Conjoint analysis is a market approach that allows optimization of the product’s feature and its pricing plan. The preferences of the customers are identified which leads to the analysis of the various parameters related to the marketing of the products. Nonetheless, the analysis performed provides a clear understanding of the market share that the product can possibly claim. It identifies the people in the market that can show a willingness to adapt to the product.
The conjoint analysis applies to diverse types of businesses and products for optimal market analysis from small-scale to large-scale marketing campaigns. Conjoin analysis approaches the problem by breaking it down into several components that are referred to as attributes or levels of product. The process explores the diverse combination of these features that contribute most to the assessment of consumer preferences.
It provides an alternative to the survey approach that directly asks questions to the customer about the experience and requirements related to the product and services. Conjoin analysis follows a realistic approach where subsets of choices go through vigorous statistical operations. Product designing, business decision making, strategic marketing plan, need-based marketing segmentation, and environmental impacts of the product are some prime use cases of conjoint analysis in diverse businesses.
The general steps involved in conducting conjoin analysis are:
- Identification of the business problem
- Formulate comprehensive research questions
- Identify suitable research methodology
- Relevant data collection
- Pre-processing of data
- Analysis of data
- Visualization and presentation of data
- Decision making
These eight steps apply to most of the conjoin analysis while the analysis procedure of the conjoin analysis depends on the type selected for analysis.
CBC (Choice-Based Conjoint)
The problems based on marketing as well as the economic decision-making are handled with choice-based conjoint analysis. The choice of the user is considered about what type of product they are interested in buying. It does not approach the decision based on the ranking or rating system, since it considers that it is an unrealistic approach. Instead, it asks for the purchase preferences of the user rationally.
ACBC (Adaptive Choice-Based Conjoint)
The subset of choices or features provided to the participants is directed towards fetching the details about the characteristics of the products and services. The intensity of their demand for the feature is also contemplated to obtain the most effective outcomes. The combination of choices stipulated in the ACBC approach adds competitiveness and refines the results.
MBC (Menu-Based Choice)
The menu-based choice uses advanced tools for detailed analysis to figure out the menu choices. It iteratively applies multiple checks. To perform conjoin analysis driven by a menu-based approach, higher statistical expertise is required to carry out the procedure since it involves modelling complex data structures related to the product choices of the consumer.
Full-profile conjoint analysis
Consumers are bombarded with a detailed description of information related to the product before they respond to their product choices. The product information is made available in a quantitative format. The methods that full profile conjoint analysis employs are common practices where no specific expertise or complex procedure is involved.
Max-Diff conjoint analysis
The max diff conjoint analysis checks the choice of the consumer on two extremes where it asks the user to select the items that are the best as well as those that are worst. In this technique, no mild or moderate option is provided to the user and the user continuously swings between two extreme ends. Max different is an easier approach to respond to as well as for analysis.
Discrete Choice Analysis
The discrete choice analysis is also known as the preferred studies. The discrete choice analysis is a sophisticated approach that is extremely useful in transportation-based research. The automobile industry can inquire about the user preferences related to the model, type, and medium of transportation.
The hybrid approach combines goods of various approaches where two objectives are prioritized. First, it focuses on simplifying the information that is delivered to the user. Secondly, the analysis of the choices is conducted as well as the correlations of the choices selected by the user. The hybrid model is self-explanatory where the user is capable of directly assessing its choices.
The conjoint analysis approach has to help up with the deep inspection throughout academics as well as in professional researcher areas for the last three decades. It is extensively exhausted in products, transportation, pharmaceutical, goods, and service. The conjoint analysis is extremely helpful in identifying consumer preferences and market analysis.
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Shepherd, D.A. and Zacharakis, A., 2018. Conjoint analysis: A window of opportunity for entrepreneurship research. In Reflections and extensions on key papers of the first twenty-five years of advances. Emerald Publishing Limited.
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Block, J., Fisch, C., Vismara, S. and Andres, R., 2019. Private equity investment criteria: An experimental conjoint analysis of venture capital, business angels, and family offices. Journal of corporate finance, 58, pp.329–352.
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