Lifetime Value In new format
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Transcript Lifetime Value In new format
CHAPTER 3
Research design , Data
sources
3-1 Research Design:
Delineating What Data to Collect and
How to Collect It
A research design is the basic plan that guides data
collection and analysis. It must specify:
the type of information to be collected
(consistent with the project objectives)
possible data sources
the data collection procedure
(accurate, economical and timely)
3-1a Types of Research
1. exploratory research – to
improve research
2. conclusive research – to
help choose between courses
of action
3. performance-monitoring
research – feedback on
chosen course of action
Figure 3-1 Types of
research
3-1b Exploratory Research:
Determining the 'Space' of Possible
Marketing Actions
Exploratory research facilitates problem recognition and
definition. It is appropriate when the research objectives
include:
identifying problems or opportunities
gaining perspective on the nature of the problem
gaining perspective on variables involved
establishing priorities
formulating possible courses of action
identifying possible pitfalls in doing conclusive research
3-1c Conclusive Research: Narrowing
Down Strategic Alternatives
Conclusive research aims to narrow the field of strategic
alternatives down to one. Two types:
Descriptive research characterizes marketing phenomena
without testing for cause-and-effect relationships. It is used
for:
determining the frequency of certain marketing phenomena
determining the degree of association between marketing
variables
making predictions regarding marketing phenomena
Causal research gathers evidence on cause-and-effect
relationships through experimentation.
3-1i Longitudinal Design and PanelBased Research
Consumer panels monitor performance continuously for
a fixed sample measured repeatedly over time
(longitudinally). Advantages of panels:
reveal important aspects of consumer behavior that cannot be
gleaned from cross-sectional data
gather more accurate data than cross-sectional surveys
gather extensive background and geodemographic information
on participants
reduce bias through period-by-period recording of purchases
tend to cost less per data point than surveys
3-2 Data Sources for Marketing
Research Applications
Sources of marketing data:
1. respondents
communication with respondents
verbal response through focus group or in-depth interviews
depends on self-reporting
observation of respondents
accurately records what people do and how
omits reporting of underlying attitudes
2. analogous situations
case histories
simulations
3-2 Data Sources for Marketing
Research Applications (cont.)
Sources of marketing data (cont.):
3. experimentation to test cause-and-effect relationships
direct manipulation of key independent variables and
measurement of their effects on dependent variables
controlling other variables that might affect ability to make
valid causal inferences
4. secondary data
data already collected for some other purpose
internal or external
3-3 Secondary Data
internal secondary data generated within the organization
lower cost
accurate
more available
external secondary data – generated by government or syndicated
sources
government publications
trade association data
books
bulletins
reports
periodicals
The Balancing Act with Secondary Data
*Inexpensive
*Can be Secured Quickly
*Unknown Accuracy
*Ill Fitting for the Problem
The Nature of Secondary Data
Primary data
Secondary data
Internal Information
Sales & Expense reports
Salespeople’s reports
Street News
Executive Judgments
Extended internal information
The Nature of Secondary Data (contd.,)
Secondary data
External Information
Library sources
Books
Periodicals
Government documents
Computerized databases
Nonlibrary sources
Trade associations
Government Agencies
Media companies
Syndicated data
Internet sources
Creating an Internal Database
An Internal Database is a collection of related information
developed from data already within the organization.
Why is it important?
Case of Capital One
Lifetime Value
Collective memory banks
Created from qualitative data
NUD*IST
How a modern database
system works
Mail, Email, Phone
Customer
Transactions
Marketing
Database
Inputs from Retail,
Phone, Web
Updated
several
times per
day
Data Access
And Analysis
Software
Appended
Data
Marketing
Staff
Access on
the web
Two Kinds of Database People
Constructors
People who build databases
Merge/Purge, Hardware, Software
Creators
People who understand strategy
Build loyalty and repeat sales
You need both kinds!
Retention is the way to measure loyalty
90%
80%
70%
Percentage
Retained
from
Previous
Year
60%
50%
40%
30%
20%
10%
0%
1
2
3
4
Years as a customer
5
Retention pays better than acquisition
Annual Profit
$48
$60
$40
$20
$0
($20)
($40)
($60)
($80)
($62)
New Customer
3rd Year
Customer
Building Customer Value in four words...
Treat
different
customers
differently
What doesn’t work:
Treating all customers alike
This 28% lost 22% of the
bank’s profits!
79.67%
Profit %
80.00%
60.00%
24.82%
40.00%
15.83%
1.52%
20.00%
0.00%
-20.00%
-21.83%
Bank Customers by Profitability
-40.00%
5%
11%
28%
28%
28%
Compared with newcomers, Long term
customers:
Buy more per year
Buy higher priced options
Buy more often
Are less price sensitive
Are less costly to serve
Are more loyal
Have a higher lifetime value
Key retention strategy: cross selling
90%
80%
70%
60%
Retention 50%
Rate
40%
30%
20%
10%
0%
1
2
3
4
Number of Products Owned
5
Why do businesses exist at all?
Answer: Customers!
Get more customers
Keep them longer
Grow them into bigger customers
Marketing to Customer Segments
Your Best Customers 80% of Revenue
Your Best Hope for New
Gold Customers
1% of Total
Revenue
GOLD
Move Up
These may be losers
Spend Service
Dollars Here
Spend Marketing
Dollars Here
Reactivate or
Archive
Examples of Profitable Strategies
Newsletters
Surveys and Responses
Loyalty Programs
Customer and Technical Services
Friendly, interesting interactive web site
Event Driven Communications
Lifetime Value
Net profit you will receive from the transactions with a given
customer during the time that he/she continues to buy from
you.
Lifetime value is “Good Will”
To compute it, you must be able to track customers from
year to year
Main use: To evaluate strategy
Long term customers buy more often
3.0
2.5
2.0
Number of
purchases 1.5
per yer
1.0
0.5
0.0
1
2
3
4
Years as a customer
5
Long term customers buy higher
priced items
$70
$60
$50
Average $40
Purchase
$30
Price
$20
$10
$0
1
2
3
4
Years as a customer
5
Retention rates go up over time
90%
80%
70%
Percentage
Retained
from
Previous
Year
60%
50%
40%
30%
20%
10%
0%
1
2
3
4
Years as a customer
5
Model Assumptions
There is only one customer segment
Acquisition of new customers only happens in year 1
Lapsed customers
Revenue Side of the Equation
Year 1
Customers
Retention rate in %
Spending rate in $
Total Revenue
Year 2
20,000
40
150
3,000,000
Year 3
8,000
45
160
1,280,000
3,600
50
170
612,000
Cost Side of the Equation
Year 1
Year 2
Year 3
Variable costs in %
Variable costs $
Acquisition cost @ $40
60
1,800,000
800,000
50
640,000
0
45
275,400
0
Total costs
2,600,000
640,000
275,400
Profit Side of the Equation
Gross Profit = Total Revenues – Total Costs
Discount Rate = [1+(i * rf)] n
where n = no of years to be discounted
rf = risk factor
Net Present Value (NPV) Profit = Gross Profit / Discount Rate
Cumulative Profit = Sum of all NPV Profit till current year
Lifetime Value = Cumulative Profit for the year / Total Number of
customers ‘N’
Profit Side of the Equation
Year 1
Gross profit
Discount rate
Net present value profit
Cumulative NPV profit
Lifetime Value
Year 2
Year 3
400,000
1
400,000
400,000
640,000
1
551,724
951,724
336,600
1
249,333
1,201,057
20.00
47.59
60.05
Scoring Customers – RFM Analysis
Create a customer database. Include prospects.
Use past customer behaviors to predict future behaviors.
Using RFM to find best customers
Recency, Frequency, Monetary (RFM) analysis can be used to
categorize customers.
Best Customers are those who:
Bought from you recently
Buy from you frequently
Spend a lot of money on your products and services.
Recency
Recency is the time that has elapsed since the customer
made his most recent purchase.
A customer who made his most recent purchase last month
will receive a higher recency score than a customer who
made his most recent purchase three years ago.
Example of a Scoring system:
1 = Customers who made a purchase more than 9 months
ago
2 = Customers who made a purchase more than 3 months
ago but fewer than 9 months ago
3 = Customers who made a purchase in the last 3 months
Frequency
Frequency is the total number of purchases that a customer
has made within a designated period of time.
A customer who made six purchases in the last three years
would receive a higher frequency score than a customer who
made one purchase in the last three years.
Example of a Scoring system:
1 = Customers who made a single purchase in the past 12
months
2 = Customers who made between two & 12 purchases in
the past year.
3 = Customers who made more than 12 purchases in the
past year.
Monetary
Monetary is each customer's average purchase amount.
A customer who averages a $100 purchase amount
would receive a higher monetary score than a customer
who averages a $20 purchase amount.
Example of a Scoring system:
1 = Customers with an average purchase amount up to
$15.
2 = Customers with an average purchase amount from
$15 to $50.
3 = Customers with an average purchase amount greater
than $50.
Calculating RFM
Rank customers in your database based on time since last
purchase - Divide into 3 equal groups with 3 being the
33% of customers who bought most recently
Do the same thing again for Frequency.
Repeat the same exercise for Monetary or total dollars
spent.
These three codes give us 27 different categories of
customers ranging from 333 – 111.
ANALYZE your Customers: Highest
Monetary Cells
113
213
313
123
223
323
133
233
333
ANALYZE your Customers: Lowest
Monetary Cells
111
211
311
121
221
321
131
231
331
Benefits of RFM Analysis
RFM Analysis can provide answers to the following questions:
Can I identify my best customers?
Who do I e-mail offers to? When do I e-mail them? How often?
Should I promote to some customers more often than others?
How can I tell when I’m losing a customer?
Can I refine my marketing mix variables?
The next step after knowing and analyzing your
customers is CLONING your customers.
Advantages of Secondary Data
Clarify or redefine the problem /opportunity
May actually provide solutions
May provide primary research method alternatives
May divulge potential difficulties
May provide necessary background information
Limitations of Secondary Data
Lack of availability
Lack of relevance
Resources
Appraising Secondary Data
Who sponsored the research?
Who conducted the research?
Who provided the information?
Who reported the information?
What information was gathered?
Why was the information gathered?
When was the information gathered?
How was the information gathered?
Where was the information gathered?
A Decision Support System
What is a DSS?
An interactive, personalized mapping system designed to
be initiated and controlled by decision makers
In Marketing, it is known as MKIS (Marketing
Information Systems)
Some basic ideas about MKIS
Complex systems
Deal with a variety of data sources
Cost-benefit considerations
Characteristics of an MKIS
Interactive
Flexible
Discovery oriented
Easy to learn and use
Advantages of an MKIS
Cost savings
Increased understanding of the decision environment
Better decisions
Improved value of the information
Data Mining
What is Data Mining?
the process of exploration and analysis, by automatic and
semiautomatic mean, of large quantities of data in order
to discover meaningful patterns and rules.
The technology is "data mining." Extension of statistics.
Data Mining
Primarily used by companies with a strong ‘customer’ focus
Wal Mart
NBA Advanced Scout
Data Mining
Data Mining
Customer Acquisition
Customer retention or loyalty
Customer abandonment
Market-basket analysis