Interview Techniques and Data Collection

Market Research

• Market research connects customers and marketers through information
• Goals: Improve customer satisfaction through product development and marketing strategies better than competitors
• Role in decision making:
  • Define marketing issues
  • Identify relevant data
  • Collect data
  • Process information for better management
  • Find solutions to marketing problems
• When to conduct Market Research:
  • Insufficient existing information
  • Research results are usable
  • Time available for data analysis
• Caution: Market research can be manipulated
• Example: Satisfaction evaluation with mobile operator (using balanced versus unbalanced scales)

Market Research Process

• Problem Definition (Planning):
  • Set research objectives
  • Define the marketing problem clearly (avoiding misinterpretations)
  • Define researcher's problem and decisions alternatives
• Research Design (Design):
  • Identify needed information
  • Decide research type (exploratory or conclusive)
  • Define target population
  • Define sample frame and selection process
  • Design and test data collection methods
  • Determine sample size
• Data Collection (Performance):
  • Conduct qualitative/quantitative research
  • Test the subject/questionnaire
  • Train/select field staff
  • Collect data (fieldwork)
  • Quality data control
• Data Analysis (Performance):
  • Analyze respondent thoughts on the marketing issue
  • Check data accuracy and consistency
  • Summarize data into tables
• Report and Recommendations (Performance):
  • Management receives summary of results and conclusions
  • Report is the major project evaluation tool

Data Collection: Questionnaire and Scales

• Questionnaires: structured instruments for collecting data from respondents
• Types of scales:
  • Closed (e.g., satisfaction)—easy to analyze
  • Semi-open (e.g., reason for choice)—fixed options but allows additional details
  • Open (e.g., suggestions)—used for open-ended responses (not most common)
• Questionnaire design considerations:
  • Clear, precise wording
  • Order of questions (consider potential bias)
  • Question types (e.g., multiple choice, rating scales)
  • Qualitative (open) versus quantitative (closed) questions
• Question wording:
  • Correctly define the issue (singular/plural, who, what, when, where)
  • Accessible language (avoid ambiguity)
  • Avoid biased or leading questions
• Question order:
  • Qualifying questions (e.g., targeting criteria)
  • Basic information
  • Classification questions (socio-economic/demographic)
  • Sensitive questions (place at the end of the questionnaire)
• Questionnaire design is subjective, but there are rules for good structure
• Types of scales (Nominal, Ordinal, Interval, Ratio)

Types of Empirical Sampling

• Convenience Sampling: accessible individuals
• Judgmental Sampling: researcher's opinion of suitability
• Quota Sampling: sample proportionally represents subgroups within the population
• Iterative sampling: choosing households in a specific route (e.g., specific building or route)
• Snowball Sampling: respondent recommends others in the population
• Place of consumption sampling: (e.g., in a shopping center, restaurant)

Probabilistic/Random Sampling

• Simple Random Sampling: each individual has an equal chance of selection
• Stratified Random Sampling: population divided into groups and individuals randomly sampled from each group
• Cluster Sampling: population divided into clusters and a few clusters selected at random
• Two-stage sampling: similar to cluster sampling, but further random sampling of individuals within the selected clusters

Non-sampling Errors

• Errors in measurement and data processing.
  • Example: Inaccurate transcription or coding errors
• Coverage Errors: not all individuals or subgroups of the population are represented in the frame or sample
• Nonresponse errors: individuals selected don't participate in the survey
  • Method for treatment: additional attempts for contact, incentives and careful questioning design

Presentation of Results

• Report must be easy to follow, written with precision, and accurate. It must be comprehensive for the reader. Should contain detailed results, conclusions, recommendations, detailed appendices, technical terminology must be avoided