Marketing Research[/b]
• Marketing Research is the systematic gathering, recording, analyzing and evaluating the data related to the marketing problems
• Importance/applications of MR[/b][/b]
• Helps in every function of marketing
• Key role in marketing process
• Understanding of the consumer and the marketing environment
Applications of MR[/b]
• Decision – making in each element of marketing mix
• Particular ad campaign
• Know the Acceptance levels of the product
• Effectiveness of middlemen
• Research on product[/b]
• Reviewing product line, Quality , BPL
• Actual uses of the product
• New uses of the product
• Testing of new products
• On service requirements
• Size of market
• Market profile
• Studying market segmentation
• Accurate business trends
• Research on consumer
• Profile, buying behaviour, purchase decision, consumption pattern
• Determine brand awareness and loyality
• Customer satisfaction level
• Media research – research into viewership of specific television programs
• Research on sales
• Sales quotas, territories,sales forecast, sales management
• Image studies – consumer perception
• Research on Distribution[/b]
• Types of distribution
• Attitudes of channel members
• Intensity of wholesale and retail coverage
• Channel margin
• Location of wholesale and retail outlets
• Research on Advertising[/b]
• Copy research
• Tracking studies – continuous monitoring mechanism regarding the theme of the advertisement, effectiveness of advertisement
Factor Analysis[/b]
• Factor Analysis
• It helps in reducing the data complexity by reducing the number of variables being studied.
• Factor Analysis is typically used to study a complex product or service in order to identify the major characteristics or factors) considered to be more important by consumers for the product or service
• Factor analysis identifies two or more questions that result in sets of responses that are highly corelated(ex: safety or economy of operation)
• For example households consider certain characteristics or factors in buying furniture for their home, investing in a bank, automobile etc
• Factor analysis can bring out the hidden or latent dimensions relevant in the relationships among product preferences.
• If the product characteristics influencing the consumer preferences are not clear, factor analysis is used in revealing the most important characteristics of the product among preferences
• Factor analysis is useful when a large mass of data is to be simplified and condensed
• It is the most popular “analysis of interdependence” techniques because one of its goals is usually referred as data reduction.
• It simplifies data analysis by taking advantage of the correlating among the variables. it also helps in extracting the overlapping information by reducing the problem down to just a few core factors
• Applications of factor analysis[/b][/b]
• For example : The marketing manager of a two wheeler company designed a questionnaire to study for customers feedback about its two wheeler and inturn keen in identifying the factors of the study
• The identification of the variables are
• Fuel efficiency, life of two-wheeler, handling convenience, quality of the original spares, breakdown rate, price etc
• The application of the factor analysis to group these variables into factors
Critical Marketing Applications of Factor Analysis[/b]
• Factor analysis has also been used in lifestyle and psychographic research problems to
• a. Develop consumer profiles reflecting people’s attitudes, activities, interests, opinions, perceptions, and preferences to better predict their consumption and purchase behavior.
• b. Ascertain key attributes that determine customer preferences for products (e.g., brand equity studies), or organizations
• c. assess the company’s image
• d. isolate the dimensions of print ads that most affect readership
• e. develop measure of job satisfaction
• Conclusion
• Concept of factor analysis
• Applications of factor analysis
[/b]
Cluster analysis[/b]
• Cluster Analysis is an interdependence technique of Multivariate analysis.
• Cluster analysis is useful in identifying aggregates of consumers who behave similarly. By determining the areas where they live and the demographics of those areas from census data, geodemographic segments of the population can be formed. (people of similar groups).
• It is widely used in market segmentation studies. A firm segmenting its market is seeking to group potential customers into homogenous groups that are large enough to be profitably cultivated.
• The segmentation base could involve many characteristics , including socioeconomic, psychological, and buyer behavior variables.
• Cluster analysis helps the market researcher to identify natural groupings of customers even with the complex multivariate data.
• Cluster analysis assign objects to groups so that there is as much similarity within groups, and difference between groups .
• Another application for cluster analysis is test markets
• Test markets for products, prices, promotional campaigns etc., require two cities (or two groups of cities), one to serve as the test market, the other to serve as a control. By using cluster analysis we can find out the cities which are similar are nature(e.g in terms of income, education, lifestyles etc)
• Cluster analysis is typically applied to data consisting of many variables that have been collected from a large sample of respondents
• For ex: A sporting goods manufacturer was attempting to identify the market segments for all types of sporting equipment
• Cluster analysis is useful in identifying homogenous groups of buyers
• It is useful in determining the elements of competition by clustering brands or products within the large market structure
Critical Applications of Cluster analysis
• 1.Sort households demand patterns for electricity
• 2.Group T.V programs into similar types on the basis of viewers’ reports
• 3.Group other media in terms of the similarity of their audience appeal
• 4.Develop homogenous configurations of census e.g for consumer and political purposes
• 5. group brands and products on the basis of how similar to competitors’ products they are perceived to be, thus how likely they are to serve as substitutes
• 6. determine spheres of opinion leadership in word-of-mouth networks
Assess the similarity of countries and cultures in world markets.
Discriminant analysis(DA)[/b]
• Discriminant analysis is a multivariate statistical method of marketing research.
• DA is a method of constructing a linear combination of the variables (i.e., a weighted sum) in such a way that this newly created function optimally discriminates among the groups. We can then assess how the groups differ with respect to the linear combination score
• DA is useful in determining the characteristics that differentiate the following :
• a. light and heavy users of a product
• b. purchasers of our brand and those of competing brands
• Customers who patronize every-day-low-pricing retail outlets those who shop at high-end, service-oriented ones
• Good, mediocre, and poor sales representatives
• Good and poor loan risks
• Critical applications of DA
• a. To determine the characteristics that distinguish the listening audiences of radio stations
• b. to differentiate among segments of automobile buyers
• c. To predict adopters and non adopters of new products
• d. to relate purchase behavior to advertising exposure
• e. to determine the relationship between personality variables and consumer decisions.
• f. to
• Marketing Research is the systematic gathering, recording, analyzing and evaluating the data related to the marketing problems
• Importance/applications of MR[/b][/b]
• Helps in every function of marketing
• Key role in marketing process
• Understanding of the consumer and the marketing environment
Applications of MR[/b]
• Decision – making in each element of marketing mix
• Particular ad campaign
• Know the Acceptance levels of the product
• Effectiveness of middlemen
• Research on product[/b]
• Reviewing product line, Quality , BPL
• Actual uses of the product
• New uses of the product
• Testing of new products
• On service requirements
• Size of market
• Market profile
• Studying market segmentation
• Accurate business trends
• Research on consumer
• Profile, buying behaviour, purchase decision, consumption pattern
• Determine brand awareness and loyality
• Customer satisfaction level
• Media research – research into viewership of specific television programs
• Research on sales
• Sales quotas, territories,sales forecast, sales management
• Image studies – consumer perception
• Research on Distribution[/b]
• Types of distribution
• Attitudes of channel members
• Intensity of wholesale and retail coverage
• Channel margin
• Location of wholesale and retail outlets
• Research on Advertising[/b]
• Copy research
• Tracking studies – continuous monitoring mechanism regarding the theme of the advertisement, effectiveness of advertisement
Factor Analysis[/b]
• Factor Analysis
• It helps in reducing the data complexity by reducing the number of variables being studied.
• Factor Analysis is typically used to study a complex product or service in order to identify the major characteristics or factors) considered to be more important by consumers for the product or service
• Factor analysis identifies two or more questions that result in sets of responses that are highly corelated(ex: safety or economy of operation)
• For example households consider certain characteristics or factors in buying furniture for their home, investing in a bank, automobile etc
• Factor analysis can bring out the hidden or latent dimensions relevant in the relationships among product preferences.
• If the product characteristics influencing the consumer preferences are not clear, factor analysis is used in revealing the most important characteristics of the product among preferences
• Factor analysis is useful when a large mass of data is to be simplified and condensed
• It is the most popular “analysis of interdependence” techniques because one of its goals is usually referred as data reduction.
• It simplifies data analysis by taking advantage of the correlating among the variables. it also helps in extracting the overlapping information by reducing the problem down to just a few core factors
• Applications of factor analysis[/b][/b]
• For example : The marketing manager of a two wheeler company designed a questionnaire to study for customers feedback about its two wheeler and inturn keen in identifying the factors of the study
• The identification of the variables are
• Fuel efficiency, life of two-wheeler, handling convenience, quality of the original spares, breakdown rate, price etc
• The application of the factor analysis to group these variables into factors
Critical Marketing Applications of Factor Analysis[/b]
• Factor analysis has also been used in lifestyle and psychographic research problems to
• a. Develop consumer profiles reflecting people’s attitudes, activities, interests, opinions, perceptions, and preferences to better predict their consumption and purchase behavior.
• b. Ascertain key attributes that determine customer preferences for products (e.g., brand equity studies), or organizations
• c. assess the company’s image
• d. isolate the dimensions of print ads that most affect readership
• e. develop measure of job satisfaction
• Conclusion
• Concept of factor analysis
• Applications of factor analysis
[/b]
Cluster analysis[/b]
• Cluster Analysis is an interdependence technique of Multivariate analysis.
• Cluster analysis is useful in identifying aggregates of consumers who behave similarly. By determining the areas where they live and the demographics of those areas from census data, geodemographic segments of the population can be formed. (people of similar groups).
• It is widely used in market segmentation studies. A firm segmenting its market is seeking to group potential customers into homogenous groups that are large enough to be profitably cultivated.
• The segmentation base could involve many characteristics , including socioeconomic, psychological, and buyer behavior variables.
• Cluster analysis helps the market researcher to identify natural groupings of customers even with the complex multivariate data.
• Cluster analysis assign objects to groups so that there is as much similarity within groups, and difference between groups .
• Another application for cluster analysis is test markets
• Test markets for products, prices, promotional campaigns etc., require two cities (or two groups of cities), one to serve as the test market, the other to serve as a control. By using cluster analysis we can find out the cities which are similar are nature(e.g in terms of income, education, lifestyles etc)
• Cluster analysis is typically applied to data consisting of many variables that have been collected from a large sample of respondents
• For ex: A sporting goods manufacturer was attempting to identify the market segments for all types of sporting equipment
• Cluster analysis is useful in identifying homogenous groups of buyers
• It is useful in determining the elements of competition by clustering brands or products within the large market structure
Critical Applications of Cluster analysis
• 1.Sort households demand patterns for electricity
• 2.Group T.V programs into similar types on the basis of viewers’ reports
• 3.Group other media in terms of the similarity of their audience appeal
• 4.Develop homogenous configurations of census e.g for consumer and political purposes
• 5. group brands and products on the basis of how similar to competitors’ products they are perceived to be, thus how likely they are to serve as substitutes
• 6. determine spheres of opinion leadership in word-of-mouth networks
Assess the similarity of countries and cultures in world markets.
Discriminant analysis(DA)[/b]
• Discriminant analysis is a multivariate statistical method of marketing research.
• DA is a method of constructing a linear combination of the variables (i.e., a weighted sum) in such a way that this newly created function optimally discriminates among the groups. We can then assess how the groups differ with respect to the linear combination score
• DA is useful in determining the characteristics that differentiate the following :
• a. light and heavy users of a product
• b. purchasers of our brand and those of competing brands
• Customers who patronize every-day-low-pricing retail outlets those who shop at high-end, service-oriented ones
• Good, mediocre, and poor sales representatives
• Good and poor loan risks
• Critical applications of DA
• a. To determine the characteristics that distinguish the listening audiences of radio stations
• b. to differentiate among segments of automobile buyers
• c. To predict adopters and non adopters of new products
• d. to relate purchase behavior to advertising exposure
• e. to determine the relationship between personality variables and consumer decisions.
• f. to