The Difference Between Open-Ended Questions And Closed-Ended Questions Is That Marketing Research Basics

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Marketing Research Basics

MARKETING RESEARCH

(Marketing Research – Nargundkar)

• Introduction

• Overview of the MR Process

• Research Methods and Design

• Question Design

• Sampling Methods

Introduction

Role:

• To collect market information to be used for various aspects & levels of Marketing.

• MR is different from market intelligence.

• MR information is used as a basis for future action or to measure marketing variables

• MI is primarily used in a competitive context

MR applications:

• Strategic (long term) &

• Tactical (short term)

Examples of MR:

• Consumer buying habits for detergents – package size, frequency, promotional effect, brand loyalty

• Potential demand for ready-to-eat chapatti in Mumbai

• To know whether Tulsi or Coconut oil or Neem is best in a soap

• To determine the effectiveness of an advertising campaign for a car brand

• To find the level of satisfaction with an ISP

• To find out the factors that influence the purchase of mobile phones

Types of MR:

1. Primary

2. Second

• Conceptual research

• Product research

• Price research

• Distribution analysis

• Advertising research

• Copy testing

• Media research

When to do MR:

• To fill the information gap

• The cost of MR is lower than the cost of obtaining a decision

Limitations of MR:

• Perception, intuition & judgment are sometimes more successful than MR

• Hot Shot cameras, before 1990

• MR suggests that there is no need, but the product is a big hit

• Andaman shoes

MR Ethics:

• Information not to be misused

• Non-coercive information

• Confidentiality

• The analysis should not be biased

Online research:

• Data warehousing

• Data mining

MR Process Overview

• Information needs

• Defining the research objective

• Research design

• Exploratory: to generate hypotheses for further studies

• Descriptive

• Longitudinal: long term in a particular segment

• Cross-sectional: one shot

• Casual: to determine the relationship between X and Y (any variables)

• Data collection

• Data analysis

• Inference

Research Methods and Design

Quantitative research techniques

• Depth interview

• Focus groups

• Projective techniques

• Word association

• Complete the sentences

Research validity

• Marketing test

Question Design

• Language

• Difficulty level

• Fatigue

• Researcher cooperation

• Social bias

• Ease of recording

• Coding

• Purpose

• Sequencing questions (logically)

• Monotony

• Analysis required

scales

• Nominal

• 1 male, 2 female

• Ordinal

• Rank

• Interval

• Satisfaction (1-5)

• Ratio

• Semantic differential

• Easy–/—/—/—-/–difficult

Question types

• Established

• Unstructured

• Tomorrow ends

• Closing ended

• Disguised

• Not disguised

• Dichotomous (2 options)

• Lots of choices

• Ranks or rankings

• Paired comparison

Scale and type of question depends on:

• Information required

• Output format

• Ease of tabulation

• Ease of translation

• Ease of statistical analysis

• Reduction of errors

Sampling Methods

Terminology:

• Population

• Universe

• Sample element

• Sampling frame

• Sampling unit

Calculating the sample size:

• When the mean is estimated

n = Zs/e^2

Z = Z score from std. normal distribution

s = population std. deviations

e = tolerable error

eg

A 95% confidence level is required

So, Z = 1.96

s = range = 10 – 1 = 9 = 9/6 = 1.5

e = 0.5

n = 1.96 * 1.5/ 0.5^2 = 34.57 = 35

Similarly, for Z= 1.96, s = 1.5 & e = 0.25

n = 138

• To estimate the proportion

n = pq Z/e^2

p = frequency of occurrence of something expressed as a proportion

q = frequency of non-occurrence

So, n = 0.25 * 0.75 1.96/0.03^2 = 800

The sample size depends on:

• Z, e

• Number of centers

• Lots of questions

• Time and budget

Sampling techniques

• probability

• Simple random: drawing

• Stratified random

• n = Z/e^2 E WS^2

• Cluster sampling

• Systematic sampling

• Multi stage or combination sampling

• Unlikely

• Quota sampling

• Sampling judgment

• Ease of sampling

• Snowball sampling

Errors

• Sampling errors

• Non sampling errors

Univariate and multivariate techniques

Knowledge of Basic Statistics is required for MR

• probability

• Normal distribution

• Poisson distribution

• % & percentage

• Correlation

• Return

• ANOVA

• Std. deviations

• t test

• z test

• Chi square test

• Conjoint analysis

• Factor analysis

• Cluster analysis

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