Description
It covers the basics of Research.Then this ppt explains how to use this data using SPSS and excel to come up with positioning maps.It makes a P Map using MDS(multi dimensional scaling) and SPSS software.
Positioning based on market research
What is Positioning???
It is a process by which marketers try to create an image or identity in the minds of their target market for its product, service or organization As per Marketing Guru AL Ries & Jack Trout it is “Battle for Mind of the consumer”
It is done to differentiate one product from other Positioning should be relevant, differentiated and single minded
2
Process
Identify important attributes for a product class
Judgments of existing brands on these important attributes Ratings of an “ideal” brand?s attributes
Perceptual Map
3
Industry Overview.
? 70 year old Industry in India. ? Total Production of 12.5 Lacs passenger cars in India till October 2008. ? 63% share of small car segment ? Annual Sales of Auto segment is Rs.5 lac crores. ? Average new cars launched per year are 12 nos. ? 12% growth recorded over last year. ? 13 Nos players in Auto segment in India.
4
Market Share
Santro Alto Wagonar Spark 800
5
Roadmap To research
Problem Statement Research Objective Theoretical Framework Hypothesis if required Tool Construction Data Analysis Conclusion
6
Management Problem
Given the current market & industry scenario, analyse the number and nature of dimensions consumers use to percieve different brands of small cars in the market place.
7
Research Objective
To understand consumer?s perception of the small segment cars in the Indian market and positioning of current brands on these dimensions & suggest suitable positioning strategies for a new entrant in the market
8
Variables
Independent : Customer perception Dependant : Positioning of Car in small segment
9
Independent Variables
Perception of Existing Brands Attributes of Small Cars Fuel Efficiency Spaciousness Price Looks After sales Service. Availability Resale Value.
10
Past Research
Primary Data A questionnaire was prepared and gathered from sample population Secondary Data Company websites Past research reports Marketing Journals On the basis of a past survey, the important attributes for a small car were understood.
11
Attributes
Attributes
4 key attributes were identified by Market Research, based on past data Respondents were then asked to rank these 4 key attributes
Attribute Price Spaciousness Fuel Efficiency Maintenance Ranking 1 2 3 4
12
Input Data for tool used
Input Data
Perceptions
Preferences
Direct (Similarity Judgments)
Derived (Attribute Ratings)
13
Input Data - Questionnaire
Aim – To understand Perceptions in consumers mind
A questionnaire – divided in 3 parts 1. Self Information – age, sex, occupation (not related to research)
2. Perception data – with Direct Approach 3. Perception data – Derived Approach
14
Sample Information
Sample Size : 50 Nos Occupation : Service/ Business. Male : 34 Female : 16 Nos. Potential Buyers Age Group : 25 – 70 years. Location : Mumbai Method of Sampling : Convenience.
15
Tool Used
Multidimensional Scaling
class of procedures for representing perceptions and preferences of respondents spatially by means of visual display.
Perceived or Psychological relationships among stimuli (brands) are
represented as geometric points called „spatial maps?
16
USE OF MDS
Image measurement. ?Market Segmentation. ?Product Positioning. ?New Product development. ?Assessing Advertisement effectiveness. ?Channel Decisions ?Attitude Scale Construction. ?Pricing Analysis.
?
17
Perception Data-Direct Approach
Respondents judged the similarities / dissimilarities of various brands using their own criteria (using Semantic Differential Scale)
Resp -1
Very Dissimilar 1 Wagon R VS Santro Wagon R VS Spark Wagon R VS Alto Santro VS Spark Santro VS Alto Alto Vs Spark 3 4 6 4 5 2 3 4 5 6 Very Similar 7
6
18
Perception Data-Derived Approach
Respondents rate brands on identified attributes Eg : Rating of Alto
1
2
3
4
5
6
7
is spacious
X
is not spacious
is high priced
X
is not high priced
19
MDS & SPSS
Using SPSS, MDS is run Spatial maps obtained for each respondent
20
Important parameters
R- Square Goodness of fit measure. Indicates how well MDS model fits input data. Higher values better and values > 0.60 acceptable
S- Stress value. Lack of fit measure. Higher value of stress indicate poorer fits. Differ with type of MDS procedure & data being analysed.
21
STEP ONE
22
STEP TWO
23
STEP THREE
24
STEP FOUR
25
STEP FIVE
26
STEP SIX
27
STEP SEVEN
28
OUTPUT ONE
Stress and Fit Measures
Normalized Raw Stress Stress-I Stress-II S-Stress Dispersion Accounted For (D.A.F.) Tucker's Coefficient of Congruence .00020 .01428(a) .05539(a) .00056(b) .99980 .99990
PROXSCAL minimizes Normalized Raw Stress. a Optimal scaling factor = 1.000. b Optimal scaling factor = .996.
29
OUTPUT TWO
Stress and Fit Measures Normalized Raw Stress Stress-I Stress-II S-Stress Dispersion Accounted For (D.A.F.) Tucker's Coefficient of Congruence .00186 .04312(a) .22786(a) .00614(b) .99814 .99907
PROXSCAL minimizes Normalized Raw Stress. a Optimal scaling factor = 1.002. b Optimal scaling factor = 1.014.
30
OUTPUT THREE
Stress and Fit Measures
Normalized Raw Stress Stress-I Stress-II S-Stress Dispersion Accounted For (D.A.F.) Tucker's Coefficient of Congruence .00186 .04312(a) .22786(a) .00614(b) .99814 .99907
PROXSCAL minimizes Normalized Raw Stress. a Optimal scaling factor = 1.002. b Optimal scaling factor = 1.014.
31
Conclusion & Recommendations
WagonR
Spark PRICE Santro
Alto NANO
SPACIOUS
32
THANK YOU
33
doc_755227080.ppt
It covers the basics of Research.Then this ppt explains how to use this data using SPSS and excel to come up with positioning maps.It makes a P Map using MDS(multi dimensional scaling) and SPSS software.
Positioning based on market research
What is Positioning???
It is a process by which marketers try to create an image or identity in the minds of their target market for its product, service or organization As per Marketing Guru AL Ries & Jack Trout it is “Battle for Mind of the consumer”
It is done to differentiate one product from other Positioning should be relevant, differentiated and single minded
2
Process
Identify important attributes for a product class
Judgments of existing brands on these important attributes Ratings of an “ideal” brand?s attributes
Perceptual Map
3
Industry Overview.
? 70 year old Industry in India. ? Total Production of 12.5 Lacs passenger cars in India till October 2008. ? 63% share of small car segment ? Annual Sales of Auto segment is Rs.5 lac crores. ? Average new cars launched per year are 12 nos. ? 12% growth recorded over last year. ? 13 Nos players in Auto segment in India.
4
Market Share
Santro Alto Wagonar Spark 800
5
Roadmap To research
Problem Statement Research Objective Theoretical Framework Hypothesis if required Tool Construction Data Analysis Conclusion
6
Management Problem
Given the current market & industry scenario, analyse the number and nature of dimensions consumers use to percieve different brands of small cars in the market place.
7
Research Objective
To understand consumer?s perception of the small segment cars in the Indian market and positioning of current brands on these dimensions & suggest suitable positioning strategies for a new entrant in the market
8
Variables
Independent : Customer perception Dependant : Positioning of Car in small segment
9
Independent Variables
Perception of Existing Brands Attributes of Small Cars Fuel Efficiency Spaciousness Price Looks After sales Service. Availability Resale Value.
10
Past Research
Primary Data A questionnaire was prepared and gathered from sample population Secondary Data Company websites Past research reports Marketing Journals On the basis of a past survey, the important attributes for a small car were understood.
11
Attributes
Attributes
4 key attributes were identified by Market Research, based on past data Respondents were then asked to rank these 4 key attributes
Attribute Price Spaciousness Fuel Efficiency Maintenance Ranking 1 2 3 4
12
Input Data for tool used
Input Data
Perceptions
Preferences
Direct (Similarity Judgments)
Derived (Attribute Ratings)
13
Input Data - Questionnaire
Aim – To understand Perceptions in consumers mind
A questionnaire – divided in 3 parts 1. Self Information – age, sex, occupation (not related to research)
2. Perception data – with Direct Approach 3. Perception data – Derived Approach
14
Sample Information
Sample Size : 50 Nos Occupation : Service/ Business. Male : 34 Female : 16 Nos. Potential Buyers Age Group : 25 – 70 years. Location : Mumbai Method of Sampling : Convenience.
15
Tool Used
Multidimensional Scaling
class of procedures for representing perceptions and preferences of respondents spatially by means of visual display.
Perceived or Psychological relationships among stimuli (brands) are
represented as geometric points called „spatial maps?
16
USE OF MDS
Image measurement. ?Market Segmentation. ?Product Positioning. ?New Product development. ?Assessing Advertisement effectiveness. ?Channel Decisions ?Attitude Scale Construction. ?Pricing Analysis.
?
17
Perception Data-Direct Approach
Respondents judged the similarities / dissimilarities of various brands using their own criteria (using Semantic Differential Scale)
Resp -1
Very Dissimilar 1 Wagon R VS Santro Wagon R VS Spark Wagon R VS Alto Santro VS Spark Santro VS Alto Alto Vs Spark 3 4 6 4 5 2 3 4 5 6 Very Similar 7
6
18
Perception Data-Derived Approach
Respondents rate brands on identified attributes Eg : Rating of Alto
1
2
3
4
5
6
7
is spacious
X
is not spacious
is high priced
X
is not high priced
19
MDS & SPSS
Using SPSS, MDS is run Spatial maps obtained for each respondent
20
Important parameters
R- Square Goodness of fit measure. Indicates how well MDS model fits input data. Higher values better and values > 0.60 acceptable
S- Stress value. Lack of fit measure. Higher value of stress indicate poorer fits. Differ with type of MDS procedure & data being analysed.
21
STEP ONE
22
STEP TWO
23
STEP THREE
24
STEP FOUR
25
STEP FIVE
26
STEP SIX
27
STEP SEVEN
28
OUTPUT ONE
Stress and Fit Measures
Normalized Raw Stress Stress-I Stress-II S-Stress Dispersion Accounted For (D.A.F.) Tucker's Coefficient of Congruence .00020 .01428(a) .05539(a) .00056(b) .99980 .99990
PROXSCAL minimizes Normalized Raw Stress. a Optimal scaling factor = 1.000. b Optimal scaling factor = .996.
29
OUTPUT TWO
Stress and Fit Measures Normalized Raw Stress Stress-I Stress-II S-Stress Dispersion Accounted For (D.A.F.) Tucker's Coefficient of Congruence .00186 .04312(a) .22786(a) .00614(b) .99814 .99907
PROXSCAL minimizes Normalized Raw Stress. a Optimal scaling factor = 1.002. b Optimal scaling factor = 1.014.
30
OUTPUT THREE
Stress and Fit Measures
Normalized Raw Stress Stress-I Stress-II S-Stress Dispersion Accounted For (D.A.F.) Tucker's Coefficient of Congruence .00186 .04312(a) .22786(a) .00614(b) .99814 .99907
PROXSCAL minimizes Normalized Raw Stress. a Optimal scaling factor = 1.002. b Optimal scaling factor = 1.014.
31
Conclusion & Recommendations
WagonR
Spark PRICE Santro
Alto NANO
SPACIOUS
32
THANK YOU
33
doc_755227080.ppt