Each product or service is the result of a combination of attributes. For this reason, before launching a new product or service and optimizing an existing one, it is essential to analyze its attributes and identify which combination can be better received by consumers. For this purpose, a market study known as a Conjoint Analysis can be carried out.

 

What is a Conjoint Analysis?

 

A Conjoint Analysis, analysis conjoint, or multi-attribute model, is a quantitative market research technique that allows you to identify the relative value of each of the product features and the combination of characteristics that would be most successful among consumers preferences. Conjoint Analysis allows you to analyze the process of consumer choice and preferences, identifying how consumers form priorities when purchasing a product and service.

The analysis’s objective is to evaluate new launches and established products. In the case of existing products, it identifies the importance given by consumers, both current and potential, to the product’s characteristics and what most influences them at the time of purchase. In the case of innovations, the model makes it possible to identify the characteristics most valued by consumers, minimizing risks and ensuring the product’s success.

We are all consumers, and when we buy, some features weigh more heavily on us than others when deciding on one product. Perhaps we are willing to pay more for a more airtight package, or we prefer to spend less, and the size of the product is smaller. The combination and importance of these factors and how they affect our purchasing decision is what Conjoint Analysis analyzes.

For example, for a dairy company preparing to launch a new yogurt, Conjoint Analysis allows it to identify the level of preference for each of the possible combinations of characteristics (type of packaging, flavors, price, size, etc.) and how these may affect the purchase decision. 

It is, therefore a multivariate analysis that allows us to answer, for example, the following questions: 

  • Which attributes are most relevant to the consumer?
  • Which characteristics or options determine the purchase decision?
  • What is the level of preference for each of the combinations?
  • Which combination of attributes presents the most significant sales potential?
  • What is the optimal product price?
  • Segmentation of potential customers

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When is it useful to conduct a Conjoint Analysis?

 

Conjoint studies can be applied in different sectors and for any product and service type. A service, is especially relevant in the case of:

  • Launching or redesigning a new product, aims to increase its probability of success.
  • Predicting consumers’ buying behavior and knowing which characteristics they value most, as well as the weight of these in the purchase decision. For example, when buying a cell phone, an example of conjoint survey question would be what does the customer prioritize: camera, screen resolution, size, price, etc.?

 

Types of Conjoint Analysis

 

There are different forms of Conjoint Analysis but the most common, which differ mainly by the type of design, are:

  • Choice Based Conjoint Analysis (CBC): multi-attribute model that allows to understand the attributes and options that move the consumer to product choice. It is a widely used type of analysis since it is a purchase simulation where the consumer, from different predefined scenarios, chooses the combination they would buy after analyzing the characteristics of each of the proposals presented.
  • Adaptive Conjoint Analysis (ACA, also known as ACBC): a multi-attribute model that allows us to understand the differences and factors that move consumers to choose between different brands. The ACA is suitable for studies with many attributes and competing brands. In this case, we also work with a purchase simulation. The difference concerning CBC is that there are no predefined questions, but the survey is based on the answers given by the consumer.

 

How to make a conjoint analysis?

 

Before performing a conjoint analysis, it is necessary to determine the product’s attributes and main levels or options to generate an experimental model as efficiently as possible. The aspects to be taken into account are summarized in 7 points:

  • Select the relevant attributes within the category. The greater the number of attributes, the more complex the study will be, so it is recommended not to choose more than six attributes.

Different qualitative research methods, can be used to select them, as well as consulting with the team that created the product or gathering information. For example, in the case of a yogurt launch, the relevant attributes could be the type of packaging, price, and size.

  • Select the levels or options for each attribute. That is, select the possible options for each of the defined attributes. For example, packaging (glass, cardboard, plastic), size (100g, 110g, 120g), etc… For this, it is important to take into account:

– The characteristics presented by the competition (in the case of existing categories).

– Try to minimize the levels to simplify the consumers’ evaluation.

– Consider, as far as possible, working with the same number of levels or minor differences, thus ensuring the model’s effectiveness.

  • Determine the combination of attributes and levels that we would like to evaluate. The process of selecting the combinations of features and levels is known as experimental design and requires extensive statistical and mathematical analysis.

To present an agile and dynamic consumer survey, thus ensuring the most efficient experimental model possible, a maximum of 25 attribute combinations is recommended, although ideally no more than 16.

  • Prepare the questionnaire to show the consumer the products with their combinations to be tested. It is necessary to determine how we will show the stimuli and whether we will use images or descriptions (in the measure possible, it is advisable to display images).
  • Design the survey data collection procedure. At this point, the products are presented in different scenarios to a representative market sample to be evaluated according to the Conjoint Analysis model chosen.
  • Select the computational method to obtain the necessary insights. Using statistical analysis techniques, the analysis utility values or partial utility, i.e. the importance values of the attributes, are determined. 

Scores that measure how much each characteristic influences the consumer’s decision-making process. 

  • Evaluating product options. Once the utility values have been obtained, we can conclude which product presents the most significant sales potential. And which combination of attributes and levels is the most attractive to the consumer, what market share the product would obtain, what its sales projection is, and which segment of the population we should target.

 

Like any market research technique, Conjoint Analysis presents its advantages and disadvantages.

 

Advantages of Conjoint Analysis

 

Conjoint analysis is a powerful tool that provides us with a wide range of consumer decision-making information. Its advantages include: 

  • Choosing the most valuable attributes for consumers to position a brand. 
  • Identify the influence of an attribute on the purchase decision. 
  • Estimating the success of a product before its launch. 
  • Calculate the potential market share of a new product. 
  • Decide on the optimal price for a product. 
  • Segment the market in relation to the attributes of a product.  
  • Identify which product is likely to be most successful in the market. 

 

Disadvantages of Conjoint Analysis

 

The multi-attribute model is a valuable but complex tool to design and implement. Hence, it is necessary to have knowledge of the technique or rely on specialized advice to perform the analysis

As for its disadvantages as a research tool, I would point out that it can only be used if more than two attributes and two levels or options for each attribute are being considered. Also, the model presents limited options from which respondents are forced to choose.

In any case, if this type of analysis does not meet your objectives, there are alternatives that can help you get the insights you need quickly and efficiently. Through the Zinklar platform, for example, you can carry out different projects always accompanied by a team of experts. Would you like to discover all the possibilities offered by the platform? ¡Sign up and try it out!

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