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Architects	
  of	
  Fact-­‐Based	
  Decisions™	
  
Profi%ng	
  from	
  Customer	
  Analy%cs	
  	
  
in	
  the	
  era	
  of	
  Big	
  Data	
  
March	
  25th,	
  2014	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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	
  
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:	
  

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Profiting from customer profitability + big data fitzgerald analytics

  • 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: