Profiting from customer profitability + big data fitzgerald analytics

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Measuring and managing customer profitability in the big-data era. How to capitalize on the opportunity. …

Measuring and managing customer profitability in the big-data era. How to capitalize on the opportunity.

In today's era of Big Data and related technology, the benefits of "customer-centricity" are within our reach. Analysis of Big Data sources helps to better understand customer needs, preferences, attitudes, expectations, sentiments, and buying behavior. Yet to achieve this potential, organizations need to understand and apply the classic but essential concepts of customer profitability, customer lifetime value (CLV), and customer value management analytics. Join us for an event on how to approach this challenge.


When linked with customer profitability metrics, these insights enable more profitable decisions in product design, sales, marketing, customer care, loyalty management, and risk management. This session will help attendees capitalize on this opportunity. We will cover the classic high-impact basics of measuring and managing customer profitability, customer lifetime value (CLV), as well as how to use new Big Data insights to get more value from these efforts. This tutorial which cover the topic in 5 practical steps:

1. Introduction to Customer Profitability Analytics: What is customer profitability analysis, why is it so valuable, and what are the key concepts and methodologies used to measure customer profitability, customer lifetime value (CLV), and related metrics?

2. High-Impact Use-Cases of Customer Profitability Analytics: What are the key ways customer profitability analytics is used enhance results? We will describe the highest-value ways to use customer profitability metrics to improve business results, with concrete examples in each of the following categories:
o Customer Lifetime Value optimization ("CLV")
o Customer loyalty and retention
o Share of wallet maximization
o Marketing ROI
o Impact of Customer Service, Customer Experience, and Customer Satisfaction on Profit
o Product design, pricing, promotion, and positioning
o Allocation of resources (capital, budget, HR, etc)
o Risk management

3. How to Calculate Profitability at the Customer Level : We will walk through the algorithms you need to use to turn raw data into customer profitability metrics, and share tips on how to customize them depending on your business. Related applications will also be covered, such as how to use the same algorithms to measure profit per household, salesperson, distributor, or other entity relevant to how your business makes money.

4. Data & Tech Requirements

5. Using Big Data to Maximize ROI on Customer Analytics: What are the top 5 opportunities to use Big Data to increase the benefits achieved through customer profitability analytics and related initiatives?

Speakers: Jaime Fitzgerald, Founder and Managing Partner, Fitzgerald Analytics, and Konrad Kopczynscki, Director at Fitzgerald Analytics. Konrad and Jaime have applied customer profitability methodologies to dozens of clients.

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  • 1. Architects  of  Fact-­‐Based  Decisions™   Profi%ng  from  Customer  Analy%cs     in  the  era  of  Big  Data   March  25th,  2014  
  • 2. 2   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Introduc%on:    Jaime  and  Konrad   17+ years advising clients in Financial Services, Retail, and Public Sector. Created the Data to Dollars Value Chain™ framework & methodology, used by to serve our clients at Fitzgerald Analytics. Now “open-sourcing” the methodology via: •  The Book •  Online learning resources •  Training seminars on data-monetization •  Customized training + consulting Specialists  in  the  process  of  turning  Data  into  Results.  
  • 3. 3   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   The  Data  to  Dollars™  Stack   Insights   Analysis   Data   Tools,  PlaCorms,  Technology,  People,  and  Processes   Decisions,  Ac%ons,  and  Results   Made  be'er  by  the  right   Created  by  the  right   Which  depends  on  access  to  the  right   And  selec7on  of  the  right   Plan:   Act:  
  • 4. 4   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   The  Stack  is  Also  a  Value  Chain…   Insights   Analysis   Data   Tools,  PlaCorms,  Technology,   People,  and  Processes   Decisions,  Ac%ons,  and  Results  Plan:   Act:   Dollars     To     Data     Made  be'er  by  the  right   Created  by  the  right   Which  depends  on  access  to  the  right   And  selec7on  of  the  right  
  • 5. 5   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   §  New  Data   Source   Acquisi5on   §  Data  Discovery     §  Data  Quality   §  Data   Governance     Analysis   Insight   §  Decisions   §  Ac5ons   §  Financial  Impact   §  New  Data   §  New   Opportuni5es   The  Data  to  Dollars  Value  Chain™   3.  Dollars     2.  Analysis     1.  Data     Naviga%on   Tips:     1.  Set  Clear  Goals   and  translate   into  concrete   plans   2.  Stay  Agile  (loop   back  oQen)   3.  Keep  Oriented   (“line  of  sight”  /   “why  am  I  doing   this?)  
  • 6. 6   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Set  Your  Ul%mate  Goal   “Yes,  that  math   works…”   “Yep,  those  are  the   two  types  sources  of     gross  profit”   “Yep…math  works  here   too…”   Causal  Models  and  Causal  Clarity™   Causal  Clarity™  is  star@ng  with  our  goal  and  then  figuring  out  what  we  needs  to  be   done  in  order  to  deliberately  cause  the  goal  to  happen.       Source:  CFNA  /  Bridgestone-­‐Firestone  Presenta@on   Service   Marke7ng   Compensa7on   Gross  Profit   Store     Expenses   Retail  Store   Profits   Sales   Gross  Margin  on   Sales   Gross  Margin  on   Sales   Sales   Tires   Overhead   Illustra%ve  Example  
  • 7. 7   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Table  of  Contents   1.  Customer  Profitability  Analy%cs  (CPA)   2.  High  Impact  Use  Cases   3.  Calcula5ng  CPA  at  the  Customer  Level   4.  Data  and  Tech  Requirements     5.  Using  Big  Data  to  Maximize  ROI  on  CPA  
  • 8. 8   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Seeking  the  Origins  of  Profitability…  
  • 9. 9   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Customer  Rela%onships  are  the  Source  of  Results   “There  is  only  one  valid  defini5on  of  a   business  purpose:  to  create  a  customer”   -­‐  Peter  Drucker,     The  Prac@ce  of   Management,   1954  
  • 10. 10   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Customer  Profitability  Defined  (aka  “CPA”)   Your  P&L     Statement   Deconstructed  into  a  P&L   for  each  of  your  customers   The  contribu7on  each  customer  makes  to  your  total  profit  or  loss.         In  other  words,  a  “customer-­‐level  P&L  statement”    
  • 11. 11   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   History  of  Customer  Profitability  Analysis   §  Prac5ced  since  the  early  1980s.      Banks  were  early  adopters   §  First  Manha_an  Consul5ng  Group  one  of  several  firms  to     pioneer  the  method  for  clients   §  Massive  results  unlocked  over  the  years  and  ongoing   §  Some  notable  mishaps  along  the  way…   §  S5ll  considered  by  many  to  be  “obscure”  or  “not  possible  here”   …which  is  unfortunate!  
  • 12. 12   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Customer  Profitability  is  The  Ul%mate  KPI   “There  is  only  one  valid  defini5on   of  a  business  purpose:     to  create  a  customer”   (The  Prac5ce  of  Management,  ‘54)  
  • 13. 13   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Loss  per  Customer   Example  CPA  Output:  “Decile  Chart”   Top   (Most   Profitable   10%)   2nd   3rd   4th   5th   6th   7th   8th   9th   Bo_om   (Least   Profitable   10%)   Profitability  Deciles    (each  bar  =  10%  of  customers,  ranked  by  profitability)   Average   Best  Customers   Mid-­‐Value   Losing  Money   Profit  per  Customer  
  • 14. 14   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   The  “reality  behind  the  averages”  enables  beaer  decisions   Loss  per  Customer   Top   (Most   Profitable   10%)   2nd   3rd   4th   5th   6th   7th   8th   9th   Bo_om   (Least   Profitable   10%)   Profitability  Deciles    (each  bar  =  10%  of  customers,  ranked  by  profitability)   Average   Priori%ze  for   reten%on,  target  to   acquire  more….   Grow  share  of  wallet   Revisit  costs  to  serve,    pricing,  and  root  causes   of  unprofitability   Profit  per  Customer  
  • 15. 15   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example  of  an  Individual  P&Ls:  Bank   P&L  Item  (Yearly)   High  Profit  Customer   Low  Profit  Customer   Revenue   Checking  Account   $300   $36   Savings  Account   $100   N/A   Credit  Card   $600   $15   Mortgage   $1,000   N/A   Cost  Of  Goods  Sold  (Interest  Expense)   $800   $5   Opera%onal  Costs   Pro-­‐Rated  Customer  Acquisi5on   (Sales  +  Marke5ng  Expense)   $80   $40   Other  Marke5ng   $5   $5   Customer  Service   Offline  /  Online  /  Phone   $5  /  $2  /  $5   $20  /  $2  /  $5   Statements   Offline  /  Online   $0  /  $1   $30  /  $1   Other  Opera5ons   $5   $5   Net  Profit   $1,097   ($62)   Large   Varia7ons   Illustra%ve  
  • 16. 16   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Classic  CPA  Output:  “Waterfall  Chart”   Product  A,    $50   Product  B,    $40   Services,  $25   Cost  to  Aquire,  $30   Cost  to  Serve,  $30   Overhead,  $20   Profit,  $35   $0   $50   $100   Product  A   Product  B   Services   Cost  to   Aquire   Cost  to   Serve   Overhead   Profit   Key  components  of  profit  and  loss  per  customer   $  per  Customer   16  
  • 17. 17   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Maximizing  profitability  of  the  full  customer  rela%onship     Customer  Life%me  Value  (aka  CLV)  =  the  accumulated   profit  or  loss  from  each  customer  over  the  course  of   that  customer’s  rela5onship  with  you.    Including:     1. Cost  of  acquiring  the  customer  (genera%ng  first   purchase)   2. Revenue  from  all  products  over  %me   3. Costs  of  goods  and  services  sold  (COGS)   4. Customer  service  costs   5. Opera%ng  costs   6. Cost  of  capital  
  • 18. 18   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Table  of  Contents   1.  Customer  Profitability  Analy5cs  (CPA)   2.  High  Impact  Use  Cases   3.  Calcula5ng  CPA  at  the  Customer  Level   4.  Data  and  Tech  Requirements     5.  Using  Big  Data  to  Maximize  ROI  on  CPA  
  • 19. 19   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Managing  Customer  Life%me  Value   Customer   Behavior   Offers   Service   Customer   Experience   Messaging   Our  Offerings  +   Ac%ons   Business   Impact   Advocacy   Recep5vity   (to  new  info,   offers,  etc.)   Revenue     $  Now     $  Future   Intangibles   Word  of  Mouth   Advocacy   Referral   Nega5ve  Word  of   Mouth   Costs   Loyalty   Demographics   Customer  Interac%ons   Aaributes   Wants  +  Needs   Customer  Knowledge   Psychographics   Profitability  /   History     Affini5es   Rela5onships   Etc.   Situa5onal     needs   Situa5onal   Aspira5ons   Price  Sensi5vity   Service  Sensi5vity   Channel   Preferences   Etc.  
  • 20. 20   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Elements  of  Maximizing  Customer  Life%me  Value   Symbol   Elements   Customer  Acquisi5on  /  Marke5ng  ROI   Share  of  Wallet  Maximiza5on   Customer  Loyalty  and  Reten5on   Product  Design,  Pricing,  Promo5on,  and  Posi5oning.     Alloca5on  of  Resources  (Capital,  Budget,  HR,  etc..)   Impact  of  Customer  Service,  Customer  Experience,  and  Customer  Sa5sfac5on  on   Profit   Risk  Management     In  this  sec%on  we  share  a  set  of  case  studies,  each  of  which  involves  the  use  of  customer   profitability  analysis  to  improve  one  or  more  of  the  elements  below  
  • 21. 21   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example:  Credit  Cards  –  Taking  Profitable  Risks   Life%me  profit  per  dollar  of  credit  card  sales   $- $0.02 $0.04 $0.06 $0.08 $0.10 1st Quartile 2nd Quartile 3rd Quartile 4th Quartile LifetimeProfitperDollarofSales More Risk Less RiskQuartiles by Risk Level The Riskier Half of The Card Company Customers Generate 6 to 9 Cents per Dollar of Sales…. …while the “Safer Half” of The Card Company Customers Produce only 1 to 3 Cents per Dollar of Sales…. CLV   Elements         Customer   Acquisi5on           Product   Design         Risk   Management    
  • 22. 22   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example:  High-­‐Value  Customers  of  Apple   “Apple  Evangelists”    -­‐-­‐  Buy  Mul@ple  Products…and  Upgrade  ORen    -­‐-­‐  Self-­‐sufficient  /  expert  users  –  the  need  less  support   CLV   Elements         Customer   Acquisi5on           Share  of   Wallet           Customer   Loyalty  
  • 23. 23   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example:  Mid-­‐Value  Customers  of  Apple   “Limited  Rela7onship”    -­‐-­‐  Buy  only  1  or  2  Apple  Products…and  rarely  upgrade    -­‐-­‐  Not  self-­‐sufficient,  need  more  help  from  support   CLV   Elements           Share  of   Wallet           Customer   Service           Customer   Loyalty  
  • 24. 24   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example:  Nega%ve-­‐Profit  “Customers”  of  Apple   “Resource  Hogs”    -­‐-­‐  Rarely  buy,  if  ever,  and  buy  lowest  margin  products    -­‐-­‐  Consume  dispropor@onate  sales,  service,  and  support            resources.          -­‐-­‐  Frequent  warrantee  or  insurance  replacement  claims     CLV   Elements           Resource   Alloca5on           Customer   Service           Product   Design         Risk   Management  
  • 25. 25   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   CLV   Elements         Loyalty           Product   Design         Resource   Alloca5on           Risk   Management   Customer  loyalty:  Delta’s  Frequent  Flier  Program     Decision  Implemented:  Tie  Tier  Status  to  Revenue  per  Mile   instead  of  solely  miles  traveled.     Key  insight:  Customer’s  were  gaming  the  system  to  gain   lucra5ve  5er  status     Behavior  Observed:  A  surprising  %  of  not  profitable   customers  were  earning  elite  status.    
  • 26. 26   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Delta’s  Loyalty  Program:  Causal  Model   Revenue   Revenue  /  Mile   =   Miles  Flown   X   Before  the  change,   Delta  was   incen7vizing  miles   flown   The  new  program  is   incen7vizing   revenue   1 2 CLV   Elements         Loyalty           Product   Design         Resource   Alloca5on           Risk   Management  
  • 27. 27   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   What  Delta  Must  have  Realized…   Decile:   1   2   3   4   5   6   7   8   9   10   %  of  All  Elite   Members   30%   20%   10%   10%   8%   8%   8%   3%   2%   1%   Rev  /  Mile   $10   $8   $5   $4   $4   $4   $2   $1   $1   $1   Illustra%ve   CLV   Elements         Loyalty           Product   Design         Resource   Alloca5on           Risk   Management  
  • 28. 28   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Risk  Management:  American  Express  Forgets  to  Bill     Decision  Implemented:  discover  and  fix  an  opera5onal   error  that  led  to  some  customers  not  being  charged  their   annual  fee.     Key  insight:  Certain  customers  had  not  been  billed  a   yearly  fee  in  YEARS     Behavior  Observed:  A  sub-­‐sec5on  of  loyal  customers   appeared  to  be  genera5ng  no  revenue  from  Annual  Fees   CLV   Elements         Product   Design         Risk   Management    
  • 29. 29   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   American  Express  Pla%num:  Illustra%ve  Customer  P&L   1-­‐year  Elements  of  P&L   Customer  #1   Customer  #2   Revenue   Annual  Fees   $500   $0   Late  Fees   $20   $20   Interest  Expense   $30   $30   Other  Fees   $60   $60   Cost  Of  Goods  Sold  (Interest  Expense)   $50   $50   Opera%onal  Costs   $150   $250   This  difference  should  not   exist  for  the  same  product   CLV   Elements         Product   Design         Risk   Management    
  • 30. 30   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Guide  to  Capitalizing  on  CLV  (use  this  to  recap  from  examples)   If  you  Know  This  About  Your  Customers   You  Can  Benefit  in  These  Ways:   The  right  risky  customers  end  up  crea5ng  a   huge  amount  of  value  over  their  life5me.     ID  the  most  important  customers  and  retain   more  value  from  customers  that  on  first  glance   seem  risky.     Customers  who  only  buy  one  or  two  items  end   up  cos5ng  us  the  most  in  in-­‐person  customer   support   Create  customer  service  alterna5ves  that  will   migreate  these  customers  to  less  costly   customer  support  channels.   Frequent  travelers  make  up  the  majority  of   your  best  customers,  but  a  sizable  minority  of   frequent  travels  are  below  average,  in  large   part  because  they  use  other  carriers  most  of   the  5me.     Poach  travellers  from  other  carriers   If  certain  customer  of  the  same  product  are   not  genera5ng  fee  revenue.   You  can  iden5fy  where  there  may  be  an   opera5onal  lapse  where  you  are  leaving  money   on  the  table.    
  • 31. 31   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Table  of  Contents   1.  Customer  Profitability  Analy5cs  (CPA)   2.  High  Impact  Use  Cases   3.  Calcula%ng  CPA  at  the  Customer  Level   4.  Data  and  Tech  Requirements     5.  Using  Big  Data  to  Maximize  ROI  on  CPA  
  • 32. 32   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Gesng  the  Math  Right   Key  Drivers  of  Profit  –  Simple  Map   Gross  margin    Expenses   Customer   Profit   Non-­‐Capital  Expenses   Gross  Sales   COGS   Cost  of  Capital    
  • 33. 33   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Gesng  the  Math  Right:  Rela%ve  Difficulty     The  challenge  increases  as  you  proceed   downward…   Gross  margin    Expenses   Customer   Profit   Non-­‐Capital   Expenses   Gross  Sales   COGS   Cost  of   Capital     HarderMath/ TougherChoices
  • 34. 34   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   The  Math:    Gross  Margin   Gross  Sales  =     The  Sum  of  the  Number  of  Sales  of  Each  Product    x  the  Selling   Price  of  Each  Product   Less   The  Sum  of  the  Number  of  Sales  of  Each  Product    x  the  Cost  of   Each  Product  (to  the  company)      
  • 35. 35   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Gross  Sales:  Product  Examples  from  Financial  Services   §  Personal  Banking   •  Checking   •  Savings   •  Credit  Card   •  Mortgage   §  Brokerage  Account  with  Checking   •  Investments/Trading   •  Checking   •  Savings  
  • 36. 36   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Expenses:  Variable  vs.  Fixed   Variable   Expenses   Fixed   Expenses   §  Expenses  which  vary   from  period  to  period   based  on  the  volume  of  a   unit   §  Examples:  ACH   Transac5ons,  Statements   Printed,  Receipts   §  Expenses  which  remain  fixed   despite  fluctua5ng  volumes   §  Example:  Cost  of  DEVELOPING   a  Web-­‐Based  Banking   Applica5on  (although  the  cost   of  hos5ng  +  support  is  variable)   Expenses   Non-­‐ Capital   Expenses   Cost  of   Capital     Fixed   Expenses   Variable   Expenses  
  • 37. 37   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   The  Math:  Alloca%ng  Variable  Expenses   For  each  expense  line  item,   Customer  Expense  equals     Expense  per  Unit  x  Number  of   Units     Example:    3  Bank  Teller  TXNS  x   $10  per  Teller  Transac%on     Expenses   Non-­‐ Capital   Expenses   Cost  of   Capital     Fixed   Expenses   Variable   Expenses  
  • 38. 38   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   The  Math:  Alloca%ng  Fixed  Expenses   For  each  category  of  fixed   costs,  allocate  based  on  the   factor  that  makes  the  most   sense  given  your  analy%c   purpose.     Common  op%ons:   1)  Per  customer   2)  Per  transac%on   3)  Per  ac%vity   4)  Per  dollar  of  sales  or  Gross  Profit     Expenses   Non-­‐ Capital   Expenses   Cost  of   Capital     Fixed   Expenses   Variable   Expenses  
  • 39. 39   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   What  Affects  “Cost  to  Serve”?   Low  Cost-­‐to-­‐Serve  Customers   High  Cost-­‐to-­‐Serve  Customers   Order  standard  products   Order  custom  products   High  order  quan55es   Small  order  quan55es   Predictable  order  arrivals   Unpredictable  order  arrivals   Standard  delivery   Customized  delivery   No  changes  in  delivery  requirements   Change  delivery  requirements   Electronic  processing  (EDI)  (zero  defects)   Manual  processing   Li_le  to  no  pre-­‐sales  support  (standard  pricing   and  ordering)   Large  amounts  of  pre-­‐sales  support  (marke5ng,   technical,  and  sales  resources)   No  post-­‐sales  support   Large  amounts  of  post-­‐sales  support   (installa5on,  training,  warranty,  field  service)   Replenish  as  produced   Require  company  to  hold  inventory   Pay  on  5me   Pay  slowly  (high  accounts  receivable)   Source:  Kaplan  &  Narayanan  with  revisions  by  Fitzgerald  Analy5cs  
  • 40. 40   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Week  of: 31-­‐ Oct 7-­‐ Nov 14-­‐ Nov 21-­‐ Nov 28-­‐ Nov 5-­‐ Dec 12-­‐ Dec 19-­‐ Dec 26-­‐ Dec 2-­‐ J an 9-­‐ J an 16-­‐ J an 23-­‐ J an Phase 1.4 Define methodological approach (methods, concepts, technology options) 1.2 Determine potential segmentation criteria 3.4 Troubleshoot data Key  Tasks 2.3 Develop revenue and costing algorithms 2.4 Account for cross- unit effects 4.4 Document recommendations for ongoing maintenance and enhancement 1.1 Gather input via interviews 1.3 Determine data availability 1.5 Plan development of prototype 2.5 Document methodology and data sources 1.  Strategy  &  Planning 2.  Design  Methodology  and   Algorithms 3.  Build  Prototypes 4.  Segment  Analysis 2.1 Understand data sources in detail 2.2 Request and test data extracts 4.3 Identify key insights to drive additional segmentation analysis 4.1 Rank customers by decile 4.2 Initial segmentation analysis 3.1 Program customer profitability algorithms 3.2 Validate and modify where necessary to ensure accuracy 3.3 Finalize documentation of data definitions and profitability algorithms Example  Project  Timeline  (Aggressive  Ini%al  Prototype)  
  • 41. 41   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Table  of  Contents   1.  Customer  Profitability  Analy5cs  (CPA)   2.  High  Impact  Use  Cases   3.  Calcula5ng  CPA  at  the  Customer  Level   4.  Data  and  Tech  Requirements     5.  Using  Big  Data  to  Maximize  ROI  on  CPA  
  • 42. 42   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Data  Requirements:  Input  Data   Data  Type   Purpose  in  CPA     Crucial  Considera%ons   Customer  List  +  Aaributes   Basis  of  Analysis.     Unique  ID   Defini5on  of  Customer  (!)  or   relevant  en55es  (Household?   B2B  Account?  Etc.)   Sales  Transac%on  Data   Gross  Revenue   Transac5ons  need  to  be   product  specific   Product  Cost  Data   Gross  Margin   How  variable  is  cost  for  a  given   product?   What  product  sourcing   decisions  might  we  make?   Expenses  by  Line  Item   Alloca5ng  Costs   How  to  categorize  costs   Ac%vity  and  transac%on   volume  data   To  allocate  costs  of   ac5vi5es   Where  possible,  ac5vity  data   that  is  customer  specific  is  best   Where  ac5vity  data  is  not   tracked  by  customer  served,   other  categoriza5on  is  useful   (example:  product,  geography,   etc.)  
  • 43. 43   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Data  You  Must  Create  to  Implement  CPA   Data  Type   Decisions   Cost  Alloca%on   Factors   Granularity  of  ABC  cos%ng     “Anomaly  Management”     Best  way  to  allocate  fixed  costs     “Proxy   Benchmarks”   What  missing  data  needs  to  be  es%mated  with  a   proxy,  and  under  what  circumstances?     What  proxy  best  suits  the  purpose      
  • 44. 44   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example:  Credit  Card  CPA  Model   Revenue Side • The Customer Profitability process takes all customer transaction activity * (revenue-generating and charge -offs) and organizes them by customer , by year , and by month • Key assumption : calculated factor to assess direct mail revenue Dimensions Customer Month Year Measures Customer Statement Balance Risk Management Data Dimensions Customer Month Year Measures Sales Fees/Charges Direct Mail Bad Debt TXN Data Input Process Output Dimensions Customer Month Year Measures Customer Profitability Model 1. Revenue line items* 2, Expense generating line items** 3. Profit Expense Side Expense line item assumptions • The model breaks down all expense line items and attributes them at the customer level • The model attributes them at the customer level by applying cost factors (to various customer activities that imply costs Interest expense assumptions • Cost to private label card companyof its accounts receivables (i.e. cost of borrowing money customer statement balances) • Dependent on various interest rate indices Expense Data
  • 45. 45   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Data  Management     Good:   §  ETL  Process  feeding  a  superimposed  external  client  structure   (and  for  each  dimension  such  as  product,  etc)     Beaer:   §  Single  client  iden5fier  inside  all  systems  for  straight-­‐through   processing.    Other  standard  reference  tables.     Best:   §  An  ability  to  adapt  to  changes  in  business  structure  with   changes  to  data  management  and  data  quality.    In  short,   companies  who  manage  data  well  have  an  analy5c  advantage.    
  • 46. 46   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Example:  Data  Flow  Data  Used  in  CPA  Analysis   POS Sale ECSDS HEMS Host ECSDS Management System ICD JDA NEW marketing Automation System CustomerLevelMetrics CustomerProfitability Data Prophix Accounting System ReportWeb Accounting: P&L CostAdjustment Cost Master Book Labor cost Parts cost Generic product cost Nat’l Customer Database HR database future Archer OLD Marketing Information System
  • 47. 47   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Table  of  Contents   1.  Customer  Profitability  Analy5cs  (CPA)   2.  High  Impact  Use  Cases   3.  Calcula5ng  CPA  at  the  Customer  Level   4.  Data  and  Tech  Requirements     5.  Using  Big  Data  to  Maximize  ROI  on  CPA  
  • 48. 48   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Big  Data  +  CLV  Management:  3  Key  Spots   Customer   Behavior   Offers   Service   Customer   Experience   Messaging   Our  Offerings  +   Ac%ons   Business   Impact   Advocacy   Recep5vity   (to  new  info,   offers,  etc.)   Revenue     $  Now     $  Future   Intangibles   Word  of  Mouth   Advocacy   Referral   Nega5ve  Word  of   Mouth   Costs   Loyalty   Demographics   Customer  Interac%ons   Aaributes   Wants  +  Needs   Customer  Knowledge   Psychographics   Profitability  /   History     Affini5es   Rela5onships   Etc.   Situa5onal     needs   Situa5onal   Aspira5ons   Price  Sensi5vity   Service  Sensi5vity   Channel   Preferences   Etc.   1 2 3 Richer  Customer   Knowledge   Beaer   predic%ons   Ac%ons  
  • 49. 49   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Big  Data  +  Customer  Knowledge   Demographics Attributes Wants  +  Needs Customer  Knowledge Psychographics Profitability  /   History   Affinities Relationships Etc. Situational   needs Situational   Aspirations Price  Sensitivity Service  Sensitivity Channel   Preferences Etc. 1 Text  Analy%cs:   1)  Call  center  transcripts   2)  Social  Media     (Listening  +  Service)   Social  Media   1)“Graph  Analysis”   2)  Affinity  signals     Loca%on  data     High-­‐performance  processing!   Clickstream  Analy%cs   -­‐-­‐  Interests   -­‐-­‐  Response  to  UI   Examples:  
  • 50. 50   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Big  Data  +  Customer  Behavior   Advocacy Receptivity (to  new  info,   offers,  etc.) 2 Text  Analy%cs:   1)  Call  center  transcripts   2)  Social  Media     (Listening  +  Service)   Social  Media   1)“Graph  Analysis”   2)  Affinity  signals     Loca%on  data     High-­‐performance  processing!   Clickstream  Analy%cs   -­‐-­‐  Interests   -­‐-­‐  Response  to  UI   Examples:  
  • 51. 51   How  to  profit  from  Customer  Analy5cs  in  the  era  of  Big  Data  |  Copyright  Fitzgerald  Analy5cs  2014,  all  rights  reserved   Big  Data  +  Our  Offerings  and  Ac%ons   Customer Behavior Offers Service Customer   Experience Messaging Our  Offerings  +   Actions Advocacy Receptivity (to  new  info,   offers,  etc.) Loyalty Customer  Interactions 2 3 Text  Analy%cs:   1)  Call  center  transcripts   2)  Social  Media     (Listening  +  Service)   Social  Media   1)“Graph  Analysis”   2)  Affinity  signals     Loca%on  data     High-­‐performance  processing!   Clickstream  Analy%cs   -­‐-­‐  Interests   -­‐-­‐  Response  to  UI   Examples: