Core Market Research & Strategy Terms
Addressable Market: The total market opportunity available for a product or service, often segmented by geography, demographics, or behavioural characteristics.
Affinity Analysis: Statistical technique identifying relationships between different variables, commonly used to understand customer preferences and content consumption patterns.
Attribution Modelling: Framework for assigning credit to different touchpoints in the customer journey – paid, owned, earned – crucial for understanding content effectiveness across channels (conversion, retention, revenue).
Audience Segmentation: Process of dividing target markets into distinct groups based on shared characteristics, behaviours, or geographic locations.
Behavioural Analytics: Study of user actions and patterns to understand preferences, predict future behaviour, and optimise content strategy.
Brand Awareness: Measure of how familiar consumers are with a brand, tracked through surveys, search volume, and social media mentions.
Brand Equity: Commercial value derived from consumer perception and recognition of a brand name, measurable through premium pricing and loyalty metrics and reflected in pricing power, reduced acquisition cost, and resilience during crises.
Brand Health: Comprehensive assessment of a brand’s performance across multiple dimensions including awareness, perception, preference, and loyalty.
Brand Positioning: Strategy defining how a brand differentiates itself in the market and occupies a distinct place in consumers’ minds.
Brand Sentiment: Qualitative measure of public opinion towards a brand, analysed through social media monitoring, reviews, and survey data.
Brand Tracking: Ongoing measurement of brand performance metrics over time to monitor changes in awareness, perception, and market position.
Churn Rate: Percentage of customers who discontinue purchasing, subscribing or engaging with a brand during a specified period.
Competitive Intelligence: Systematic collection and analysis of information about competitors’ strategies, strengths, and weaknesses.
Consumer Journey Mapping: Visual representation of the customer experience across all touchpoints, from awareness to conversion and retention.
Customer Acquisition Cost (CAC): Total cost of acquiring a new customer, including marketing, sales, and content creation expenses.
Customer Lifetime Value (CLV): Predicted revenue a customer will generate throughout their relationship with a business.
Customer Retention Rate: Percentage of customers who continue using a service over a given period, indicating customer satisfaction and loyalty.
Customer Satisfaction (CSAT): Metric measuring how satisfied customers are with a company’s products, services, or experiences.
Cohort Analysis: Method of analysing user behaviour by grouping users based on shared characteristics or experiences over time.
Conversion Funnel: Model representing the customer journey from initial awareness to final purchase or desired action.
Cross-Tabulation: Statistical technique examining relationships between two or more categorical variables in survey data.
Data Mining: Process of discovering patterns and relationships in large datasets to extract actionable insights.
Data Quality Framework – e.g., ESOMAR / GRBN 2023 standards.
Demographic Segmentation: Market division based on age, gender, income, education, occupation, and other statistical characteristics.
Design Effect (DEFF) – inflation factor on variance due to complex sample design.
Digital Footprint: Trail of data created by online activities, .Trace of identifiers, behaviours and content that individuals leave online – while valuable for understanding user behaviour and preferences ethical use requires consent and compliance with privacy laws such as the Australian Privacy Principles (APPs).
Fieldwork – umbrella term for data-collection execution (CATI, CAWI, F2F).
Funnel Analysis: Examination of user progression through defined steps towards a goal, identifying drop-off points and optimisation opportunities.
Geographic Segmentation: Market division based on location, including country, region, city, climate, and population density.
Incidence Rate (IR) – proportion of screened respondents who qualify.
Key Performance Indicator (KPI): Measurable values demonstrating how effectively objectives are being achieved.
Lifetime Value to Customer Acquisition Cost (LTV:CAC): Ratio comparing long-term customer value to acquisition cost, crucial for sustainable growth.
Market Penetration: Percentage of target market that has purchased or engaged with a product or service.
Market Research: Systematic gathering, recording, and analysis of data about customers, competitors, and the market.
Market Segmentation: Process of dividing a broad market into distinct groups of consumers with similar needs or characteristics.
Market Share: Company’s sales as percentage of total industry sales, measurable by revenue, units, or other metrics.
Market Sizing: Process of determining the total addressable market for a product or service.
Net Promoter Score (NPS): Customer loyalty metric based on likelihood to recommend a company to others.
Non-Response Bias – systematic differences between respondents and non-respondents.
Predictive Analytics: Use of statistical techniques and machine learning to forecast future trends and behaviours.
Price Sensitivity Analysis: Research method determining how price changes affect demand for products or services.
Product-Market Fit: Degree to which a product satisfies strong market demand and meets customer needs.
Psychographic Segmentation: Market division based on personality traits, values, interests, and lifestyle characteristics.
Purchase Intent: Measure of consumers’ likelihood to buy a product or service within a specific timeframe.
Return on Investment (ROI): Financial metric measuring efficiency of investment, calculated as gain minus cost divided by cost.
Share of Voice: Brand’s percentage of total market conversation or advertising compared to competitors.
Share of Wallet: Percentage of a customer’s total spending in a category that goes to a particular brand.
SWOT Analysis: Strategic planning tool examining Strengths, Weaknesses, Opportunities, and Threats.
Target Market: Specific group of consumers a business aims to reach with its products and marketing efforts.
Total Addressable Market (TAM): Total revenue opportunity available for a product or service.
Unaided Awareness: Measure of brand recognition without prompting or assistance from researchers.
Voice of Customer (VOC): Process of capturing customer feedback, preferences, and expectations through various research methods.
Weighting – adjustment factors applied post-field to correct sampling bias.

Research Methods & Methodologies
A/B Testing: Statistical method comparing two versions of content, web pages, or campaigns to determine which performs better for specific metrics.
Action Research: Participatory research method where researchers work with participants to solve real-world problems.
Aided Awareness: Brand recognition measured when consumers are shown brand names, logos, or other prompts.
Anthropological Research: Study of human behaviour and culture through observation and participation in natural settings.
Automotive Research: Specialised research focusing on vehicle preferences, buying behaviour, and transportation needs.
Behavioural Economics Research: Study combining psychology and economics to understand decision-making processes.
Biometric Research: Use of physiological measurements like eye tracking, facial coding, and EEG to understand consumer responses.
Causal Research: Research design aimed at establishing cause-and-effect relationships between variables.
Case Study: In-depth investigation of a single individual, group, event, or phenomenon.
Comparative Research: Method comparing different groups, markets, or conditions to identify similarities and differences.
Concept Testing: Research method evaluating consumer response to new product or service ideas before development.
Conjoint Analysis: Statistical technique used to understand how consumers value different attributes of products or services.
Content Analysis: Systematic analysis of communication content to identify patterns, themes, and meanings.
Copy Testing: Research method evaluating advertising effectiveness before launch.
Cross-Cultural Research: Study comparing behaviours, attitudes, and preferences across different cultures.
Cross-Sectional Study: Research design collecting data from different subjects at a single point in time.
Customer Journey Research: Method mapping and analysing the complete customer experience across all touchpoints.
Delphi Method – iterative expert surveys for consensus.
Depth Interview: One-on-one qualitative interview exploring topics in detail with individual respondents.
Descriptive Research: Research design aimed at describing characteristics of a population or phenomenon.
Design Research: User-centred research method focusing on understanding user needs for product development.
Diary-Based Ethnography – hybrid qual/quant via mobile diaries.
Diary Studies: Research method where participants record their experiences, behaviours, or thoughts over time.
Digital Ethnography: Qualitative research method studying online communities and digital behaviours.
Discrete Choice Modelling: Statistical technique analysing how consumers make choices among alternatives.
Ethnography: Qualitative research method involving the systematic study of people and cultures through observation and participation.
Exit Interview: Research method collecting feedback from departing customers or employees.
Experimental Research: Research design manipulating variables to establish cause-and-effect relationships.
Exploratory Research: Initial research conducted to clarify and define problems or opportunities.
Eye Tracking: Biometric research method measuring where and how long people look at visual stimuli.
Facial Coding: Research technique analysing facial expressions to understand emotional responses.
Field Experiment: Research conducted in natural, real-world settings rather than controlled laboratory environments.
Focus Group: Qualitative research method involving guided discussions with small groups of target audience members.
Forced Exposure: Lab‑based technique where participants are deliberately shown an advertisement or stimulus to measure unaided reactions.
Galvanic Skin Response (GSR): Biometric measurement of skin conductance to assess emotional arousal.
Grounded Theory: Qualitative research method developing theories based on systematic data collection and analysis.
Hall Test: Research method where respondents are invited to a central location to evaluate products or concepts.
Home Use Test (HUT): Research method where consumers test products in their natural usage environment.
Implicit Association Test (IAT): Method measuring unconscious associations between concepts and attributes.
In-Context Research: Method studying behaviours and experiences in their natural environment.
In-Depth Interview (IDI): One-on-one qualitative interview exploring topics thoroughly with individual participants.
Intercept Survey: Data collection method where researchers approach potential respondents in specific locations.
Laddering: Qualitative research technique exploring the connections between product attributes and personal values.
Longitudinal Study: Research design that collects data from the same subjects over extended periods to track changes.
Market Mix Modelling: Statistical analysis technique measuring the impact of various marketing activities on sales.
Maximum Difference Scaling (MaxDiff): Research technique identifying the most and least important items from a set of options.
Message Testing: Research method evaluating the effectiveness of marketing communications before launch.
Mixed Methods Research: Approach combining quantitative and qualitative research methods for comprehensive insights.
Mobile Ethnography: participant-led video captures in-situ.
Monadic Testing: Research design where each respondent evaluates only one product or concept.
Mystery Shopping: Research method where trained evaluators pose as customers to assess service quality.
Narrative Research: Qualitative method analysing stories and personal accounts to understand experiences.
Neuromarketing: Research approach using neuroscience techniques to understand consumer behaviour and decision-making.
Observation Research: Data collection method involving systematic watching and recording of behaviours or phenomena.
Online Bulletin Board: Qualitative research method using private online forums for extended discussions.
Online Community Research: Method studying behaviours and opinions within digital communities.
Paired Comparison: Research technique comparing items two at a time to establish preferences or rankings.
Panel Study: Longitudinal research design following the same group of participants over multiple time periods.
Participatory Research: Method involving participants as co-researchers in the study design and analysis.
Phenomenological Research: Qualitative approach focusing on understanding lived experiences and their meanings.
Pilot Study: Small-scale preliminary study conducted to test research methods before full-scale research.
Pop-up Research: Quick, informal research method collecting immediate feedback in real-time.
Pre-Post Testing: Research design measuring changes by comparing conditions before and after an intervention.
Projective Techniques: Qualitative research methods using ambiguous stimuli to uncover underlying attitudes.
Protocol Analysis: Research method where participants verbalise their thought processes while completing tasks.
Psychophysiological Research: Study using physiological measurements to understand psychological responses.
Qualitative Research: Exploratory research method focusing on understanding motivations, opinions, and attitudes.
Quantitative Research: Systematic investigation using statistical techniques to analyse numerical data.
Quasi-Experimental Design: Research method comparing groups without random assignment.
Retail Audit: Research method tracking product sales and inventory at retail locations.
River Sampling – real-time recruitment from web traffic.
Scenario Planning: Strategic research method exploring possible future situations and their implications.
Semiotics: Study of signs and symbols to understand cultural meanings and brand communication.
Sentiment Analysis: Computational study of opinions, sentiments, and emotions expressed in text data.
Sequential Monadic Testing: Research design where respondents evaluate multiple products in sequence.
Sequential Overlap Sampling – modern online panel refresh technique.
Shopper Research: Study of consumer behaviour in retail environments and purchasing decisions.
Simulated Test Market: Research method using models to predict market performance without actual launch.
Store Audit: Research method tracking product availability, pricing, and merchandising at retail locations.
Test Market: Research method launching products in limited geographic areas before full rollout.
Thematic Analysis: Qualitative research method identifying and analysing patterns of meaning in data.
Think-Aloud Protocol: Research technique where participants verbalise their thoughts while completing tasks.
Tracking Study: Ongoing research measuring changes in key metrics over time.
Triangulation: Research strategy using multiple methods or sources to validate findings.
Usage and Attitude (U&A) Study: Research examining how consumers use products and their attitudes towards them.
Van Westendorp Price Sensitivity Metre: Research technique determining optimal pricing by measuring price acceptance.
Video Ethnography: Research method using video recordings to study behaviours in natural settings.

Data Collection Methods & Techniques
API (Application Programming Interface): Set of protocols enabling data exchange between different software systems.
Automated Data Collection: Process of gathering information using software and algorithms without manual intervention.
Balanced Scorecard: Strategic performance‑management framework translating organisational vision into a balanced set of financial and non‑financial KPIs.
Big Data: Extremely large datasets requiring specialised tools and techniques for analysis.
Biometric Data Collection: Gathering physiological and behavioural characteristics for identification and analysis.
Bootstrapping: Statistical method of resampling data to estimate population parameters.
Bot/Speeding Detection – automated QA checks in online surveys.
CAPI (Computer-Assisted Personal Interviewing): Face-to-face interview method using computers or tablets.
CATI (Computer-Assisted Telephone Interviewing): Telephone survey system using computer software.
CAWI (Computer-Assisted Web Interviewing): Online survey method through web browsers.
Census: Complete enumeration of a population, collecting data from every member.
Chatbot Research: Data collection method using automated conversational interfaces.
Cookie Tracking: Method collecting user behaviour data through small files stored on devices.
Crowdsourcing: Data collection method leveraging large groups of people to gather information.
Data Aggregation: Process of gathering and combining data from multiple sources.
Data Fusion: Technique combining data from different sources to create comprehensive datasets.
Data Harvesting: Automated collection of data from various digital sources.
Data Lake: Storage repository holding vast amounts of raw data in its native format.
Data Mart: Subset of a data warehouse focused on specific business areas.
Data Mining: Process of discovering patterns and relationships in large datasets.
Data Streaming: Real-time processing of continuous data flows.
Data Warehouse: Centralised repository storing integrated data from multiple sources.
Deduplication (Digital Fingerprinting) – removing repeat respondents across panels.
Digital Diary: Electronic method for participants to record experiences and behaviours.
eConsent – digital informed-consent capture (GDPR/APP compliant).
EEG (Electroencephalography): Biometric technique measuring brain electrical activity.
ETL (Extract, Transform, Load): Process of extracting, transforming, and loading data.
fMRI (Functional Magnetic Resonance Imaging): Neuroimaging technique measuring brain activity.
Gamification: Using game elements in research to increase engagement and data quality.
GPS Tracking: Location-based data collection using Global Positioning System technology.
Hyperlocal Data: Extremely location-specific information for small geographic areas.
IoT (Internet of Things): Network of interconnected devices collecting and exchanging data.
Machine Learning: AI subset enabling systems to learn from data without explicit programming.
Mobile Data Collection: Gathering information through smartphones and mobile applications.
Natural Language Processing (NLP): AI technology for understanding and processing human language.
Online Panel: Pre-recruited group participating in multiple research studies over time.
PAPI (Paper-and-Pencil Interviewing) – still used in remote areas.
Passive Data Collection: Gathering information without active participant involvement.
Raking (Iterative Proportional Fitting) – see also Weighting.
Real-Time Data Collection: Immediate gathering and processing of information as it occurs.
Sensor Data: Information collected from devices measuring environmental conditions or behaviours.
Social Media Mining: Extracting insights from social media platforms and user-generated content.
Syndicated Research: Standardised research studies sold to multiple clients.
Synthetic Respondents / LLM Simulations – emerging method for pilot testing.
Telematics: Technology combining telecommunications and informatics for data collection.
Transactional Data: Information captured from business transactions and customer interactions.
Unstructured Data: Information without predefined format, such as text, images, or audio.
Wearable Technology: Body-worn devices collecting biometric and behavioural data.
Web Analytics: Collection and analysis of website usage data.
Web Scraping: Automated extraction of data from websites.
WiFi Analytics: Data collection method tracking device connections and movements.

Sampling Methods & Techniques
Accidental Sampling: Non-probability sampling method selecting readily available subjects.
Adaptive Sampling: Method adjusting sample selection based on previously collected data.
Address-Based Sampling (ABS) – Australia Post PAF or G-NAF frame usage.
Area Sampling: Probability sampling method dividing geographic areas into clusters.
Cluster Sampling: Probability method selecting entire groups rather than individuals.
Convenience Sampling: Non-probability method selecting easily accessible participants.
Disproportionate Sampling: Sampling method where subgroups are not proportionally represented.
Double Sampling: Two-stage sampling method using initial sample to inform second sample.
Dual-Frame Sampling – blending landline + mobile or phone + online frames.
Elimination Sampling: Method progressively removing cases that don’t meet criteria.
Extreme Case Sampling: Purposive sampling focusing on unusual or outlier cases.
Homogeneous Sampling: Purposive sampling selecting participants with similar characteristics.
Incidental Quota / Soft Quota – flexible quotas within hard sample caps.
Judgement Sampling: Non-probability method where researchers select participants based on expertise.
Maximum Variation Sampling: Purposive sampling capturing wide range of perspectives.
Multi-Stage Sampling: Complex probability sampling involving multiple phases.
Network Sampling: Method using social networks to identify and recruit participants.
Nonprobability Sampling: Sampling method where not all population members have equal selection chance.
Optimal Allocation: Sampling strategy minimising variance for fixed sample size.
Oversampling: Deliberately selecting more participants from specific subgroups.
Probability Sampling: Method where every population member has known selection probability.
Proportional Sampling: Method maintaining population proportions in the sample.
Purposive Sampling: Non-probability method selecting participants based on specific criteria.
Quota Sampling: Non-probability method ensuring specific characteristics are represented.
Random Sampling: Probability method giving each population member equal selection chance.
Random-Digit Dialling (RDD) – number generation for CATI.
Replacement Sampling: Method where selected units can be chosen again.
Representative Sampling: Technique ensuring sample accurately reflects population characteristics.
Respondent-Driven Sampling: Method where participants recruit other participants.
Sample Frame: List or database from which a sample is drawn.
Sampling Error: Difference between sample statistics and true population parameters.
Sampling Fraction: Proportion of the population included in the sample.
Simple Random Sampling: Basic probability method with equal selection probability.
Snowball Sampling: Non-probability method where participants recruit others from their networks.
Stratified Sampling: Probability method dividing population into subgroups before sampling.
Systematic Sampling: Method selecting every nth member from a population list.
Theoretical Sampling: Sampling method used in grounded theory research.
Time Sampling: Method collecting data at specific time intervals.
Typical Case Sampling: Purposive sampling selecting average or normal cases.
Venue-Based Sampling: Method recruiting participants at specific locations.
Volunteer Sampling: Non-probability method relying on self-selected participants.
Weighted Sampling: Technique giving different importance to different sample segments.

Survey Design & Questionnaire Development
Acquiescence Bias: Tendency to agree with statements regardless of actual opinions.
Adaptive Questionnaire (Responsive Surveying) – auto-adjusts based on early answers.
Aided Recall: Memory test providing cues or prompts to help respondents remember.
Anchor Effect: Bias where initial information influences subsequent responses.
Attention Checks / Trap Questions – validity screens.
Balanced Scale: Rating scale with equal numbers of positive and negative response options.
Battery Questions: Series of questions using the same response format.
Bipolar Scale: Rating scale with opposite endpoints (e.g., satisfied to dissatisfied).
Branching: Survey logic directing respondents to different questions based on answers.
Central Tendency Bias: Tendency to avoid extreme response options.
Closed-Ended Questions: Questions providing predetermined response options.
Cognitive Interviewing: Method testing survey questions by understanding respondent interpretation.
Constant Sum Scale: Rating method where respondents allocate points across options.
Contingency Questions: Questions asked only if specific conditions are met.
Double-Barrelled Questions: Problematic questions asking about two different issues simultaneously.
Extremity Bias: Tendency to select extreme response options.
Filter Questions: Questions determining whether respondents should answer subsequent questions.
Forced Choice: Questions requiring selection without neutral options.
Funnelling: Question sequence moving from general to specific topics.
Halo Effect: Bias where one positive trait influences perception of other traits.
Hawthorne Effect: Behaviour change resulting from awareness of being observed.
Implicit Association Test (IAT): Method measuring unconscious associations between concepts.
Incognito (Red-Herring) Questions – detect straight-liners or A.I. respondents.
Leading Questions: Questions that suggest or encourage particular responses.
Likert Scale: Psychometric scale measuring attitudes using ordered response categories.
Loaded Questions: Questions containing assumptions or emotional language.
Matrix Questions: Multiple items presented with the same response scale in grid format.
Multiple Choice Questions: Questions offering several predetermined response options.
Nominal Scale: Measurement scale for categorical data without order.
Open-Ended Questions: Questions allowing respondents to answer in their own words.
Ordinal Scale: Measurement scale for ranked or ordered categorical data.
Piping: Survey technique inserting previous responses into subsequent questions.
Prestige Bias: Tendency to give socially desirable responses.
Question Bank Re-Use – ISO-20252 documentation requirement.
Question Order Effects: Influence of question sequence on responses.
Ranking Questions: Questions asking respondents to order items by preference or importance.
Ratio Scale: Measurement scale with true zero point and equal intervals.
Recall Bias: Systematic error in remembering past events or experiences.
Recency Effect: Tendency to favour recently presented information.
Response Bias: Systematic tendency to respond in ways that don’t reflect true opinions.
Response Rate: Percentage of invited participants who complete the survey.
Satisficing: Tendency to provide adequate rather than optimal responses.
Scale Reliability: Consistency of measurement across multiple items.
Scale Validity: Extent to which a scale measures what it claims to measure.
Screening Questions: Initial questions determining participant eligibility.
Semantic Differential Scale: Rating scale using bipolar adjectives.
Skip Logic: Programming directing respondents to appropriate questions based on answers.
Social Desirability Bias: Tendency to give responses perceived as socially acceptable.
Straight-Lining: Response pattern where participants select the same option repeatedly.
Survey Fatigue: Decreased response quality due to survey length or frequency.
Unipolar Scale: Rating scale with single direction (e.g., none to extremely).
Vignette Questions: Scenarios presented to respondents for evaluation or judgement.
Yes/No Questions: Binary questions with only two response options.

Statistical Analysis & Techniques
Alpha Level: Probability threshold for determining statistical significance.
Analysis of Covariance (ANCOVA): Statistical method controlling for confounding variables.
Analysis of Variance (ANOVA): Technique comparing means across multiple groups.
Autocorrelation: Statistical relationship between a variable and its lagged values.
Bartlett’s Test: Statistical test for equality of variances across groups.
Bayesian Analysis: Statistical approach updating probability estimates with new data.
Beta Coefficient: Measure of relationship strength between variables in regression.
Binomial Test: Statistical test for proportions in binary data.
Bonferroni Correction: Adjustment for multiple comparisons to control Type I error.
Canonical Correlation: Analysis examining relationships between multiple variable sets.
Chi-Square Test: Statistical test for association between categorical variables.
Cluster Analysis: Statistical method grouping similar observations.
Cochran’s Q Test: Statistical test for differences in proportions across groups.
Coefficient of Determination (R²): Measure of variance explained by regression model.
Confidence Interval: Range of values likely containing the true population parameter.
Confirmatory Factor Analysis: Statistical method testing predefined factor structures.
Correlation Analysis: Statistical method measuring relationships between variables.
Correspondence Analysis: Technique visualising relationships in contingency tables.
Cronbach’s Alpha: Measure of internal consistency reliability.
Cross-Validation: Method assessing how statistical analysis generalises to independent data.
Design-Based Weighting Variance (Taylor Series) – for complex samples.
Discriminant Analysis: Statistical method predicting group membership.
Effect Size: Measure of practical significance of statistical findings.
Exploratory Factor Analysis: Statistical method identifying underlying factors.
F-Test: Statistical test comparing variances between groups.
Fisher’s Exact Test: Statistical test for association in small samples.
Friedman Test: Non-parametric alternative to repeated measures ANOVA.
Heteroscedasticity: Condition where variance is not constant across observations.
Hierarchical Bayesian (HB) Estimation – common in conjoint/U&A.
Homoscedasticity: Condition where variance is constant across observations.
Hypothesis Testing: Statistical method for making inferences about population parameters.
Independent Samples T-Test: Statistical test comparing means between two groups.
Interaction Effect: Situation where effect of one variable depends on another variable.
Interquartile Range: Measure of variability between 25th and 75th percentiles.
Kruskal-Wallis Test: Non-parametric alternative to one-way ANOVA.
Latent Class Analysis – segment discovery.
Levene’s Test: Statistical test for equality of variances.
Linear Regression: Statistical method modelling relationship between variables.
Logistic Regression: Statistical method for binary or categorical outcome variables.
MANOVA (Multivariate ANOVA): Analysis of variance with multiple dependent variables.
Mann-Whitney U Test: Non-parametric alternative to independent samples t-test.
Margin of Error: Range of values above and below sample statistic.
Mean: Average value of a dataset.
Median: Middle value when data is arranged in order.
Mode: Most frequently occurring value in a dataset.
Multicollinearity: High correlation between independent variables in regression.
Multiple Regression: Statistical method with multiple predictor variables.
Multivariate Analysis: Statistical analysis involving multiple variables simultaneously.
Non-Parametric Tests: Statistical tests not requiring normal distribution assumptions.
Normal Distribution: Bell-shaped probability distribution.
Null Hypothesis: Statement of no effect or no difference being tested.
One-Way ANOVA: Analysis of variance with one independent variable.
Outlier: Data point significantly different from other observations.
P-Value: Probability of observing results if null hypothesis is true.
Paired Samples T-Test: Statistical test comparing means from same subjects.
Parametric Tests: Statistical tests requiring specific distribution assumptions.
Pearson Correlation: Measure of linear relationship between continuous variables.
Percentile: Value below which a percentage of observations fall.
Post-Hoc Tests: Statistical tests following significant ANOVA results.
Power Analysis: Calculation of probability of detecting true effects.
Principal Component Analysis: Technique reducing dimensionality of data.
Propensity Score Matching – balance treatment/control in quasi-experiments.
Quartiles: Values dividing dataset into four equal parts.
Random Forest: Machine learning algorithm using multiple decision trees.
Range: Difference between maximum and minimum values.
Regression Analysis: Statistical method examining relationships between variables.
Reliability: Consistency of measurement across repeated administrations.
Repeated Measures ANOVA: Analysis of variance for multiple measurements from same subjects.
Sampling Distribution: Distribution of sample statistics across multiple samples.
Shapiro-Wilk Test: Statistical test for normality of distribution.
Significance Level: Probability threshold for rejecting null hypothesis.
Skewness: Measure of asymmetry in distribution.
Spearman Correlation: Measure of monotonic relationship between variables.
Standard Deviation: Measure of variability around the mean.
Standard Error: Standard deviation of sampling distribution.
Statistical Power: Probability of detecting true effects when they exist.
Statistical Significance: Determination that observed effects are unlikely due to chance.
T-Test: Statistical test comparing means between groups.
Time Series Analysis: Statistical method analysing data over time.
Trimmed Mean: A statistical measure calculated by removing a percentage of extreme values (outliers) from a dataset and then computing the mean of the remaining values. It provides a more robust measure of central tendency by reducing the impact of extreme values.
Two-Way ANOVA: Analysis of variance with two independent variables.
Type I Error: Incorrectly rejecting a true null hypothesis.
Type II Error: Failing to reject a false null hypothesis.
Validity: Extent to which a test measures what it claims to measure.
Variance: Measure of variability in a dataset.
Wilcoxon Signed-Rank Test: Non-parametric alternative to paired samples t-test.
Z-Score: Standardised score indicating standard deviations from mean.
Z-Test: Statistical test for means when population variance is known.

Digital & Online Research Terms
Ad Blocking: Technology preventing display of online advertisements.
Affiliate Marketing: Performance-based marketing where rewards are based on actions.
Algorithm: Set of rules or instructions for solving problems or completing tasks.
Analytics: Systematic analysis of data to discover patterns and insights.
Application Programming Interface (API): Set of protocols for building software applications.
Artificial Intelligence (AI): Computer systems performing tasks typically requiring human intelligence.
Attribution Window: Time period during which conversions are credited to marketing touchpoints.
Beacon Technology: Location-based technology using Bluetooth signals.
Big Data: Datasets too large and complex for traditional data processing applications.
Bounce Rate: Percentage of visitors leaving a website after viewing only one page.
Brand Mention: Reference to a brand name across digital platforms.
Chatbot: Computer program designed to simulate conversation with human users.
Click-Through Rate (CTR): Percentage of people clicking on a link out of total viewers.
Cloud Computing: Delivery of computing services over the internet.
Content Management System (CMS): Software for creating and managing digital content.
Conversion Rate: Percentage of users completing a desired action.
Cookie: Small file stored on user’s device to track website interactions.
Cookie-less Tracking (post-2025 privacy changes).
Cost Per Click (CPC): Amount paid for each click on an advertisement.
Cost Per Impression (CPM): Amount paid for every thousand advertisement impressions.
Cost Per Acquisition (CPA): Amount paid for each conversion or customer acquisition.
Customer Relationship Management (CRM): Technology managing company interactions with customers.
Data Analytics: Process of examining datasets to draw conclusions.
Data Visualisation: Graphical representation of information and data.
Deep Learning: Machine learning using neural networks with multiple layers.
Digital Marketing: Marketing using digital channels and technologies.
E-commerce: Electronic commerce conducted over the internet.
Engagement Rate: Measure of user interaction with content.
Event Tracking: Monitoring specific user actions on websites or apps.
Exit Rate: Percentage of visitors leaving from a particular page.
First-Party Data – customer-owned data assets.
Geofencing: Creating virtual boundaries around physical locations.
Google Analytics: Web analytics service tracking and reporting website traffic.
Heatmap: Visual representation of user behaviour on web pages.
Impression: Single instance of an advertisement being displayed.
Internet of Things (IoT): Network of interconnected devices collecting data.
JavaScript: Programming language commonly used for web development.
Keyword: Word or phrase used in search engines to find information.
Landing Page: Web page designed for specific marketing campaigns.
Machine Learning: AI subset enabling systems to learn from data.
Marketing Automation: Technology automating marketing processes.
Mobile Analytics: Analysis of mobile app and website usage.
Natural Language Processing (NLP): AI technology processing human language.
Omnichannel: Integrated approach across all customer interaction channels.
Organic Traffic: Website visitors from unpaid search results.
Page Views: Number of times a web page is viewed.
Paid Search: Advertising model where advertisers pay for clicks on search ads.
Panel Quality Score (e.g., QScore, TrustScore).
Personalisation: Tailoring content and experiences to individual users.
Pixel: Small piece of code tracking user behaviour on websites.
Programmatic Advertising: Automated buying and selling of online advertising.
Real-Time Bidding: Automated auction process for digital advertising.
Retargeting: Advertising to users who previously visited a website.
Search Engine Marketing (SEM): Marketing using search engines.
Search Engine Optimisation (SEO): Process of improving website visibility in search results.
Server-Side Tagging – GA4 & privacy-first analytics.
Session: Period of user interaction with a website.
Social Media Analytics: Analysis of social media platform data.
Social Media Listening: Monitoring social media for brand mentions and conversations.
Social Media Monitoring: Tracking social media platforms for specific keywords or mentions.
Unique Visitors: Number of distinct individuals visiting a website.
User Experience (UX): Overall experience users have with digital products.
User Interface (UI): Point of interaction between users and digital products.
Viral Coefficient: Metric measuring how effectively content or products spread through social networks.
Web Analytics: Collection and analysis of website usage data.
Website Traffic: Number of visitors to a website.
Zero-Party Data – data intentionally shared by the user (preference centres).

Specialised Research Areas
Advertising Research: Study of advertising effectiveness and consumer response to marketing communications.
Agricultural Research: Research focused on farming practices, crop yields, and agricultural economics.
Automotive Research: Study of vehicle preferences, transportation needs, and automotive industry trends.
B2B Research: Business-to-business research focusing on organisational buying behaviour and decision-making.
Clinical Research: Study of medical treatments, drugs, and healthcare interventions.
Communications Research: Study of message effectiveness, media consumption, and communication channels.
Consumer Behaviour Research: Study of how individuals make purchasing decisions and use products.
Corporate Research: Internal research conducted by companies for strategic decision-making.
Cross-Cultural Research: Study comparing behaviours and attitudes across different cultures.
Customer Experience Research: Study of customer interactions and experiences with brands.
Economic Research: Study of economic trends, market conditions, and financial behaviours.
Educational Research: Study of learning processes, educational methods, and academic outcomes.
Employee Research: Study of workforce attitudes, engagement, and organisational behaviour.
Environmental Research: Study of environmental issues, sustainability, and green consumer behaviour.
Financial Services Research: Study of banking, insurance, and investment services.
Food and Beverage Research: Study of food preferences, consumption patterns, and nutrition.
Government Research: Research conducted by or for government agencies and public policy.
Healthcare Research: Study of health behaviours, medical treatments, and healthcare delivery.
International Research: Cross-border research addressing global markets and cultural differences.
Media Research: Study of media consumption, audience measurement, and content effectiveness.
Non-Profit Research: Research conducted for charitable organisations and social causes.
Pharmaceutical Research: Study of drug development, medical treatments, and healthcare products.
Political Research: Study of political attitudes, voting behaviour, and public opinion.
Product Research: Study of product development, features, and consumer preferences.
Public Opinion Research: Study of public attitudes towards issues, policies, and candidates.
Retail Research: Study of shopping behaviour, store performance, and retail trends.
Social Research: Study of social issues.
Healthcare-Specific Research Methods & Engagement
Advisory Board Research: Strategic research method assembling groups of healthcare professionals to provide ongoing insights on medical trends, treatment protocols, and industry developments. Typically involves 8-12 experts meeting quarterly with structured agendas and compensation frameworks.
Clinical Decision Journey Mapping: Specialised research method tracking healthcare professionals’ diagnostic and treatment decision-making processes from patient presentation to treatment selection, including influence factors and information sources.
Clinical Evidence Review Research: Systematic research method where healthcare professionals evaluate and provide feedback on clinical data, study results, and evidence packages for new treatments or medical devices.
Continuing Medical Education (CME) Research: Study of educational preferences, learning patterns, and knowledge gaps among healthcare professionals to inform medical education programme development.
Digital Health Technology Adoption Research: Study of healthcare professionals’ attitudes, barriers, and adoption patterns regarding electronic health records, telemedicine, mobile health apps, and other digital healthcare tools.
Healthcare Professional (HCP) Segmentation: Market division of medical professionals based on speciality, practice setting, years of experience, patient volume, prescribing patterns, and technology adoption levels.
Key Opinion Leader (KOL) Research: Targeted research with influential healthcare professionals who shape medical practice and peer opinions within their specialities or therapeutic areas.
Medical Affairs Research: Research supporting scientific and clinical activities in pharmaceutical and medical device companies, including investigator-initiated studies and real-world evidence generation.
Peer-to-Peer Research: Research method leveraging healthcare professionals to interview other medical professionals, often resulting in more candid responses about clinical practices and challenges.
Physician Journey Research: Comprehensive study of healthcare professionals’ career development, from medical school through specialisation to practice evolution, including decision factors and support needs.
Point-of-Care Research: Study of healthcare delivery at the location where patient care occurs, examining workflow efficiency, technology integration, and patient-provider interactions.
Real-World Evidence (RWE) Research: Collection and analysis of data on healthcare treatments and outcomes from routine clinical practice rather than controlled trial environments.
Therapeutic Area Research: Specialised research focusing on specific medical conditions or disease areas, requiring deep clinical knowledge and regulatory understanding.
Healthcare Professional Engagement Strategies
Adverse Event Reporting: Mandatory process for documenting and reporting unexpected medical occurrences during research, required under pharmaceutical regulations and medical device safety protocols.
Clinical Research Ethics: Framework ensuring healthcare professional research meets ethical standards, including informed consent, patient privacy, and conflict of interest management.
Good Clinical Practice (GCP): International quality standard for designing, conducting, and reporting clinical research involving human subjects, mandatory for healthcare professional studies.
Health Insurance Portability and Accountability Act (HIPAA) Compliance: US privacy regulation governing the handling of protected health information in healthcare research, with equivalent frameworks globally.
Institutional Review Board (IRB) Approval: Ethics committee review and approval process required for research involving healthcare professionals in clinical settings.
Medical Research Ethics Committee (MREC): Regulatory body reviewing research proposals involving healthcare professionals to ensure ethical standards and patient protection.
Physician Payment Sunshine Act Compliance: Transparency requirements for documenting payments and transfers of value to healthcare professionals participating in research.
Privacy and Confidentiality Protocols: Comprehensive frameworks protecting healthcare professional and patient information during research activities, including data encryption and access controls.
Research Governance: Systematic framework ensuring healthcare research meets quality, safety, and ethical standards while complying with regulatory requirements.
Therapeutic Goods Administration (TGA) Guidelines: Australian regulatory framework governing research involving healthcare professionals and medical products.
Professional Recruitment and Incentives
Academic Medical Center (AMC) Partnerships: Collaboration frameworks with university-affiliated healthcare institutions for recruiting physician researchers and accessing clinical populations.
Clinical Research Organisation (CRO) Partnerships: Collaborative frameworks with contract research organisations specialising in healthcare professional recruitment and study execution.
Fair Market Value (FMV) Compensation: Regulatory-compliant payment framework ensuring healthcare professionals receive appropriate compensation for research participation time and expertise.
Healthcare Professional Honoraria: Standardised payment structures for medical expert participation in research, advisory boards, and consulting activities, designed to meet regulatory compliance requirements.
Investigator Site Networks: Established relationships with clinical research sites and principal investigators for recruiting healthcare professionals in pharmaceutical and medical device studies.
Medical Society Partnerships: Collaboration with professional medical associations to access their member networks for research recruitment whilst maintaining ethical standards.
Opinion Leader Identification: Systematic process for identifying influential healthcare professionals within therapeutic areas based on publication records, speaking engagements, and peer recognition.
Professional Development Credits: Research participation frameworks offering continuing medical education (CME) credits, maintenance of certification (MOC) points, or other professional development benefits.
Specialist Referral Networks: Recruitment approach leveraging professional relationships between specialists and referring physicians to access hard-to-reach medical populations.
Teaching Hospital Collaborations: Research partnerships with academic medical centres providing access to resident physicians, attending physicians, and clinical faculty.
Data Collection Methodologies for Healthcare Professionals
Clinical Practice Pattern Analysis: Systematic study of how healthcare professionals diagnose, treat, and manage specific conditions in real-world practice settings.
Delphi Consensus Methodology: Structured communication technique using expert healthcare professional panels to achieve convergence of opinion on complex medical topics.
Electronic Health Record (EHR) Data Mining: Analysis of clinical data from electronic medical records to understand prescribing patterns, treatment outcomes, and healthcare delivery efficiency.
Medical Chart Review: Systematic analysis of patient medical records by healthcare professionals to evaluate treatment patterns, outcomes, and clinical decision-making processes.
Pharmaceutical Sales Data Analysis: Study of prescription data, market share information, and prescribing trends to understand healthcare professional behaviour and market dynamics.
Prescription Writing Simulation: Research method where healthcare professionals evaluate hypothetical patient scenarios and document their treatment decisions for analysis.
Real-World Data (RWD) Collection: Gathering information from healthcare delivery settings, including electronic health records, claims databases, and patient registries.
Retrospective Chart Analysis: Research method examining historical patient records to understand past treatment patterns and outcomes in clinical practice.
Treatment Protocol Development Research: Collaborative research with healthcare professionals to develop, test, and refine clinical practice guidelines and treatment algorithms.
Virtual Reality Clinical Simulation: Advanced research method using VR technology to study healthcare professional decision-making and skills in controlled, reproducible scenarios.
Quality Assurance and Validation
Clinical Data Verification: Process of confirming accuracy and completeness of healthcare research data through source document review and audit procedures.
Inter-Rater Reliability Assessment: Statistical measurement of agreement between healthcare professional evaluators in research studies requiring clinical judgement.
Medical Expert Validation: Quality assurance process involving independent healthcare professionals reviewing research findings for clinical accuracy and relevance.
Peer Review Validation: Quality control method where healthcare professionals evaluate research methodologies and findings within their areas of clinical expertise.
Professional Credentialing Verification: Process of confirming healthcare professionals’ qualifications, licensure, and good standing before research participation.
Research Site Monitoring: Systematic oversight of healthcare research locations to ensure compliance with study protocols and regulatory requirements.
Source Data Verification (SDV): Quality assurance process comparing research data to original medical records and source documents to ensure accuracy.
Standard Operating Procedures (SOPs): Documented protocols governing all aspects of healthcare professional research to ensure consistency and compliance.
Statistical Analysis Plan (SAP): Pre-specified analytical framework for healthcare research ensuring unbiased interpretation of results and regulatory compliance.
Training and Competency Assessment: Systematic evaluation of healthcare professionals’ understanding of research protocols and procedures before study participation.
Therapeutic Area Specialisations
Cardiology Research: Specialised research focusing on cardiovascular conditions, treatment protocols, and cardiac care delivery among healthcare professionals.
Dermatology Practice Research: Study of skin condition management, dermatological treatments, and cosmetic procedure adoption among dermatologists and related specialists.
Emergency Medicine Research: Research examining acute care delivery, emergency department workflows, and critical care decision-making among emergency healthcare professionals.
Endocrinology Research: Specialised research focusing on diabetes management, hormone therapies, and metabolic disorder treatment among endocrinologists and related practitioners.
Gastroenterology Research: Study of digestive system disorders, treatment approaches, and procedural adoption among gastroenterology specialists.
Mental Health Professional Research: Research examining psychiatric treatment approaches, therapy methodologies, and mental health service delivery among psychiatrists, psychologists, and counsellors.
Neurology Research: Specialised research focusing on neurological conditions, brain disorder treatments, and neurosurgical procedures among neurology specialists.
Oncology Research: Comprehensive research examining cancer treatment protocols, chemotherapy regimens, and oncological care delivery among cancer specialists.
Orthopedic Research: Study of musculoskeletal treatments, surgical procedures, and rehabilitation protocols among orthopedic surgeons and related specialists.
Pediatric Healthcare Research: Specialised research focusing on child healthcare delivery, pediatric treatments, and family-centered care among pediatric healthcare professionals.
Primary Care Research: Study of general practice medicine, preventive care delivery, and patient management approaches among family physicians and general practitioners.
Pulmonology Research: Research examining respiratory condition management, lung disease treatments, and breathing disorder protocols among pulmonology specialists.
Technology and Innovation Research
Artificial Intelligence in Healthcare Research: Study of AI adoption, machine learning applications, and automation acceptance among healthcare professionals.
Digital Therapeutics Research: Research examining healthcare professional attitudes toward software-based medical interventions and digital treatment platforms.
Health Information Technology (HIT) Adoption: Study of electronic health record implementation, clinical decision support systems, and digital workflow integration.
Medical Device Innovation Research: Research examining new medical technology adoption, device preferences, and clinical integration challenges among healthcare professionals.
Patient Portal and Digital Communication Research: Study of healthcare professional experiences with patient communication technologies and digital engagement platforms.
Precision Medicine Research: Research examining personalised treatment approaches, genetic testing integration, and individualised therapy adoption among healthcare professionals.
Robotic Surgery Research: Study of surgical robot adoption, training requirements, and procedural outcomes among surgical specialists.
Telehealth and Telemedicine Research: Comprehensive research examining remote healthcare delivery, virtual consultation effectiveness, and digital care integration.
Wearable Technology in Healthcare Research: Study of healthcare professional attitudes toward patient monitoring devices, fitness trackers, and remote patient management tools.
Clinical Decision Support Systems (CDSS) Research: Research examining computerised assistance tools for clinical decision-making and their integration into healthcare workflows.










Healthcare-Specific Research Methods & Engagement
Healthcare Professional Engagement Strategies
Data Collection Methodologies for Healthcare Professionals
