Conjoint analysis is a type of survey method that tells you what people value in a product in order to make better predictions about how people will act when they see that actual product. In this article, we will extensively discuss conjoint analysis, the types of conjoint analysis, and the application.

What is Conjoint Analysis?

Conjoint analysis is defined as a technique in survey research that helps you determine which features are most important to people, and how much those features matter. It is also used as a business research technique that helps identify how people make choices.

This is achieved by presenting them with choice-based scenarios and asking them to choose their preferred option. The scenarios are presented to the respondent consistently in order to measure their preferences. The data collected can be analyzed and used to predict customer behavior when making purchase decisions.

Conjoint analysis has been used for over 50 years in many industries, including healthcare, banking, insurance, retail, automotive and more. It’s a great way to understand what matters most to your customers. Conjoint analysis is also a powerful research tool that offers insight into customer preferences.

It can be used to determine;

• How customers think about products or services they’re considering purchasing
• Whether they’re willing to pay more for certain features or benefits of those products/services
• Which attributes are most important when making those decisions – like price versus quality.

For example, if people are asked whether they would rather have an ice cream cone with sprinkles or without, it would be easy for them to answer this question. If instead, they were asked whether they would rather have an ice cream cone with sprinkles and hot fudge sauce or just sprinkles, it becomes harder for them to decide which option they prefer because there are two competing preferences at work (sprinkles versus hot fudge).

Read: Max-Diff Surveys: Definition, Examples, Pros & Cons

The conjoint analysis presents a look at these kinds of trade-offs between different attributes so that the combinations of features that are most appealing to consumers can be determined. This is also because the term “conjoint” means “joined together,” so this technique allows you to join several different ideas into a single concept in order to see how they influence each other and produce different effects on our perceptions about products.”

Key Conjoint Analysis Terms

1. Features: A feature is a characteristic or attribute of a product. Take for example the Apple Watch. Some of its features are its color, size, and weight.
2. Task: A task is a choice between 2 or more products. The task format often resembles a survey question and asks respondents to choose between several products using different attributes.
3. Relative importance: This term refers to the importance of a particular feature in influencing someone’s decision about which product to buy. For example, in choosing between 2 laptops, this might be the RAM size or screen size.
4. Profiles: A profile is a set of features that are presented to respondents in order to measure their preferences.
5. Levels: When you’re creating conjoint tasks, there will be levels of each feature, which represent the possible values of any given attribute, for example, small/medium/large or black.
6. Market simulations: Market share simulation refers to how often people pick certain features or levels over others when they are given a choice between two or more configurations of said features/levels.
7. Brand premium: A brand premium is how much more consumers will pay for your product when it has your brand name on it than if it didn’t have any brand at all. It helps you understand the value of your brand in the marketplace.
8. Utility values: Conjoint analysis measures the “utility” of each attribute to determine how much value customers place on that attribute. The higher the utility value for an attribute is, the more important that attribute is to consumers.
9. Price elasticity: This refers to how sensitive consumers are to pricing changes. Put simply, price elasticity tells you whether or not people will still buy your product if you raise its price.

Read: 7 Types of Data Measurement Scales in Research

Importance of Conjoint Analysis

Conjoint analysis is an established technique for understanding how people value different attributes (feature, function, benefits) that make up an individual product or service. The objective and importance of conjoint analysis are to determine what combination of a limited number of attributes is most influential on respondent choice or decision making.

Conjoint analysis is the most popular method for measuring the trade-offs that consumers make among the various attributes of competing brands or products. It can be used to determine such things as:

• The optimal price/quality combination to use in pricing a new product.
• The relative importance that consumers place on different features of your product versus those of your competitors.
• The optimum way to position your brand versus competitor brands is based on the factors that are most important to consumers.

Read: Survey Ranking Question: Examples, Scales and Types

Applications of Conjoint Analysis

The applications of conjoint analysis are:

1. Pricing: conjoint analysis is used to analyze what price points will be the most effective for a specific product.
2. Concept testing: concept testing is usually done when a new product idea has been developed, and its goal is to gauge consumer opinion on the product. This helps the company decide whether or not to pursue that particular product.
3. Advertising development: this involves finding out how consumers view an ad and how that ad affects their perceptions of a brand.
4. Forecasting/prediction models: in addition to helping with pricing and concept tests, companies also use conjoint analysis to help forecast demand for a particular product. The conjoint analysis helps them determine what features and characteristics consumers find most desirable in a product. This gives them the information they can use to predict consumer behavior.

Types of Conjoint Analysis

There are two main types of conjoint analysis: Choice-based Conjoint (CBC) Analysis and Adaptive Conjoint Analysis (ACA).

1. Choice-based Conjoint (CBC) Analysis

Choice-based conjoint is a marketing research method in which respondents choose between a series of product profiles or “concepts”. It is a way to determine how people value the different features that make up an individual product or service. Choice-based conjoint analysis is one of the most accurate ways of determining how consumers value different attributes of products and services when making decisions to purchase.

Its name comes from the fact that respondents are asked to choose or in some cases rank among various combinations of product attributes and levels. Their choices provide insights into the relative importance they place on each attribute, as well as their preferences for each level.

The following are the three main types of Choice-based Conjoint analysis:

• Full Profile CBC: In this type of Choice-based Conjoint analysis, each respondent is presented with all possible combinations of attributes for evaluation.
• Adaptive CBC: In this type of Choice-based Conjoint analysis, each respondent starts by being shown a subset of profiles (usually 4 or 6). Then, based on their responses to the first set of profiles, additional profiles are shown to each respondent until sufficient information has been gathered. The data is then analyzed to determine which attribute levels are preferred over others and by how much.
• Adaptive Choice-Based Conjoint (ACBC): This is very similar to Adaptive CBC in that it begins with a subset of profiles which are then refined based on the respondent’s answers.

2. Adaptive Conjoint Analysis (ACA)

ACA is a computer-assisted method that allows respondents to evaluate each concept one at a time. The software generates concepts randomly, based on specifications set by the researcher. ACA takes less time than CBC and accommodates more attributes, levels, and concepts. It can be difficult to analyze without specialized software. It is used to determine how customers feel about those features, and how much they are willing to pay for them.

Both ACA and CBC start by asking participants to evaluate profiles made up of various attributes, but the way that information is collected differs between these two types of conjoint analysis.

Advantages of Conjoint Analysis

Conjoint analysis is a powerful marketing research technique used to determine which features of a product are most important to consumers. By doing this, you can make informed decisions about how to design a new product or improve an existing one.

1. It’s relatively easy to administer
2. It’s less expensive than other methods
3. It can be used for both new and existing products
4. Conjoint analysis is a great way to get insight into your customers’ minds
5. The results are then used to make decisions about what features should be included in the final product design and how they should be priced.

Read: User Research: Definition, Methods, Tools and Guide

Disadvantages of Conjoint Analysis:

1. It takes more time and money than other methods
2. The information may be biased by the order in which questions are asked
3. You have to ask a lot of questions, which can be overwhelming for some customers
4. It can be hard to analyze all the data that’s been collected

Conclusion

Conjoint analysis can help you understand which product features and price points attract the most customers. It is important for researchers to understand how conjoint analysis works and make use of it where appropriate.