The term conjoint analysis has been used in market research as a statistical technique to determine how people would value various attributes such as benefits, feature and function, making up a product or service. This is intended to determine which combination of limited attributes is most prominent based on the choice of respondents.
This method is used using a controlled set of products or services that will be presented to respondents. It will analyze how the respondents make preferences between the products in order to determine implicit valuation of individual elements. Such implicit valuations can be utilized in the creation of market models that should be able to estimate revenue, market share, and profitability.
The procedure of conjoint analysis involves the gathering of data through marketing research survey. However, conjoint analysis can likewise be applicable for carefully designed data or configurator from the test market experiment.
Basically, you can gain thorough understanding about the market and the value or your services or products as how respondents see it. This can be viewed on a listing showing attribute levels and corresponding utilities that should be calculated for certain attribute levels.
With this method, it can also be useful to run market simulations in order to predict the reaction of the market with regards to different scenarios. For instance, you can receive your own program for simulation. Thus, you and your managers will be able to make their own scenarios based on the market. This will enable you to see how the market has reacted in response to price cuts, new products, and other changes.
List of Advantages of Conjoint Analysis
1. Brand Equity
The method of conjoint analysis is perfect for measuring value of brand names related to competing brands. Unlike other methods of measurement for brand equity, conjoint analysis should be able to obtain information regarding brand strength or popularity compared to specific product prices and features.
It may not be enough to have only a dominant brand name if majority of the market is price sensitive. More so, it is possible to desire a set of features that is enough to offset the investment regarding brand equity. In conjoint analysis, however, it is imperative to make estimates on how the market makes such tradeoffs between specific features, prices, and brands.
2. Useful in Market Segmentation
One of the best techniques to measure the benefits as seen by buyers is the use of conjoint analyses. It is the measurement of the actual and perceived benefits wherein it lies at the center of most of the approaches of market segmentation.
Understanding the value that people put in your services or products will allow you to design marketing programs that should communicate the benefits. It will also enable you to redesign existing products or make new products using the benefits you have in mind.
3. Close Resemblance of Customer Decisions
Customers are able to provide decisions in the market place. This is where they are allowed to look at available alternatives and pick one being preferred more. With conjoint analysis, they can mimic the decision process made by customers. In fact, even if can be difficult to prove, the more it closely resembles real behavior, the more the results will become valid and reliable.
4. Measuring Price Sensitivity
Utilities for price levels will offer one measure of sensitivity of the market or the market segment. Upon the calculation of the interaction between price and the other attributes, it is possible to measure the sensitivity of prices that may vary with respect to the brand name as well as the other attributes. Thus, it is possible to run simulations at different price points so that it will be easier to calculate changes in your own or in your competitor’s prices.
5. Ease of Calculating Attribute Interactions
Brand and price are attribute interactions. When applying conjoint analysis, it can be easier to calculate these attribute interactions, which can be included without increasing the complexity of research design. These are mostly used in choice-based conjoint exercises.
6. Enables Purchase Decisions
Respondents are able to choose none-of-these option in making purchase decisions. This is one of the alternatives which is to walk away even without purchasing anything. In a choice-based conjoint analysis, it will allow the user to include this response on the model and account for this within the calculation of utilities.
List of Disadvantages of Conjoint Analysis
The design of conjoint studies has been considered complex in nature.
2. Resorting to Simplification
In accordance with so many options, respondents are able to resort to simplification strategies.
3. Difficult to Use
There is no procedure for the conversion of perceptions regarding the actual features to perceptions regarding a reduced set of features, which makes it difficult to utilize for the research of product positioning.
4. Inability to Articulate Attitudes
When it comes to new categories, respondents find it hard to articulate attitudes. Moreover, they may feel being forced of thinking regarding the issues they are not supposed to give much attention to.
5. Over- or Undervaluation of Variables
In the event of making poorly designed studies, there is a tendency that the variables will be overvalued or undervalued.
6. Poor Market Share Reading
There is a tendency to provide poor readings of the market share because it did not take into account the quantity of goods per purchase.
If you want to conduct conjoint studies, it will require greater information processing that you can get from respondents compared to traditional survey methods. Thus, you must be able to place conjoint exercise in front of your respondents in order to examine the information and they should proceed using their own pace.
Conjoint studies are basically conducted using mail, disk-by-mail surveys or recruited to a main location to conclude a survey via a computer or paper. As a matter of fact, it will be easier for most businesses aiming to conduct such studies because there are added means of conducting conjoint analysis among high-tech markets, high-income consumers, and businesses.