mr rem_ppt

Market(ing!) Research Techniques

Saurab, Srikanteaswaran, Mehak

NicheIIM Ahmedabad

Contents

1. Role of Marketing Research2. Syndicated Research In India3. Defining the MR Problem and developing an Approach4. Developing a Research Plan5. Qualitative Research6. Data Analysis7. Sampling8. Factor Analysis9. Conjoint Analysis10.Discriminant and Cluster Analysis11.Multi-dimensional Scaling

Role of Marketing Research

To connect customer, consumer, and public to the marketer through information in order to identify and define marketing opportunities and problems; generate, refine and evaluate

marketing actions; monitor marketing performance and improve understanding of marketing as a process

To gather and transform customer dialogues into potential actions that lead to either an increase in sales or in customer

satisfaction

Source: Malhotra, Dash (Marketing Research - An applied orientation)

Defining the MR Problem

DEFINING THE PROBLEM - THINGS TO KEEP IN MIND

• Purpose of the study• Relevant background information• Information needed• How will the information be used in decision making?

Ideally before defining the problem, there should be • Discussion with decision makers• Interviews with industry experts• Analysis of secondary data• Some qualitative research (like focus groups)


Developing an Approach

Developing an approach requires

• Formulating an objective or theoretical framework• Identifying analytical models• Developing Research Questions and Hypotheses• Determining the information needed

The process should ideally also involve • Discussion with decision makers and industry experts• Analysis of secondary data• Qualitative research• Pragmatic considerations


Developing a Research PlanAn ideal research plan involves the following steps

• Definition of Information Needed• Secondary Data Analysis• Qualitative Research• Methods of collecting quantitative data (survey, observation

and experimentation)• Measurement and scaling procedures• Questionnaire Design• Sampling Process and Sample Size• Plan of Data Analysis


Qualitative Research

Qualitative Research is unstructured and exploratory by nature and should be used at the very beginning (to get a better understanding of the problem) and at the very end (to check viability of solution).

The following are some of the popular qualitative research techniques• Focus Group Discussions• In-depth Interviews• Word Association• Pilot Surveys• Case Studies


Data Preparation

Garbage in, Garbage Out

Before analysis of data can begin, data has to be prepared for the analysis. This involves

• Questionnaire Checking• Editing• Coding• Transcribing• Data Cleaning• Statistical Adjusting (Weighting, Variable Respecfication,

Scale Transformation)


Factor Analysis

Conjoint Analysis

Measurement: Scaling Techniques

There are two types of scaling techniques - Comparative and Non-comparative.

Comparative Scaling Techniques• Paired Comparison• Rank Order• Constant Sum• Q-Sort• Magnitude Estimation

Non-Comparative Scaling Techniques• Continuous Rating• Itemized Rating


Discriminant and Cluster Analysis Discriminant analysis helps to identify the independent variables that discriminate a nominally scaled dependent variable of interest. The linear combination of independent variables indicates the discriminating function showing the large difference that exists in the two group means. In other words the independent variables measured on an interval or ratio scale discriminate the groups of interest to study. [Wilks' Lambda: In the ANOVA table, the smaller the Wilks's lambda, the more important the independent variable to the discriminant function.]There are several different ways that can be used to estimate discriminant function coefficients, but all work on the same general principle: the values of the coefficients are selected so that differences between the groups defined by the dependent variable are maximized with regard to some objective function. The cluster analysis is used to classify objects or individuals into mutually exclusive and collectively exhaustive groups with high homogeneity within clusters and low homogeneity between clusters. In other words cluster analysis helps to identify objects that are similar to one another, based on some specified criterion. Cluster analysis will cluster individuals by their preferences for each of the different brands.

Source: www.blurtit.com/q541594.html

Multi-dimensional ScalingIn marketing, MDS is a statistical technique for taking the preferences and perceptions of respondents and representing them on a visual grid, called perceptual maps.From a non-technical point of view, the purpose of multidimensional scaling (MDS) is to provide a visual representation of the pattern of proximities (i.e., similarities or distances) among a set of objects. Toothpaste Data Set: SPSS

Source: en.wikipedia.org/wiki/Multidimensional_scaling

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