big data meets customer profitability analytics
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For more content from the same event, including a discussion of Customer Profitability Analysis and Big Data tools, please see: meetup.com/Analytics-and-Data-in-Financial-Services/pages/Big_Data_meet_Customer_Profitability_Analytics/TRANSCRIPT
Architects of Fact-Based Decisions™
Big Data Meets Customer Profitability Analytics
April 10, 2012
Brought to you by the team at Fitzgerald Analytics
2Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Introduction
1. Big Data… Big Results?
2. Customer Profitability Analysis
3. Implications of Big Data
4. Conclusion and Questions
Table of Contents
3Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Tonight’s Event
As usual, it’s about the journey to results.
Really Big Data
Product of everywhere
Big DataProduct of Alberta
Small Data
1
3
2
4Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Our Perspective
Skeptical…
Cautious…
Optimism….
5Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
What’s Wrong with a Little Hype ??
6Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
We are Talking about Something New and Exciting:
“Data is the New Oil” – World Economic Forum Report
7Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
And Something Old, Essential, & Profitable
“There is only one valid definition of a business purpose: to create a customer.”
(The Practice of Management, ‘54).
8Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Co-Presenters (#AnalyticsFSI)
Jaime Fitzgerald@jfitzgerald
Craig Williston@craig_williston
NikhilMahen@nikhilmahen
Konrad Kopczynski@konradFA
Gniewko Lubecki
9Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Introduction
1. Big Data… Big Results?
2. Customer Profitability Analysis
3. Implications of Big Data
4. Conclusion and Questions
Table of Contents
10Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Will Big Data Unlock Big Results?
It depends…
...on the principles you work by.
11Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
The Word’s Most Successful Data Professionals…
#B W T E I M!
What is Covey was a Big Data Gal in 2012?
12Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
2. Insight You Need
3. Analytic Methods
4. Data You Need
5. Tools, Platforms, Technology, People, and Processes
1. Your Goal
Beginning with the End in Mind
13Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Fitzgerald Analytics: Converting Data to Dollars™
Better Data Better Analysis Better Results
“A Journey of a Thousand Miles….”
Worth The Trip!
1
3
2
14Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Key Steps in the Journey to Results
Data Governance
Data Management
Data Quality
New Data Source Acquisition
Analysis Insight Better Decisions
Better Processes
More Customers
Happier Customers
3. Results2. Analytics1. Data
15Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Introduction
1. Big Data… Big Results?
2. Customer Profitability Analysis
3. Implications of Big Data
4. Conclusion and Questions
Table of Contents
16Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Definition & History
Customer Profitability Analysis is: 1) Measuring the contribution each customer makes to overall profits, and to the key drivers of those profits. In other words, a “customer-level version” of your corporations P&L statement. 2) Analysis that USES these customer-level metrics to improve results (there are a large number of applications)
History: Around since at least the early 1980s. Banks were early adopters First Manhattan Consulting Group a pioneer Massive results unlocked over the years and ongoing Some notable mishaps along the way… Still considered “obscure” by many…
17Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
The Concept Illustrated
Your P&L Statement
Deconstructed into a P&L for each of your customers
18Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Loss
per
Cus
tom
erCustomer Profitability Output: Classic 1st Step
Top(MostProfitable10%)
2nd 3rd 4th 5th 6th 7th 8th 9th Bottom(Least
Profitable10%)
Profitability Deciles (each bar = 10% of customers, ranked by profitability)
Average
Best Customers
Mid-ValueLosing Money
Profi
t per
Cus
tom
er
19Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Customer Segmentation and Lifetime Value (CLV)
Customer Retention
Cross-sell, Up-sell
Marketing Optimization & ROI
What do Customer Profitability Metrics Enable?
2
3
1
4
New Financial Product Design & Innovation5
A Top 5 List…
20Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Integration: Connecting The Dots
New Product Design5
Customer Lifetime Value + Segmentation
Customer Retention Cross-Sales / Up-Sales
1
2 3
Marketing ROI4
A few examples of how inter-related these processes are…
New
Info
rmati
on a
nd In
sigh
ts
21Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 21
Example: Taking Profitable Risks…
IF well managed, card companies often get most of their “riskier” customers
$-
$0.02
$0.04
$0.06
$0.08
$0.10
1st Quartile 2nd Quartile 3rd Quartile 4th Quartile
Lif
etim
e P
rofi
t p
er D
olla
r o
f S
ales
More Risk Less RiskCredit Score Band
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….
22Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved 22
“Lifetime Performance Curves”: Finance + Late Fee Income
The divergence is even more striking when Late Fees are added to Finance Income.
Performance Curves by Credit Quartile: Income from Finance and Late Fees
$0.00
$25.00
$50.00
$75.00
$100.00
$125.00
$150.00
$175.00
1 4 7 10 13 16 19 22 25 28 31
Months after 1st Purchase
Fin
ance
Fee
s +
Lat
e F
ees
Quartile1
Quartile2
Quartile3
Quartile4
1st Quartile Accounts generate more than 6 times as much revenue from these sources as accounts from the 4th Quartile….
23Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Example: Tata Nano
Initial target: “Cheap” car for middle class
What actually happened:1) Cost 20-50% greater than initially proposed; lost “Cheap” tag2) “Middle Class” less willing to accept the technical glitches the Nano faced..
RESULT: Customer Expectations not met
Customer Analysis: Bought heavily by people who already own one car
New target: “Utility” car for city dwellers, often a 2nd car.
24Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Challenge: From Descriptive to Prescriptive.
I can’t deposit decile charts in the bank either…
And my analysts can only think up so many customer segments, A|B Tests, Etc….
25Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Known Pitfall: Not Looking Beyond the Data… …
…
1995
2012
26Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Challenges to Creating Customer Profit Metrics
Calculating profit seems pretty simple!
Revenue
Expenses
Profit Direct Expense
Allocated Expenses
+
27Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Conceptually Simple
At first this seems simple enough…
Personal Banking
• Checking
• Savings
Brokerage Account with Checking
• Investments/Trading
• Checking
• Savings
28Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Representative “Universal Bank” Product Suite But today’s banks are big, complex, and poorly integrated.
Equities Stocks Derivatives Program Trading
Fixed Income Corporate Bonds Municipal Bonds Derivatives
Interest Rate Credit
Commodities Futures Forwards
Foreign Exchange
Sales & Trading
Capital Markets (IPO) Mergers & Acquisitions Project Financing Structured Financing
Investment Banking
Cash Management Trade Finance Corporate Trust Custody
Transaction Banking
Mutual Funds Separately Managed
Asset Management
Wealth Management Consulting
Trust Services
Private Wealth Mgmt
29Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Single Product Area
By Region
By Company
Impact of Mergers
Mergers add to the complexity…
• One product, if booked into regional systems and sold by both companies, in a merger can feed from 6 separate systems.
• At the very least, numbering schemes from the two companies will be different.
• At worst, every system will have a unique number or name for a single client.
Bank 2 Bank 1 Bank 2 Bank 1 Bank 2Bank 1
Europe AsiaAmericas
EquityTrading
30Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
“Slicing” Customer Profitability
Firms often seek to view customer profitability by:
Client
Client Segments
Product
Region
What about other metrics that may help with profit analytics:
Trade Volumes
Trade Fails
Client Service Center Issues
Assets Under Management
(AUM)
If you can’t even get the revenue by client how will you tie in other information?
31Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Solution? Data Management Data management is a precondition to customer metrics…
Good: ETL Process feeding a superimposed external client structure
(and for each dimension such as product, etc) Better: Single client identifier 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 analytic advantage.
32Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Perspective on Data Management
33Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Introduction
1. Big Data… Big Results?
2. Customer Profitability Analysis
3. Implications of Big Data
4. Conclusion and Questions
Table of Contents
34Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Defining Big Data: “Three Vs”
"Big Data“ is seen as data with:
greater volume…
greater variety…
and/or
greater velocity….
35Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Another Way to Define “Big Data” -
What methods are required to realistically make use of it?
Traditional Method? Big-Data Method?
Note that this definition hinges on methods applied, not on dataset sizes:
36Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Build Customer Profitability Models Identify costs & revenues Build profiles Feed data from
internal and external sources
Maintain data warehouses
Profitability Management Becomes More Refined Over Time through an Iterative Process Driven by Customer Knowledge
• Create consistent message • Target action to individuals• Optimize product / service
portfolio
Data Warehouse
New Customer Knowledge Feed campaign results into data
warehouses
Test predictive accuracy of model
Break down segment into individual customer analyses
Drive Action Into Frontline Systems Create consistent message
Target action to individuals
Optimize product/service portfolio
Face-to- Face
Phone
InternetExternal Data
Sources
37Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Big-Data Approaches and Tools Make Data Analysis
Possible, for very large data sets that cannot be handled at all with typical relational databases.
Faster, for large data sets that can be handled with typical relational databases, but doing so would take a long time. This is the situation in the example above.
Cheaper, for large data sets that can be handled with typical relational databases, but doing so would be very expensive.
38Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Big Data Allows Us To Work with Large Datasets We can analyze datasets larger than ever before
Beyond a certain point, conventional methods just aren’t feasible – Google couldn’t run on a relational DB
For larger datasets, big-datamethods make more sense
For smaller datasets,conventional methods aremore cost-effective
Dataset size
IT C
osts
For a given desired speed of analysis…
Traditional methods
Big-datamethods
39Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Big Data Allows Us To Get Results Faster We can get results faster than ever before
Analysis speed
IT C
osts
For a given dataset size…
Conventionalmethods
Big-datamethods
SLOW FAST
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Data on its own is useless
?Big Data
Related Technologies
Methods
41Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Add Customer Profitability
Instantly
Daily / weekly / monthlySmall Data
Big Data
42Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Add new business rules
Instantly
Instantly
Instantly
Instantly
Big Data
Father just started at Bank of America
His son’sfavorite color is
blue
All his friends have
Chase
InstantlyBig Data
43Big Data Meets Customer Profitability Analytics | Copyright Fitzgerald Analytics 2012, all rights reserved
Introduction
1. Big Data… Big Results?
2. Customer Profitability Analysis
3. Implications of Big Data
4. Conclusion and Questions
Table of Contents