CONJOINT ANALYSIS

CONJOINT ANALYSIS : 

CONJOINT ANALYSIS PRESENTED BY: NIDHI SHARMA

Outline : 

Outline Introduction Definition Conjoint analysis decision process Areas of application Models

Introduction : 

Introduction Metric/ Non- metric responses conversion using an interval scale Examples- This This OR THIS

DEFINITION : 

DEFINITION Measures consumer preferences for alternative product concepts. Helps derive utility value attached by customers to the product attributes. Hypothetical models proposition. Helps estimate market share and profits

Contd. : 

Contd. Psychometrics Marketing research Conjoint is becoming very much removed from theoretical roots i.e hypothetical models to Numerical measurement of behavior Factorial designs instead of fractional factorial designs Moving from non-metric to metric

Slide 6: 

Research Problem Define Stimuli (factors and levels) Basic model form Full profile Trade off Pairwise Data Collection Select preference measure Survey Administration Assumptions Select estimation technique Evaluate results Interpret results Validate Apply results Conjoint Analysis Decision Process This technique requires a lot of upfront work to think through the design, data collection, and analysis options.

Areas of application : 

Areas of application Find the product with the optimum set of features Determine the relative importance of each feature in consumer choices Estimate market share among products Identify market segments Evaluate the impact of price changes or other marketing mix decisions.

Models : 

Models Decompositional model—An individual’s overall preference or evaluation for a product is decomposed. Best suited for understanding consumers reactions Evaluates predetermined attribute combinations that represent potential products or services.

Compositional vs. Decompositional : 

Compositional vs. Decompositional Compositional Y = A1 + A2 Collect A1 and A2 and relate it to Y. Estimate weights to create a predictive model Decompositional Y = A1 + A2 Collect Y and relate it to A1 and A2 which are already fixed, and determine weights.

Concept exemplified : 

Concept exemplified Green & wind’s illustration 3 package designs (A,B,C) 3 brand designs (x, y, z) 3 prices (1,2,3) Guarantee of the product (y/n) Derive utility for all attributes b/w 0 to 1. Higher utility stronger preference. Factorial design combinations (3*3*3*2)=54 combinations possible.

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