Home Tech What is conjoint analysis, and how is it helpful for an organization in producing specific products?

What is conjoint analysis, and how is it helpful for an organization in producing specific products?

by Rohan Mathew
What is conjoint analysis

Every successful organization is working well because it satisfies its customers. If the customers are happy with the products and services, the organization will continue to grow. More customers will get attached to the organization because of its positive feedback. 

Organizations can satisfy the customers only if it delivers the products or services according to their desires and expectations. Organizations tend to survey their customers to collect their responses and make products according to their will. This type of survey is called a conjoint survey. Let us discuss it in detail.

What is conjoint analysis?

Conjoint analysis is a type of survey or research used to gather useful information about the products and their pricing. It helps the organization in setting the product price, change or add new features, launch a new product or determine market trends

In this type of research, customers are asked to choose or compare the features of a product. They suggest changes or new features about the product. In this way, the organization gets to know the likes and dislikes of customers about their product. They set the pricing accordingly. 

Take a look at this conjoint analysis example

When to use conjoint analysis?

Whenever the organization launches a new product, it is a good idea to conduct a conjoint analysis to know the views of the customers. The best part is setting the pricing through it. When customers are asked to compare the features or rank the variations, there are more chances of increase in the sales by fulfilling those desires. 

Terminologies of conjoint analysis:

There are different terminologies used in conjoint analysis. Some of its basic terminologies are discussed below:

Attribute:

Attributes refer to the features of the product. If the company has launched a product that comes in varieties like color, size, model, price, or flavor. Within each attribute is a level, for example a medium of large size. It is important to collect responses from customers about these variations. Commonly, attributes are the first asked question from the customers. 

Concept:

The concept refers to the combination of various attributes in a single product. For example, customers may want to have an ice-cream composed of a scoop of vanilla, a scoop of chocolate followed by the rush of almonds and pistachio along with chocolate candies on top. It will create a new product containing attributes of almost all types of ice-creams. The term Concept is also called cards in some software.  

Set:

A set contains different concepts and is also called a task. Customers may choose a single concept from a set and create another set. 

Part-worths:

Part-worths is the most important term to know in the conjoint analysis. It represents which attribute of the product gets the most value from the customers. By collecting responses from customers, organizations determine the worth of the product. 

Customers rank each attribute or express their opinions which then leads to better production and pricing strategies. Instead of part-worths, most people use the term ‘utility’.

Analyzing the results of a conjoint survey study

Conjoint analysis uses logistic regression to calculate the output of the various attributes and levels. These coefficients are referred to as “utilities” or “part-worths”. Like in the above example conjoint output, each  attribute has an importance value, and each level has a utility value. The importance is simply a weighted average of the total utilities in each level. The more important an attribute is, the greater on average it’s utilities are. 

For each attribute you would look at the utility value of each level to gain a more detailed understanding. If “medium” has double the value of “small” you could interpret that as: “respondents think a medium size bring double the satisfaction that small does”. 

Related Articles

Leave a Comment