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key terms

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. Some people also refer to it as Automated Intelligence, referring to the principle behind AI. While human intervention is not needed at the task performance, getting to this stage requires a lot of human programming to make the automation happen.

A test for the differences among the means of several groups. Analysis of variance is a collection of statistical models and their associated estimation procedures used to analyze the differences among several means. ANOVA was developed by the statistician Ronald Fisher. Example: testing the average product satisfaction between different life stages. When only testing the difference between two means (e.g. are men more satisfied than women?), a significance test (or T-test) is performed.

Completely automated telephone interviews that use interactive voice technology and require no human interviewer. Respondents answer the closed-ended questions with their touch-tone telephone.

CHAID is a type of decision tree technique, based upon significance testing. It can be used to create rules to classify future respondents into identified groups using a number of different questions, or to detect interrelationships between different questions. For example, the combination of age and gender helps to further explain the different types of snacks that people consume.

A CRM (customer relationship management) database is a resource containing all client information collected, governed, transformed, and shared across an organization. It includes marketing and sales reporting tools, which are useful for leading sales and marketing campaigns and increasing customer engagement.

CUBE (Consumer & Customer Understanding in Belgium) is a community of like-minded people, who have a passion for consumer and customer understanding, by uniting research agencies with marketing professionals, research buyers, suppliers, consultants, academics, students and research communities worldwide.

Customer experience, also known as CX, is your customers’ holistic perception of their experience with your business or brand. CX is the result of every interaction a customer has with your business, from navigating the website to talking to customer service and receiving the product/service they bought from you. Everything you do impacts your customers’ perception and their decision to keep coming back or not—so a great customer experience is your key to success.

Market research is conducted using a self-service platform, as opposed to partnering with a market research agency or research consultant.

A membership organization for market, social, and opinion researchers that was founded in 1947. The name ESOMAR is an abbreviation of their original name, the European Society for Opinion and Marketing Research, which reflects the original catchment of the organisation.

The Market Research Society (MRS) is the UK professional body for research, insight and analytics. They have 5,000 individual members and over 500 accredited Company Partners in over 50 countries who are committed to delivering outstanding insight.

Net Promoter Score is a widely used customer/consumer experience test that asks a simple question: on a scale of 1-10, how likely are you to recommend this business, brand, product or service to a friend or colleague?

An NPS survey asks the Net Promoter Score question to a specified target population. This allows companies to gauge how well they are doing on the NPS scale with their specific target customer or potential customer.

The P2P or path to purchase is the journey a user takes across channels and campaigns to convert from a prospect into a customer. It can also be called the customer journey

Any testing related to the overall user experience of a product (usually app or software). UX testing tends to be more holistic than usability testing, running qualitative and quantitative studies of each phase of the user journey.

A database of individuals who have agreed to be available for surveys of varying types and topics. Rising rates of refusals and non-response, make it more difficult to recruit for a single survey, therefore sampling from a pool of potentially willing marketing research respondents can be seen as an appropriate way of saving time and money.

A specialised type of individual interview where respondents are interviewed while they shop in a retail store and combines observation with detailed questioning.

An approach that values numerous small experiments over a few large bets, rapid iterations over big-bang campaigns, and responding to change over following a plan.

The hypothesis where some difference or effect is expected (i.e. a difference that cannot occur simply by chance).

A badly constructed question that results in respondents and researchers reading different meanings into what is being asked, resulting in inappropriate or unexpected answers.

Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns towards effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.

An approach taken to analyse qualitative data using codes or comments on the transcripts to categorise the points being made by respondents.

A type of cluster sampling in which the clusters are created on the basis of the geographic location of the population of interest.

Profiling is the process of collecting demographic information to define an audience or population. Researchers may need to conduct surveys of a population to determine if there are enough available survey takers for the demographic or another target they want to run.

An examination and verification of the movement and sale of a product. There are three main types: wholesale audits, which measure product sales from wholesalers to retailers and caterers, retail audits, which measure sales to the final consumer, and home audits, which measure purchases by the final consumer.

Baby boomers are the demographic cohort following the Silent Generation and preceding Generation X. The generation is often defined as people born from 1946 to 1964, during the post–World War II baby boom.

A chart that uses a series of bars that may be positioned horizontally or vertically to represent the values of a variety of items.

Brand awareness is the extent to which consumers are familiar with a brand, the extent to which the brand’s intended perception matches reality, and the extent to which a company’s brand is helping or hurting sales.

Brand equity, in marketing, is the worth of a brand in and of itself — i.e., the social value of a well-known brand name. The owner of a well-known brand name can generate more revenue simply from brand recognition, as consumers perceive the products of well-known brands as better than those of lesser-known brands.

The creation of a Brand Equity measure, and also any Key Driver analysis to determine what drives Brand Equity (e.g. which brand imagery statements are most related to brand equity).

Brand fit measures the fit of a brand’s profile of product qualities with the desirability of these qualities within a segment. For example, if a brand performs well on criteria that are important to a particular segment, then that brand will have a good fit with the segment. A very helpful analysis for optimising brand positioning.

A projective technique presenting a set of competing brand names to respondents and getting them to group them into categories based on certain dimensions such as innovativeness, value for money, service quality and product range.

A projective technique involving respondents imagining a brand as a person and describing their looks, their clothes, their lifestyles, employment, etc.

A technique used for establishing brand and price preferences. Respondents are presented with a set of branded products priced at the lowest possible price point for each of the brands in question. The respondent is asked to select which products they’d choose. The price of the product selected is increased to the next level, and they are then asked again which product they’d choose. This process is repeated until a product reaches its maximum price and is still selected.

A statistical technique to identify how much one set of independent variables (e.g. Age, Gender, Social Class) drives another set of dependent variables (e.g. Snack Choice). It is particularly useful when there are multiple dependent variables or the variables are categorical (e.g. Age, Gender etc.). It can also be used within segmentation, for example to segment the relationship between attitudes and behaviours.

Research that examines whether one variable causes or determines the value of another variable.

Research involving collecting data from every member of the population of interest.

A virtual space or facility that can be used for online focus groups where individuals are recruited who are willing to discuss a subject online usually using text.

A statistical test that tests the ‘goodness of fit’ between the observed distribution and the expected distribution of a variable.

Choice-based conjoint is a specific type of conjoint analysis where respondents are asked to make a choice between different sets of products/services, to derive the overall appeal of each component part. This is given either as a discrete choice or as a chip-allocation style response (e.g. number out of 10 next purchases allocated to each product/service).

A question that requires the respondent to make a selection from a predefined list of responses. There are two main types of closed questions: dichotomous questions with only two potential responses and multiple response questions with more than two.

Closed-ended questions are those that offer a limited selection of answers to choose from, such as a single or multiple-selection question, matrix, or scaling question type.

Cluster analysis is the statistical term for the creation of segments – the process of dividing markets into groups that are similar to each other, but different to the other groups.

A probability sampling approach in which clusters of population units are selected at random and then all (one-stage cluster sampling) or some (two-stage cluster sampling) of the units in the chosen clusters are studied.

The procedures involved in translating responses into a form that is ready for analysis. Normally involves the assigning of numerical codes to responses.

Competitive analysis testing helps you better understand how your potential customers are discovering your competitor’s product, feature preferences, user behaviour and more.

The rate at which surveys are completed as compared to the number of surveys started by respondents. To calculate the completion rate, divide the number of completes by the number of starts.

A type of stimulus material that uses a set of boards to illustrate the different product, advertising or pack designs.

The process of testing a big idea, concept testing allows you to run ideas past a sample of your target market before producing them. These ideas can be new logos, new product ideas, new ad campaign ideas and more.

A statistical technique that provides a quantitative measure of the relative importance of one attribute over another. It is frequently used to determine what features a new product or service should have and also how products should be priced. An abbreviation of “consider jointly”, Conjoint Analysis is a powerful statistical technique to understand what combination of a limited number of attributes or features is most influential in the consumer’s decision-making process.

An analysis of the underlying theories and past research supports the inclusion of the various items in the scale. It is most commonly considered in two forms, convergent validity and discriminant validity.

Valuable information on the preferences, opinions, habits and emotions of your most valuable customers. Consumer insights usually encompass insights related to a product or service.

A technique used to understand which consumers to target and service with distinct marketing propositions, or to tailor brands, products, pricing, communication to specific groups and make more effective use of marketing resources.

The analysis of any form of communication, whether it is advertisements, newspaper articles, television programmes or taped conversations. Frequently used for the analysis of qualitative research data.

Software used for qualitative research basically counts the number of times that pre-specified words or phrases appear in the text.

A subjective yet systematic assessment as to how well a rating scale measures a topic of interest. For example, a group of subject experts may be asked to comment on the extent to which all of the key dimensions of a topic have been included.

A research approach that involves observing participants in a controlled setting.

Survey participants can be split into two groups–an experimental group, exposed to a product or service, and a control group that is neutral. A common example is ad effectiveness testing, where researchers can track a respondent’s exposure to an ad through cookies. They then split those who have viewed the ad and those who have not into separate groups, asking the same questions to see how responses differ.

A non-probability sampling procedure in which a researcher’s convenience forms the basis for selecting the potential respondents (i.e. the researcher approaches the most accessible members of the population of interest).

A measure of the extent to which the results from a rating scale correlate with those from other scales or measures of the same topic/construct.

Text files placed on a user’s computer by web retailers in order to identify the user when he or she next visits the website.

A statistical approach to examine the relationship between two variables. Uses an index to describe the strength of a relationship.

The price you pay per completed survey. This calculation is based on certain factors of your survey, including the number of screening questions, quotas, demographic/geographic filtering and more.

A managerial tool used for scheduling a research project. It is a network approach that involves dividing the research project into its various components and estimating the time required to complete each component activity.

A statistical test used to measure the split-half reliability of a summated rating scale. Also known as coefficient alpha.

A feature of your survey platform that presents data in a table with rows and columns, designed to help researchers observe two or more variables at the same time. Crosstabs are useful when you want to divide your respondents into subgroups to see how a dependent variable changes the results.

A totality of cognitive, affective, sensory, and behavioural consumer responses during all stages of the consumption process including pre-purchase, consumption, and post-purchase stages.

A marketing approach designed around customer needs and interests. It is about prioritizing customers over any other factor, using a blend of intuition, common sense, and solid data about customer behaviour.

Any information collected by your survey, along with any outside information collected, observed, generated or created in service of your research goals.

Removing unqualified, biased or incomplete responses from a survey. This process improves the data quality and protects against survey bias.

An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.

Data visualization is an interdisciplinary field that deals with the graphic representation of data. It is a particularly efficient way of communicating when the data is numerous as for example a time series.

When a respondent begins a survey and doesn’t complete it. These are also called Starts. Drop-offs are not counted as completes and, therefore, you will not be charged for them.

In digital marketing and technology, engagement often refers to metrics surrounding the use of platforms, content features or apps (think clicks, time on page, etc). In market research, engagement refers to how users interact with your survey.

Research that involves meeting respondents face-to-face and interviewing them using a paper-based questionnaire, a laptop computer or an electronic notepad.

A statistical technique to examine the similarities between items in order to identify a more concise summary of themes. For example, from a list of 20 statements on car imagery, we may identify a factor in reliability, design, performance, environment and image.

A study designed to determine the likely success of a project, product or service. There are many factors that go into a feasibility study, including existing competitors, production limitations, timing, estimated pricing and more. Brands or researchers may conduct feasibility studies to determine the market interest in a new product or service, or even to help determine the feasibility of a future research project.

A distribution of the survey questionnaire.

Generation Alpha (or Gen Alpha for short) is the demographic cohort succeeding Generation Z. Researchers, and popular media use the early 2010s as starting birth years and the mid-2020s as ending birth years. Named after the first letter in the Greek alphabet, Generation Alpha is the first to be born entirely in the 21st century. Most members of Generation Alpha are the children of Millennials.

Generation X, a term typically used to describe the generation of Americans born between 1965 and 1980, although some sources used slightly different ranges. It has sometimes been called the “middle child” generation, as it follows the well-known baby boomer generation and precedes the millennial generation.

Generation Y, Gen Y, or Millennials, are the demographic cohort following generation X and preceding generation Z. Researchers and popular media use the early 1980s as starting birth years and the mid-1990s to early 2000s as ending birth years, with the generation, typically being defined as people born from 1981 to 1996.

Generation Z, colloquially also known as zoomers, is the demographic cohort succeeding Millennials and preceding Generation Alpha. Researchers and popular media use the mid-to-late 1990s as starting birth years and the early 2010s as ending birth years. Most members of Generation Z are children of Generation X. They are born between 1997 and 2012.

Information that is not provided by respondents directly but is gathered from available data.

The incidence rate is the measure of the rate of occurrence or the percentage of people eligible to participate in a survey, based on the targeting criteria selected.

Market insight is the discovery of a relevant, actionable and previously unrealized reality about a target market as the result of deep, subjective data analysis.

The analysis of the relationship between a dependent variable (e.g. brand strength) and one or more independent variables (e.g. brand imagery statements). Its purpose is to determine whether a relationship exists and the strength of the relationship and used to help prioritise what to focus on.

A survey was often undertaken at an exhibition or trade show using touch screen computers to collect information from respondents. Such computers can be programmed to deliver complex surveys supported by full-colour visuals as well as sound and video clips. They can be much cheaper to administer in comparison with the traditional exit survey undertaken by human interviewers.

A type of Key Driver Analysis, Kruskals’ relative importance analysis is an alternative to other techniques such as ordinary regression analysis, which can give misleading results when there is missing data, or when variables are strongly related to each other (which is typical of research data).

A badly constructed question tends to steer respondents toward a particular answer. Also known as a loaded question.

A Likert Scale is typically a 5 or 7 point scale that asks a respondent to express how much they agree or disagree with a statement

Linear regression is used to find out the relative importance of different drivers in order to re-create a dependent variable. For example, the influence of brand imagery items on brand appeal.

Logistic regression is used to find out the relative importance of different drivers in order to re-create a dependent variable when the dependent variable is binary (e.g. Yes/no or Buy/not buy). It is used when the usual linear regression cannot be used and is particularly useful in propensity modelling.

A type of creative testing focused on changes, updates or just current opinions of a brand or product logo. This type of survey may contain questions gauging how appealing, authoritative or on-brand a logo is, or even reveal possible changes to a brand logo and ask potential customers to weigh in.

Researchers performing a longitudinal study will run the same survey many times over short or long periods, in an effort to observe how the opinions, behaviours or habits of the same population change over time.

An application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

The margin of error, also called the confidence interval, is a statistical measurement of the difference between survey results and the population value, expressed as a percentage. Within the survey ecosystem, the margin of error measures the difference between your survey results and how accurately they reflect the views of the overall population.

Studies that focus on the size, scope and potential of a market. Before launching a new product, companies may want to figure out the size of the potential market by broadly surveying interest for that product across key areas and demographic groups. This helps companies determine how large a product rollout may be needed.

Market research refers to the gathering of consumers’ needs, preferences, habits, behaviours and more in an attempt to better understand a company’s potential customers, brand positioning and potential interest in a product or service.

A matrix question asks respondents to make selections for multiple options on a scale. A matrix of multiple selection questions lets you select multiple responses for a single option.

A matrix single selection question will ask you to select one answer per option on a scale. For example, a matrix may contain elements of a hotel, asking respondents to rate elements like the pool or the lobby bar using a variety of potential responses.

Also known as the Advertising ID, this unique ID number is how mobile advertisers are able to cookie users and keep track of engagement with mobile ads.

Multiple selection questions contain a list of options and ask respondents to select all that apply. For example, the question “what kind of music do you like?” will contain a list of music types so respondents can select all types they prefer.

Studies concerning the names of things–new product names, new website URLs, new brand names or even the name of a new film or TV show–naming tests help reveal potential perception issues that can occur.

Natural Language Processing helps machines “read” text (or another input such as speech) by simulating the human ability to understand a natural language such as English, Spanish or Chinese. Natural Language Processing includes both Natural Language Understanding and Natural Language Generation, which simulates the human ability to create natural language text e.g. to summarize information or take part in a dialogue. As a technology, natural language processing has come of age over the past ten years, with products such as Siri, Alexa and Google’s voice search employing NLP to understand and respond to user requests. Sophisticated text mining applications have also been developed in fields as diverse as medical research, risk management, customer care, insurance (fraud detection) and contextual advertising. Today’s natural language processing systems can analyze unlimited amounts of text-based data without fatigue and in a consistent, unbiased manner. They can understand concepts within complex contexts, and decipher ambiguities of language to extract key facts and relationships or provide summaries. Given the huge quantity of unstructured data that is produced every day, from electronic health records (EHRs) to social media posts, this form of automation has become critical to analysing text-based data efficiently.

Non-probability sampling excludes some of the population in your sample, and that exact number can not be calculated – meaning there are limits on how much you can determine about the population from the sample. These methods include convenience sampling, quota sampling, judgement sampling and snowball sampling.

An open-ended question that requires a numeric answer. For example, researchers may ask how much money you’d potentially pay for a product or service.

A technique used to understand needs on different occasions (e.g. having a coffee to wake up in the morning, or having a social coffee with friends after work) in order to help with new product development in repertoire markets, or for brand positioning for clients with multiple brands.

Online panels collect responses either via a fully opt-in structure, including a signup page, or start with some form of digital outreach to potential respondents who have agreed to take surveys in advance. Panellists are then recruited to participate in specific surveys, for example via email invitation to the page of the panel provider.

Studies that provide consumer feedback on product packaging. Would you be more or less likely to buy a product with new packaging? Does the packaging effectively convey what is inside? How do your potential customers feel when they look at your new packaging?

A collection of potential respondents who have agreed to take a survey in advance of the survey’s fielding process. These respondents are typically promised some type of incentive in exchange for joining the panel, which would effectively pay them for their time.

Piping allows researchers to personalize surveys by ‘piping’ an answer from a previous question into a later question. For example, you can ask a respondent their name or occupation on the first question, and then add that name or occupation to future questions to make the questions more personalized.

The population is the total group of respondents who you attempted to survey. If they complete your survey, they become part of your sample.

Price elasticity measures how sensitive the demand for your product is to changes in price. For example, price elasticity measures how many customers will continue to purchase your product or service if you increase the price.   Products or services can fall into one of three buckets: Price elastic —price changes significantly affect the demand for a product or service (i.e. price elasticity >> 1). Price inelastic —price changes have little impact on the demand for a product or service (i.e. price elasticity << 1). Price unit elastic — a price change is proportional to the change in demand and moves at the same rate (i.e. price elasticity = 1).

Price Sensitivity Measurement (PSM) is a technique used to understand price preferences.

Primary data refers to the data collected by researchers directly from respondents using surveys, interviews or direct observation.

Primary research refers to the methodology of using only data collected directly from respondents, rather than relying on data collected during previous research or from some external source (government agencies, employment records, etc).

Probability sampling refers to a randomized method of respondent selection. In order to utilize probability sampling, researchers have to have a method that ensures every member of the population has an equal chance of being chosen to participate (like picking names out of a hat).

A degree to which a particular product meets the demands of the market it is in. Have you created the minimum viable product for your market, that solves a problem or need that exists? Product (or market) fit studies aim to survey early adopters or potential customers to see if the product meets previously identified criteria for satisfaction within a market.

A final test of a product, product testing gives users access to a prototype and seeks to identify opinions–positive or negative–of a product before it goes to market.

Unlike demographics, which explain who your respondents are, psychographics seeks to explain why they do what they do. While any quantitative study, group of screening questions or even secondary location data can net your demographic data, psychographics is more often culled from qualitative studies. For example, is your respondent concerned with health and appearance? Do they enjoy socializing or are they more introverted? You can get answers to these questions from scale-based quantitative questions, but open-ended questioning or interviewing often provides more depth to these groupings. Depending on how you plan to use them, you should consider this before creating your survey.

The public opinion refers to the opinions of a majority of people in a certain population. Polling public opinion requires taking as broad of a study as possible and asking direct, quantifiable questions about specific issues.

The qualification rate is the estimated percentage of people you expect to qualify for your survey based on your targeting criteria, screening questions and other filters.

Qualitative survey questions aim to gather data that is not easily quantified such as attitudes, habits, and challenges. They are often used in an interview-style setting to observe behavioural cues that may help direct the questions.

Quantitative research is about collecting information that can be expressed numerically. Quantitative research is usually conducted through surveys or web analytics, often including large volumes of people to ensure trends are statistically representative.

Your questionnaire is the list of questions you plan to ask your respondents. There are many different types of survey questions you can ask, depending on your survey goals. Questionnaires are effective because they can be designed to suit any product or company and can elicit any information that the customer is willing to give. On the other hand, sometimes questionnaires have a low completion rate so it is essential that they are given to the right people and take a short amount of time to complete.

Quotas are limits you can set for the number of responses your survey collects from a particular group. They can be set across the entire survey or on a given question or segment. Unlike weighting, which ties your quotas to existing data sets like a national or local census, quotas can be chosen by the researcher to match the goals of your survey. If, for example, you’d like to survey a population that is 75% female, you can do that.

A respondent is a person who meets your targeting criteria and completes your survey in full.

The response rate is the percentage of the total targeted population who responded to your survey.

Refers to the respondents who matched your targeting criteria and completed your survey.

The number of completes your survey receives.

Screening questions help researchers ensure they are getting the exact sample they want using filtering that falls outside of available targeting criteria. For example, if you only want to include people in your survey who have seen the movie Pulp Fiction, your screening question would ask potential respondents if they have seen the film, and screen them based on their answers.

Secondary data refers to data that has been collected outside of the bounds of a researcher’s survey, but which the researcher can use to add context.

Secondary research refers to the summary or synthesis of existing research toward a new research goal. In this practice, previous primary research projects are used as sources.

Segmentation studies seek to separate larger audiences into smaller segments based on similar tastes, interests, perceptions and other secondary factors like education, employment or lifestyle.

Social media monitoring involves using a tool or range of tools to listen to what is being said across the internet, with a particular focus on social media and Web 2.0 sites, as well as news sites and the like. It is important to note that despite the name, social media monitoring tools are not solely focused on social websites – although results can be filtered on these only if required.

A measurement to quantify whether a result is just due to chance or due to some significant factor. Getting a survey that is not statistically significant comes from sampling error. That’s when your sample doesn’t accurately reflect the population of your survey and, therefore, may cause skewed results. There are two things to contend with when trying to remove sampling error: sample size and variation. The larger the sample size, the less chance there is in the result which reduces sampling error and increases significance. Controlling for the variability of your sample also can impact sampling error–the more variability in your sample, the more prone to error the study will be.

Structural Equation Modelling (SEM) is a statistical technique for testing and estimating causal relationships, using a combination of statistical data and qualitative causal assumptions. Factor analysis, path analysis and regression all represent techniques used within SEM, which also allows the construction of variables that are not measured directly. As an example, it can be used to model and understand the relationship between different aspects of customer satisfaction and how these explain customer loyalty.

In its most basic form, a survey refers to the questionnaire – delivered either in person or online – that a researcher administers in the service of a research study.

Targeting refers to the criteria you select to screen potential survey respondents. Once targeting is selected, a population is created and your survey is delivered.

Text mining (also referred to as text analytics) is an artificial intelligence (AI) technology that uses natural language processing (NLP) to transform the free (unstructured) text in documents and databases into normalized, structured data suitable for analysis or to drive machine learning (ML) algorithms.

Tracking studies use the same questionnaire, delivered over time, to track brand awareness, monitor customer satisfaction, study consumer interest in new products or services, analyze the effectiveness of advertising creative and more. Tracking studies may be delivered to the same populations (to gauge how perceptions of the same group change as time goes on) or different populations to view time as just one factor impacting shifting perceptions.

Usability testing aims to test user experience changes on real users to determine if the experience has been positively or negatively impacted by any changes. Unlike more traditional product testing, usability testing usually focuses more on design changes and more commonly relates to app or software development.

Online material such as comments, profiles photographs produced by end-users.

Value-based pricing is a method of price setting where the price is based on how much a product or service is worth for a customer, i.e. how much value the product benefits offer, instead of price-setting based on the cost of the product, i.e. the cost-plus method.

The bringing together of a group of individuals using a video link and telecommunications. Can potentially be used for group discussions, particularly where the respondents are located in various parts of the world.

A projective technique that involves asking respondents what brands or products they associate with specific words. In addition to the direct outputs regarding brand imagery, it is also a very useful technique for building rapport within a group discussion and getting everybody contributing and involved.

A visual depiction of words used by respondents in qualitative research or the content appearing on social network sites or publications. The font size of the words is determined by the number of times a word has been used. The more that a topic or word is talked about, the bigger it is.