1. Business Research Methods William G. Zikmund
Chapter 8:
Secondary Data

2. Chapter 8: Exploratory Research and Qualitative Analysis
1. Definition of Secondary Data 2. Advantages & Disadvantages of Secondary Data 3. Typical Objectives for Secondary Data Research Designs 4. Classification of Secondary Data

3. 1. Definition of Secondary Data
Data gathered and recorded by someone else prior to and for a purpose other than the current project
Is often:
Historical
Already assembled
Needs no access to subjects

4. 2. Advantages & Disadvantages of Secondary Data
Inexpensive
Obtained Rapidly
Information is not Otherwise Accessible
Disadvantages:
Uncertain Accuracy
Data Not Consistent with Needs
Inappropriate Units of Measurement
Time Period Inappropriate; Secondary Data may be Dated

5. Evaluating Secondary Data
Does the data help to
answer questions
set out in the
problem definition?
Applicability
to project
objectives
Does the data apply to
the time period of
interest?
Does the data apply to
the population of
interest?

6. Evaluating Secondary Data (continued)
Do the other terms
and variable
classifications
presented apply?
Applicability
to project
objectives
Are the units of
measurement
comparable?
If possible, go to the
original source of the
data?
Accuracy
of the data

7. Is the cost of data acquisition worth it? Is there a possibility
Accuracy
of the data
Is there a possibility
of bias?
Can the accuracy of
data collection be
verified?
Use data

8. 3. Typical Objectives for Secondary Data Research Designs
Fact Finding:
Identifying consumption patterns
Tracking trends
Model building:
Estimating market potential
Forecasting sales
Selecting trade areas and sites
Data Base Marketing (Data Mining):
Development of Prospect Lists
Enhancement of Customer Lists

9. 3.1. Fact Finding
Aim: to collect descriptive and comparative information to support decision making.
Comparing company’s data with (e.g. total annual sales) company’s competitors data and/or
Comparing company’s present data with company’s own data in other time periods.

10. 3.2. Model Building
Aim: to calculate a dependent variable by using independent variable(s) having specific effects on this dependent variable.
First, facts about one or more independent variables are collected;
Then, the effects or ratios of these independent variables on the dependent varible will be specified
Finally, the dependent variable will be calculated.

11. 3.3. Data Based Marketing (Data Mining)
Aim: to dig through and analyze volumes of data to discover patterns about a company’s customers, products, and activities.
Practice of maintaining a customer data base
Names
Addresses
Past purchases
Customers’ responses to company’s past efforts
Data from numerous sources

12. 4. Classification of Secondary Data
Data can be classified according to the origin:
Internal Data
External Data

13. 4.1. Internal Data Internal and proprietary data are more descriptive
Examples for internal data:
Accounting information
Sales information
Backorders or rejected orders
Customer complaints

14. 4.2. External Data
Data created, recorded, or generated by an entity other than the researcher’s organization
Examples for External Data sources:
Government
Trade associations
Newspapers and journals
Libraries, Books and periodicals
The Internet
Vendors and Producers, etc.