Monday, 5 September 2011

CONJOINT ANALYSIS.................!

Conjoint Analysis is concerned with understanding how people make choices between products or services or a combination of product and service, so that businesses can design new products or services that better meet customers’ underlying needs.

Although it has only been a mainstream research technique for the last 10 years or so, conjoint analysis has been found to be an extremely powerful of way of capturing what really drives customers to buy one product over another and what customers really value.

A key benefit of conjoint analysis is the ability to produce dynamic market models that enable companies to test out what steps they would need to take to improve their market share, or how competitors’ behaviour will affect their customers.

Steps in Developing a Conjoint Analysis

Developing a conjoint analysis involves the following steps:

  1. Choose product attributes, for example, appearance, size, or price.
  2. Choose the values or options for each attribute. For example, for the attribute of size, one may choose the levels of 5", 10", or 20". The higher the number of options used for each attribute, the more burden that is placed on the respondents.
  3. Define products as a combination of attribute options. The set of combinations of attributes that will be used will be a subset of the possible universe of products.
  4. Choose the form in which the combinations of attributes are to be presented to the respondents. Options include verbal presentation, paragraph description, and pictorial presentation.
  5. Decide how responses will be aggregated. There are three choices - use individual responses, pool all responses into a single utility function, or define segments of respondents who have similar preferences.
  6. Select the technique to be used to analyze the collected data. The part-worth model is one of the simpler models used to express the utilities of the various attributes. There also are vector (linear) models and ideal-point (quadratic) models.

The data is processed by statistical software written specifically for conjoint analysis.

Conjoint analysis was first used in the early 1970's and has become an important marketing research tool. It is well-suited for defining a new product or improving an existing one.

Example: Attitudes towards dishwashing products

1. Clean: glass/dishes clean

2. Shiny: glass/dishes shiny

3. Smell: Non-perfumed/lemon fresh/intensive lemon fresh

4. Quantity: small/medium/x-large

5. Packaging: loose in box/tab in plastic/tab in dissolving plastic

6. Design: single/multi-colored/multi-colored + ball

Questions answered by Conjoint Analysis

  1. Do I have the right pricing strategy?
  1. How important are new features?
  1. Does my brand matter?

Practical applications:

Conjoint Analysis in Health and Medicine: Conjoint analysis is used to measure the relative value of specific components of health status and health-care alternatives by decomposing an alternative into its constituent parts (10-13). For example, the component attributes that define a pharmaceutical intervention might include efficacy outcomes, safety and tolerability outcomes, mode of administration, and cost. In all conjoint analyses, different levels are assigned to each component attribute to create a series of profiles which study subjects are asked to evaluate through rating, ranking, or choice tasks. Subjects’ systematic evaluation of these profiles allows researchers to infer the relative importance of each component attribute as well as changes in the levels of each component attribute.


Sushma Pamidi (Ops – Group 2)

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