Midterm 1 Flashcards
(45 cards)
What is Marketing Research?
A collection of techniques for collecting, recording, analyzing and interpreting date for business decision making.
Backward marketing research
Research done from the end, product-forward. Produces action-oriented results.
How to qualify marketing research
Reliability, cost, potential profits with/without info, management’s ability to use info
Expected profit
E(profit) = probability*profit1 + probability*profit2 E(info) = E(Profit + Info) - E(Profit)
Exploratory Research
Used when there is an ambiguous problem. Requires secondary data, qualitative data.
Descriptive Research
Used when the problem is somewhat defined, need to know how to solve it. Requires a survey.
Causal Research
Used when problem is clearly defined to find solutions. Requires an experiment.
Primary data sources
Benefits: Up to date, perfect fit for questions, control over how it is collected.
Qualitative: Focus group, interview
Quantitative: Survey, Experiment
Secondary data sources
Benefits: Cheaper than primary data, readily available. Good starting point.
Sources of Data
Scanner Data: literally use scanners, see who’s buying what. Can’t see why
Single-source Data: Nielsen ex. Use stream of data from single consumer (panel)
Geo-segmentation: Segmentation by demographics, lifestyle
Attitudes, Intentions, Behavior
Attitude: a positive or negative evaluation of a product
Intention: an indication of an individual’s readiness to perform a given behavior
Behavior: an individual’s observable response
When to use qualitative research?
Exploratory studies: to establish basis for quantitative research
New product development: after quantitative research to identify gaps
Focus groups: Pros and cons
Pros: Easy, good for in-depth info, complex issues can be discussed, one person’s experiences stimulate others
Cons: Superficial reactions, not quantifiable, group process may stunt frank exchange, minority viewpoints may not be heard
Zaltman Metaphor Elicitation Technique
Uses metaphor to reveal unconscious thoughts and thoughts based on sensory info
Primary Data: Qual vs. Quant
Qual: Small # of cases, unstructured data, nonstatistical inference, give richer understanding
Quant: large # of cases, structured, statistical inference, recommends final course of action
Types of scales
Nominal: Categorical. Measures frequency of recorded variable. Ex: Male or female
Ordinal: Categorical. Can be ranked. Ex: 1-5 min, 6-10 min, etc.
Interval: Quantitative. Data can be treated as numbers. Ex: strongly disagree - strongly agree (1-5)
Ratio: Quantitative. Fill-in the blank, numbers are numbers. Ex: what is your annual salary? ___
Central tendency
Mean.
Dispersion
Variance/standard deviation
Ratio scales
Likert: agree - disagree
Rank-order: rank items by importance
Paired comparison: which of these two do you prefer?
Requirements of causal inference
- Correlation
- Temporal Antecedence (x must come before y)
- No third factor driving both
What kind of data can be used to determine causation?
Only experimental data. Correlational data (scanner, surveys) cannot be used.
Reliability
Will I get the same result if I measure again? Affected by random error.
Validity
Am I measuring what I am supposed to measure? Affected by systematic error.
Observed v. True Score
O = T + e(systematic) + e(random)
