Business Research Methods
8
Secondary Data
Research in a Digital
Age
Topic: Data Collection Method
Chapter 8
Secondary Data Research
in a Digital Age
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not be scanned, copied or duplicated, or posted to a
publicly accessible website, in whole or in part.
Business Facts on a Grand Scale
• The use of secondary
data has exploded with
the advent of largescale electronic
information sources and
the web.
• Nielsen Claritas collects
and integrates businessrelated data from
difference sources.
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8-2
Secondary Data Research
• Secondary Data
• Data gathered and recorded by someone else
prior to and for a purpose other than the
current project.
• Advantages
• Disadvantages
 Available
 Uncertain validity
 Faster and less expensive
 Data not consistent with
than acquiring primary data
 Requires no access to
subjects
 Inexpensive—government
data is often free
 May provide information
otherwise not accessible
needs
 Inappropriate units of
measurement
 Too old
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–3
Secondary Data Research (cont’d)
• Data conversion
• The process of changing the original form of
the data to a format suitable to achieve the
research objective
◗ Also called data transformation
• Cross-checks
• The comparison of data from one source with
data from another source to determine the
similarity of independent projects.
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8–4
EXHIBIT 8.1
Evaluating Secondary Data
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8–5
Typical Objectives for Secondary-Data
Research Designs
• Fact Finding
• Identification of consumer behavior for a
product category
• Trend Analysis
◗ Market tracking—the observation and analysis of
trends in industry volume and brand share over
time.
• Environmental Scanning
◗ Information gathering and fact-finding that is
designed to detect indications of environmental
changes in their initial stages of development.
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–6
Typical Objectives for Secondary-Data
Research Designs
• Model Building
• Estimating market potential for geographic
area
• Forecasting sales
• Analysis of trade areas and sites
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–7
Data Mining
• Data Mining
• The use of powerful computers to dig through
volumes of data to discover patterns about an
organization’s customers and products; applies
to many different forms of analysis.
• Neural Network
• A form of artificial intelligence in which a
computer is programmed to mimic the way
that human brains process information.
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–8
Mining Data from Blogs
• Data-mining
software, like Buzz
Report, search
millions of blogs
looking for
messages related to
particular products
and trends.
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8-9
Data Mining (cont’d)
• Market-Basket Analysis
• A form of data mining that analyzes
anonymous point-of-sale transaction
databases to identify coinciding purchases or
relationships between products purchased and
other retail shopping information.
• Customer Discovery
• Involves mining data to look for patterns
identifying who is likely to be a valuable
customer.
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–10
Database Marketing and Customer
Relationship Management
• Database Marketing
• The use of customer relationship management
(CRM) databases to promote one-to-one
relationships with customers and create precisely
targeted promotions.
• The practice of maintaining a customer database
of:
◗ Names and addresses
◗ Past purchases
◗ Responses to past efforts
◗ Data from numerous other outside sources
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–11
Sources of Internal Secondary Data
• Internal and Proprietary Data
• Accounting information
• Sales information and backorders
• Customer complaints, service records, warranty
card returns, and other records.
• Intranets
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8–12
External Secondary Data Sources
• External Data
• Generated or recorded by an entity other than the researcher’s
organization.
• Information as a product and its distribution
•
•
•
•
Libraries
Internet
Vendors
Producers
◗ Books and periodicals
◗ Government
◗ Media
◗ Trade associations
◗ Commercial sources
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–13
EXHIBIT 8.7
Information
as a Product
and its
Distribution
Channels
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8–14
Commercial Sources
• Market-share data
• Demographic and census updates
• Consumer attitude and public opinion
research
• Consumption and purchase behavior data
• Advertising research
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–15
Single-Source and Global Research Data
• Single-Source Data
• Diverse types of data offered by a single company.
• Usually integrated on the basis of a common
variable (i.e., geographic area or store).
• Government Agencies
• Global secondary data
◗ Typical limitations of secondary data
◗ Additional pitfalls
 Unavailable in some countries
 Questionable accuracy (political influences)
 Lack of standardized research terminology
• CIA’s World Factbook; National Trade Data Bank
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
8–16
Around the World of Data
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8-17
Business Research Methods
8
Survey Research:
An Overview
Survey Research: An Overview
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publicly accessible website, in whole or in part.
Survey Research
• Respondents
• People who verbally answer an interviewer’s
questions or provide answers to written
questions.
• Sample Survey
• A survey that emphasizes contacting
respondents who are a representative sample
of the target population.
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9–19
Using Surveys
• Survey Objectives
• Surveys attempt to describe what is happening,
what people believe, what they are like, or to learn
the reasons for a particular business activity.
• Survey research is descriptive research:
◗ Identifying characteristics of target markets
◗ Measuring consumer attitudes
◗ Identifying information regarding activities that could
make the company more “green”
• Surveys can be both quantitative and qualitative.
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
9–20
Advantages of Surveys
• Advantages of Surveys
• Gathering information via surveys is:
◗ Quick
◗ Inexpensive
◗ Efficient
◗ Accurate
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9–21
Errors in Survey Research
• Random Sampling Error
• A statistical fluctuation that occurs because of
chance variation in the elements selected for a
sample.
• Systematic Error
• Error resulting from some imperfect aspect of the
research design that causes respondent error or
from a mistake in the execution of the research.
• Sample Bias
• A persistent tendency for the results of a sample to
deviate in one direction from the true value of the
population parameter.
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9–22
EXHIBIT 9.1
Categories of Survey Errors
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9–23
Respondent Error
• Respondent Error
• A category of sample bias resulting from some
respondent action or inaction such as
nonresponse or response bias.
• Nonresponse Error
• The statistical differences between a survey
that includes only those who responded and a
perfect survey that would also include those
who failed to respond.
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9–24
Respondent Error
• Nonrespondents
• People who are not contacted or who refuse to
cooperate in the research.
◗ No contacts: people who are not at home or who are
otherwise inaccessible on the first and second contact.
◗ Refusals: People who are unwilling to participate in a
research project.
• Self-Selection Bias
• A bias that occurs because people who feel
strongly about a subject are more likely to respond
to survey questions than people who feel
indifferent about it.
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9–25
Response Bias
• Deliberate Falsification
• Occasionally people deliberately give false
answers.
◗ Misrepresent answers to appear intelligent
◗ Conceal personal information
◗ Avoid embarrassment
• Average-person hypothesis:
◗ Individuals may prefer to be viewed as average, so
they alter their responses to conform more closely
to their perception of the average person.
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9–26
Response Bias
• Unconscious Misrepresentation
• When a respondent is consciously trying to be truthful
and cooperative, response bias can arise from the
question format, the question content, or some other
stimulus that affects their response to a question.
• Sources of misrepresentation:
◗ Misunderstanding the question
◗ Unable to recall details
◗ Unprepared response to an unexpected question
◗ Inability to translate feelings into words
◗ After-event underreporting
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9–27
Types of Response Bias
• Acquiescence Bias
• A tendency to agree with all or most questions.
• Extremity Bias
• The tendency of some Individuals to use extremes when
responding to questions.
• Interviewer Bias
• The presence of the interviewer influences respondents’ answers.
• Social Desirability Bias
• Bias in responses caused by respondents’ desire, either conscious
or unconscious, to gain prestige or appear in a different social
role.
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9–28
Administrative Error
• An error caused by the improper
administration or execution of the research
task.
• Data-processing error: incorrect data entry,
incorrect computer programming, or other
procedural errors during data analysis.
• Sample selection error: improper sample design or
sampling procedure execution.
• Interviewer error: mistakes made by interviewers
failing to record survey responses correctly.
• Interviewer cheating: filling in fake answers or
falsifying questionnaires by an interviewer.
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9–29
Classifying Survey Research Methods
• Structured/Unstructured Questionnaires
• Structured question: imposes a limit on the
number of allowable responses.
• Unstructured question: does not restrict
respondents’ answers.
• Disguised/Undisguised Questionnaires
• Undisguised questions: assume the respondent
is willing to answer.
• Disguised questions: assume the purpose of
the study must be hidden from the respondent.
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9–30
The “Mere-Measurement” Effect
• Means that simply
answering a question about
intentions will increase the
likelihood of the underlying
behavior—if the behavior is
socially desirable.
• If respondents receive
information that puts them
on their guard against
persuasion, the meremeasurement effect is
lessened and sometimes
even generates the
opposite behavior.
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9-31
Classifying Survey Research Methods (cont’d)
• Temporal Classification
• Cross-sectional study: various segments of a
population are sampled and data are collected
at a single moment in time.
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9–32
Categorizing Survey Research Methods (cont’d)
• Temporal Classification (cont’d)
• Longitudinal study: A survey of respondents at
different times, thus allowing analysis of response
continuity and changes over time.
◗ Tracking study: uses successive samples to compare trends
and identify changes in variables such as consumer
satisfaction, brand image, or advertising awareness.
◗ Consumer panel: a survey of the same sample of individuals
or households to record (in a diary) their attitudes, behavior,
or purchasing habits over time.
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9–33