Untitled Deck Flashcards
(62 cards)
1
Q
The problem businesses have
A
Marketers need information to develop and deliver products and/or services that can satisfy their customers’ need.
2
Q
Marketing Research
A
The process of gathering and interpreting data for use in developing, implementing, and monitoring the firm’s marketing plans.
3
Q
Examples of questions marketing research can help answer
A
Planning- What kind of products are people buying?
Problem Solving- Questions regarding product, place, promotion, process, people
Control- How does our product compare to competitors, Are customers satisfied with our product?
4
Q
Reasons why studying market research is important
A
- Some students will discover that marketing research can be rewarding and fun
- To learn to be a smart consumer of marketing research results.
- Gain an appreciation of the process what it can and can not do.
5
Q
Steps in the Marketing Research Process
A
- Define information using exploratory research (Problem)
- Capturing data necessary for satisfying the information need. This can be accomplished by using existing data from inside or outside the firm or by collecting new data of various types for the problem or opportunity at hand (Data Collection)
- Data analysis and interpreting data
- Information Reporting
6
Q
Research to Avoid
A
Advocacy research is conducted to support a position rather than to find the truth about an issue
- sugging attempts to sell products or services or ideas under the guise of marketing research.
Research should also be avoided when resources, such as time and budget, to do the research appropriately are lacking
7
Q
Problem formulation process
A
- Meet with client
- Clarify the problem/opportunity
- State the managers decision problem
- Develop a full range of possible research problems
- Select research problem
- Prepare and submit the research request agreement
8
Q
Difference between planned and unplanned change
A
- Unplanned changes in the marketing environment: how a firm responds to new technology, a new product introduced by a competitor, or a change in demographics or lifestyles
- Planned changes in the marketing environment: development and introduction of new products, improved distribution, more effective pricing, and promotion.
Planned change is oriented more toward the future and is proactive; unplanned change tends to be oriented more toward the past and is often reactive. Planned change is change that the firm wishes to bring about
9
Q
Discovery-oriented decision problem
A
Decision problem that typically seeks to answer “what” or “why” questions about a problem/opportunity. The focus is generally on generating useful information.
10
Q
Strategy-oriented decision problem
A
A decision problem that typically seeks to answer “how” questions about a problem/opportunity. The focus is generally on selecting alternative courses of action.
11
Q
Research problem
A
A statement of the decision problem in research terms, from the researcher’s perspective.
12
Q
Sections in a research agreement
A
- Background: The events that led to the manager’s decision problem
- Decision Problem: The underlying question confronting the manager. A brief discussion of the source of the problem (i.e., planned versus unplanned change) should be included, along with a discussion of (a) whether the problem is discovery-oriented or strategy-oriented and (b) whether this is a onetime or recurring information need
- Research problem(s): The range of research problems that would provide input to the decision problem
- Use: The way each piece of information will be used.
- Population and subgroups: The groups from whom the information must be gathered.
- Logistics: Approximate estimates of the time and money available to conduct the research
13
Q
The four primary Vs of “big data.”
A
Volume, Velocity, Variety, Veracity
14
Q
Volume
A
The sheer amount of data being collected in “big data” systems.
15
Q
Velocity
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The pace of data flow, both into and out of a firm
16
Q
Variety
A
The combination of structured and unstructured data collected in “big data” systems
17
Q
Veracity
A
The accuracy and trustworthiness of data collected in “big data”systems
18
Q
Big Data
A
The process of capturing, merging, and analyzing large and varied data sets for the purpose of understanding current business practices and seeking new opportunities to enhance future performance.
19
Q
Descriptive Analysis
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Designed to enhance understanding of available data to benefit firm performance
20
Q
Predictive Analysis
A
Designed to aid both explanatory and forecasting abilities for the betterment of the firm. Differs from descriptive analysis in that predictive analysis focuses on future-oriented, potential behaviors as opposed to merely classifying past behaviors.
21
Q
Prescriptive Analysis
A
Designed to optimize the various courses of action available to enhance firm performance.
22
Q
Causal Research
A
The major emphasis is on determining cause-and-effect relationships.
- typically take the form of experiments because experiments are best suited for determining cause and effect
23
Q
Descriptive Research
A
Describing a group on various characteristics (e.g., brand attitude,preferences, demographic variables) or the relationship between characteristics (e.g., is brand attitude different forsenior adults versus young adults?)
24
Q
Exploratory Research
A
Exploratory: Investigates unknown topics (e.g., interviews to find new trends).
25
To say that one thing "caused" another, three conditions must be met
1. There must be consistent variation betweenthe cause and the effect
2. The time order of the cause and the effect must be correct
3. Other explanations must be eliminated
26
3 major purposes of descriptive research
1. To describe the characteristics of certain groups
2. To determine the proportion of people who behave in a certain way
3. To make specific conditions
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Cross-sectional study
Investigation involving a sample of elements selected from the population of interest that are measured at a single point in time
- a single survey on coffee preferences (sample survey)
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Longitudinal study
Investigation involving a fixed sample of elements that is measured repeatedly through time
- yearly survey on coffee habits
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Continuous Panel
A fixed sample of respondents who are measured repeatedly over time with respect to the same variables
- monthly tracking of coffee sales
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Discontinuous panel
A fixed sample of respondents who are measured repeatedly over time but on variables that change from measurement to measurement
- coffee trend surveys every 5 years
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Examples of Observational Research
Direct observation:watching the actual activity.
Indirect Observation: the outcomes of the behavior are observed, rather than the behavior itself.
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Structured observation
Method of observation in which the phenomena to be observed (typically behaviors) can be defined precisely along with the categories used to record the phenomena
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Unstructured observation
Method of observation in which the researcher has agreat deal of flexibility in terms of what to note and record- used in explaoratory research more than any other
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Undisguised Observation
The subjects are aware that they are being observed
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Disguised observation
The subjects are not aware that they are being observed
36
Main methodsof administering questionnaires
Online surveys
- including mobile surveys and online communities
Telephone interviews
Personal interviews
Paper-based surveys
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3 aspects to consider in questionaires
Sampling control refers to the ability of a particular method to identify and obtain responses from a sample of respondents from the target population.
Information control is concerned primarily with the number and types of questions that can be used and the degree to which researchers and/or respondents might introduce errors into the answers or their interpretations.
Administrative control refers to resource issues, such as the time and monetary costs of the different approaches
38
Validity
The extent to which differences in scores on a measuring instrument reflect true differences among individuals, groups, or situations in the characteristic that it seeks to measure or true differences in the same individual, group, or situation from one occasion to another, rather than systematic or random errors- It refers to the accuracy or truthfulness of a measurement.- Does the measurement actually measure what it is supposed to measure?
39
Reliability
Ability of a measure to obtain similar scores for the same object, trait,or construct across time, across different evaluators, or across the items forming the measure- It refers to the consistency or stability of a measurement over time.- Does the measurement produce consistent results?
- consistently hitting the center of target
40
Measurement
The process of assigning numbers to represent properties of an object's attributes
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Four levels of measurement
Nominal Scale (Lowest Level)
- numbers are assigned to objects or classes of objects solely for the purpose of identification and nothing else (SSN)
- The modeis the only legitimate summary measure of central tendency or average
Ordinal
- Numbers are assigned to data on the basis of some order (e.g., more than, greater than) of the objects.
- Because there is an order of respondents, we can use the median to find average
- "Rank these drinks"
Interval- The assigned numbers legitimately allow the comparison of the size of the differences among and between members
- The mean is "meaningful" for interval scales because of the equal intervals between scale positions.
Ratio (Hghest level)
- Measurement that has a natural, or absolute, zero and therefore allows the comparison of absolute magnitudes of the numbers
- Height and Weight
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Question Design Including Response Options and Clear Word Choices
Asking a simple "why" question opens the door for people to use different frame of reference. So, break the question into two.
- Ex: How did you start using Crest? What is your primary reason for using it?
That's one reason that pretesting is soimportant—to make sure that a question won't be interpretedin different ways by different people
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How do we improve our chances that a respondent knows the answers to our questions?
Filter question: A question used to determine if a respondent is likely to possess the knowledge being sought; also used to determine if an individual qualifies as a member of the defined population
- AKA screening or qualifying question
44
Sampling frame
The list of population elements from which a sample will be drawn; the list might consist of geographic areas, institutions, individuals,or other units
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Population
All cases that meet designated specifications for membership in the group
- All college students in the U.S.
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Sample
Selection of a subset of elements from a larger group of objects
- A smaller group selected from the population to make inferences about the whole
- 1,000 randomly chosen college students from different universities.
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Selecting a Sample procedure
Sampling techniques can be divided into two broad categories: probability and nonprobability samples
nonprobability sample
- A sample that relies on personal judgment in the elementselection process.
Probability sample
A sample in which each target population element has a known, non zero chance of being included in the sample
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6 step process for drawing a sample
Define the Target Population
Identify the Sampling Frame
Select a Sampling Procedure
Determine the Sample Size
Select the Sample Elements
Collect the Data from the Designated Elements
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6 Types of Sampling Error
Sampling Error
- The difference between the sample's results and the true population results, due to random chance.
- Ex: If you survey 100 people but their opinions don't perfectly match the entire population.
Noncoverage Error
- When some groups in the population are left out of the sample.
- Ex: Surveying only online users, but missing people without internet access.
Nonresponse Error
- When some selected people don't respond to the survey
- Ex: You select 100 people, but only 60 answer your survey.
Response Error
- When people give incorrect answers, either by mistake or on purpose
- Ex: A person misremembering or deliberately lying about their age.
Recording Error
- Mistakes made when recording or entering data.
- Ex: Typing the wrong number when inputting survey responses.
Office Error
- Mistakes made during the analysis or processing of data.
- Ex: A data entry clerk accidentally miscalculates totals in the report.
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Ways to improve response rates
Survey Lenght
- Dont have long ones
Guarantee of Cofidentiality
- Promise to keep identity private
Interview Characteristics and Training
- Try to make interview have similar background to person being interviewed
Personalization
Response Incentives
Follow up survey and reminder
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Response rate
The number of completed interviews with responding units divided by the number of eligible responding units in the sample.
52
Data Coding
The process of transforming raw data into symbols (usually numbers). Build a codebook.
- Ex: 0= No, 1= Yes
A codebook contains explicit directions about how raw data for each case are coded in the data file.
- The transformation involves judgment on the partof the coder. Ex: Coder rounds "sometimes as Yes rather than No
53
Two forms of hypothesis
Null (Ho)
- proposed result is not true for the population
- The null hypothesis assumes no effect or relationship
- There is NO difference
Alternative (Ha)
- a proposed result is true for the population- suggests that an effect or relationship does exist.
- There IS a difference
54
Testing Hypothesis about individual variables
Significance level: The acceptable level of error selected by the researcher,usually set at 0.05. The level of error refers to the probability of rejecting the null hypothesis when it is actually true for the population
p -value:The probability of obtaining a given result if the null hypothesis were true in the population.
chi-square goodness-of-fit test:A statistical test to determine whether some observed pattern of frequencies corresponds to an expected pattern
55
Cross tabulation
A multivariate technique used for studying the relationship between two or more categorical variables. The technique considers the joint distribution of sample elements across variables
In most multivariate analyses, you'll determine whether one variable (the independent or predictor variable) has an influence on another variable (the dependent or outcome variable).
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Pearson chi-square (X 2) test of independence
A commonly used statistic for testing the null hypothesis that categorical variables are independent of one another
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Independent samples t-test for means
A technique commonly used to determine whether two groups differ on some characteristic assessed on a continuous measure.
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Paired sample t-test
A technique for comparing two means when scores for both variables are provided by the same sample.
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Pearson product-moment correlation coefficient
A statistic that indicates the degree of linear association between two continuous variables. The correlation coefficient can range from -1 to +1
60
Preparing the Oral Presentation
keep in mind that many of your listeners won't fully understand the technical aspects of your research
quality presentation can disguise poor research to some extent, but quality research cannot improve a poor presentation.
Use a lot of simple slides, one minute per slide, make easy to read
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OPEN UP Presentation Skills
Organized
- Take charge! They look poised and polished. They sound prepared. They do not waste time. Their goal is not tooverwhelm, but to inform, persuade, influence, entertain or enlighten. Their message is well-structured and clearly defined
Passionate
-Exude enthusiasm and conviction. If the presenter doesn't look and sound passionate about the topic, whywould anyone else be passionate about it? Exceptional presenters speak from the heart and leave no doubt as to where they stand. Their energyis persuasive and contagious.
Engaging
- Engage each audience member. They build rapport quickly and involve the audi-ence early and often. If you want their respect, you must first connect
Natural
- Conversational feel. Make it look easy. They appear comfortable with any audience. A presenter who appears natural appears confident.
Understand Your Audience
- Learn as much as they can about their audience before presenting to them. The more theyknow about the audience, the easier it will be to connect and engage
Practice
- Those who practice improve. Those who don't, don't. Exceptional skills must become second nature. Practice is the most important partof the improvement process. If your delivery skills are second nature, they will not fail under pressure
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Two fundamental rules of delivering a good oral presentation
Know your stuff
Know your audience: Always keep in mind the purpose of the research and the general answers your audience is interested in learning about. You'll also need to understand the level of technical sophistication of the overall audience. No jargon
