Group C_ Conjoint analysis process and example

Conjoint analysis: process and examples for implementation

Conjoint analysis helps organizations understand which factors drive decisions. Analysts determine factor preferences by presenting multiple combinations of factors and asking respondents to rank them. Market researchers often use conjoint analysis to determine which product features are most critical to purchase decisions.

Conjoint analysis must currently be run using syntax. Unlike most procedures in SPSS for Windows, conjoint analysis requires the user to invoke two files:

1.Plan File:The plan file contains the combinations that will be presented to the participants.

2. Data File:The data file contains the participants' responses.

The syntax includes the full location of the plan file, but uses an asterisk to alert SPSS to use the file in the data editor as the data file. 

You can also save utilities—the values assigned to each factor from the conjoint—using the utility command. Make sure to include the utility command at the end of the syntax run and indicate where to save the file. You can use this to segment customers based on their preference patterns.

Step 1: Generating the Plan file:
Open SPSS ->Data > Orthogonal Design-> Generate 

Define factors :

Example : In a Hi-Tech hotel survey, IMNU students defined LAPTOP_CARRY, INT_CONNECT_VIDEO_DEMAND,VIDEO_CONF_VOIP, PRICE_PREMIUM as different factors.
They got 9 profiles by orthogonal design.

Step 2: Data -> Orthogonal Design->Display 

This will give you profiles (Multiple combination of factors).Go to your subject and find out their ranking for the given profiles.

Step 3: Generate the data file
This file is generated on basis of ranking provided to different preferences.

Step 4: Run a conjoint Analysis:CONJOINT PLAN='C:\Documents and Settings\Administrator\Desktop\VXLPLAN.SAV'
/DATA=*
/SUBJECT=ID
/FACTORS=LAPTOP_CARRY INT_CONNECT_VIDEO_DEMAND 
VIDEO_CONF_VOIP PRICE_PREMIUM
/RANK=PREF1 TO PREF9
/UTILITY='C:\Documents and Settings\Administrator\Desktop\OUTPUT.SAV'
/PLOT=SUMMARY
/PRINT=SUMMARYONLY.

Step 5: Analyze the output

Examples :-

Conjoint analysis can be used for many cases; some of them could be to study the factors that influence customers, purchasing decisions. Products possess attributes such as price, color, ingredients, guarantee, environmental impact, predicted reliability and so on. Conjoint analysis is based on a main effects analysis-of-variance model. Subjects provide data about their preferences for hypothetical products defined by attribute combinations. Conjoint analysis decomposes the judgment data into components, based on qualitative attributes of the products. A numerical part-worth utility value is computed for each level of each attribute. Large part-worth utilities are assigned to the most preferred levels, and small part-worth utilities are assigned to the least preferred levels. The attributes with the largest part-worth utility range are considered the most important in predicting preference. Conjoint analysis is a statistical model with an error term and a loss function.

Amar Kumar

14067

Operations, Group C

Source: -  http://www.surveyanalytics.com