Tata Motors Final Template Sunila

8/3/2019 Tata Motors Final Template Sunila

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• Detailed literature review to arrive at a list of attributes that guide automobile purchase behaviour

• Research paper analysis for model applications relevant to project objectives

Secondary Research

• ___ IDIs to capture visible feature needs and ____FGDs to capture latent and hidden needs

• Dealer interviews and interviews with experts to get feature preference

Exploratory Research

• Clustering of product attributes and features that are relevant to users of various car segments

• Functional + Dysfunctional questions asked for product features for eventual segmentation

KANO Models to segment product attributes

• Attributes are split into Must-be, One dimensional, Attractive and Indifferent Attributes

• Literature review + Exploratory Research + KANO Questionnaire + KANO Table Analysis used for theabove

KANO Final feature disposition

• Gauging attribute level preferences, attribute important and profile ratings/ rankings through gamedesigns

• Simulation of car buying environment and travel environments to gauge latent attribute preferences

INDEX Fair: Quantitative Research

• Gauging customer perceived monetary value through utility values

• Use of cross validation procedures to validate data

Hybrid Conjoint Analysis for Customer Perceived Monetary Value

• Df

• df

Inputs to New Product Development





LiteratureReview

IDIs FGDs

KANO

Questionnaire

KANO

Table

Segment

product

requirements

Input tofurtheranalysis

Clustering of attributes

Functional and dysfunctional

questions for each feature ineach cluster in each segment

Customer Requirements

Negative

Positive Like Must be Neutral Live with Dislike

Like Q A A A O

Must be R I I I M

Neutral R I I I M

Live with R I I I M

Dislike R R R R Q

M - Must be

O - One dimensional

A- Attractive

I- Indifferent

Q- Questionable

R- Reverse



Must be FeaturesThese are features that must be in the product. Customers will not buy the

product without these features but putting this features do not provide

brownie points. Consumers expect these features to be there.

One-dimensional featuresHigher functionality of this product results in greater customer satisfaction.

Competition between brands is primarily on these features.

Attractive featuresThese features are manifested through latent needs. With these features

consumers find products more appealing but will buy despite their absence.

Indifferent featuresCustomers don’t care if the feature is present or not.





Attribute

Clusters

Levels of attributes

Hybrid ConjointAnalysis design

Data Collection

Cross Validation

Market ShareSimulation

PerceivedMonetary Value

• Clustering of attributes relevant to owners of product segments (from Phase I)

•

These clusters are used as attributes for profile design in Hybrid Conjoint Analysis

•Hypothetical models chosen randomly for market share simulation

•What-if analysis

•First Choice hit rate and Correlation coefficients

•Reliability & validity is checked through above external & internal cross validations

•Desirability rated on a 7 point scale; attribute importance-100 pt constant sum

• 6-9 full profile Conjoint design to gauge customer willingness to buy & preferences

•Part worth values of various attribute levels and price levels are estimated

•Exchange rates between price and utility are used to estimate monetary values

•4 One-dimensional attributes and 2 excitement attributes are chosen as levels

•Levels decided through discussions with experts, literature review and IDIs

•Collection of attribute-level desirability values and attribute importance data

•Conjoint responses to a set of full profiles based on attribute clusters and levels















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Tata Motors Final Template Sunila

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