GLOSSARY

A Priori Segmentation – Market segmentation that is not empirically-based. It involves segmenting markets on the basis of pre-defined assumptions, custom, or hunches.

A/B Testing – A method of comparing two versions (A and B) of a webpage, email, or other marketing assets to determine which performs better. A/B testing is often used to optimize elements like headlines, images, or calls to action.

Ad Hoc Research – A one-time research project designed for a particular purpose (as opposed to being conducted regularly or as part of a larger research program).

Adaptive Conjoint – An interactive conjoint design, ideal for situations in which the number of attributes exceeds what can reasonably be done with more traditional conjoint methods. Adaptive conjoint gives priority to attributes that are most relevant to the respondent and avoids respondent fatigue by focusing on fewer attributes at a time.

Agile Research – An iterative and flexible approach to market research that emphasizes quick turnaround times, continuous adaptation, and collaboration. Agile research is well-suited for rapidly changing markets and product development cycles.

Aided Recall – A questioning approach that attempts to stimulate a respondent’s memory with clues about an object of interest.

Analysis of Variance (ANOVA) – A method of testing metric variables against a single dependent categorical measure to determine whether or not the means differ across all groups.

ANOVA (Analysis of Variance) – A statistical method used to test the equality of means among multiple groups. ANOVA assesses whether there are any statistically significant differences between the means of three or more independent groups.

Applied Research – Research designed specifically to solve a particular problem or objective (as opposed to theoretical or exploratory research).

Attitude, Awareness & Usage Study (AAU) – A longitudinal (tracking) study that measures the attitudes, awareness, and usage levels for a product or brand.

Attitudes – Mental states used by individuals to structure the way they perceive their environment and to guide the way which they respond. A psychological construct comprised of cognitive, affective, and intention components.

Attitudinal Scaling – Questioning technique where respondents rate an object (brand, product, service, etc.) on a pre-defined scale, such as “extremely valuable”, “somewhat valuable” and “not valuable.”

Attribute – A characteristic or property of an object or person.

Augment – To increase the number of respondents included in a segment or sub-segment beyond what a random sample would provide.

Augmented Reality (AR) Surveys – Surveys that incorporate augmented reality elements to enhance the respondent’s experience. AR surveys often involve overlaying digital information or visuals onto the respondent’s real-world environment.

Awareness – The proportion of people who are familiar with a product, brand name, or trademark.

Back Checking – The process through which data collected is verified and authenticated, by contacting the respondent directly.

Balanced Scales – A scale used in questionnaires where the number of positive and negative categories is equal.

Banner Point – The heading for a single column of data in cross-tabulations.

Base – The sample size or number of respondents used to compute percentages in a data table.

Bayesian Statistics – Statistics that incorporate prior knowledge and accumulated experience into probability calculations. Bayesian analysis can be applied to a number of traditional analyses such as regression and the estimation of conjoint utilities.

Behavior – The past and present overt responses of subjects.

Benchmark – A control source against which you compare the area you’re studying. For example, you may compare the results of a study in one state to the results of the nation as a whole.

Between-Subjects Design – An experimental design in which different participants are assigned to different levels of the independent variable. It contrasts with within-subjects designs where the same participants experience different conditions.

Bias – A systematic tendency of a sample to misrepresent the population. Biases may be caused by inadequate sampling of the population, survey or item non-response, interviewing techniques, wording of questions, data entry, etc.

Big Data Analytics – The use of advanced analytics techniques to analyze large and complex datasets, often generated from various sources, to uncover patterns, trends, and associations that can inform decision-making.

Bipolar Scale – A rating scale that uses symmetrical and opposing end points (e.g. agree/disagree, good/bad) to capture attitudes or evaluations. Bipolar scales typically invoke at least 5 scale points, and use escalating modifiers (e.g. somewhat, very) to describe values as they deviate further from a midpoint. The midpoint value represents a point of indifference or equality between the opposing end points.

Blind Study – A study where all brand identity is removed or hidden, most frequently to avoid bias.

Blinding (Single-blind, Double-blind) – A technique in which participants or researchers are unaware of the group assignments or treatment conditions. Single-blind involves hiding information from participants, while double-blind involves hiding information from both participants and researchers.

Blockchain in Market Research – The use of blockchain technology to ensure the security, transparency, and integrity of research data. Blockchain can enhance the reliability of survey responses and maintain the privacy of participants.

Brand – A specific name, symbol or design which is used to distinguish a product or service from competitors.

Brand Associations – Attributes, values, or other meanings (images, emotions, etc.) that are attached or associated with a brand.

Brand Equity – The concept wherein the brand is considered an asset insofar as it can be sold or bought for a price. A powerful brand is said to have high brand equity.

Brand Extension – A branding or marketing strategy where a new product or service is launched under the existing brand name of a well-developed product or service.

Bulletin Board Groups – Online qualitative research that utilizes bulletin boards or message boards to have discussions, read and comment on postings, share files, etc.

Business to Business (B2B) – Describes the market where a business is selling it’s product or service to another business (as opposed to consumers).

Business to Consumer (B2C) – Describes the market where a business is selling its products direct to consumers.

Buyer Persona Research – The process of creating detailed and semi-fictional representations of ideal customers based on market research and real data. Buyer personas help businesses tailor their marketing and product strategies to specific customer segments.

Buying Behavior – The process purchasers go through when deciding which products or services to buy.

Buying Intent – The likelihood that a respondent will purchase a product or service.

Card Sorting – A UX research technique in which participants organize and categorize information on cards to help designers understand the most intuitive and user-friendly ways to structure information on a website or app.

CART/CHAID Analyses – Two tree-based methods for segmenting respondents that maximize differences with respect to an outcome (dependent) variable. Tree-based methods evaluate each potential predictor and divide the sample by the characteristic that maximizes differences across respondents. Splitting stops when certain statistical criteria are met, leaving the segments defined in terms of the nodes created from each split. These methods are capable tools for sifting through a large amount of information to identify powerful classification variables, and are thus used often in data mining efforts.

Case Study – A detailed and in-depth examination of a specific individual, group, organization, or situation. Case studies involve comprehensive data collection and analysis to provide a holistic understanding.

Causal Relationship – A precondition influencing a variable of interest, or, in more strictly, a change in one variable that produces a change in another variable.

Census – A survey of an entire population or universe.

Chatbot Surveys – Surveys conducted through interactive chatbots, automated programs that simulate conversation with respondents. Chatbot surveys offer a more conversational and engaging experience, often used in online and mobile research.

Chi-Square Statistic – A statistical test used to determine the independence or association between categorical variables. Chi-square tests are often employed in contingency table analysis.

Choice Modeling – A multivariate statistical method used to simulate real-world buying behavior (also called Choice-Based Conjoint).

Churn Rate – The percentage of customers who stop using a product or service during a given time period. Churn rate is a critical metric for subscription-based businesses.

Closed-end Question – Questions that require a respondent to select from a pre-defined set of responses.

Cluster – In a sampling context, a cluster is defined as a category assigned to a neighborhood based on the assumption that the households share certain demographic, social, and economic characteristics. In a segmentation context, a cluster is a homogenous group of respondents who are defined through cluster analysis.

Cluster Analysis – A technique for segmenting respondents without using a predictor (dependent) variable. It identifies segments using a variety of data, including attitudinal, usage, or preference inputs. Cluster analysis uses one of algorithms to group people who are maximally similar to one another and maximally different from other groups. Cluster analysis is best viewed as an exploratory technique, since it is impossible to determine the “right” number of segments for any given market.

Coding – The process of assigning numeric values to responses from open-ended or other-specify questions.

Comparative Scales – A scale that requires one object (brand, product, service, etc.) to be compared to other objects.

Completes – Completed research interviews.

Completion Rate – The percentage of qualified respondents who complete a survey in its entirety.

Computer-Aided Self-administered Interviewing (CASI) – A computer-based interview that respondents complete themselves, usually at a pre-determined location.

Computer-Aided Telephone Interviewing (CATI) – Interviews conducted over the telephone, where the interviewer is using a computer-based program.

Computer-Aided Web Interviewing (CAWI) – Interviews conducted over the internet.

Concept Description – A brief description of a new product or service.

Concept Test – A test of a product concept where the concept is evaluated by a sample of the target segment.

Conceptual Mapping – A moderation technique in which participants are asked to place the names of products or services on a grid. How they group the items on the diagram is used to stimulate discussion.

Concurrent Validity – The extent to which the results of a new measurement correlate with those of a well-established measurement for the same construct.

Confidence Intervals – A range of values used to estimate the precision of a sample statistic. Confidence intervals provide a range within which the true population parameter is likely to fall.

Confidence Level – The probability that a particular confidence interval will include the true population value.

Conjoint Analysis – A quantitative research technique used in pricing research to understand how consumers value different features or attributes of a product. Conjoint analysis helps in pricing optimization by assessing trade-offs.

Consideration Set – All the alternatives that potential buyers would consider in their next purchase of the product or service.

Content Analysis – A research method that involves systematically analyzing the content of textual, visual, or audio data to identify patterns, themes, and meanings. Content analysis is often used to examine communication materials, documents, or media.

Control Group – The group in an experiment that does not receive the experimental treatment. It provides a baseline for comparison with the experimental group to assess the effect of the independent variable.

Convenience Bias – A bias that occurs when the sample is not representative because it is based on convenience, leading to potential distortions in results.

Convenience Sample – A non-random sample of respondents, selected based off of convenience.

Copy Testing – The process of using market research to evaluate the effectiveness of advertising, typically against metrics such as memorability, appeal and impact.

Correlation – A statistical measure that quantifies the degree to which two variables are related. Correlation coefficients range from -1 to 1, with -1 indicating a perfect negative correlation, 0 indicating no correlation, and 1 indicating a perfect positive correlation.

Counterbalancing – A technique used to control for order effects in repeated-measures designs. It involves varying the order in which participants experience different conditions.

Covariate Control – The statistical technique of including a covariate in the analysis to control for its influence on the dependent variable, reducing variability.

Covariate – A variable that is related to both the independent and dependent variables in a statistical model. Covariates are often included to control for their effects and isolate the relationship of interest.

Crossover Design – An experimental design in which each participant serves as both the experimental and control group in different phases of the study. It helps control for individual differences.

Cross-Platform Analytics – The analysis of data across multiple platforms and devices to gain a comprehensive understanding of consumer behavior and interactions. Cross-platform analytics helps researchers adapt strategies to reach diverse audiences.

Cross-Tabulation – Breaking out survey results by different groups of respondents (by age, gender, etc.).

Custom Marketing Research – Customized marketing research to address specific projects for corporate clients.

Customer Feedback Loop – A systematic process for collecting, analyzing, and implementing customer feedback. The feedback loop helps organizations continuously improve their products or services based on customer insights.

Customer Journey Research – An analysis of the various touchpoints and interactions a customer has with a brand throughout their entire relationship. Customer journey research helps businesses understand and optimize the customer experience.

Customer Lifetime Value (CLV) – The predicted net profit a company expects to earn from a customer throughout their entire relationship. CLV helps businesses understand the long-term value of acquiring and retaining customers.

Customer Retention – The ability of a company to retain its existing customers over time. High customer retention is often a sign of customer satisfaction and loyalty.

Customer Satisfaction (CSAT) – A metric that measures how satisfied customers are with a product or service. CSAT is often measured through surveys asking customers to rate their satisfaction on a scale.

Customer Segmentation – The process of dividing a customer base into distinct groups based on shared characteristics, behaviors, or needs. Customer segmentation is valuable for targeted marketing and product development.

Customer Value Analysis (CVA) – Analysis of customer satisfaction within an organization as compared with a competing organization’s customer satisfaction. CVA is used to determine profitable customer relationships, areas where the organization and competing organizations succeed /fail, the profitability per customer, the overall customer value of a firm and customer value for its competition, the value and cost of potential customers, and the cost of retaining customers. Gives a detailed picture of the organization’s strengths and weaknesses, as well as customer expectations.

Data – Unassimilated facts about the market.

Data Collection – The process of collecting research data.

Data Mining – Using statistical and advanced software to query large sets of data.

Data Processing – Organization of data for the purpose of producing desired information; involves recording, classifying, sorting, summarizing, calculating, disseminating, and storing data.

Data Visualization – The techniques used to communicate data or information by encoding it as visual objects contained in graphics. The goal is to communicate information clearly and efficiently to users.

Database – An organized store of data, usually within a computer.

Deduping – Identifying and removing duplicate records in a data file.

Delphi Method – A forecasting method that involves iterative rounds of surveys or questionnaires among a panel of experts to achieve consensus on a particular issue.

Demand Characteristics – Cues or features of an experiment that convey information to participants about the expected outcome, influencing their behavior.

Demographics – Description of the vital statistics or objective and quantifiable characteristics of an audience or population. Demographic designators include age, marital status, income, family size, occupation, and personal or household characteristics, such as age, sex, income, or educational level.

Dependent Variable – A symbol or concept expected to be explained or caused by the independent variable. It is the variable measured on each subject to determine whether its value is affected by the independent variable. Also known as criterion variable.

Depth Interview – A discussion between the moderator and interviewee. This technique avoids groupthink and enables deep probing of the subject matter. AKA in-depth interview.

Discrete Choice Analysis – A variation of conjoint analysis that uses respondent choices rather than rankings or ratings to express product preferences. Discrete choice provides a more realistic context for many product decisions, and also allows the opportunity to express a lack of interest through a “None of these” option. Although discrete choice has traditionally been limited to deriving utilities at the aggregate level, recent advances have made it possible to create utilities for each respondent. This results in better overall estimation as well as opportunities for preference-based segmentation using choice-based techniques.

Discrete Variable – A quantitative variable that can assume a finite or at most a countable number of values such as the number of children in a family.

Discriminant Analysis – Similar to regression, but predicts group membership rather than strength of association against a metric variable. This technique is a useful way to find the characteristics that best define differences across groups. It can also be used in conjunction with cluster analysis to derive equations that allow the segmentation to be applied consistently to future observations.

Discussion Board – An online platform where participants engage in discussions, share opinions, and respond to prompts. Discussion boards are utilized in online qualitative research to facilitate asynchronous communication.

Discussion Guide – Also called a Moderator’s Guide, an outline of topics, questions, and prompts used during qualitative focus groups or interviews. It provides a structured approach to research discussions.

Dropout Rate – The percentage of qualified respondents who begin a survey or research activity but do not complete it. Dropout rates are monitored to assess participant engagement.

Dyads – A focus group conducted with two participants. Dyads offer a unique dynamic for exploring interpersonal dynamics and interactions.

Econometric Models – Statistical models used to analyze economic relationships and forecast economic trends, often incorporating market research data.

Effect Size – A measure that quantifies the size of the difference or strength of the relationship between variables. Effect sizes are important for interpreting the practical significance of statistical findings.

ESOMAR – A European-based association of market researchers, issuing and binding members with rules of conduct for market research.

Estimate – A numerical value obtained from a statistical sample and assigned to the population parameter.

Ethnography or Observational Research – The observational study of human behavior in it’s natural environment.

Ethnography – A qualitative research method that involves observing and immersing researchers in the natural environment of the participants to understand their behaviors, interactions, and cultural context.

Executive Interviews – Executive decision-makers use a different set of criteria from those of consumers. An in-depth interview provides extensive knowledge of the executive decision-making process. Phone or in-person interviews are conducted to complete these interviews.

Experimental Design – The structured plan or blueprint for conducting an experiment. It outlines the procedures, treatments, and conditions under which the study will be conducted.

Experimental Group – The group in an experiment that is exposed to the experimental treatment or condition. Changes in the experimental group are compared to the control group.

External Validity – The extent to which causal relationships measured in an experiment can be generalized to outside persons, settings and times.

Face Validity – The intuitive test of whether a measurement seems to measure what it is suppose to measure.

Factor – An underlying construct defined by a linear combination of variables.

Factor Analysis – An approach that, like cluster analysis, identifies relationships without using an outcome (dependent) variable. Grouping related characteristics instead of related people, factor analysis reveals unobserved “dimensions” that underlie a larger number of observed variables. This technique can either identify a subset of variables to represent these dimensions, or derive new variables that are composites of the original variables associated with each dimension. In either case, subsequent analyses (e.g. regression or cluster) can benefit from variable reduction.

Factorial Design – An experimental design that involves manipulating more than one independent variable. It allows researchers to examine the effects of multiple factors simultaneously.

Familiarity – Level of knowledge of a brand or product.

Focus Group – A research discussion group comprising eight to twelve participants, guided by a moderator, to explore opinions, perceptions, and attitudes on a specific topic. Focus groups facilitate group dynamics and interaction.

Geodemographics – The analysis of demographic and geographic data to identify and target specific consumer segments based on where they live.

Geofencing – A location-based technology that allows researchers to set up virtual boundaries in specific geographic areas. Geofencing is used to trigger surveys, notifications, or data collection when individuals enter or exit defined locations.

Grounded Theory – A qualitative research methodology focused on developing theories from the data itself rather than testing existing theories. It involves iterative data collection and analysis to build concepts and theories.

Group Dynamics – The interaction among people in a group. An effective moderator can enable group dynamics to promote helpful discussion by various techniques, as well as minimize the potentially negative effects of group dynamics.

Hawthorne Effect – The alteration of human behavior when individuals are aware that they are being observed, potentially impacting research outcomes.

Heatmap – A graphical representation of data in which values are represented by colors. In UX research, heatmaps are often used to visualize user interactions on a webpage, showing areas of high and low engagement.

Heuristic Evaluation – A usability inspection method where experts evaluate a product’s user interface based on established usability principles (heuristics). This helps identify potential issues and areas for improvement.

History Effect – External events or circumstances that occur during the course of an experiment and may affect the dependent variable.

Honorarium – The payment provided to focus group participants. The amount varies dramatically, based on the difficulty of recruiting the participants. Also called the co-op payment or incentive.

Hypothesis Testing – The process of making inferences about a population parameter based on sample data. Hypothesis testing involves formulating a null hypothesis, collecting data, and assessing the evidence against the null hypothesis.

In-App Analytics – The analysis of user behavior within a mobile or web application. In-app analytics help developers and product managers understand how users interact with the app and identify areas for improvement.

Incentive – The payment to participants for coming to a focus group. The amount varies dramatically, based on the difficulty of recruiting the participants. Also called honorarium or co-op payment.

Independent Variable – In an experimental setting, a variable that is controlled or manipulated by the researcher. In most multivariate analyses, however, these are simply the variables used to predict an outcome (or dependent) variable. Also known as predictor variables.

In-Depth Interviews (IDIs) – A qualitative research technique that involves conducting intensive one-on-one interviews with participants to explore their perspectives, experiences, and attitudes in detail.

Infographic – A visual image such as a chart or diagram used to represent information or data.

In-Home/Observational Research – Often times, people act differently than how they say they act, therefore, it is important to view people doing activities or using products in their home or office environment to better understand their behavior. This enables a client to develop better solutions for their customers. Asking questions is always worthwhile, but observing behavior adds another rich layer of understanding.

Insights Association – A trade organization for market research which outlines guidelines and code of ethics for researchers.

In-Store Interviews – Asking people questions at the point of purchase is a valuable tool used to understand the reasons and motivations of a specific decision. In a facility setting, the respondent may forget why they selected a specific brand at that crucial moment. By intercepting shoppers we can gain an edge and discover market-actionable insights.

Instrumentation – Changes in the measuring instrument or observation technique over the course of an experiment, which may affect the results.

Interaction Effect – The combined effect of two or more independent variables that is not simply the sum of their individual effects. It indicates that the effect of one variable depends on the level of another variable.

Intercept – A recruitment method in which an interviewer stops people in a public location, such as a mall, and administers a survey or conducts a brief interview.

Interviewer Error – An error that results from conscious or unconscious bias in the interviewer’s interaction with the respondent. Interviewer errors can impact data quality.

Interviewer – The person responsible for recruiting participants for a focus group or conducting qualitative interviews. The interviewer plays a crucial role in the research process.

Jobs to Be Done (JTBD) Research – A research framework focused on understanding the fundamental reasons why customers “hire” a product or service to get a specific “job” done. JTBD research delves into the functional and emotional aspects of customer needs.

Key Drivers Analysis – A statistical approach to prioritizing the relative impact of various factors on an outcome (dependent) variable of interest. Key Drivers Analysis (KDA) is often used to compare the importance of a feature or attribute against the strength of performance. While it is typically synonymous with Regression Analysis, KDA can be conducted using a variety of Multivariate Analysis.

Kurtosis – A measure of the “tailedness” of a probability distribution. High kurtosis indicates heavy tails, while low kurtosis indicates light tails.

Landing Page – A specific webpage that a user reaches after clicking on a link or advertisement. Landing pages are designed to encourage a particular action, such as making a purchase or filling out a form.

Level of Significance – The stated probability at which a hypothesis is either accepted or rejected. In most cases, differences are accepted only if they occur at the 95% level or higher. This is interpreted to mean that, by accepting the statistical difference, we are observing an actual population difference in 95 out of 100 cases. In the other 5 cases, the observed difference is actually attributable to random error.

Likert Scale – One of the most common approaches to capturing attitudes or opinions, Likert Scales use a Bipolar Scale that captures the strength of agreement or disagreement with multiple items that combine to form an empirically validated concept. The term is generally used to describe any single question using a 5-point scale, although this obscures distinctions with other scale constructs and anchors.

Linguistic Analysis – The study of language and its structures to gain insights into communication patterns, meanings, and cultural nuances. Linguistic analysis is applied in qualitative research to understand how language shapes perceptions and behaviors.

Logistic Regression – A variation on OLS regression that predicts a binary outcome such as agreement (yes vs. no) or purchase (buy vs. not buy). Discriminant analysis can also be used to predict dichotomous group membership, but “logit” is generally preferred due to its broader applicability. Logit output indicates whether each predictor variable increases or decreases the probability of the outcome.

Logit – A variation of logistic regression that is typically applied to the analysis of respondent choices. Multinomial logit (MNL) is the preferred method for synthesizing the impact of multiple-predictor variables on a categorical outcome involving more than two choices, such as choice-based conjoint data. As with logistic regression, MNL output indicates the impact of each characteristic on the probability of brand choice.

Longitudinal Study – A research design that involves repeated observations or measurements of the same subjects over an extended period to analyze trends and changes.

Machine Learning in Market Research – The application of machine learning algorithms to analyze data, make predictions, and uncover insights in market research. It enhances the ability to handle large datasets and identifies complex patterns.

Main Effect – The overall effect of one independent variable on the dependent variable, ignoring the effects of other variables. In a factorial design, there can be main effects for each independent variable.

Mapping – The process by which a computer generates thematic maps that combine geography with demographic information and a company’s sales data or other proprietary information.

Market – The total of all individuals or organizations that represent potential buyers.

Market Segmentation – The development and pursuit of marketing programs directed at subgroups or segments of the population that the organization could possibly serve.

Marketing Research – The specification, gathering, analyzing, and interpretation of information that links the organization with its market environment.

MaxDiff Analysis – An approach to prioritizing many features or attributes by asking individuals to identify the most and least important items. People are often better at identifying extremes (“maximum differences”) than at making granular assessments. By repeatedly identifying the best and worst items among a subset of features, we are able to derive individual ratings that are discriminating and free from scale usage bias. Advanced applications of MaxDiff will implement anchoring techniques to overlay resulting scales with meaningful thresholds.

Menu-Based Conjoint – A variation of Choice Modeling that applies to decisions that include multiple stages, bundles or customization. Menu-Based Conjoint (MBC) examples include simulating restaurant orders or car configurations, but MBC can be applied to any purchase model that requires multiple choices, customization, or product cannibalization. MBC is more complex than tradition choice modeling, which has implications for base size and project scope.

Message Testing – The process of evaluating and refining communication messages, such as advertisements or marketing content, to ensure they resonate with the target audience. Message testing helps optimize the effectiveness of communication strategies.

Methodology – The research procedures used; the section of the final report in which the researcher outlines the approach used in the research, including the method of recruiting participants, the types of questions used, etc.

Mini Groups – A smaller version of a focus group, typically comprising four to six participants. Mini groups offer a more intimate setting for in-depth discussions.

Mobile Ethnography – A research method where participants use their mobile devices to document and share their daily experiences, behaviors, and opinions. It provides real-time insights into participants’ lives.

Mobile Surveys – A method of data collection means by using functions of mobile phones, smartphones and tablets. It makes use of strengths from mobile communication and applies these strengths to research purposes.

Moderator – The person responsible for leading and guiding a focus group or qualitative research session. The moderator facilitates discussion and ensures the research objectives are met.

Multicollinearity – The presence of high correlations between independent variables in a regression analysis, which can complicate the interpretation of individual variable effects.

Multiple Classification Analysis (MCA) – An extension of regression analysis that is typically used in satisfaction research. Unlike regression, it allows the analyst to find exceptional (non-linear) relationships that demonstrate the “penalty” or “reward” associated with various levels of each predictor variable. MCA requires larger sample sizes than regression, and is most valuable when examining the impact of variables with discrete values, such as attribute ratings.

Multivariate Analysis – The simultaneous analysis of multiple variables to understand their interrelationships. Multivariate analysis techniques include factor analysis, discriminant analysis, and canonical correlation analysis.

Mutually Exclusive – Events are said to be mutually exclusive if they have no intersection.

Net Promoter Score (NPS) – A metric used to measure customer loyalty and satisfaction, based on the likelihood of customers recommending a company’s products or services.

Net Revenue Retention (NRR) – A metric that measures the revenue retained from existing customers, accounting for churn, upgrades, and expansions. NRR is used to assess the overall health of a customer base.

Netnography – An online research method that involves studying and analyzing social interactions, behaviors, and cultural expressions within online communities and forums. It aims to understand the dynamics of virtual communities and their impact on consumer behavior.

Neuromarketing – The application of neuroscience principles to marketing research. Neuromarketing techniques, such as brain imaging, aim to understand and influence consumer behavior at a subconscious level.

Nominal Data – Categorical data without inherent order or ranking. Examples include gender, colors, or types of fruit.

Non-Disclosure Agreement (NDA) – A legal contract outlining the confidentiality terms between researchers and clients or participants. NDAs protect sensitive information.

Non-Probability Sampling – Any sampling method where the probability of any population elements inclusion is unknown or ignored, such as with convenience sampling. Examples include purposive sampling and convenience sampling.

Non-Response Error – An error that occurs due to non-participation of some eligible respondents in the study. This could be due to the unwillingness of the respondents to participate in the study or the inability of the interviewer to contact the respondent.

Non-Response Bias – An error due to the inability to elicit information from some respondents in a sample, often due to refusals.

Normal Distribution – A continuous distribution that is bell shaped and symmetrical about the mean.

Null Hypothesis – A statistical hypothesis that suggests there is no significant difference or relationship between variables. Hypothesis testing aims to either reject or fail to reject the null hypothesis based on sample data.

Objectives – The information to be developed from a study to serve the project’s purpose.

Observation – A data collection method where the relevant behaviors are recorded.

Observational Research – A research method where behavior is directly observed in a natural or controlled environment. It is often used in ethnography and usability studies.

On the Street Interviews – A qualitative method in which a respondent is stopped on the street and asked for their feedback. Usually lasts between 5-10 minutes.

One-on-One or In-Depth Interview – A discussion between the moderator and interviewee. This technique avoids group-think and enables deep probing of the subject matter.

Online Communities (MROCs) – Market Research Online Communities (MROCs) are targeted groups of people recruited into private online venues to participate in research-related activities over an extended period.

Online Community Boards – Virtual platforms where individuals with shared interests or characteristics gather to discuss various topics. In market research, online community boards are utilized for qualitative research, allowing participants to share opinions, experiences, and insights.

Online Survey – A survey administered over the internet, allowing respondents to complete it at their convenience. Online surveys are cost-effective and offer quick data collection.

Ordinal Data – Categorical data with a meaningful order or ranking, but the intervals between values may not be consistent.

Outlier – A data point that significantly differs from the rest of the data. Outliers can skew statistical analyses and are often examined for data quality.

Panel – A group of individuals who have agreed to participate in multiple research studies over time. Panels are often used for longitudinal research.

Perceptual Map – A spatial representation of the perceived relationships among objects in a set, where the objects could be brands, products, or services.

Persona – An archetype or representation of a typical user of a product or service. Personas are created based on user research and help designers and marketers understand the needs and motivations of different user segments.

Pilot Study – A small-scale research study conducted before the main study to test procedures, instruments, and processes. It helps identify and address potential issues.

Placebo Effect – Changes in participants’ behavior due to the belief that they are receiving a treatment, even if the treatment has no active ingredients or therapeutic effect.

Placebo – A substance or treatment that has no therapeutic effect but is used in experiments to control for the psychological effects of receiving treatment.

Population – The entire group of individuals or instances about whom the researcher wants to draw conclusions. The population is often too large to study entirely, so a sample is selected.

Pop-Up – A form of surveying that shows a pop-up window invitation while respondents are on a website.

Positioning – Location of a brand or product in consumers’ minds relative to competitive products.

Predictive Analytics – The use of statistical algorithms and machine learning techniques to analyze historical data and make predictions about future events or trends.

Predictive Modeling – The use of statistical models and algorithms to predict future outcomes based on historical data. In market research, predictive modeling helps forecast trends, customer behavior, and potential market scenarios.

Predictive Validity – The extent to which a measurement or test accurately predicts future performance or outcomes. Predictive validity is a type of criterion-related validity.

Pretest – A small-scale test or trial run of a survey or research instrument to identify potential problems before full-scale implementation.

Price Sensitivity Meter – A series of questions used to determine perceived normal price, penetration price, highest reasonable price, and lowest reasonable price.

Pricing Research – The systematic investigation of optimal pricing strategies for products or services. Pricing research involves analyzing market conditions, consumer perceptions, and competitive pricing to determine the most effective pricing model.

Primary Data – Data collected to address a specific research objective.

Primary Research – Conducting research to collect new data to solve a marketing information need. See also secondary research.

Principal Component Analysis (PCA) – A technique used to transform correlated variables into a set of uncorrelated variables called principal components. PCA is often used for dimensionality reduction.

Probability Distribution – A mathematical function that describes the likelihood of obtaining the possible values of a random variable. Common probability distributions include normal, binomial, and Poisson distributions.

Probability Sampling – A sampling method where each member of the population has a known and non-zero chance of being selected. Random sampling is a common form of probability sampling.

Probing – A follow-up technique for getting complete responses to open-ended questions by asking.

Profile Analysis – The comparison of evaluations of the alternatives in a consideration set, on the important and determinant attributes.

Projectability – The capability of research results to be extrapolated to the larger universe, on the assumption that the sample is representative of the total.

Projection – An estimate, based on assumptions about future trends in births, deaths, and migration, of a demographic characteristic such as population or number of households. Forecasts and projections are terms that are often used interchangeably.

Psychographics – Research that attempts to explain behavior by analyzing people’s personality traits and values. Often associated with lifestyle research.

P-value – A probability value that indicates the evidence against a null hypothesis. A low p-value (typically less than 0.05) suggests that the null hypothesis is unlikely, leading to its rejection.

Qualitative Data – Non-numeric data that describes qualities, characteristics, or attributes. It is often collected through open-ended questions, interviews, or observations.

Qualitative Research – Research designed primarily for exploratory purposes, such as getting oriented to the range and complexity of consumer activity, clarifying the problem, and identifying likely methodological problems. Examples include focus groups, case studies, and one-on-one interviews.

Quantitative Data – Numeric data that can be measured and counted. It is often analyzed using statistical methods to identify patterns and relationships.

Quantitative Research – Research conducted for the purpose of obtaining empirical evaluations of attitudes, behavior or performance. Designed to generate projectable numerical data about a topic.

Quasi-Experimental Design – An experimental design that lacks random assignment or a control group. Quasi-experiments are often used when randomization is not feasible.

Questionnaire – A set of questions designed to generate data necessary for accomplishing the objectives of the research project.

Quota Sampling – A non-probability sampling method that is constrained to include a minimum from each specified subgroup in the population, regardless of their actual probability of inclusion.

Quota – A defined, required number of units.

Random Assignment – The process of randomly assigning participants to different experimental conditions or groups. It helps ensure that individual differences are equally distributed across groups.

Random Error – Measurement error due to changing aspects of the respondent or measurement situation.

Random Sampling – A sampling method where each member of the population has an equal chance of being selected. Random sampling increases the generalizability of research findings.

Random Variable – A variable whose values are determined by chance. Random variables can be discrete or continuous.

Randomization – A procedure in which the assignment of subjects and treatments to groups is based on chance. Randomization ensures control over the extraneous variables and increases the reliability of the experiment.

Randomized Block Design – An experimental design in which participants are first divided into blocks based on certain characteristics, and then randomly assigned to different treatment conditions within each block.

Randomized Controlled Trial (RCT) – An experimental design in which participants are randomly assigned to either the experimental or control group. RCTs are commonly used in medical and psychological research.

Range – A measure of the spread or dispersion of a set of values. It is the difference between the maximum and minimum values.

Ratio Data – Numeric data with a consistent interval and a true zero point. Examples include height, weight, and income. Ratio data allow for meaningful ratios and proportions.

Regression Analysis – A fundamental and versatile research technique that seeks to explain an outcome (dependent) variable in terms of multiple predictor (independent) variables. This analysis reveals the nature and strength of the relationship between each predictor variable and the outcome, independent of the influence from all other predictors. The term typically refers to Ordinary Least Squares (OLS) regression, which models a linear relationship among variables.

Regression to the Mean – The statistical phenomenon where extreme values tend to move closer to the average in subsequent measurements.

Relevance – A criterion used to judge whether a market research study acts to support strategic and tactical planning activities.

Reliability – The consistency and stability of a measurement instrument. Reliable measures produce consistent results over time and across different conditions.

Replication – The repetition of an experiment to confirm its results and assess the reliability of findings.

Representative Sample – A sample in which each unit has a known probability of selection that is accounted for either through sampling or weighting. A representative sample is obtained using probability, or random sampling.

Research Objectives – A precise statement of what information is needed, consisting of the research question, the hypothesis, and the scope or boundaries of the research.

Research Process – The series of stages or steps underlying the design and implementation of a marketing research project, including the establishment of the research purpose and objectives, information value estimation, research design, and implementation.

Respondent – The individual from whom data are collected. Also called participant, unit, unit of analysis, subject or experimental unit.

Respondent Fatigue – When a respondent begins to lose interest in a survey (due to length, complicated questions, etc.) and can provide invalid or inaccurate responses.

Response Bias – The tendency of respondents to distort their answers systematically for a variety of reasons, such as social desirability or prestige seeking.

Response Error – Error that occurs due to the respondents providing inaccurate information (intentionally or unintentionally). This might be due to the inability of the respondent to comprehend the question or misunderstanding the question due to fatigue or boredom.

Response Rate – The percentage of individuals or units that participate in a survey or research study out of those who were contacted or eligible.

Sample – A subset of the population selected for study. The characteristics of the sample are used to make inferences about the population.

Sampling Bias – The presence of systematic error in a sampling process that results in an unrepresentative sample. Sampling bias can affect the generalizability of research findings.

Sampling Distribution – The distribution of a statistic (e.g., mean or proportion) across multiple samples taken from the same population. The sampling distribution helps make inferences about the population parameter.

Sampling Error – The variability between the characteristics of a sample and the characteristics of the population. Sampling error is unavoidable but can be minimized through random sampling.

Sampling Frame – A listing of population members from which the sample is drawn.

Sampling Frame Error – Error that occurs when the sample is drawn from an inaccurate sampling frame.

Sampling Plan – A detailed outline of the procedures for selecting a sample. The sampling plan includes decisions about the sampling method, size, and frame.

Sampling Unit – The individual elements or units that make up the population and are considered for inclusion in the sample. The sampling unit depends on the research context.

Screener – Questions used to capture the appropriate respondents for a particular research solution.

Screening Sample – A representative sample of the population being studied that is used to develop or pretest measurement instruments.

Secondary Data – Data collected for some purpose other than the present research purpose.

Secondary Research – Analyzing information from previously conducted research projects. See also primary research.

Segment – Portion selected on the basis of a special set of characteristics. Also used to describe the outcome of a segmentation, such as with cluster analysis.

Segmentation – A type of advanced analysis that divides respondents into groups who are similar to each other and differentiated from other groups.

Semantic Differential Scale – A rating scale that uses opposing terms or statements to anchor end points of a Bipolar Scale. Semantic Differential scales differ from Bipolar Scales in that the end points do not necessarily have to be symmetrical with one another, and the scale itself is based on agreement or association with the opposing terms rather than identifying different levels of the terms themselves.

Sensitivity – The ability of a measurement instrument to discriminate among meaningful differences in the variable being measured.

Sentiment Analysis – The use of natural language processing and text analysis to determine the sentiment expressed in online content, such as social media posts, reviews, and comments. Sentiment analysis gauges public opinion and attitudes.

Significance Level (Alpha) – The threshold used to determine statistical significance. Commonly set at 0.05, the significance level represents the probability of rejecting the null hypothesis when it is true.

Significant Difference – In mathematical terms, difference between tests of two or more variables. The significance difference varies with the confidence level desired.

Simple Random Sampling – A sampling method in which each population member has an equal chance of being selected.

Skewness – A measure of the asymmetry of a probability distribution. Positive skewness indicates a distribution with a longer right tail, while negative skewness indicates a longer left tail.

Skip Pattern – A form of survey logic that uses answers to previous questions to determine whether or not respondents should be asked certain questions.

Snowball Samples – A form of non-probability sampling where respondents provide referrals for additional research respondents.

Snowball Sampling – A non-probability sampling method where existing study participants recruit further participants, often used in hard-to-reach populations.

Social Listening – The process of monitoring and analyzing online conversations, particularly on social media platforms, to gain insights into consumer opinions, sentiment, and trends related to a brand, product, or industry.

Standard Deviation – The square root of variance.

Standard Error – The standard deviation of a distribution of sample means; the square root of the variance of the sampling distribution.

Standard Industrial Classification (SIC) System – A uniform numbering system developed by the US Government for classifying industrial establishments according to their economic activities.

Statistic – Any of several characteristics of a sample.

Statistical Control – Adjusting for the effects of confounded variables by statistically adjusting the value of the dependent variable for each treatment condition.

Structural Equation Modeling (SEM) – A statistical technique that combines factor analysis and multiple regression to analyze the structural relationships between measured variables and latent constructs. SEM is often used in social sciences and psychology to model complex relationships.

Stub – A row heading in data tables or tabulations.

Survey Method – A method of data collection, such as telephone or personal interview.

Syndicated Research – Studies in which the sponsoring research company defines the audience to be surveyed and the interval between studies and the questions to be asked. Clients share the same results and costs.

Target Population – The population that is being studied. Ideally, the target population should be fully represented within the sampling frame.

Test Marketing – The introduction of a new product in selected test cities that represent a typical market, so that results of the performance in these markets can be projected on a national basis.

Tests of Significance – Tests for determining whether observed differences in a sample are sufficiently large as to be caused by something other than mere chance.

Text Analysis – The examination of written or spoken language to extract meaningful information and patterns. Text analysis encompasses various techniques, including content analysis, sentiment analysis, and linguistic analysis.

Thematic Analysis – A qualitative research approach that involves identifying, analyzing, and reporting patterns (themes) within data. Researchers categorize and interpret recurring themes to derive insights.

Threats to Internal Validity – Factors that may lead to incorrect conclusions about the causal relationship between the independent and dependent variables in an experiment.

Time Series Analysis – The examination of data collected over time to identify patterns, trends, and seasonality.

Top of Mind Awareness – The very first response to open-ended questions such as brand awareness.

Topline – A brief summary of the preliminary results of the research.

Touchpoint – Any interaction point between a customer and a brand, product, or service. Touchpoints can include website visits, social media interactions, customer support, and more.

Tracking Studies – Monitoring the performance of things like advertisements or brands by regular surveying of the audience.

Trade-Off Approach – A method of collecting data for trade-off analysis in which the respondent is asked to rank each combination of levels of two attributes from most preferred to least preferred.

Transcript – The written account of a focus group or other qualitative interview (such as one-on-one interviews).

Tree Testing – A method used in information architecture research to evaluate the findability and organization of information within a website or app. Participants are given tasks to perform based on a simplified text version of the site structure.

Triads – A focus group conducted with three people.

Type I Error – The error that occurs when a true null hypothesis is incorrectly rejected. Also known as a false positive.

Type II Error – The error that occurs when a false null hypothesis is not rejected. Also known as a false negative.

Unaided Recall – A questioning approach in which the respondent is asked to remember an object of interest without the assistance of clues from the researcher.

Unipolar Scale – A rating scale that captures the presence or absence (e.g. not at all vs. completely) of attitudes or evaluations. Unipolar scales can invoke as few as 3 scale points, and use escalating modifiers (e.g. somewhat, very) to describe values as they deviate further from a baseline level. Midpoint values are not used the same as in a Bipolar Scale and should be avoided other than to identify a halfway point between presence and absence.

Universe – Also known as the population, the universe is the entire group from which respondents are selected.

Unstructured Data – Data that does not have a pre-defined data model or is not organized in a predefined manner, often requiring advanced techniques for analysis.

Usability Test – Test of a website, software, or other product to determine its effectiveness for the user or customer.

Usability Testing – A method of evaluating a product’s user interface and overall user experience by observing real users as they interact with the product. Usability testing helps identify issues and areas for improvement.

Utility – In trade-off analysis, the worth or value of each level of each attribute relative to the other levels.

UX Research (User Experience Research) – The study of users’ behaviors, needs, and preferences to improve the design and usability of products or services. UX research employs methods like usability testing, interviews, and surveys to gather insights.

Validity – The ability of a measurement instrument to measure what it is supposed to measure.

Variability – Differences in the measurement of variables.

Variable – Any characteristic that can be measured on each unit of the population.

Variance – A measure of dispersion based on the degree to which elements of a sample or population differ from the average element.

Verbatim – Transcribing the provided response of a respondent word-for-word.

Virtual Reality (VR) in Research – The use of virtual reality technology to create immersive and simulated environments for research purposes. VR is employed to study consumer reactions, preferences, and behaviors in realistic settings.

Wave – A longitudinal (or “tracking”) study may consist of several waves of interviews.

Web Based Research – A method of qualitative or quantitative research that takes place via the web. For qualitative research, this often occurs in real time and lends itself to geographically dispersed segments of the market that would otherwise be difficult to recruit for a traditional focus group. For quantitative research, questionnaires are written for the Internet and delivered to the respondent through email invitations, pop-up surveys, or banner recruitment.

Weighting – A procedure by which each response in the database is assigned a number according to some specified rule. Probability weighting is a theoretically-based method by which respondents are given greater or less weight based on their probability of inclusion in the sampling scheme. Post hoc weighting is an atheoretical method that attempts to account for various types of bias by weighting the sample to match an external reference on a variety of characteristics.

Within-Subjects Design – An experimental design in which each participant is exposed to all levels of the independent variable. It contrasts with between-subjects designs where different participants experience different conditions.

Z-Score – A standard score that indicates how many standard deviations a data point is from the mean of a distribution. Z-scores are used to assess the relative position of individual data points.

Z-test – A statistical test that is based on the standard, normal distribution.