Conjoint analysis advance marketing research

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Conjoint analysis advance marketing research

  1. 1. GROUP PROJECT TOPIC : CONJOINT ANALYSIS PRESENTING BY: Ashish Dahiya 044 Aravind Uppala 123 Dasari Pradeep 126 Sangam Lalsivaraju 138 Rajesh Mishra 151 Neetu Gupta 155
  2. 2. Introduction to Conjoint analysis • Conjoint analysis attempts to determine the relative importance, consumers attach to salient attributes and the utilities they attach to the level of attributes. • This information is derived from consumer evaluations of brand profiles composed of these attributes and their levels . • The respondents are presented with stimuli that consists of attribute levels.
  3. 3. Contd… • They are asked to evaluate these stimuli that consist of combinations of attribute levels in terms of their desirability. • Based on the evaluations utility of each level of attribute is determined with help of Conjoint analysis.
  4. 4. Purpose Conjoint analysis has been used in marketing for a variety of purposes, some includes: • Determining the relative importance of attributes in the consumer choice process • Estimating market share of brands that differ in attribute levels • Determining the composition of the most preferred brand • Segmenting the market based on similarity of preferences for attribute levels
  5. 5. Area of application • New Product Launch
  6. 6. Research Objective • To determining the composition of most preferred product ( Car type, fuel Type and Price) , where the customer finds maximum utility.
  7. 7. Research Design
  8. 8. Sample Design • The method which we chose to get sample frame is Convenient sampling, the sample size is 20.
  9. 9. Data Collection Design • Data was collected from the respondent’s order of preferences through the list of combinations that were provided by us.
  10. 10. Statistical Design • The combinations were generated by orthogonal method from SPSS. • The responses were tabulated manually on SPSS data file.
  11. 11. Operational Design • The operations were carried out with the Syntax of a pre-programmed conjoint analysis. • The results were analyzed with the help of utilities table and importance table.
  12. 12. Combinations SL.No Profile ID Car Type Fuel Type Price in Lakhs 1 1 Sedan CNG 6 2 2 Sedan Petrol 8 3 3 Sedan Diesel 9 4 4 SUV CNG 8 5 5 SUV Petrol 9 6 6 SUV Diesel 6 7 7 MUV CNG 9 8 8 MUV Petrol 6 9 9 MUV Diesel 8
  13. 13. Responses SL.No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Profile 1 2 1 2 1 2 3 1 2 1 2 3 4 1 5 3 2 5 6 2 1 Profile Profile Profile Profile Profile Profile Profile Profile 2 3 4 5 6 7 8 9 1 5 6 3 9 4 7 8 3 4 2 6 5 8 9 7 4 1 3 5 7 6 9 8 3 4 2 6 5 8 7 9 4 1 5 3 9 7 8 6 1 5 2 8 7 9 6 4 9 6 4 7 2 5 3 8 3 1 5 4 7 6 9 8 4 3 2 9 8 6 7 5 5 3 1 7 4 9 8 6 1 5 7 2 9 6 4 8 1 6 2 8 3 7 9 5 5 2 4 7 9 8 6 3 1 3 7 2 4 6 9 8 2 1 5 7 6 9 4 8 3 4 1 5 9 8 7 6 1 5 3 2 4 6 8 7 2 1 3 7 4 8 5 9 3 4 1 5 9 7 8 6 2 5 4 3 9 8 6 7
  14. 14. Analysis
  15. 15. Importance Values Car Type 25.800 Fuel Type 40.456 Price 33.743
  16. 16. Utilities Utility estimate -.167 .343 -.567 .343 CNG 1.333 .343 -.583 .343 Diesel -.750 .343 6 Lakhs .667 .343 8 Lakhs .250 .343 9 Lakhs Constant .343 Petrol Price .833 MUV Fuel type Sedan SUV Type of car Standard error -.917 .343 5.500 .241
  17. 17. Conclusion • Customers perceiving maximum utility from sedan (.833) compared to SUV (-.167) & MUV (-.567) • Customers perceiving maximum utility from CNG (1.333) compared to Petrol (-.583) & Diesel (-.750) • Customers perceiving maximum utility from Price worth of 6 Lakhs (0.667) compared to 8 Lakhs (.250) & 9 Lakhs (.917) • So, from all the above figures and combination the maximum utility (Total utility=2.833) can be achieved with the combination of Sedan with CNG and Priced at 6 Lakhs
  18. 18. Contd… • The next alternative to get better utility (Total Utility=2.416) is from Sedan with CNG priced at 8 Lakhs • The minimum Utility (Total Utility= -2.234)is found in MUV with Diesel Priced at 9 Lakhs

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