Learn About Conjoint And Trade-Off Analysis

Related Articles

There are 31 articles in our archive related to this topic. Below are 5 selected at random and available to all users of the site.

Improving reception

With increasing competition, cable companies must be more proactive and dynamic to be successful. Customer loyalty is key to success. This article discusses how cable companies must act regarding customer loyalty. In addition to noting the information cable companies need to obtain, this article provides a case study that shows how one cable system used an innovative application of conjoint analysis in its research.

Structured Equation Models: an introduction

This article describes an analysis technique known as Structured Equations Models (SEM), also called Causal Modeling, Latent Variable Modeling, and LISREL models. The author illustrates how SEM can help analyze results of conjoint analysis to more fully understand the motivational, perceptual or psychological determinants of perceived value.

Data Use: A short history of conjoint analysis

From the early 1960s to today, the author charts the growth of and change to the practice of conjoint analysis.

Improving marketing decision-making with conjoint analysis

This article presents factors for conducting effective conjoint analysis research. Topics include effectively preparing for a conjoint study, clarifying product attributes and levels, pilot testing, efficiently collecting data and making results clear and actionable for management.

Using virtual reality-based conjoint to capture the voice of the customer

When demand for a new product is highly uncertain and prototypes are expensive to develop, a research approach where potential customers evaluate hypothetical products can be extremely useful. This article describes use of TradeOff VRTM, which combines conjoint analysis and virtual reality to obtain customer feedback regarding the product design and planning process for a new Volvo truck.

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Recent Articles

Below are the 5 most recent articles on this topic. These articles were published within the last three years and are only available to registered subscribers.

Improving continuous improvement with maximum difference scaling

To perform better, companies need to know what’s most important to consumers. The author outlines how to use max-diff to identify improvement priorities.

Data Use: Adaptive choice is a good choice

Using an example of a transportation company client, the author outlines why adaptive choice-based conjoint analysis is a useful tool for developing market segmentations.

Data Use: Best practices for well-differentiated questionnaire data

How longer point scales, alternate labeling of scale points and other strategies can help you wring more meaning from your data.

Data Use: Evaluating paired comparisons, maximum difference and traditional ranking

The author examines a host of data interpretation issues related to the use of paired comparisons and maximum difference surveys.

Marketing research within the financial services sector

To keep pace with market and societal shifts and changes, the financial services industry has had to use a variety of marketing research approaches, including emotional measurement and social media, to understand consumers’ relationship with their money.

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