Identifying the features of a product or service that matter to consumers can be a bit of a struggle, especially for marketers and marketing analysts. Asking consumers to appraise its importance and significance using a scale does not help discern some features from others. A simple scale imparts the idea that everything is of utmost importance. If the entirety of a product’s or service’s attributes and features are significant, then nothing is important. To resolve this, one can utilize a conjoint analysis. In this approach, respondents are given products that are detailed with an array of features and prices. Then, the respondents will pick among the products, which are comprised of clusters of features and prices. This analysis will illustrate how consumers compromise with the diverse attributes and prices. The result will determine the most significant characteristics that entice customers to purchase the product, the optimum degree of each characteristic, and the effect on the probable product demand.

What is a Conjoint Analysis?

Regarded as among the widely-used quantitative approaches in marketing research, conjoint analysis is utilized in gauging predilections towards a product feature, in identifying how price changes will impact the demand for the product or service, and in projecting the likelihood of a successful market release of the product or service. Through conjoint analysis, the market can be segmented according to the similarities of the product attributes, the design or configuration of the most favored brand can be specified, and the market share of brands that have disparate degrees of product features can be appraised.

Methods in a Conjoint Analysis

There are different approaches in utilizing a concept analysis. There is the Ratings-Based System, Choice-Based Conjoint (CBC), Partial-Profile Choice-Based Conjoint (Partial-Profile CBC), Adaptive Choice-Based Conjoint (ACBC), and Full-Profile Conjoint. These techniques can be adapted depending on the key decision areas. For instance, if more than eight attributes are to be examined, ACBC should be employed. In addition, let us say that the research is to be conducted through paper-and-pencil method, CBC is the best way to go. For relatively large sample size, it is suggested to use ACBC.

Ratings-Based System

The Ratings-Based System is the first technique in a conjoint analysis that dates back in the 1970s. In here, participants are directed to rank a series of concept cards. Every card shows a product concept constituting an array of features.

Choice-Based Conjoint

To date, CBC is considered as the most commonly used approach in conjoint analysis. Unlike a ratings-based system where participants will rank product concepts, this type of analysis will ask the participants which among a set of products would they likely purchase.

Adaptive Choice-Based Conjoint

In ACBC, survey participants are asked to set up their favored products and screen them by establishing consideration sets. From these sets, the respondent will select what he/she thinks is best. Basically, this type of conjoint analysis targets the participant’s highly favored product feature.

Full-Profile Conjoint

A full-profile conjoint analysis is a prominent means of gauging attribute utilities. Here, survey participants are given an enormous number of product descriptions for product acceptance or assessment.

Steps in Conducting a Conjoint Analysis

There may be different methods in a conjoint analysis but they have a similar process of conducting it.

Describe and Establish the Attributes

Understanding the customer’s purchasing decision process involves identifying the product features or attributes that customers take into account when making a purchase. Previous experiences, past studies, and defined research goals will dictate which of the features are significant and which of them need to be shown during product differentiation of the company’s new product and its competition.

After distinguishing the product attributes, the next step concerns establishing the attribute levels. The ideal number of attribute levels to be examined must be enough to achieve the research goals while curtailing the survey participants’ responsibilities. Usually, there are at least three levels per product feature, where each level have distinct disparities from the others.

Select the Approach

There are various approaches in conducting a conjoint analysis that researchers can use. These methods can be used depending on the sample size, number of attributes, nature of product features, and research objectives. The most common techniques are CVA and CBC.

Design the Research

Now that you have defined the attributes, established its levels, and selected the approach, the next phase is to design the concept profiles. An example is creating product concept narratives based on the attributes and levels utilized in the study.

Collect and Analyze the Data

Typically, conjoint analysis is administered through online surveys. This method is not only cheap but efficient but is also ideal for large sample size. After the participants completed the survey, researchers will use statistics in building a product and price structure that customers will favor in an actual market.

Build and Run a Market Simulator

After a conjoint survey, the results are used to build a market simulator that will let users perform “what-if” studies.