Day10_Team I_Priskilina Basumatari

DAY 10_TEAM I_PRISKILINA BASUMATARI

Purpose of discriminant analysis:

The main purpose of a discriminant function analysis is to predict group membership based on a linear combination of the interval variables. The procedure begins with a set of observations where both group membership and the values of the interval variables are known. The end result of the procedure is a model that allows prediction of group membership when only the interval variables are known. A second purpose of discriminant function analysis is an understanding of the data set, as a careful examination of the prediction model that results from the procedure can give insight into the relationship between group membership and the variables used to predict group membership.

We need to:

Analyze>Classify>Discriminant

·         Select grouping variable as default.

·         Select all other variables as independent.

·         Select means in statistics.

·         Select summary table in classify.

·         Check all 3 option & Save

 Now, we get the modified Data View:

Three new variables Dis_1, Dis1_1, Dis1_2 & Dis2_2 have been added.

We can use these variables for comparison and finding out the probability of accuracy of our results for better decision making.

Conjoint Analysis:      

Is a statistical technique used in market research to determine how people value different features that make up an individual product or service.

The objective of conjoint analysis is to determine what combination of a limited number of attributes is most influential on respondent choice or decision making. A controlled set of potential products or services is shown to respondents and by analyzing how they make preferences between these products, the implicit valuation of the individual elements making up the product or service can be determined. These implicit valuations (utilities or part-worth’s) can be used to create market models that estimate market share, revenue and even profitability of new designs.

We learned the process of creating Plan cards

Method: Data>Orthogonal designs>Generate

An sav format file will be created.

Now, Data>Orthogonal designs>Display

Example:

	Card ID	Taste	Nutri	Qty	Looks	Price	Loca	Type
1	1	Bad	Med	Unltd	Appetising	VFM	Outside mess	Veg
2	2	Bad	Med	Unltd	Unapp	High	Mess	Veg
3	3	Bad	High	Ltd	Appetising	VFM	Mess	Veg
4	4	Good	High	Unltd	Unapp	VFM	Mess	NonVeg
5	5	Good	High	Unltd	Appetising	High	Outside mess	NonVeg
6	6	Bad	Low	Unltd	Unapp	VFM	Outside mess	NonVeg
7	7	Good	Low	Ltd	Unapp	High	Mess	Veg
8	8	Bad	High	Ltd	Unapp	VFM	Mess	NonVeg
9	9	Bad	High	Ltd	Unapp	High	Outside mess	Veg
10	10	Good	High	Unltd	Appetising	VFM	Mess	Veg
11	11	Good	High	Unltd	Unapp	High	Outside mess	Veg
12	12	Good	Med	Ltd	Appetising	High	Mess	NonVeg
13	13	Good	Med	Ltd	Unapp	VFM	Outside mess	NonVeg
14	14	Bad	Low	Unltd	Appetising	High	Mess	NonVeg
15	15	Good	Low	Ltd	Appetising	VFM	Outside mess	Veg
16	16	Bad	High	Ltd	Appetising	High	Outside mess	NonVeg

                                                                    

Benefits of conjoint analysis

• Conjoint analysis is an efficient quantitative methodology that enables companies to forecast price elasticity of demand and sales potential
• Conjoint analysis is the best way to determine (and simulate) the purchase likelihood and estimate volumetric for competing products under a wide variety of pricing scenarios
• For situations in which you need to determine which combination of packaging options, names, benefit statements and price will result in maximum market acceptance, conjoint analysis is a “best practice” technique for strategic marketing
• Conjoint analysis is designed to elicit information on purchase decisions in a hypothetical, yet realistic, purchase setting. Respondents are given a series of choices among hypothetical products and choose the product they would be most likely to purchase – or they may choose no product at all. By analyzing the data, the relative significance of product attributes and critical price points that affect purchase likelihood are identified