In this glossary, the most important market research terms from this database and the textbooks are simply explained

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Dashboards are visual representations of survey data that are often updated in real time. They can consist of a variety of charts and graphs and provide a quick overview of key survey results.

Data analysis

Data analysis typically involves three steps: Data collection, data cleaning, and tabulation.

Data collection is the first step in data analysis. This involves collecting data from quantitative or qualitative sources such as surveys, questionnaires, interviews, or focus groups. After data collection, data cleaning takes place. Here, errors, outliers and invalid data are removed to improve the quality of the data.

After the data has been cleaned, tabulation takes place. Here, the data is presented in tabular form, with the target groups in the table header and the answers to the questions in the page breakdown. These tables provide a quick overview of the results and facilitate comparison between different groups.

In addition to tabulation, the MR Directory also lists multivariate analysis, conjoint analysis, max-diff, driver analysis or TURF analysis. Multivariate analysis makes it possible to examine complex relationships between different variables and identify correlations. Conjoint analysis makes it possible to study consumer preferences for different product attributes, while TURF analysis examines the reach of products in different target groups.

Data cleansing

Data cleansing aims to analyse, correct and transform raw data to ensure that data quality is high and that analyses produce reliable and meaningful results.

Raw data can contain errors, discrepancies, outliers, inconsistencies and, in the case of online surveys, responses from bots that could distort the results of the analysis. Data cleaning can address these issues to increase the accuracy and reliability of the data.

Data collection

Data collection in market research can be carried out using various methods. Essentially, it is possible to generate data via surveys, observations or the structuring of existing information.

Surveys can be conducted either in a test studio, via an online panel, online within a target group for which one has the contact data (CAWI), in writing (PAPI), in person (CAPI), by telephone (CATI) or via touchpoint screens (CAVI). Participants answer questions about their opinions, attitudes and behaviors. The advantage of the survey is that the questionnaire can be individually adapted to the task and the target group can be defined.

Observation is another component of market research. Here, the behavior of the target group is directly observed in order to gain insights into their behavioral patterns and decisions. This can take the form of voice or facial coding, eye tracking, usability tests, as well as collecting data via diaries, for example. Observations uncover feelings and behaviors that are usually unconscious and difficult to articulate. Also falling into the realm of observations are desk research activities that analyze the competition, known as competitive intelligence.

Structuring existing information is a third method of data collection in market research. Here, large data sets or information on the Internet are analyzed to gain insights. In these cases, we also speak of digital data collection. The limitations of Big Data analysis often lie in the lack of differentiation by target groups and a lack of qualitative explanation for the measured values.

The choice of the appropriate method of data collection depends on various factors, such as the target group and its accessibility, the scope of the study, the available resources and how easy it is to query the subject of the study.

Data visualization

Data visualization plays a critical role in market research by transforming complex data into engaging and easy-to-understand graphs and charts. MR Directory distinguishes four variants of data visualization: charting, dashboards, reporting, and market intelligence platforms.

Digital Diaries

Digital diaries are electronic versions of traditional diaries that are created and managed using digital platforms, apps or software.

Digital diaries are available on different devices such as smartphones, tablets or computers and storage in the cloud prevents loss of content. Another advantage is the multimedia integration: Users can integrate not only texts, but also photos, videos, audios and links into their entries.

In the field of market research, digital diaries can provide valuable insights into the behaviour, attitudes and needs of consumers. Market researchers use digital diaries to answer the following questions:

1. Consumer behaviour: How do consumers use certain products or services in their everyday lives? What challenges or pleasures do they experience?

2. Product use: What experiences do users have with a particular product? Which functions do they use most often? What difficulties do they encounter?

3. Customer experience: How do customers rate their interactions with a brand or company? What positive or negative experiences did they have?

4. Attitudes and opinions: What attitudes, opinions and desires do consumers have about specific products or topics?

5. Changes over time: How do consumer behaviours and attitudes evolve over time? Are there trends or patterns?

6. Advertising and marketing: how do consumers react to advertising, marketing campaigns or new product launches?

7. Target group analysis: what segmentation criteria can be derived from the diaries? Which consumer groups show similar behaviours or preferences?

Digital diaries are also often used in ethnography, which aims to provide a detailed description and interpretation of human behaviour, culture and social practices in a particular community or group.

Discriminant Analysis

Discriminant analysis examines which variables best help distinguish between groups. It answers questions such as: Which variables contribute most to the distinction between groups? How well can the groups be predicted based on the variables present?

DIY Market Research Platforms

DIY platforms are software solutions that enable companies to set up and evaluate market research studies themselves and visualize the results. MR Directory differentiates between platforms with and without a panel. Platforms with their own panel can optionally access respondents from an online panel of the provider. In general, however, the target group of the online panel is very broad. For more pointed target groups and when selecting a platform without a panel, one needs one’s own respondents, such as employees/customers, or panel participants from a third-party provider.

Market research platforms are often promoted as an effective and inexpensive way for companies to conduct market research studies. This often ignores the fact that programming the questionnaire takes up a lot of time, especially at the beginning, which the project managers in the companies may miss elsewhere. Therefore, when making your selection, make sure that you have support that can answer open questions at any time.

When selecting a provider, in addition to the question of where the participants come from, the possibility of the questions takes on a central role. Starting with the filtering, through the selection of questions, to the evaluation, there are a number of things to consider. With regard to the integration of special questions, such as the implicit measurement of emotions, or the different analyses, such as drivers, conjoints, max diffs or turf analyses, the providers differ considerably in some cases.

Driver Analysis
A driver analysis is a method of identifying the influencing factors or drivers that affect consumer behavior, preferences, or purchase decisions. The goal is to find out which factors correlate most strongly with a particular outcome, such as the purchase of a product or customer satisfaction.

Driver analysis is usually conducted in the form of a survey. Participants are asked questions about their attitudes, opinions, behaviors and preferences. Typically, one uses a Likert scale or similar scales to record the answers. Questions may address different aspects, depending on the specific research objective. For example, questions could be asked to assess the importance of certain product features, the impact of advertising campaigns, or the importance of brand image.

Various methods are used for the statistical evaluation of a driver analysis, depending on the type of data and the research objectives. One commonly used method is regression analysis, particularly multiple linear regression. This method makes it possible to analyze the influence of several independent variables (the potential drivers) on a dependent variable (the outcome). By analyzing the regression coefficients and their significance, it is possible to determine which factors are most strongly related to the outcome under study.

Driver analysis provides information on which factors have the greatest influence on the behavior or decision under investigation. For example, it can provide insight into which product features are most important to consumers, which advertising messages are most effective, or which aspects of the customer experience most influence customer satisfaction. These insights can help companies optimize their marketing strategies, product development, and customer experience to better meet the needs and preferences of their target audience.