Question

In conjoint analysis, what is the nature of the relationship between market share and revenue per unit for a product/service design? Please also explain "why"

Answer 1

In conjoint analysis, the nature of the relationship between market share and revenue per unit for a product/service design is a survey-based statistical technique used in market research that helps determine how people value the different attributes (functions, functions, benefits) that constitute a particular product or service.

The purpose of the pooled analysis was to determine whether the combination of determinants was most influential in respondents' choices or decisions. A controlled set of potential products or services for survey respondents is presented, and by analyzing the way they choose between these products, the actual evaluation of each item that constitutes the product or service can be determined. These empirical estimates can be used to create market models that evaluate market share, revenue, and even profitability of new designs.

Conjoint is of mathematical psychology and was founded by Paul El Green, professor of marketing at the Wharton School at the University of Pennsylvania. Other prominent pioneers in the joint analysis include Professor V. "Seenu" Srinivasan of Stanford University who developed a linear programming procedure for sequencing data and a self-explanatory method, Richard Johnson, who developed the technique of Adaptive analysis of compounds in the 80s. Those years, and Jordan Louvier, who developed and developed methods based on options for collaborative analysis and related techniques such as worst case scaling.

Today it is used in many social sciences and applied sciences including marketing, product management and operational research. It is often used to test consumer acceptance of new product designs, in evaluating advertising attractiveness, and in service design. It is used in product locations, but there are some that create problems with the implementation of this integrated analysis.

Collaborative analysis techniques can also be termed multidimensional composite models, selection of models with different characteristics or preferences, and are part of a set of commercial analytical tools widely used for analysis. Systematic decisions. These tools include sales, brand value, Trade - off, and mathematical methods such as AHP, evolutionary algorithms, or rule-making experiments.