Consumer Research
Publication date: 10/01/2019

Consumer Research

Introduction to Consumer Research

Overview of Customer and Behavioral Research Methods

Consumer Research provides a full suite of tools for analyzing consumer and behavioral research data. You collect information about how customers use products or services, how satisfied they are with your offerings, and what new features they might desire. The resulting insights let you create better products and services, happier customers, and more revenue for your organization. Tools for analyzing these consumer research activities are located in the Consumer Research menu. Use the following platforms to analyze your data:

The Categorical platform enables you to tabulate, plot, and compare categorical responses in your data, including multiple response data. You can use this platform to analyze data from surveys and other categorical response data, such as defect records and study participant demographics. Using the Categorical platform, you can analyze responses from data tables that are organized in many different ways. See Categorical Response Analysis.

The Choice platform is designed for use in market research experiments, where the ultimate goal is to discover the preference structure of consumers. Then, this information is used to design products or services that have the attributes most desired by consumers. See Choice Models.

The MaxDiff platform is an alternative to using standard preference scales to determine the relative importance of items being rated. A MaxDiff experiment forces respondents to report their most and least preferred options, thereby forcing respondents to rank options in terms of preference. See MaxDiff.

The Uplift platform enables you to maximize the impact of your marketing budget by sending offers only to individuals who are likely to respond favorably. It can do this even when you have large data sets and many possible behavioral or demographic predictors. You can use uplift models to make such predictions. This method has been developed to help optimize marketing decisions, define personalized medicine protocols, or, more generally, to identify characteristics of individuals who are likely to respond to some action. See Uplift Models.

The Multiple Factor Analysis platform enables you to analyze agreement among panelists in sensory data analysis. You can use MFA to analyze studies where items are measured on the same or different attributes by different instruments, individuals, or under different circumstances. See Multiple Factor Analysis.

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