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5 - Descriptive Research
Terms in this set (19)
Research that provides an accurate snapshot (or describes) some aspect of the market environment.
-Comprises LARGE majority of marketing research studies.
Nature of Descriptive Research:
-Hypotheses are tested but are tentative and speculative
-Relationship studies will not be causal in nature.
3 Situations of when to use Descriptive Research:
1) Describing characteristics (eg. age, income)
2) Estimating proportion of people who behave in a certain way (eg. usage, consumption patterns)
3) Make predictions (eg. Demand estimation based on historical data)
3 Examples of Descriptive Data:
1) Profiles of segments (socio-demographics)
2) Market Shares
3) Historical University vs. High school GPA
2 Steps in Preparing Descriptive Research:
In order to ensure that the data and analyses will address the research objectives, we must:
1) Prepare dummy tables to catalog the data, results, and structure of analyses
2) Check each variable in data and the proposed analysis. Link them back to research objectives.
2 Types of data used in descriptive research:
Longitudinal Descriptive Data:
Involves examining similar data over longer periods of time.
Examples of Longitudinal Data:
-examining a specific variable from a specific customer group over a long period of time to form a trend
-High-school vs. University average GPA
2 Types of Longitudinal Data:
1) True panel
2) Omnibus panel
Involves using the same sample of respondents in order to gather longitudinal data.
Involves selecting a new sample of respondents each period from the total representative population in order to gather longitudinal data.
Advantages of Omnibus panel (over true panel):
-Easy access to participants
Advantages of True panel (over omnibus panel & cross-sections):
-Repeated measurements of same set of respondents allows researchers to find more insights (eg. turnover analysis/brand switching or loyalty rates)
Cross-Sectional Descriptive Data:
-A snapshot of a single point in time.
2 Most frequently used cross-sectional analyses:
Frequencies vs. Cross-Tabulations:
Frequencies - Occurrence of variables of interest, one at a time (eg. Yes/No)
Cross-tabulation - simultaneous occurrence of multiple variables of interest
Frequencies vs. Cross-Tab examples:
Frequencies - Do you believe in Santa Claus? Yes/No
Cross-Tabulation - takes the proportions of those replying Yes/No and places them into secondary categories (eg. Men/Women, or High/Low education)
Cross-sectional Data example: "brand choice" example
If we stood at a grocery store one day and asked 1,000 shoppers which brand of cereal they purchased, we will obtain data for time period 1.
If we stood at the same grocery store in a week's time and asked 1,000 other shoppers which brand of cereal they purchased, we will obtain data for time period 2.
Any changes between these variables will show relationships of brand market shares relative to the total consumer base.
However, in order to calculate brand loyalty/brand retention rates, we must use true panel data.
Longitudinal vs. Cross-sectional Data: (Variables to consider)
1) Turnover analysis/trends
2) Characteristics of Respondents
3) Representative Sample
4) Costs of maintaining sample
5) Cost per period
THIS SET IS OFTEN IN FOLDERS WITH...
1&2 - Introduction to Marketing Research: Approach…
3 - Marketing Research Process
4 - Exploratory Research (Research Designs)
6 - Causal Research
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