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  1. article

    Don't let technology take control of focus groups

    Focus groups continue to be one of the most popular and fastest-growing market research techniques. Technological advances have affected the way marketing people operate in the 1990s. This article encourages focus group researchers to review some of the basic building blocks of the focus group technique to ensure that none of them are being compromised with the new approaches.

  2. glossary

    Data Crosstabulation

    Examination of the responses to one question relative to responses to one or more other questions. Data crosstabulation examines and analyzes the relationship among two or more categorical variables. Specifically, this method compares the responses to one question relative to responses to one or more other questions. This statistical technique involves creating a table displaying the distribution of data points across these variables, which leads to discovering insights into patterns and associations. Data crosstabulation go beyond simple data examination and delve deeper into the relationships between categorical variables. This process can reveal valuable insights that might not be apparent with basic statistics. Who relies on data crosstabulation? Marketing researchers, analysts and professionals employ data crosstabulation to uncover connections among variables, such as demographics, purchasing behaviors and preferences. Why should I care about data crosstabulation? Data crosstabulation is key to making marketing decisions because the process identifies correlations and trends within specific customer segments. Insights are valuable in determining targeted marketing strategies, product positioning and marketing campaigns.

  3. glossary

    Probability of a Simple Event

    A number between zero and one that measures the likelihood that will occur when the experiment is performed. The probability of all simple events in a sample must sum to one. The probability of a simple event refers to the likelihood that one specific, defined outcome will occur from a single trial or experiment. In marketing research, it might involve calculating the chance that a customer chooses a particular product, clicks an ad or responds to a survey. What are the key aspects of the probability of a simple event in marketing research? Focuses on a single, clearly defined outcome. Measured as a ratio: favorable outcomes ÷ total outcomes. Ranges from zero (impossible) to one (certain). Used in basic predictive modeling and scenario analysis. Often a building block for more complex probability analyses. Why is the probability of a simple event important in market research? It helps researchers estimate the likelihood of specific consumer actions, such as trying a product or switching brands. These insights guide campaign planning, message testing and risk mitigation strategies. Who relies on the probability of a simple event in marketing research? Survey designers and analysts. Media planners and digital marketers. Brand managers evaluating trial rates. Retail analysts assessing purchase likelihood. Predictive modelers using foundational probability. How do market researchers use the probability of a simple event? Market researchers apply the probability of a simple event to model individual behaviors, such as the chance a consumer will purchase after viewing an ad. For example, if 200 out of 1,000 respondents say they would try a new snack, the probability of that event is 0.2, or 20%. Researchers use these calculations to estimate conversion rates, guide A/B testing decisions and forecast campaign effectiveness. This foundational probability concept also feeds into larger models that evaluate multiple variables and outcomes.

  4. glossary

    Unidimensional Scaling

    Procedures designed to measure only one attribute of a respondent or object. Unidimensional scaling in market research refers to a measurement technique used to assess respondents' opinions, attitudes or preferences on a single specific attribute or dimension. It aims to quantify individuals' perceptions on a single scale, making it easier to compare and analyze their responses. Who relies on unidimensional scaling in market research? Market researchers, survey designers and analysts rely on unidimensional scaling to evaluate consumers' opinions or feelings about a single characteristic. This method is commonly used to measure customer satisfaction, product preference or other one-dimensional concepts to gain insights into consumer sentiment and make informed decisions. Why should I care about unidimensional scaling in market research? Understanding unidimensional scaling is important because it allows you to collect quantifiable data about specific attributes that influence customer behavior. Whether you're in marketing, product development or strategy, utilizing unidimensional scaling can help you gauge customer sentiment and preferences accurately, leading to better-tailored offerings and strategies. Why is unidimensional scaling important to market research? Unidimensional scaling simplifies the measurement of singular attributes, making it easier to interpret and compare responses. It helps in narrowing down the focus of research, reducing complexity while providing valuable insights. By effectively using unidimensional scaling techniques, you can refine your understanding of customer perceptions and create strategies that resonate with their preferences, leading to improved business outcomes.

  5. glossary

    Interview

    A data-collection encounter in which one person (an interviewer) asks questions of another. Interviews are a qualitative research method used to gather in-depth insights from individuals through direct questioning. They can be conducted in person, by phone or online and are typically semi-structured or structured. What are the key aspects of interviews in marketing research? Allow for open-ended, exploratory responses. Can be one-on-one or in dyads/triads. Provide rich, detailed feedback. Require skilled interviewers to probe effectively. Responses are often recorded and transcribed for analysis. Why are interviews important in market research? They help uncover motivations, attitudes, emotions and decision-making processes that are difficult to capture through surveys. Interviews provide context and depth to quantitative findings. Who relies on interviews in marketing research? Qualitative researchers. Product development teams. Brand strategists. UX and CX professionals. Advertising and creative teams. How do market researchers use interviews? Researchers use interviews to explore new product ideas, understand customer journeys, gather feedback on messaging or investigate specific behaviors. Insights are analyzed thematically to inform strategy, innovation or communication.

  6. glossary

    Reliability

    Measures that are consistent from one administration to the next. Reliability refers to the consistency and stability of a measurement instrument or research method over time. A reliable measure produces similar results under consistent conditions, indicating that the data can be trusted. Who relies on reliability in market research? Survey designers, data analysts, research firms, quality assurance teams and academic researchers rely on reliability to ensure the integrity and repeatability of their findings. What are key aspects of reliability in market research? Test-retest reliability (consistency over time). Internal consistency (e.g., Cronbach’s alpha). Inter-rater reliability (agreement among observers). Affected by question clarity, survey length and respondent understanding. Essential for valid comparisons and conclusions. Why is reliability important in market research? Reliable data supports credible insights and sound decision-making. Without reliability, results may vary due to measurement error rather than actual differences or trends, undermining the value of the research. How do market researchers use reliability? Researchers assess reliability through statistical tests and quality control checks. They refine survey instruments, validate scales and ensure standardized procedures across data collection to maintain high reliability in their studies.

  7. glossary

    Analysis Of Covariance (ANCOVA)

    A statistical procedure used with one dependent variable and multiple independent variables of both categorical (ordinal, dichotomous or nominal) and continuous types; it is a variation of analysis of variance that adjusts for confounding by continuous variables. Analysis of covariance, or ANCOVA, is a statistical technique that compares the means of dependent variables across different groups while controlling the impact of one or more covariates. It combines elements of analysis of variance, or ANOVA, and linear regression to determine the influence of confounding variables. ANCOVA provides a way to remove the influence of confounding variables that could otherwise lead to incorrect conclusions. In other words, it lets researchers isolate the effects of the independent variable of interest. ANCOVA makes statistical analysis more accurate. It is most useful when researchers want to examine group differences while considering the impact of specific covariates on the outcome. Who relies on analysis of covariance? Among the fields in which ANCOVA is commonly utilized are marketing research, social sciences, psychology, education, health care and biological research. For instance, ANCOVA is relied upon by researchers, statisticians and analysts to study the impacts of interventions, treatments or independent variables while accounting for the influence of covariates to alter or even hit the relationships between the groups and the dependent variable. Why should I care about analysis of covariance? Anyone involved in conducting or interpreting research should become familiar with ANCOVA because it improves the accuracy and validity of statistical conclusions. By using ANCOVA appropriately, researchers can draw more accurate and defined inferences, thus strengthening their research and findings.

  8. glossary

    Crosstabulation

    Examination of the responses to one question relative to responses to one or more other questions. Crosstabulation, sometimes called crosstab, analyzes the relationships among two or more categorical variables. This statistical technique examines the responses to one question in relation in response to one or more other questions. It involves creating a contingency table that displays the frequency distribution of variable combinations, which permits researchers to discover patterns, trends and associations among categories. This method reveals insights into consumer behavior, preferences and other relevant marketing factors. Crosstabulation goes beyond simple data presentation and explores the connections among categorical variables. This technique also identifies correlations, dependencies and trends that might not be immediately obvious. Who relies on crosstabulation? Market analysts, product managers, advertising professionals and strategic planners use crosstabulation to make decisions about marketing strategies and to better understand their target audience. Why should I care about crosstabulation? Crosstabulation uncovers hidden patterns and relationships within marketing data. By using this method, marketing professionals can make decisions that are grounded in data-driven insights. Crosstabulation clarifies how different variables interact.

  9. focus_group_facility

    Fieldwork Minneapolis

    Large, viewable test kitchen! the only one of its kind in the area. Fieldwork Minneapolis, located in the heart of shopping bliss! Our excellent recruiting, detailed project management and hospitable service keep you coming back.

  10. article

    Measuring the effectiveness of its DTC TV ads helps pharma firm gauge ROMI to brands

    Presents a case study of how one pharma company used an analysis of its direct-to-consumer advertising to determine the most sales-effective ad program.

  11. glossary

    Grid Test

    A means of testing more than one variable at a time. In marketing research, a grid test is a means to evaluate more than one variable at a time. This method assesses and analyzes customer preferences and perceptions when judging product attributes and features. Respondents are presented with a grid-like matrix on which product attributes are listed along the columns and rows. They are asked to rate the combinations of attributes. Their insights are used by researchers to understand how various attributes interact and influence consumer preferences. Insights from a Grid Test can be beneficial for several reasons. For starters, they allow researchers to identify product attributes that influence consumer decision making. What’s more, they can pinpoint attributes that can be used in product design to align with consumer preferences. In addition, the findings enable marketing professionals to construct effective marketing campaigns by highlighting the attributes that matter most to their audience. Simply stated, the Grid Test expands understanding of consumer behavior and provides evidence for making marketing decisions. Who relies on a grid test? Marketing professionals, product developers and researchers turn to grid tests to collect insights into consumer preferences in order to prioritize product and service attributes. The findings also are used to make informed decisions about product development, positioning and marketing strategies. Why should I care about a grid test? A grid test is a systematic technique to analyze how various attributes affect consumer choices. Insights can help marketing professionals and businesses to improve products, services and marketing efforts to better resonate with target audiences.

  12. glossary

    Hall Tests

    When face-to-face interviews are conducted at one or more specified locations often a large room or hall. In marketing research, a hall test is a research method that involves inviting participants to a controlled location, such as a hall or simulated shopping situation, and asking them to respond to certain stimuli, like food, beverages or advertising. This testing evaluates consumer reactions in a controlled environment, such as insights into consumer preferences and behaviors. Hall tests provide information about consumer interactions with products and services to professionals in product development, marketing or decision-making. They offer insights into consumer preferences, likes, dislikes and potential barriers to purchasing. Who relies on a hall test? Companies and brands seeking to introduce new products or enhance existing ones turn to hall tests to gain insights. In addition, market researchers, product developers and marketing teams use tests to understand consumer perceptions of products, purchasing decisions and potential areas of improvement. Why should I care about a hall test? Hall tests provide insights into consumer preferences, likes, dislikes and potential barriers to purchasing. Product developers, marketing professionals and decision makers use these findings to guide strategies, make informed decisions and plan successful product launches.