Conjoint Analysis in Marketing

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Conjoint analysis are terms used to describe a statistical tool that marketing researchers use to assess the value consumers attach to different features of a service or product. In marketing, conjoint studies are normally carried out to determine the combination of features of a certain service or product that are likely to have the most influence on a customer’s choice or decision making.

In other words, conjoint analysis is all about trade-offs and features (Green, and Srinivasan 4). The combination of such features is very important especially when developing marketing models on the revenue generated by a given brand. They also assist market researchers to project the market share and/or profitability of a given brand.

Conjoint analysis enables you to pose questions that compel respondents to make trade-offs on features. In addition, you can also project the value that respondents place on the individual features of a brand in line with the kind of trade-offs made. Finally, conjoint analysis enables you to simulate the reactions of the market to different trade-offs features that you might be considering.

For more than three decades now, market researchers mainly in the United States and Europe have been using conjoint analysis to help them understand customer choices and preferences. The main area of marketing where conjoint analysis is mainly used extensively is in new product development.

In addition market researchers have also used conjoint analysis to determine product/service pricing and targeting dynamics. A number of studies show that discrete choice and conjoint models have been received well in both Europe and North America (Wyner 216). Brand name is a key attribute to marketing and for this reason it has been included as a fundamental conjoint attribute in conjoint studies. Besides enabling marker researchers to assess brand equity, conjoint analysis has also proven useful in assessing brand value.

Marketing researchers find conjoint analysis quite interesting as it effectively provides answers to a number of the most significant and frequently asked marketing questions. One of the advantages of conjoint analysis is that because it is superior to other marketing analytical methods, it gives answers where other basic techniques may not. Conjoint analysis also enables marketing researchers to understand marketing preference better (Wyner 217).

In this case, conjoint analysis helps marketing researchers to understand structures with regards to the preferred product attributes by customers. Other than determining the importance of an attribute, conjoint analysis provides quantitative assessments of the comparative appeal of definite levels of the attributes.

Also, conjoint analysis helps to predict market choices by comparing tradeoffs between various attributes. Conjoint analysis can also help to develop marketing strategies. In this case, marketing researchers could use the simulation capacity of conjoint analysis to isolate marketing strategies that enables us to achieve measurable goals like revenue or maximum share (Green and Srinivasan 7).

Marketers could also effectively segment the market using conjoint results. For example, they can segment customers based on other important attribute scores or utility values.

The conjoint analysis is faced with a few obstacles when it comes to validation. When a certain method or technique repeatedly provides projections that reflect the true behavior of consumers, we tend to gain more confidence with such a method. In the case of conjoint analysis however, various crucial differences are evident between the activities in the actual market and the research process.

For example, the conjoint analysis assumes that the availability and awareness of all the alternatives is 100%. This is rarely the case in the actual market. As such, it becomes very hard to adjust these projections to cater for the variations.

In conjoint analysis, the marketing researchers often provide survey respondents with abstractions of services or products under study. Whereas an automotive conjoint analysis could offer verbal descriptions of the different features of the product or service under consideration, varying reactions could emerge when it comes to the actual execution of the features in question (Wittink and Cattine 93).

Also, the time taken to conduct a conjoint analysis and implement the ensuing marketing efforts produces a time lag that could result in the changing of a lot of factors between testing and execution. For instance, the entry of a new competitor in the market could alter a few issues.

Another disadvantage of conjoint analysis is that nearly all conjoint studies tend to be “proprietary” and for this reason, it becomes hard to identify public cases that could be used for validation. Most client companies are reluctant to share information as there is no incentive to do so.

Conjoint studies are also limited by the fact that they are mainly used as a tool to indentify the winner form a group of potential services and products ((Wittink and Cattine 94). In this case, the marketing researchers only introduce the eventual winner to the market, thereby making it hard to compare the winner with other potential products.

In spite of the aforementioned limitations, there is compelling evidence in literature to suggest that conjoint techniques can attain sensible predictive accuracy.

Conjoint analysis finds use in making choices between different brands. Say for example you want to determine which car between a Toyota and a Ford a customer is likely to buy. Using a paired comparison type of ranking, the market researcher provides the choice of a car brand from a given country of origin (in this case, Ford is from the United States while Toyota is a Japanese brand).

Assuming that both cars retail at the same price (for example, $ 25,000), the market researcher might allocate a discount of 6% for the Ford brand and a 10% discount for the Toyota brand. Information on the country of assembly is also given. In this case, the Ford brand has been assembled in the United States, while the Toyota brand has been assembled in Mexico.

Obviously, the differences in the amount of discount each dealership is willing to give and the country of assembly will inform the client’s decision while choosing the brand to purchase.

This decision might also be influenced by the distance that a client has to travel to get to either of the dealerships. In this case, let us assume that the client takes approximately 30 minutes to get to both the Toyota dealership and the Ford dealership.

However, when it comes to the issue of reliability, the Toyota dealership might be more reliable than the Ford dealership in that it gives personalized attention to the client while the Ford dealership still practice the “one size fit all” approach. As such, a client is likely to make a purchase on his/her first visit to the Toyota dealership as opposed to the Ford dealership. Such a comparison type of ranking system is likely to influence a customer’s intention to purchase a given brand, and not another.

Works Cited

Green, Paul and Srinivasan, Venkatesan. “Conjoint analysis in marketing: new developments with implications for research and practice”. Journal of marketing, 54(1990):3-19. Print.

Wittink, Dick and Cattine, Philip. “Commercial use of conjoint analysis: an update”. Journal of marketing, 53(1989): 91-6. Print.

Wyner, Gordon. “Uses and limitation of conjoint analysis-part 1.” Marketing Research 42(1992): 216-218. Print.

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Conjoint Analysis in Marketing

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