In today's competitive market, it has become essential for brands to acknowledge what the consumers want. Depending on their budget, brands can try a lot of things to sustain in the market. However, success comes only to those who are able to meet the requirements of the consumers. While there are several ways to determine what the consumer wants, most business leaders prefer to conduct a conjoint analysis.
Conjoint analysis is an advanced technique used for statistical market research. It helps a researcher to understand how people make complex choices. Using this technique, businesses try to measure their potential customers value the most while making a purchase decision.
Imagine you are responsible for the marketing activities of a car manufacturer. For an effective marketing strategy, you need to identify what the consumers want from a car manufacturer. For example, you may need to find out whether the customers value comfort or do they value the features more? Or, is it the pricing of the cars that customers value the most? Conjoint analysis can help you get the answer to those questions.
Interestingly, there are several types of conjoint analyses that researchers can use for their needs. However, in most cases, the choice-based conjoint (CBC) is chosen by the researchers. The reason is that CBC offers combinations of attributes and also asks respondents about their preferences. In other words, CBC most closely resembles real-world buying behavior.
Like a majority of market research methods, a CBC analysis also banks on surveys for a comprehensive result. However, conjoint survey questions can be quite taxing for the respondents. So, you need to pay close attention while conducting the whole analysis program, especially the survey part.
The best part about conjoint analysis is that you don’t need to ask every individual respondent to get the rankings. Through mathematical analysis, you can produce the ultimate rankings. This method not only combines the answers to the surveyed questions but also infers the answers to questions that were never asked. Here are some tips on how to conduct a CBC analysis.
Attributes are the characteristics or features of the product or service. While preparing the survey questions, you need to ensure that you include all the attributes that influence the customers' purchase decisions. If you miss a significant attribute, it may cause an error in the results. However, you cannot overwhelm the respondents by providing too many choices for attributes. 3-4 choices are enough.
Levels are the different measurements for certain attributes. For instance, if you are looking for the price, the levels can be $999, $550, $1200, depending on the product/service. While testing, you need to ensure that the chosen levels are not too close to each other. If you are testing motorbikes, don’t choose 350cc, 355cc, and 360cc as the levels for engine power. Go for levels like 350cc, 500cc, and 700cc.
While preparing the survey form for the test, you need to be careful about the words you use. You need to ensure that the language is neutral and free from biases. For instance, if you choose words like “cheap” or “expensive” instead of using the exact pricing as the levels, it may come off as biased. Also, you need to define each attribute independently without causing any confusion.
As mentioned, considering too many attributes for the test is not a good practice for surveys. Number of attributes means number of combinations, which further call for more number of responses. This can increase the cost and time required for the project. So, it is important to consider the numbers for attributes and levels in order to limit the required number of responses at an achievable figure.
Just remember these things while creating the survey questions and use the right tools to analyze the survey data.
Like any other analytical process, the conjoint analysis also has its fair share of advantages and disadvantages. Before you try the process all by yourself, it is better to have a look into the pros and cons.
Conjoint analyses are used in a variety of market research and insight applications. The list is long. However, we have narrowed down to five of them that are more significant in today’s world.
Shelf-display conjoint analysis is an effective application of the conjoint analysis technique. It helps determine the changes in the demand for specific SKU (stock keeping units) due to changes in price. Also, it can be used to optimize the set of SKUs and prices offered within a category to boost coverage, share, and revenue.
Conjoint can also be used for pricing research to understand the value of different features that make other products special. In this form of conjoint design, the price is just one attribute among several others. The brand name is another crucial factor that plays a crucial role in the research. And using this technique, it becomes possible to separate the direct value of the brand name from specific features of the product.
Healthcare and pharmaceutical research are two areas where conjoint analysis and trade-off approaches can be of different types of use. When these industries prepare or design drugs and health interventions, they maintain a fundamental balance between effectiveness, safety, and convenience. For health providers, conjoint analysis can help understand the relative value of different health interventions.
This is one of the popular applications of conjoint analysis. For new products, creating and describing the features to fit within a conjoint exercise can be extremely effective. It can help in thinking and setting key priorities and targets. It can even optimize a large number of features potentially through multiple exercises.
The use of conjoint analysis is steadily increasing in the area of human resources. With the help of this method, the HR team tries to understand how employees value and trade-off various forms of benefits and remuneration packages. This helps to set optimum policies across the business group.
Besides, the conjoint analysis method is used in optimizing membership schemes, club features, needs-based segmentation, and much more.
There are quite a few conjoint analysis tools in use. If you want to conduct accurate conjoint analysis, you need to use them too. Here is a list of the most popular ones that you can consider.
Conjoint.ly is a digital platform that allows the users to perform conjoint analysis for a fraction of traditional cost. With this tool, users can find respondents in a number of ways. To test something within the organization, the user can simply copy the survey link to share with people. Otherwise, he has the option to integrate the URL into another survey platform. This tool can even send invites, track responses and do a lot more than regular surveying tools.
1000minds is another digital platform which helps conduct prioritization, group decision-making, conjoint analysis, and maximizing value for money. This tool uses PAPRIKA (Potentially all pairwise rankings of all possible alternatives) to help businesses, government, and non-profit users to make better decisions. Interestingly, the operations are based on considering multiple objectives or criteria.
Survey Analytics is a feedback platform that helps manage feedback from clients over the internet platform. It works in unison with QuestionPro, which is a leading provider of global online customer feedback capabilities. Together, these two tools can offer the most comprehensive survey, feedback, and insightful participation at the same time. Also, they help the users to engage customers, employees, and other significant parties.
Lighthouse studio is quite popular among its users for its efficiency in conducting quantitative research. In fact, the software was initially designed to manage surveys and other data related to analytics. Using this tool, the users can get a complete preview of the survey and test it on a local PC without any internet connection.
The package “Support.CEs” provides supplementary and supportive assistance to the implementation of choice experiments. It has seven essential functions, which include:
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