In this glossary, the most important market research terms from this database and the textbooks are simply explained
Market Intelligence Platforms
Market intelligence platforms are also classified under data visualization in the MR Directory. Such platforms usually bring together customer data, sales data and marketing activities from various sources. Market Intelligence refers to the ability to gather, analyze and interpret information about a market or industry.
Market research refers to the systematic collection, analysis and interpretation of data that provides information about the market, target groups, demand and supply of products or services. The aim of market research is to provide a sound basis for decisions in marketing, product development, pricing or sales. Typical questions in market research can be: 1. How large is the target group for a particular product or service? 2. What are the attitudes, needs, wishes and expectations of the target group? 3. How high is the customers’ willingness to pay? 4. How good is the image of a company or brand? 5. How large is the market share of a company compared to its competitors? 6. How successful is a marketing campaign? 7. How satisfied are customers with a product or service? 8. How are new products or services received by potential customers? To answer these questions, market research can use various methods such as surveys, observations or the analysis of existing data.
A max-diff analysis, also called maximum difference scaling or best-worst scaling, is a method of market research used to determine the preferences or relative importance of different options. It is a technique that helps determine the ranking or ranking of items in a list. Max-diff analysis is commonly used in product development, brand research, pricing, and other areas to gain insight into consumer preferences and perceptions. In a max-diff analysis, participants are presented with multiple sets of items from which they must select the best and worst item in each case. By performing such a pair comparison task multiple times, a preference ordering of the items emerges based on the observed choice decisions. For example, the questions in a max-diff analysis might be asked as follows: “From the following options, please select the one that you feel is the best.” “From the following options, please select the one you feel is the worst.” Items are usually selected randomly, and it is important that each item appears as both the best and worst item in different pairwise comparisons to obtain an accurate ranking. A max-diff analysis can be used to answer several questions, for example: Order of preference: which options are considered the best and worst by participants? Importance: Which options are considered most important and least important by participants? Relative utility: What is the difference in preference between the different options?
Multivariate analyses are statistical procedures used to examine relationships between multiple variables. They allow for a more comprehensive look at data by analyzing multiple variables simultaneously. The most common procedures include: Regression analysis, factor analysis, cluster analysis, discriminant analysis, and principal component analysis.
Multivariate Regression Analysis
Multivariate regression analysis examines the relationship between a dependent variable and multiple independent variables. It answers questions such as: What influence do different variables have on the dependent variable? To what extent do these variables contribute to the prediction of the dependent variable? Are there interactions or nonlinear relationships among the variables?