Lecture 1: MR Process Flashcards
MR Process Planning Stage: Figure out what to research
- Establish the need
- Define the problem
- Establish research objectives
MR Process Data Collection Design: Design the ways to do the research
- Identify information types and sources
- Determine methods of accessing data
- Design data collection forms
- Determine the sample plan and size
MR Process Data Collection Stage: Gather data
- Collect data
MR Process Analysis Stage: Generate findings and interpret them
- Analyze data
- Prepare and present the research report
Problem Definition
The most important step
- A problem well defined is half-solved
- “If you don’t know where you want to go, any road will get you there”
- Exploratory research is often needed to find out real problems (detecting symptoms is not enough!)
- Good communication b/w marketers and marketing researchers is important
Problems vs. Symptoms: Problem
A situation requiring some type of action
Problems vs. Symptoms: Symptom
Evidence that a problem exists
Problems = Opportunities (in many cases)
- A competitor’s new product - developing our new product
A customer’s complaint letter - quality improvement
Constructs are
Information
Operational definitions are
Data
When formulating research objectives
- Researchers should consider relevant & necessary constructs and their operational definitions to be used in the research
- Each decision problem may need multiple constructs, and each construct may need multiple operational definitions / measurements
Exploratory research
- Clarifying ambiguous problems
- What are probable causes?
(Our market share is declining, I don’t know why!)
Descriptive research
- Describing characteristics of a population
- Who, what, when, where, how
(Who buys our product? What features of our product do consumers like?)
Causal research
- Identifying cause and effect relationships among variables
- Why, what-if
(Will consumers buy more of our product if we change the product package design?)
Secondary data
Collected for some other purposes
Primary data
- Gathered specifically for the current research purpose
- Need to understand measurement, scaling, sampling issues
Types of secondary data
- Internal data
- Libraries
- Information vendors
- Books and periodicals
- Government data
- Broadcast media
- Trade associations
Types of primary data
- Observations
- Interviews
- Survey methods
- Experiments
Data Analysis
- Data cleaning
- Data coding
- Data entry
- Data analysis
Descriptive statistics
Revealing general patterns
Statistical inference
Testing hypothesis on population values
Difference analysis
Comparing two or more groups
Associative analysis
Investigating relationships among two or more variables
Predictive analysis
Enhancing prediction capabilities
