes to overall profits, and to the key drivers of those profits. In other words, a “customer-level version” of your corporations P&L statement. 2) Analysis that USES these customer-level metrics to improve results (there are a large number of applications)Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 17
    • History of Customer Profitability Analysis: 1. Around since at least the early 1980s. 2. Banks were early adopters 3. Massive results unlocked over the years 4. Some notable mishaps along the way… 5. Still considered “obscure” by many…Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 18
    • The Concept Illustrated Your P&L Deconstructed into a P&L Statement for each of your customersBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 19
    • Customer Profitability Metrics Can Seem Simple… Revenue Direct Profit Expense Expenses + Allocated ExpensesBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 20
    • Yet in a complex organization Example: A “Universal Bank” Sales & Trading Investment Banking Transaction Banking  Equities  Capital Markets (IPO)  Cash Management  Stocks  Mergers & Acquisitions  Trade Finance  Derivatives  Project Financing  Corporate Trust  Program Trading  Structured Financing  Custody  Fixed Income  Corporate Bonds  Municipal Bonds  Derivatives  Interest Rate  Credit Asset Management Private Wealth Mgmt  Commodities  Mutual Funds  Wealth Management  Futures  Separately Managed Consulting  Forwards  Trust Services  Foreign ExchangeBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 21
    • And with the Impact of Mergers Here come the data silos… Equity Single Product Area Trading By Region Americas Europe Asia By Company Bank 1 Bank 2 Bank 1 Bank 2 Bank 1 Bank 2 • One product, if booked into regional systems and sold by both companies, in a merger can feed from 6 separate systems. • At the very least, numbering schemes from the two companies will be different. • At worst, every system will have a unique number or name for a single client.Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 22
    • Data Management = Precondition of Customer AnalyticsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 23
    • Customer Profitability Output: Classic 1st Step Best Customers Losing Money Profit per Customer Mid-Value Loss per Customer Top 2nd 3rd 4th 5th 6th 7th 8th 9th Bottom Average (Most (Least Profitable Profitable 10%) 10%) Profitability Deciles (each bar = 10% of customers, ranked by profitability)Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 24
    • What do Customer Profitability Metrics Enable? A Top 5 List… 1 Customer Segmentation and Lifetime Value (CLV) 2 Customer Retention 3 Cross-sell, Up-sell 4 Marketing Optimization & ROI 5 New Financial Product Design & InnovationBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 25
    • Integration: Connecting The Dots A few examples of how inter-related these processes are… 1 Customer Lifetime Value + Segmentation New Information and Insights 2 3 Cross-Sales / Customer Retention Up-Sales 4 Marketing ROI 5 New Product DesignBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 26
    • Example: Better Pricing of Risk vs. Reward Using CLV metrics to predict profits over the customer lifetime, lenders make better decisions about lending to “riskier” customers $0.10 Lifetime Profit per Dollar of Sales The Riskier Half of The Card Company Customers Generate 6 to 9 Cents per Dollar of Sales…. $0.08 $0.06 …while the “Safer Half” of The Card Company Customers Produce only 1 to 3 Cents per Dollar of Sales…. $0.04 $0.02 $- 1st Quartile 2nd Quartile 3rd Quartile 4th Quartile More Risk Credit Score Band Less RiskBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 27 27
    • “Lifetime Performance Curves”: Finance + Late Fee Income The divergence is even more striking when Late Fees are added to Finance Income. Performance Curves by Credit Quartile: Income from Finance and Late Fees $175.00 Quartile1 1st Quartile $150.00 Quartile2 Accounts generate more Finance Fees + Late Fees Quartile3 $125.00 than 6 times as Quartile4 $100.00 much revenue from these $75.00 sources as accounts from $50.00 the 4th $25.00 Quartile…. $0.00 1 4 7 10 13 16 19 22 25 28 31 Months after 1st PurchaseBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 28 28
    • Challenge: From Descriptive to Prescriptive. I can’t deposit decile charts in the bank either… And my analysts can only think up so many customer segments, A|B Tests, Etc….Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 29
    • Known Pitfall: Not Looking Beyond the Data… … … 1995 2012Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 30
    • Table of Contents Introduction 1. Big Data… Big Results? 2. Customer Profitability Analysis 3. Implications of Big Data 4. Conclusion and QuestionsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 31
    • Defining Big Data: “Three Vs” "Big Data“ is seen as data with: greater volume… greater variety… and/or greater velocity….Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 32
    • Another Way to Define “Big Data” - What are the optimal methods to accomplish your goal? Traditional Methods? Big-Data Methods? or • Centralized data storage • Distributed data storage • Centralized processing/analysis • Distributed processing/analysis • Relational databases (tables) • Non-relational databases • SQL queries to access data • Map-reduce (et al) to access data • Standardized basic analytics • Customized basic analytics • Typical tools: • Typical tools: • MS SQL Server • Hadoop • Oracle • BigTable • Tableau • Riak • Excel pivot tables • Amazon S3Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 33
    • Big Data Approaches and Tools Make Data Analysis  Possible, for very large data sets that cannot be handled at all with typical relational databases.  Faster, for large data sets that can be handled with typical relational databases, but doing so would take a long time. This is the situation in the example above.  Cheaper, for large data sets that can be handled with typical relational databases, but doing so would be very expensive.Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 34
    • Big Data Allows Us To Work with Large Datasets We can analyze datasets larger than ever before For a given desired speed of analysis… Beyond a certain point, conventional methods just aren’t feasible – Google couldn’t run on a relational DB IT Costs For larger datasets, big-data methods make more sense Dataset size For smaller datasets, conventional methods are more cost-effective Traditional Big-data methods methodsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 35
    • Big Data Allows Us To Get Results Faster We can get results faster than ever before For a given dataset size… IT Costs SLOW FAST Analysis speed Conventional Big-data methods methodsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 36
    • Table of Contents Introduction 1. Big Data… Big Results? 2. Customer Profitability Analysis 3. Implications of Big Data 4. Conclusion and QuestionsBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 37
    • Profitability Management Improves through iteration, mainly because new info and insights are gained… Build/Maintain Customer Take Smarter Actions w/ Customers Profitability Models:  Target: Who? • Create consistent message  • Message or action: What? Target action to individuals  Identify costs & revenues • Optimize product / service  Build profiles Data  Offering: Product design portfolio Warehouse  Service: How delivered?  Integrate data from “new” sources (how experienced by customer?) External New Customer Knowledge Data  Results of our actions Sources  Assess accuracy of our predictive models  Refine segmentation schema  Define new goals, questions, data “wish lists” (big data? Or small…)Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 38
    • Impact of Speed… Type of data and Our understanding technology tools: Of customers: Daily / weekly / Small Data monthly (+ related tech) Big Data Instantly (+ related techBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 39
    • …as well as “resolution” All his His son’s friends have favorite Chase color is blue Instantly Father just started at Big Data Instantly Bank of America (+ related tech Instantly Instantly Helping us Take Smarter Actions w/ Customers  Target: Is he one?  Message or action: What?  Offering: Product design  Service: How delivered? (how experienced by customer?)Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 40
    • So how does Big Data + Related Tools Help With… 1 Customer Segmentation and Lifetime Value (CLV) 2 Customer Retention 3 Cross-sell, Up-sell 4 Marketing Optimization & ROI 5 New Financial Product Design & InnovationBig Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 41
    • Q&A …Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 42