In this glossary, the most important market research terms from this database and the textbooks are simply explained
A/B tests are a method of experimental design. They are used to compare different versions of a product or advertising material with each other in order to determine which version (A or B) performs better. The test procedure is monadic, which means that each respondent sees and evaluates only one version. A/B tests can answer the following questions: 1. Which version is more effective? – A/B testing helps determine which version (A or B) responds better to defined metrics, such as click-through rate, conversion rate, revenue or time spent on the website. 2. Which design or content elements work better? – A/B testing allows you to test individual elements such as headlines, images, colours or call-to-action buttons to see which combination is most effective. 3. Which offers or prices generate more sales? – Companies can test different prices or offers to see which variation generates the highest conversion rate or sales. 4. Which email subject line increases the open rate? – In email marketing campaigns, A/B tests can be used to compare different subject lines and find out which one achieves the highest open rate. 5. Which user interface leads to better user interaction? – In app or platform development, A/B testing can help optimise the user experience by comparing different layouts or navigation elements.
Brain Activity Measurement
Measuring brain activity makes it possible to detect implicit responses and preferences by measuring electrical signals in the brain. This can be done by using electroencephalography (EEG) or functional magnetic resonance imaging (fMRI). By analyzing the activity of specific brain regions, it is possible to infer how people respond to various stimuli such as advertisements, brands, or products, even if they cannot consciously perceive or verbalize these responses.
CAPI stands for Computer-Assisted Personal Interviewing. It is a method of data collection in empirical social research in which interviews are conducted by trained interviewers, using a computer for assistance. The interviewer asks the questions using a computerized interface that displays the questions and records the responses directly into the system. CAPI offers the advantage that data are captured and stored digitally immediately, which facilitates data analysis. The choice between CAPI and PAPI depends on several factors, such as: 1. Resources: CAPI usually requires the provision of computers and related software for interviewers, while PAPI requires only paper and pens. 2. Complexity of questions: for complex questions that use complex response options or scales, CAPI may facilitate data collection because interviewers may need assistance navigating the questions and entering responses. 3. Time Frame: CAPI allows for more efficient data collection and faster data availability because responses are entered digitally directly. PAPI may require additional steps such as manually transferring the data into a digital form. 4. Privacy and data security: CAPI offers the ability to encrypt and secure the data directly, whereas with PAPI, the physical paper forms could potentially be stolen or lost.
CATI stands for Computer Assisted Telephone Interviewing. As the name suggests, this uses a computer-assisted system to conduct surveys by telephone. Computer assistance allows easier retrieval of more complex questionnaires with filter guidance. Telephone interviews are often used for surveys when regional control of random selection is possible via pre-selection, telephone numbers are available or the online population is not representative. Opinion research institutes in particular rely on a method mix of CAWI and CATI to create a representative sample.
CAVI, or Computer Assisted Visual Interviews, are a relatively new method of capturing immediate feedback from customers at the POS. Most commonly, customers can rate their satisfaction with a product or service by pressing a smileys on a touchscreen, or, after scanning a QR code, on their cell phone. This data can be monitored and analyzed in real time by staff to improve the customer experience. In addition to this function, CAVIs also have a customer engagement effect.
CAWI stands for computer assisted web interviewing. Here, surveys are conducted online and participants can answer the questions on their computer or mobile device. Computer assistance allows easier querying of more complex questionnaires with filter guidance. CAWI is a fast and cost-effective method for conducting surveys with a large sample.
Charting refers to the graphical representation of data in the form of charts, line graphs, bar graphs, or pie charts. They are used to identify and visualize trends and patterns in data.
Cluster analysis groups similar cases based on their characteristics. It answers questions such as: Are there natural groupings of cases in the data? Which cases are most similar and which are most different? How can cases be grouped into different categories or clusters?
Coding involves analysing qualitative data (e.g. interview transcripts, open answers in surveys) and sorting them into previously defined codes or categories. Many coding providers listed in The MR Directory use AI tools that can summarise and code texts.
Conjoint analysis is a statistical technique used to study consumer preferences. It makes it possible to determine the relative importance of different features of a product and to deduce how consumers make their purchasing decisions. The results of conjoint analysis can help companies target their products and services, develop marketing strategies, set prices, and predict the success of new products. Typically, participants in the survey are presented with a series of product profiles that differ in their characteristics. Each profile consists of a combination of characteristic attributes that are combined to create different product variants. Participants are then asked to rate or rank the presented product profiles. Depending on the specific method of conjoint analysis, different question types can be used: 1. rating task: participants rate each presented product profile on a scale to indicate how preferred it is compared to other profiles. 2. ranking task: participants rank the presented product profiles in order of preference. 3. choice-based task: participants are presented with different product profiles to choose from and must select the one they prefer. By evaluating the ratings or rankings given, conjoint analysis can answer several questions, including: 1. importance of product features: Which features have the greatest influence on consumers’ decisions? 2. Preference for specific feature attributes: Which specific feature attributes are preferred? 3. price acceptance: how much are consumers willing to pay for specific feature combinations? 4. market share estimates: How likely are different product variants to be chosen by consumers?
A correlation analysis is a statistical method used to examine the relationship between two or more variables. It measures the strength and direction of the linear relationship between variables. Correlation analysis provides information about how much changes in one variable affect another variable. The correlation coefficient varies between -1 and 1. A value close to -1 or 1 indicates a strong linear relationship, while a value close to 0 indicates a weak relationship.
CX Insights Platforms
CX Insights platforms are software solutions designed specifically for customer experience management. They collect, analyze, and visualize data to help companies gain insights into their customers’ experiences and identify opportunities for improvement. These platforms combine multiple data sources, such as surveys, social media feedback, customer reviews and behavioral data, to provide a comprehensive picture of customer perceptions. CX Insights platforms measure a variety of metrics to assess customer satisfaction and the quality of the customer experience. Some of the most common metrics are: 1. Net Promoter Score (NPS): NPS measures how likely customers are to recommend a company to others. It is based on a single question, “On a scale of 0 to 10, how likely are you to recommend our company/product/service to a friend or colleague?” 2. customer satisfaction (CSAT): CSAT measures customer satisfaction with a specific aspect of the customer experience. It is often determined by asking: “How satisfied are you with [product/service/support]?”. 3. customer loyalty: This metric assesses how loyal customers are to a company and how likely they are to purchase or do business with the company again. CX Insights platforms can answer several questions to improve the customer experience. Here are some examples: 1. What factors most influence customer satisfaction? 2. What is the NPS for different customer segments and how can it be improved? 3. What product features are most important to customers and how well do we meet their expectations? 4. How do customers react to specific marketing campaigns or product changes? 5. What complaints or problems do customers often have and how can they be resolved? 6. How good is customer service and how can processes be optimized to ensure a better customer experience? These platforms provide companies with the ability to collect data, analyze it, and derive actions to improve the customer experience, build customer loyalty, and ultimately drive business success.
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 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 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 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 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 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 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.
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.
Ethnography is a research method in the social sciences that aims to provide a detailed description and interpretation of human behavior, culture, and social practices in a particular community or group. This method usually involves careful observation, participation, and recording of conversations, activities, and interactions in the community under study. In doing so, researchers strive to understand the perspectives of participants and document their experiences and opinions. Ethnography can help answer a variety of questions related to social phenomena and human behavior, such as: 1. How are cultural practices and traditions transmitted in a community? 2. How do people interact with each other in different social contexts? 3. How are decisions made in groups? 4. How are conflicts resolved and compromises found? 5. How do social structures and institutions influence people’s behavior and experiences? 6. How does the behavior and culture of a community change over time? 7. How do external factors such as economics, politics, or technology influence the behavior and culture of a community? 8. How are products used and for what purpose? Overall, ethnography provides a powerful method for understanding the complex and diverse human experiences and behaviors in different communities.
Eye tracking technology is one of the implicit measurement techniques. It involves tracking a person’s eye movements to determine where they look and for how long while viewing advertisements or packaging.
Facial coding involves analyzing facial expressions to capture emotional reactions and preferences. Through the use of cameras and specialized software, facial expressions, facial expressions and emotions can be captured during the consumption of content, ads or products. This enables an assessment of consumers’ implicit emotional responses and helps evaluate the effectiveness of advertising and marketing materials.
Factor analysis allows several characteristics to be combined into factors that are independent of each other and is primarily used for data reduction. It answers questions such as: Which variables correlate most strongly with which factors? Which variables can be combined into a common construct? How much variance is explained by the identified factors?
Feedback tools are Computer Assisted Visual Interviews (CAVI) that capture immediate feedback from customers at the POS. Most commonly, customers can rate their satisfaction with a product or service by pressing a smileys on a touch screen, or, after scanning a QR code, on their mobile phone. This data can be monitored and analysed in real time by staff to improve the customer experience. In addition to this function, feedback tools also have a customer loyalty effect.
Focus groups are a qualitative research method in which a group of people come together to discuss their opinions, attitudes, experiences, and perceptions about a particular topic. These groups are usually led by a moderator who guides the discussion and ensures that all participants have the opportunity to contribute their opinions. 1. Through focus groups, various questions can be answered, such as: 2. Opinions and attitudes about a particular product, brand or service. 3. Feedback on new product concepts or ideas. 4. Understanding the needs and wants of the target audience. 5. Responses to marketing campaigns or promotional materials. 6. Identification of problems or opportunities for improvement. It is important to note that focus groups do not provide representative data because the number of participants is limited. Therefore, the results should not be generalized. Instead, they provide qualitative insights and often serve as a starting point for further research or as a complement to quantitative methods.
Implicit Association Testing (IAT)
One well-known implicit measurement technique is the implicit association test (IAT), which measures reaction times to assess the strength of association between different concepts or categories. For example, the IAT can be used to measure consumers’ implicit attitudes toward specific brands or products. The Implicit Association Test is particularly well suited for leveraging social desirability effects.
Implicit measurement techniques are used in market research to gain a broader and deeper insight into consumer perceptions and preferences. They can help uncover unconscious preferences, associations, and behavior patterns that remain hidden through surveys. Examples of implicit measurement techniques include eye tracking, brain activity measurements, IAT (implicit association tests), and facial or voice coding.
The Likert scale is one of the best-known scales in market research. It is often used to measure people’s attitudes and opinions. With the Likert scale, respondents indicate their agreement or disagreement with a statement on a multilevel scale. Typically, the Likert scale includes five or seven response options ranging from “strongly disagree” to “strongly agree.” An example of using the Likert scale would be to measure customer satisfaction with a product or service. The Likert scale belongs to the category of ordinal scales. An ordinal scale is a type of measurement scale in which the values are arranged in a specific order, but there are no set distances or intervals between the values. In a Likert scale, participants are presented with statements or questions and asked to indicate their agreement or disagreement on a multilevel scale, usually ranging from “Strongly Agree” to “Strongly Disagree.” The values on a Likert scale can be coded numerically, but it is important to note that the distances between the values cannot be considered equal. Therefore, the Likert scale is considered an ordinal scale.
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?
Online communities in market research are virtual platforms where a group of participants come together to share information, discuss ideas, and participate in research activities. These communities can either be publicly accessible or open only to selected members. Online communities are categorized as qualitative methods and provide answers to the following questions: Consumer feedback: communities allow participants to express their opinions, experiences, and desires about products or services. Companies can gather valuable feedback to improve their offerings or develop new products. Brand perception: Communities offer insights into consumer perceptions and attitudes toward specific brands. Companies can understand how their brand is perceived and which aspects can be improved. Product development: Through direct contact with the target group, companies can generate ideas for new products and gather feedback on prototypes or concepts. Communities enable close collaboration between companies and consumers throughout the product development process. Trend monitoring: Communities can help identify trends in consumer behavior, preferences, and needs. Companies can use this information to adapt their marketing strategies and identify relevant trends early on. Target group research: By analyzing the posts and interactions in a community, companies can gain insights into the demographics, geography, interests and preferences of community members. This helps in segmenting the target group and enables a targeted approach in market research. Campaign evaluation: Companies can obtain feedback on their marketing campaigns in an online community. Participants can share their opinions on promotional materials, messages or other marketing activities. This helps companies evaluate the effectiveness of their campaigns and make adjustments if necessary. Customer loyalty: Communities offer companies the opportunity to build a close relationship with their customers and strengthen customer loyalty. Through regular interactions and sharing of information and experiences, community members feel more connected to the brand.
Online focus groups
Online focus groups are a method of market research in which a group of participants come together over the Internet to participate in a moderated discussion. Compared to traditional focus groups where participants meet physically in one location, online focus groups allow for virtual collaboration. Limitations of online focus groups compared to traditional focus groups may include: Limited nonverbal communication: because participants are not physically present, important nonverbal cues may be lost. Gestures, facial expressions, and body posture are more difficult to interpret. Technical challenges: Participants need a reliable Internet connection and must have basic technical skills to participate in online focus groups. Technical issues such as disconnections can interfere with the process. Limited social dynamics: the virtual nature of online focus groups can make it more difficult to establish a natural social dynamic between participants. Participants may feel less connected and may be less open in their responses. Through online focus groups, various questions can be answered, such as: Opinions and attitudes about a particular product, brand or service. Feedback on new product concepts or ideas. Understanding the needs and wants of the target audience. Responses to marketing campaigns or promotional materials. Identification of problems or opportunities for improvement.
PAPI stands for “Paper-and-Pencil Interviewing” or “Face-to-Face Interviewing”. In this method, the questionnaire is printed on paper and can be filled out either by an interviewer or the respondent himself. and asked by an interviewer in person to the respondent. PAPI was a traditional method of data collection before computer-assisted systems (CAPI) became common. The choice between CAPI and PAPI depends on several factors, such as: Resources: CAPI usually requires the provision of computers and related software for interviewers, while PAPI requires only paper and pens. Complexity of questions: for complex questions that use complex response options or scales, CAPI may facilitate data collection because interviewers may need assistance navigating the questions and entering responses. Time Frame: CAPI allows for more efficient data collection and faster data availability because responses are entered digitally directly. PAPI may require additional steps such as manually transferring the data into a digital form. Privacy and data security: CAPI provides the ability to encrypt and secure data directly, whereas PAPI could potentially result in the physical paper forms being stolen or lost.
Principal Component Analysis
Principal component analysis reduces the dimensionality of the data by identifying a smaller number of principal components that explain most of the variance in the data. It answers questions such as: Which variables are most highly correlated with the first principal components? Which variables can be neglected without losing much information?
Principles of market research
The principles of market research, namely objectivity, validity, and reliability, are critical to achieving reliable and meaningful results. Here is an explanation of these principles: Objectivity: objectivity refers to the fact that market research results should be free of bias, personal opinion, or preference. This means that data should be collected, analyzed and interpreted in a neutral and unbiased manner. To ensure objectivity, it is important to use standardized procedures and measurement tools to ensure that all participants are treated equally and that the results are not influenced by the researcher’s personal preferences or opinions. Validity: Validity refers to the accuracy and validity of the data collected and how well it measures the intended aspects of the research objective. It is important to ensure that the measurement instruments used actually measure what they claim to measure and that the results actually provide the intended information. High validity means that the results are representative and reliable. To ensure validity, researchers should use appropriate research methods, questionnaires, or observation techniques that are tailored to the specific objectives of the study. Reliability: Reliability refers to the consistency and reliability of the data collected. It is concerned with ensuring that the results are repeatable and that similar results are obtained when the study is conducted again. Reliability is important to ensure that the results are not random and that they actually reflect underlying characteristics or changes in the target population. To ensure reliability, researchers should use standardized procedures, provide clear instructions, and ensure that the study produces similar results in different settings and at different times. These principles are critical to ensuring that market research results are trustworthy and meaningful. They help researchers build a solid foundation for making informed business decisions by providing clear and reliable information about consumer preferences, market conditions, and other relevant issues.
Qualitative market research
Qualitative market research is a method that aims to gain deeper insights into the behavior and attitudes of consumers and potential customers. Unlike quantitative market research, which focuses on the measurement of numerical data, qualitative market research refers to the collection of opinions, experiences and emotions through direct interaction with participants. There are several methods of qualitative market research, including focus groups, in-depth interviews, observations, and ethnographic research. Qualitative market research is particularly useful for gaining deeper insights into customer behaviors and motivations that cannot be captured by numerical data alone. Through the use of open-ended questions and open communication, researchers can develop a better understanding of customers’ perspectives and needs. Compared to quantitative market research, qualitative market research has the advantage of being more flexible and adaptable, allowing for a greater level of depth and detail. In simple terms, quantitative market research measures the status quo, while qualitative market research sheds light on the background, i.e. provides answers to the why. However, the results of qualitative market research can be more difficult to generalize, so it often makes sense to combine qualitative and quantitative methods to get a more complete picture of customer needs and perspectives.
Quantitative market research
Quantitative market research is usually based on standardized and uniformly structured questionnaires that are answered by a large number of research participants. The data obtained from surveys is then evaluated in statistical analyses to draw conclusions about the market needs of different target groups, customer satisfaction, the market position of companies or other aspects of the market. In contrast to qualitative market research, which uses open-ended questions and free-form discussions to gain in-depth insights into consumer behavior and attitudes, quantitative market research focuses on standardized and structured questions and the quantification of results. Put simply, quantitative market research measures the status quo, while qualitative market research sheds light on the background, i.e. provides answers to the why. In summary, quantitative market research is a valuable method for collecting and analyzing objective data and facts about the market. Compared to qualitative market research, it is more suitable for making representative statements about groups and enables statistical analysis of correlations between different variables.
Reporting software usually enables the weighting of survey data, various statistical analyses and presents the results graphically and on the basis of different target groups at the push of a button. The boundaries to dashboards are fluid.
A representative sample is considered to be a group of participants whose characteristics (such as demographics, attitudes, or behaviors) are distributed in a manner similar to the population to which the results are to be generalized. In this context, the population may include only a portion of the population. If a sample is representative of a country, it is called representative of the population.
Research Tech & IT Services
Research Tech & IT Services in The MR Directory includes software and services that enable and automate data collection, data analysis or data visualization. These range from questionnaire programming and survey software to software for monitoring social media content. Platforms that offer all three steps (collection, analysis and visualization) together are a special feature. Here, The MR Directory distinguishes between DIY platforms with or without a panel. Platforms without a panel are suitable if you have the contact addresses of the respondents yourself, i.e. in the case of customer or employee surveys, or if you can buy in the survey participants via an external online panel. DIY platforms with a connected panel are usually quite broad, so that surveys in pointed target groups with a sufficient number of cases are not possible.
In market research, different scales are used to capture consumers’ opinions, attitudes and behaviors. The different characteristics are: Nominal scale: This scale is used to categorize characteristics without indicating a ranking or spacing between categories. An example of this would be the question about gender (male, female, other). Ordinal scale: In this scale, characteristics are arranged according to their order or ranking, but without quantifying exact distances between categories. An example of this would be rating customer satisfaction on a scale of “very dissatisfied,” “dissatisfied,” “neutral,” “satisfied,” and “very satisfied.” Interval scale: This scale allows the measurement of intervals between characteristic values and has a fixed unit, but no absolute zero. An example of this would be a rating scale of 1 to 10, where a value of 5 can be considered twice as high as 2. Ratio scale: This scale is similar to the interval scale, but contains an absolute zero representing both an absence and a quantitative value. Examples would be scales measuring weight or sales.
Social Media Monitoring
Social media monitoring software is a tool designed to collect, analyze and monitor information from social media. It allows companies, organizations or individuals to track activity on social networks to gain insights into opinions, sentiments, trends and other relevant information about their brand, products, competitors or specific topics. The main role of social media monitoring software is to monitor and analyze social media content and activity. This includes tracking mentions of their own brand or company, identifying relevant hashtags and trending topics, analyzing consumer opinions and sentiments, gathering competitive intelligence, and capturing general trends in social media.
Tabulation is the process of summarising quantitative survey results, usually presenting the questions in the page breakdown and the target groups in the header.
Text analytics software focuses on processing and analyzing text content, regardless of where it was published. It can be used in various contexts, such as analyzing customer reviews, sentiment analysis of texts, keyword extraction or automated classification of texts. Text analytics can be used in social media as well as other digital channels. Unlike social media monitoring software that is specifically designed to collect and analyze information from social media, text analytics software focuses on analyzing website data or text content, regardless of its source.
Trend Analysis Software
Trend analysis software tools use various techniques and algorithms to identify patterns and trends in data. Here are some common approaches and steps that such tools can perform: Data aggregation: first, relevant data must be collected and aggregated. This can come from a variety of sources, such as social media, surveys, sales data, or other publicly available data sources. Data cleaning and pre-processing: the raw data is cleaned to ensure it is of high quality and any outliers or missing values are dealt with. This step is important to perform accurate analysis. Trend detection: various statistical methods and algorithms are used here to identify trends in the data. Linear regression, time series analysis, cluster analysis or machine learning can be used to identify patterns and correlations. Visualization: to make the results understandable, the identified trends are often presented visually. Charts, graphs or interactive dashboards can be used to present the results. Trend forecasting: Based on the identified trends, software tools can create forecasts for the future. Here, statistical models and algorithms are used to make predictions about future developments. Interpretation: Finally, the results have to be interpreted and analyzed to gain relevant insights. This step often requires human expertise and experience to put the results in the right context. It is important to note that trend analyses cannot always provide accurate predictions. Rather, they are used to identify patterns and trends in the data in order to make informed decisions and understand potential future developments.
TURF (Total Unduplicated Reach and Frequency) analysis is a method used to determine the optimal combination of products or services in a marketing campaign. It uses statistical methods to determine which combination of products or services will achieve the greatest overall reach without conflicting or canceling each other out. TURF analysis is often used in conjunction with conjoint analysis to determine which products or services are most in demand and how they can be combined to achieve the greatest reach. Typical questions in a TURF analysis might include: 1. how many people are reached by our marketing campaign? 2. how often are these people reached by the campaign? 3. which marketing tools reach the largest target group? 4. Which combination of marketing tools reaches the largest target audience with the least number of tools?
Virtual shelf tests
Virtual shelf tests help to analyze the behavior of consumers when shopping. This involves creating simulations of shelves or product displays in which various products are placed. These virtual shelves are shown to participants to observe their reactions and decision-making processes. By analyzing the results of virtual shelf tests, companies can make informed decisions about product placement, packaging design, and marketing strategy to improve consumer appeal and ultimately sales success. Specifically, the following questions can be answered: 1. Which products attract the most attention? 2. How does the placement of a product within the shelf influence consumers’ purchasing decisions? 3. Which product features or packaging appeal to consumers? 4. How do price tags or discount offers affect the perception and purchase of a product? 5. Which brands are perceived as trustworthy or high quality? 6. How do consumers respond to new product introductions compared to established products? 7. What shelf arrangement or product placement maximizes sales?
Voice Coding analyzes the voice of subjects and aims to analyze the implicit responses of individuals. By capturing pitch, sound quality, speech rate and other vocal characteristics, researchers can draw conclusions about a person’s emotional involvement, excitement or authenticity.
Webcam interviews are interviews in which participants communicate with each other via a webcam and an Internet connection. They are often used in situations where participants are in different geographic locations or time constraints prevent face-to-face meetings. The main function of webcam interviews is to create a visual and audiovisual connection between participants so that an interactive conversation can take place in real time. Through the webcam, participants can perceive nonverbal communication, facial expressions, gestures, and body posture, which in many cases is important for assessing research interviews.