Research design , Data sources

CHAPTER 3

3-1 Research Design: Delineating What Data to Collect and How to Collect It

the type of information to be collected (consistent with the project objectives)

possible data sourcesthe data collection procedure

(accurate, economical and timely)

A research design is the basic plan that guides data collection and analysis. It must specify:

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

identifying problems or opportunitiesgaining perspective on the nature of the problemgaining perspective on variables involvedestablishing prioritiesformulating possible courses of action identifying possible pitfalls in doing conclusive

research

Exploratory research facilitates problem recognition and definition. It is appropriate when the research objectives include:

3-1c Conclusive Research: Narrowing Down Strategic Alternatives

Descriptive research characterizes marketing phenomena without testing for cause-and-effect relationships. It is used for:determining the frequency of certain marketing

phenomenadetermining the degree of association between

marketing variablesmaking predictions regarding marketing

phenomenaCausal research gathers evidence on cause-and-

effect relationships through experimentation.

Conclusive research aims to narrow the field of strategic alternatives down to one. Two types:

3-1i Longitudinal Design and Panel-Based Research

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

Consumer panels monitor performance continuously for a fixed sample measured repeatedly over time (longitudinally). Advantages of panels:

3-2 Data Sources for Marketing Research Applications

1. respondentscommunication with respondents

verbal response through focus group or in-depth interviews

depends on self-reporting observation of respondents

accurately records what people do and howomits reporting of underlying attitudes

2. analogous situationscase historiessimulations

Sources of marketing data:

3-2 Data Sources for Marketing Research Applications (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 datadata already collected for some other purposeinternal or external

Sources of marketing data (cont.):

3-3 Secondary Datainternal secondary data generated within the

organizationlower costaccuratemore available

external secondary data – generated by government or syndicated sourcesgovernment publicationstrade association databooksbulletinsreportsperiodicals

The Balancing Act with Secondary Data

*Inexpensive*Can be Secured Quickly

*Unknown Accuracy*Ill Fitting for the Problem

The Nature of Secondary DataPrimary dataSecondary data

Internal InformationSales & Expense reportsSalespeople’s reportsStreet NewsExecutive JudgmentsExtended 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 DatabaseAn Internal Database is a collection of

related information developed from data already within the organization.

Why is it important?Case of Capital OneLifetime Value

Collective memory banksCreated from qualitative data

NUD*IST

MarketingDatabase

Data AccessAnd Analysis

Software

Customer Transactions

Marketing Staff

Inputs from Retail, Phone, Web

How a modern database system works

AppendedData

Mail, Email, Phone

Updated several

times per day

Access on the web

Two Kinds of Database PeopleConstructors

People who build databases Merge/Purge, Hardware, SoftwareCreators

People who understand strategy Build loyalty and repeat salesYou need both kinds!

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Percentage Retained

from Previous

Year

1 2 3 4 5

Years as a customer

Retention is the way to measure loyalty

Retention pays better than acquisition

($62)

$48

($80)($60)($40)($20)

$0$20$40$60

New Customer 3rd YearCustomer

Annual Profit

Treat different customers differently

Building Customer Value in four words...

What doesn’t work:Treating all customers alike

79.67%

24.82%15.83%

1.52%

-21.83%

-40.00%

-20.00%

0.00%

20.00%

40.00%

60.00%

80.00%

5% 11% 28% 28% 28%

This 28% lost 22% of the bank’s profits!

Bank Customers by Profitability

Pro

fit

%

Compared with newcomers, Long term customers: Buy more per yearBuy higher priced optionsBuy more oftenAre less price sensitiveAre less costly to serveAre more loyalHave a higher lifetime value

Key retention strategy: cross selling

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Retention Rate

1 2 3 4 5

Number of Products Owned

Why do businesses exist at all?

Answer: Customers!Get more customersKeep them longerGrow them into bigger customers

GOLD Spend Service Dollars Here

Spend Marketing Dollars Here

Reactivate or Archive

Your Best Customers - 80% of Revenue

Your Best Hope for New Gold Customers

Move Up

1% of Total Revenue These may be losers

Marketing to Customer Segments

Examples of Profitable StrategiesNewslettersSurveys and ResponsesLoyalty ProgramsCustomer and Technical ServicesFriendly, interesting interactive web siteEvent Driven Communications

Lifetime ValueNet 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 yearMain use: To evaluate strategy

Long term customers buy more often

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Number of purchases

per yer

1 2 3 4 5

Years as a customer

Long term customers buy higher priced items

$0

$10

$20

$30

$40

$50

$60

$70

Average Purchase

Price

1 2 3 4 5

Years as a customer

Retention rates go up over time

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Percentage Retained

from Previous

Year

1 2 3 4 5

Years as a customer

Model AssumptionsThere is only one customer segment Acquisition of new customers only happens

in year 1 Lapsed customers

Revenue Side of the Equation

Year 1 Year 2 Year 3Customers 20,000 8,000 3,600Retention rate in % 40 45 50Spending rate in $ 150 160 170

Total Revenue 3,000,000 1,280,000 612,000

Cost Side of the Equation

Variable costs in % 60 50 45Variable costs $ 1,800,000 640,000 275,400Acquisition cost @ $40 800,000 0 0

Total costs 2,600,000 640,000 275,400

Year 1 Year 2 Year 3

Profit Side of the EquationGross Profit = Total Revenues – Total

CostsDiscount Rate = [1+(i * rf)] n

where n = no of years to be discountedrf = 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

Gross profit 400,000 640,000 336,600Discount rate 1 1 1Net present value profit 400,000 551,724 249,333Cumulative NPV profit 400,000 951,724 1,201,057

Lifetime Value 20.00 47.59 60.05

Year 1 Year 2 Year 3

Scoring Customers – RFM AnalysisCreate 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 frequentlySpend a lot of money on your products and

services.

RecencyRecency 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 ago2 = Customers who made a purchase more than 3 months ago but fewer than 9 months ago3 = Customers who made a purchase in the last 3 months

FrequencyFrequency 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 months2 = Customers who made between two & 12 purchases in the past year.3 = Customers who made more than 12 purchases in the past year.

MonetaryMonetary 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 DataClarify or redefine the problem /opportunityMay actually provide solutionsMay provide primary research method

alternativesMay divulge potential difficultiesMay provide necessary background

information

Limitations of Secondary DataLack of availabilityLack of relevanceResources

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 SystemWhat 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 systemsDeal with a variety of data sourcesCost-benefit considerations

Characteristics of an MKISInteractiveFlexibleDiscovery orientedEasy to learn and use

Advantages of an MKISCost savingsIncreased understanding of the decision

environmentBetter decisionsImproved value of the information

Data MiningWhat 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 MiningPrimarily used by companies with a strong

‘customer’ focusWal MartNBA Advanced Scout

Data MiningData Mining

Customer AcquisitionCustomer retention or loyaltyCustomer abandonmentMarket-basket analysis