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Research Design. Jeremy Kees, Ph.D. Formulate Problem. Stages in the Research Process. Determine Research Design. Design Data Collection Method and Forms. Design Sample and Collect Data. Analyze and Interpret the Data. Prepare the Research Report.
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Research Design Jeremy Kees, Ph.D.
Formulate Problem Stages in the Research Process Determine Research Design Design Data Collection Method and Forms Design Sample and Collect Data Analyze and Interpret the Data Prepare the Research Report
Important Design Issues to Consider • How well do you understand the problem? • Not very well = exploratory research needed • What is your budget? • Low = exploratory research • Do you have access to a large sample? • If not, exploratory research is the way to go
Important Design Issues to Consider • Do you need to understand how a specific population feels about a particular issue? • Attitudes, evaluations, preferences, etc.? • Are you trying to choose between options? • Advertising campaign ideas or specific ads
Overview of Research Design Exploratory • “discovery” Descriptive • “relationships” Experimental • “cause-and-effect”
Typology of Marketing Research • By Source • Primary • Secondary • By Methodology • Qualitative • Quantitative • By Objectives • Exploratory • Descriptive • Experimental (Causal)
Qualitative vs. Quantitative Research • Depth versus Generalizability • Quantitative Methods • Generalizations to other populations and/or situations • Qualitative Methods • Rich Understanding • Common Assumption: • Qualitative Data = preliminary • Quantitative Data = confirmatory
Qualitative Research To gain a qualitative understanding of the underlying reasons and motivations Small number of non-representative cases Unstructured Non-statistical Develop an initial understanding Quantitative Research To quantify the data and generalize the results from the sample to the population of interest Large number of representative cases Structured Statistical Recommend a final courseof action Objective Sample Data Collection Data Analysis Outcome Qualitative vs. Quantitative Research 8
Benefits of Qualitative Research • Less expensive • Smaller sample size • Opportunity to probe respondents • Observation of “real” customer reactions • Great depth of information • Can give you “direction” for decisions • Typically informs quantitative research • Inexpensive/quick qual research can help tremendously in developing more extensive quant research
Relationship Among Research Designs Descriptive Research ExploratoryResearch Causal Research 10
Focus Groups • Focus groups: small group discussions led by a trained moderator • Objectives: • Generate ideas • Understand consumer vocabulary • Reveal consumer needs, motives, perceptions, and attitudes on products and services • Understand findings from quantitative studies 12
In-Depth Interviews (IDIs) • In-Depth interview • A set of probing questions posed one-on-one to a subject by a trained interviewer so as to gain an idea of what the subject thinks about something or why he or she behaves a certain way 13
Other Qualitative Methods • Ethnographies • developing understandings of the everyday activities of people in local settings • Observation • Insight into actual, not reported, behaviors • Mystery Shopping • Protocol analysis • involves placing a person in a decision making situation and asking him or her to verbalize everything he or she considers when making a decision
“Alternative” Techniques • Implicit Association Test • https://implicit.harvard.edu/implicit/ • Eye Tracking • Resistometer
Descriptive Research • For our purposes, “survey” research • Asking a sample of people from a population a set of questions • Using the answers to describe that population • Common Goals • Describe what is going on or exists • Estimate how groups of consumers might behave • Examine relationships between two or more variables • Predict
Descriptive Research • In contrast to exploratory (qualitative) techniques, the purpose of survey research is to produce statistics • In contrast to exploratory (qualitative) techniques, survey research is concerned with generalizability • Sampling becomes very important
Descriptive Research • Three key aspects • Designing questions • Sampling • Data collection • We want to have a study that is precise, credible, and accurate • A key issue is reducing error throughout the process (Fowler) • Poor attention to ANY of these aspects can result in poor results (Fowler, Ch. 13)
Descriptive Research • Two Basic Types • Longitudinal • FUF • CWL • Cross-Sectional • NFI
FOP Segmentation Survey Data S6 Compenent 1 S3 S4 Compenent 2 S5 Compenent 3 Compenent 4 S1 S2 Compenent 5 Compenent 1 Compenent 2 Compenent 3
FOP Segmentation • SEGMENT 2 DESCRIPTION • 15% of mom population • More kids = large HH • Older kids (ages 11-15) • Diverse (mostly Hispanic) • Many Spanish speakers • Nutrition content is imp in food purchase decisions • Urban • South • Low education (completed some HS) • Likes to shop at Whole Foods • Lower income (<$25K) Low Knowledge Moderate to High Motivation Knowledgeable Low High Low High Motivated
FOP Segmentation • SEGMENT 6 DESCRIPTION • 8% of mom population • Mostly white • Feel knowledgeable about nutrition • Exercise the most of the segments • West • Highly educated (college+) • Shops at Trader Joe’s and Whole Foods • Use Nutrition Facts Panel more than other segments • Higher income ($100K+) High Knowledge High Motivation Knowledgeable Low High Low High Motivated
Limitations… • Can we infer causation from a strong correlation? • Survey research is limited by what people are willing and able to tell us in the context of a survey • This limitation can be addressed using other methods (triangulation)
Experimental Research • Helps us determine if one or more IVs (treatment, predictors) causes or affects one or more DVs (outcome variables) • Most demanding design—strongest conclusion • Requires the highest degree of understanding of the problem
Example…. • Do Cigarette Warning Labels work? • CBS
Trade-Offs in Types of Experimental Designs NFI Project • Between-Subjects • Strongest design to get “true” effects • Toughest to get significant differences across treatment conditions • Within-Subjects • Prone to demand effects • Most likely to get significant differences across treatments • Client satisfaction vs. rigor
Evidence that supports a causal inference… • Correlation • Observe the relationship (variability) between ad spend and sales • Independent variable (treatment) occurs before the dependent (outcome) variable • Change ad spend and look for an effect on sales. • Eliminate “Alternative Explanations” • If we observe an increase in sales when we increase ad spend…. • Were there changes in any other parts of our marketing mix? • What is going on with the economy? • Any changes in competition’s ad spend? • Etc, etc, etc……
Causal Research (Experimental Design) • Internal Validity
Causal Research (Experimental Design) • External Validity
To conclude… • Experiments are the only way to show causation • But often take a back seat to descriptive studies due to time, cost, and control issues • Exploratory and descriptive studies are useful, but be careful not to infer too much • Correlation is not causation • Again, let your research questions dictate your design!
Some practical issues…. • Qualtrics Research Platform • Free you under VSB’s “site license” • Extremely user friendly, but also very robust • www.qualtrics.com
Some practical issues…. • Amazon Mechanical Turk • The most inexpensive way to collect consumer data • Extremely user friendly, but also very robust • www.mturk.com
Online Survey (created by you and housed on Qualtrics’ server) • Create HIT (Human Intelligence Task) on Mturk • Description of your study and a (Qualtrics) link to it Mturk workers (survey responders) “work” on your HIT (i.e., they take your survey) Data is recorded by Qualtrics. Participants who complete the survey are given a code to input into Mturk. Those that enter a valid code, get paid. Everyone is happy
Team Assignment #2 • Refine your research questions • Need to be clear, concise, and “testable” • Based on your research questions • Design 2 potential studies that could address your research questions • Explain the benefits and weaknesses of each approach • Pick the “best” design and explain your decision (Note: Don’t worry about measurement or sampling too much---you’ll have your chance to do that later)