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Conjoint analysis can be defined as a survey-based statistical technique that is used as a research analysis method. It attempts to understand how people make complex decisions and value different attributes that make up individual products and services. Conjoint analysis is based on the principle that all products can be broken down into attributes that define how users perceive their value.
Conjoint Analysis is often used across a sundry industry as it is applicable in various instances that aim to define the types of products consumers are most likely to buy. It can help companies make pivotal decisions regarding many aspects of their organization.
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Conjoint analysis, unlike traditional surveys, allows for the rating of different attributes that make a product. With the right survey analytics software at your disposal, It lets you screen through the responses/choices, enabling you to determine the reasons for why respondents chose them.
The four steps required to create a Conjoint Design
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Conjoint analysis is considered to be the best survey method to determine consumer values. It allows companies to understand product features and service features that customers value. This information aids businesses in making highly informed decisions when it comes to things like product development, sales, and pricing.
There are many applications of conjoint analysis. These are a few:
It works by directly asking respondents to compare different attributes to understand how they value each one. By understanding this, a company can understand how customers would appreciate its products. This information can help develop many strategies for the company’s products, pricing strategies, for example.
This type of conjoint analysis asks consumers to imitate their purchasing behavior like they would in real life. It studies the products they would choose depending on specific criteria.
ACA analysis customizes every respondent’s survey experience based on their answers to the first few questions. This conjoint analysis is usually employed in studies where multiple attributes need to be evaluated to streamline the process and obtain valuable insights from every respondent.
The full-profile conjoint analysis presents a series of full product descriptions to respondents. Then, respondents are asked to select the one that they would most likely buy.
This form of conjoint analysis will present respondents with a series of options. Then, the respondent is asked to order these options on a scale of “most likely to buy” to “least likely to buy.”
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