Conjoint Analysis
What Is Conjoint Analysis?
Conjoint analysis is a specific type of research that is focused around the research relating to products. The kind of research done under it goes beyond the standard research and data collection and therefore it is known with a separate name – conjoint analysis.
In this type of analysis, the focus is given to the way that customers make choices in their everyday life. With so much competition and so many options available to customers, they knowingly or unknowingly make a trade off while making a purchase.
It focuses on that trade off and tends to ask questions from respondents that make them rank from different kinds of features that different products have. Once the data is collected and cleaned in a proper quantifiable form it goes through a complex mathematical and statistical process in order to generate unique results.
The report generated from conjoint data collection can be beneficial in understanding consumer preference of product features or their sensitivity towards product’s pricing or success rate of the new product or the changes made to an existing product and many more.
Example Of Conjoint Analysis
Going through the definition and trying to understand it must give an impression that conjoint analysis is no rocket science. Yes, it’s not! But it’s not as simple as it may seem. Let’s look at an example and see and understand this type of analysis.
Let’s take mobile phones as our product for three different brands – Samsung, Oppo and Apple. By definition we know that it will help us understand customer view or preference for different features of products and its price.
Let’s take the mentioned features: Product price, Operating system, Screen size and Camera resolution for the phones of the above three mentioned brands. We will collect customer data for these attributes and will try to mathematically understand the impact of these features on consumers, its competitiveness, its estimated market performance and much more information can be analysed.
Now that we know and understand the term thoroughly, it’s important to note that due to its nature, there can be different variations based on the data that the company wants to collect for its products.
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Key Terminologies Relating To Conjoint Analysis
Now that we know and understand that it is different from other data collections and reports generated out of them. Therefore there are certain specific terminologies relating to conjoint analysis. Let’s look at each of these key terminologies that are used during conjoint analysis.
- Attributes: This terminology is used for the product features for which we are conducting this analysis. This can be different product brands, different product sizes and many other things depending on the product and the attributes for which this analysis is conducted.
- Levels: This terminology is used for the specification made under each attribute. For instance we can have brand as an attribute and the name of different brands included in the conjoint analysis can come under levels.
- Task: This terminology is used to define the number of times a respondent has to make a choice. For instance, the first of the five functions can be marked as step 1 out of 5.
- Concept/Profile: This terminology is used for any hypothetical product offering made to the customers and is represented as a set of attributes with different levels being shown at each task count.
- Relative importance: This terminology is used to represent ‘attribute importance’ given by the customer while making a purchase. For instance, while making a purchase for a laptop, brand can have 35% of relative importance, then size of the laptop and battery life can have 15% importance each and so on and so forth depending on the attribute given in the this analysis.
- Utility values: This terminology is used to represent the weight of each attribute given by the customer.
- Market share simulation: This terminology is post data collection term that is used to represent the change in the market value for the company if the product is made live to the customers or the new changes made to an existing product gets launched.
- Brand Premium: This terminology is also a post data collection term that is analysed by looking at the price attribute of this analysis. This tells us how much the customer will be willing to pay for the product as compared to its competitors and what will be their price sensitivity towards the brands and the products.
- Demand curve: This terminology is post analysis term and is used for the graphical representation of aggregate demand for the product at different prices and shows us the price elasticity for the product.
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Usage Of Conjoint Analysis
It is very helpful in collecting information about the various aspects of a product which a normal research or data collection and analysis cannot analyse. However, there are two use cases for which this analysis is widely famous for. Let’s look at these two use cases of conjoint analysis and get a better understanding of the same.
- Market Research
Using conjoint analysis, you get a deeper insight into consumer preference. You get to know about the different features of a product or service that is the requirement of your customer base and will most likely appeal to them. It can also be helpful in the market research for existing products as you can collect data to improve your sales at various points in the customer journey.
- Product Pricing Research
Conjoint analysis is most famous for researching and finalising the price of the product that will be fair and customers will be willing to pay, given the specific features of the products or services. Conjoint analysis works the most for pricing research as it makes customers stand in the position where they make a trade off between the different brand’s products or services with each brand having its own product price and feature.
Conclusion
Now you know what a conjoint analysis is and how you can use it to benefit your business. Don’t wait and get straight to it. It might seem very time consuming and difficult to analyze the data for this type of analysis once the data is collected. But you need not worry about it. There are multiple tools available for you to help with it for your product.
Fynzo Survey software also provides you with many tools like segmentation and filtering, relative importance and utility calculation which you can use to make your analysis easier.
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FAQs
Which is the most popular form of conjoint analysis?
In today’s time, choice based conjoint analysis is the one that is attracting major attraction of people.
What are some of the limitations of conjoint analysis?
Some of the major conjoint analysis includes complexity, difficulty to use, misguided valuation of variables and poor market share reading.
