Abandonment: The rate at which
respondents leave a survey before completing it, often
due to survey length or complexity.
Accuracy: The degree to which survey
results reflect the true values or behaviors of the
population being studied.
Acquiescence Bias: A tendency for
respondents to agree with statements or questions
regardless of their true feelings or opinions, often
skewing results.
Actionable Data: Information gathered
from surveys that can be used to inform decisions and
strategies effectively.
Administration Biases: Errors that
occur in survey administration due to factors like the
survey administrator's behavior or influence.
Administrative Burden: The workload
associated with managing and conducting surveys, which
can impact the overall quality and efficiency of data
collection.
Administration Mode: The method used to
conduct a survey, such as online, telephone, or
in-person.
Ambiguity: Uncertainty or vagueness in
survey questions that can lead to varied interpretations
by respondents.
Analytical Burden: The complexity
involved in analyzing survey data, which can increase if
the survey is poorly designed or if the data is
extensive.
Anchor: A reference point used in
survey questions to help respondents evaluate their
answers, often seen in rating scales.
Anonymity: The condition in which
respondents cannot be identified, ensuring that their
responses remain confidential.
ANOVA (ANalysis Of VAriance): A
statistical method used to compare means among three or
more groups to determine if there are significant
differences.
Attitudinal Outcome: The result of a
survey that reflects the feelings or opinions of
respondents regarding a particular subject.
Attribute: A characteristic or feature
of a subject being studied, often evaluated in
surveys.
Attribute Identification: The process
of identifying and defining key attributes related to
the survey's subject matter.
Average (Arithmetic Mean): A measure of
central tendency calculated by dividing the sum of all
values by the number of values.
Balanced Scale: A survey scale that
provides an equal number of positive and negative
response options to avoid bias.
Balanced Scorecard: A strategic
planning tool that measures organizational performance
across multiple dimensions, often used in survey
analysis.
Bar Charts: Visual representations of
data using rectangular bars to compare different groups
or categories.
Batch Surveying: The practice of
conducting multiple surveys simultaneously or in groups
to streamline data collection.
Benchmarking: The process of comparing
survey results to industry standards or best practices
to gauge performance.
Bias: Any systematic error in survey
results that can lead to misinterpretations or
inaccurate conclusions.
Bimodal: A distribution with two
different modes, indicating two prevalent response
patterns among respondents.
Binary Choice: A survey question format
that offers respondents two options (e.g., yes/no or
agree/disagree).
Bivariate Statistics: Statistical
methods used to analyze the relationship between two
variables in survey data.
Bottom Box Scoring: A method of scoring
that focuses on the lowest possible responses in a
survey, often to identify dissatisfaction.
Branching: A survey technique that
directs respondents to different questions based on
their previous answers, also known as conditional
branching or "skip and hit."
Categorical Data: Data that can be
divided into distinct categories, often used in
multiple-choice questions.
CATI (Computer Aided Telephone
Interviewing): A survey method using computer software
to assist in conducting telephone interviews.
Census: A survey that collects data
from every member of a population rather than a
sample.
Central Tendency: A statistical measure
that identifies the center of a dataset, typically
represented by the mean, median, or mode.
Checklist Question Type: A question
format allowing respondents to select multiple options
from a list.
Cherry Picking: A sampling technique
where researchers intentionally select respondents
likely to provide favorable results.
Chi Squared: A statistical test to
determine if there is a significant association between
categorical variables in survey data.
Closed-Ended Question: A survey
question that restricts responses to predefined options,
making analysis straightforward.
Cluster Sampling: A sampling method
where the population is divided into clusters, and
entire clusters are randomly selected.
Cognitive Burden: The mental effort
required from respondents to understand and answer
survey questions.
Comparative Scales: Survey scales that
ask respondents to evaluate one option relative to
another.
Composition Effect: The impact that
changes in the composition of a sample may have on
survey results.
Concern: An expression of apprehension
or worry regarding a specific issue addressed in a
survey.
Conclusion Validity: The extent to
which the conclusions drawn from survey data accurately
reflect the research question.
Conditional Branching: A survey design
feature that tailors the respondent’s path based on
their previous answers.
Confidence Interval: A statistical
range that expresses the degree of uncertainty around an
estimate derived from survey data.
Confidence Statistic: A measure of the
reliability of an estimate obtained from survey data.
Confidentiality: The practice of
keeping respondents' information private and secure
during and after data collection.
Conformity Bias: A tendency for
respondents to align their answers with perceived group
norms or expectations.
Continuous Scale: A measurement scale
that allows for an infinite number of potential
responses, often used in ratings.
Convenience Sample: A non-probability
sampling method that selects participants based on their
availability, which may introduce bias.
Correlation: A statistical measure that
describes the strength and direction of a relationship
between two variables.
Critical Incident Study: A research
method that focuses on specific instances that have
significant impact on experiences or outcomes.
Cumulative Frequency Distribution: A
method of showing the number of observations less than
or equal to a certain value in a dataset.
Customer Experience Design: The process
of designing interactions that create a positive
experience for customers throughout their journey.
Customer Experience Management (CEM or CX): Strategies and practices aimed at improving customer
interactions and satisfaction.
Customer Feedback Management (CFM): The
process of collecting, analyzing, and acting on customer
feedback to enhance products and services.
Data Cleansing: The process of
identifying and correcting errors or inconsistencies in
survey data to ensure quality.
Data Collection Form: The structured
document or digital tool used to collect survey
responses.
Data Types: Categories of data,
including qualitative and quantitative, that inform
survey design and analysis.
Demographic Questions: Questions
designed to gather information about respondents'
characteristics, such as age, gender, and income.
Descriptive Research: Research aimed at
providing an accurate representation of the
characteristics of a particular population.
Descriptive Statistics: Statistical
measures that summarize or describe the characteristics
of a dataset, such as mean and median.
Discrete Scale: A measurement scale
with distinct categories or values that cannot be
subdivided.
Dispersion: The extent to which survey
responses vary or spread out from the average or mean
value.
Double Barreled Question: A survey
question that asks about two different issues but allows
for a single response, potentially confusing
respondents.
Endpoint Anchoring: A technique where
respondents rate items using a scale with defined
endpoints, helping them gauge their responses more
accurately.
Event Surveys: Surveys that capture
feedback immediately following an event, also known as
transactional or incident surveys.
Exploratory Research: Research
conducted to gain insights and understanding about a
topic when little information is available.
Face Saving Bias: A tendency for
respondents to answer in a way that preserves their
self-image or social standing.
Fatigue: A decline in respondent
quality due to survey length or complexity, leading to
lower quality responses.
Field Research: The collection of data
outside of a laboratory or controlled environment, often
involving real-world settings.
Fixed Sum Question Type: A question
format where respondents allocate a fixed amount of
points or resources among multiple options.
Follow-Up Notices: Reminders sent to
respondents to encourage survey completion, enhancing
response rates.
Focus Groups: Small, diverse groups of
people discussing a specific topic, providing
qualitative insights that surveys may not capture.
Forced Choice Scale: A survey format
requiring respondents to choose between two or more
options, reducing neutral responses.
Forced-Ranking Question Type: A
question format where respondents must rank options in
order of preference.
Fractionation Question Type: A survey
technique that breaks down complex questions into
simpler parts for easier response.
Free-Form Question Type: Open-ended
questions that allow respondents to provide any
response, offering richer qualitative data.
Frequency Distribution: A summary of
how often each response occurs within a dataset.
Frequency Scale: A survey scale that
measures how often respondents experience a specific
event or behavior.
Fully Anchored Verbal Scale: A rating
scale where all points are defined with verbal
descriptions, providing clarity to respondents.
Generalizability: The extent to which
survey findings can be applied to a larger population
beyond the sample surveyed.
Guttman Scale: A unidimensional scale
used to measure attitudes or beliefs, where agreement
with one item implies agreement with others.
Hardcopy Survey Administration Mode: A
method of administering surveys using printed forms
rather than digital formats.
Headings: Titles or labels used in
surveys to categorize sections or questions for better
organization and clarity.
Heterogeneity: The variability or
diversity of a population that can impact survey
results.
Hindrance: Factors that impede the
completion or quality of survey responses.
Incentive: A reward offered to
respondents to encourage survey participation and
increase response rates.
Informed Consent: The process of
ensuring that respondents understand the purpose and
implications of the survey before participating.
Interval Scale: A measurement scale
that allows for the comparison of the differences
between values, with meaningful intervals but no true
zero.
Interrater Reliability: The degree of
agreement among different raters or observers evaluating
the same phenomenon in surveys.
Invalidity: The degree to which survey
results fail to accurately measure what they are
intended to measure.
Item Nonresponse: Occurs when
respondents skip certain questions, leading to
incomplete data.
Judgment Sample: A non-probability
sampling method where the researcher selects respondents
based on their judgment.
Key Performance Indicators (KPIs):
Measurable values that demonstrate how effectively a
company is achieving key business objectives.
Key Performance Indicators (KPIs):
Measurable values that demonstrate how effectively a
company is achieving key business objectives.
Likert Scale: A common rating scale
used in surveys that allows respondents to express
levels of agreement or disagreement on a statement.
Longitudinal Studies: Research studies
that collect data from the same subjects repeatedly over
time to observe changes.
Leading Language: Words or phrases in
survey questions that might influence or prompt
respondents toward a specific answer, potentially
biasing results.
Loaded Language: Emotionally charged
wording in survey questions that can lead to biased or
skewed responses from participants.
Looping: A survey design where
respondents are redirected to the same set of questions
based on specific answers, used to gather multiple
responses from a single participant across different
scenarios.
Margin of Error: A measure of the
possible error in survey results, indicating the range
within which the true value likely falls.
Market Research: The process of
gathering, analyzing, and interpreting information about
a market, including information about the target
audience.
Mean: The average value calculated by
summing all responses and dividing by the total number
of responses.
Measurement Validity: The degree to
which a survey measures what it claims to measure.
Mixed Mode Survey: A survey that
employs multiple methods of data collection, such as
online and telephone.
Mode Effect: Differences in survey
responses that result from the mode of administration
(e.g., online vs. telephone).
Measurement Error: The difference
between the actual value and the value obtained through
survey data, which can result from inaccuracies in data
collection, processing, or analysis.
Median: The middle value in a dataset
when it is arranged in order of magnitude. If the
dataset has an even number of observations, the median
is the average of the two middle numbers.
Mental Frame: The mindset or mental
approach a respondent uses when answering survey
questions, which can influence how they interpret and
respond to questions.
Mixed-Mode Administration: A survey
methodology that uses multiple data collection methods
(e.g., online, telephone, mail) to increase response
rates and reach a broader audience.
Multiple Choice Question Type: A survey
question format where respondents select one or more
options from a predetermined list of answers.
Multivariate Statistics: Techniques
used to analyze data that involves more than two
variables simultaneously, allowing researchers to
understand complex relationships between variables.
Non-Response Bias: A systematic
difference between those who respond to a survey and
those who do not, potentially skewing results.
Non-Probability Sampling: A sampling
method where not all members of the population have a
chance of being included, leading to possible biases.
Normal Distribution: A probability
distribution that is symmetric about the mean,
indicating that most values cluster around the central
peak.
Net Promoter Score® (NPS): A metric
that gauges customer loyalty and satisfaction by asking
respondents how likely they are to recommend a product
or service to others on a scale of 0-10.
Net Scoring: A method used to calculate
survey scores by subtracting the percentage of negative
responses from the percentage of positive responses.
Non-Response Bias: A type of bias that
occurs when the respondents who participate in the
survey differ in meaningful ways from those who do not,
potentially skewing results.
Open-Ended Questions: Survey questions
that allow respondents to answer in their own words,
providing qualitative insights.
Operationalization: The process of
defining variables in measurable terms for the purposes
of data collection.
Optimism Bias: The belief that bad
things are less likely to happen to us compared to
others, leading to unrealistic risk assessments.
Pilot Survey: A small-scale preliminary
survey conducted to test the feasibility, time, and
costs of a larger survey.
Population: The complete set of
individuals or items that are the focus of a survey.
Pretesting: The process of testing
survey questions on a small group before the main survey
to identify potential issues.
Periodic Surveys: Surveys that are
conducted at regular intervals (e.g., quarterly,
annually) to track changes over time.
Pie Charts: A graphical representation
of data in the form of a circle divided into segments,
where each segment represents a proportion of the
whole.
Pilot Tests (Pretest): A small-scale
trial run of a survey conducted to identify potential
issues with the survey design before it is distributed
to a larger audience.
Piped Text: A feature in survey design
that allows responses from earlier questions to be
inserted into subsequent questions or text, making the
survey feel more personalized.
Pivot Tables: A data summarization tool
used in surveys to organize and display data by
different categories, allowing users to analyze
responses across multiple dimensions.
Polar Anchoring (Endpoint Anchoring): A
technique used in scales where the extreme ends of the
scale are anchored with specific labels to guide
respondent interpretation (e.g., "Strongly
Disagree" and "Strongly Agree").
Population: The entire group of people
or entities about which a survey seeks to gather
information.
Population Parameters: Numerical
characteristics (e.g., mean, variance) that describe the
entire population being studied.
Positional Checklist Question Type: A
survey question format where respondents select one or
more answers from a list of options that appear in a
specific order.
Postal Survey Administration Mode: A
method of conducting surveys through the mail, where
respondents receive paper questionnaires and return them
once completed.
Precision: The degree to which repeated
measurements under unchanged conditions yield the same
results, indicating the consistency of a survey.
Prescriptive Research: Research focused
on providing specific recommendations or solutions based
on collected data and analysis.
Pretest (Pilot Test): A preliminary run
of a survey to test its design and functionality before
full distribution, ensuring clarity and usability.
Primacy Effect: A cognitive bias where
respondents are more likely to select options presented
at the beginning of a list due to their prominence.
Probability Sampling: A sampling method
where each member of the population has a known,
non-zero chance of being selected, allowing results to
be generalizable to the entire population.
Progress Indicators: Visual cues in
surveys (e.g., progress bars) that show respondents how
much of the survey they have completed.
Purposive or Purposeful Sampling: A
non-probability sampling technique where participants
are selected based on specific characteristics or
criteria that align with the research objectives.
Purposive or Purposeful Sampling: A
non-probability sampling technique where participants
are selected based on specific characteristics or
criteria that align with the research objectives.
Question Types: The different formats
used to ask questions in a survey, including multiple
choice, open-ended, rating scales, etc.
Questionnaire (Survey Instrument): The
set of questions or prompts designed to collect
information from respondents in a survey.
Quota Sampling: A sampling method where
researchers select participants based on specific
quotas, such as demographic or behavioral
characteristics, to ensure the sample represents the
population.
Qualitative Research: Research that
focuses on understanding the meaning and experiences of
respondents through open-ended responses.
Question Types: The different formats
used to ask questions in a survey, including multiple
choice, open-ended, rating scales, etc.
Random Sampling: A sampling method
where each member of the population has an equal chance
of being selected, reducing bias.
Rating Scale: A survey scale that asks
respondents to evaluate a specific item on a predefined
scale (e.g., 1 to 5).
Reliability: The consistency of survey
results over time and across different respondents or
groups.
Response Bias: A tendency for
respondents to answer questions in a certain way that
does not reflect their true opinions or behaviors.
Random Error: An unpredictable
variation that arises in survey data collection,
affecting measurements in a way that is not consistent
across participants.
Randomization: A process where
respondents or survey items are assigned randomly to
reduce bias and ensure each outcome has an equal chance
of occurring.
Rank, Ranking, Rank Order: A method of
ordering items or responses based on preference,
importance, or some other criteria.
Rate, Rating: A survey measure where
respondents evaluate an item or experience on a scale,
often used to measure satisfaction, agreement, or
likelihood.
Ratio Data: A type of data that
includes both an order and an equal interval between
data points, with an absolute zero (e.g., income, age,
weight).
Recall Bias: A bias that occurs when
respondents inaccurately remember past events, affecting
the reliability of their responses.
Recency Effect: A cognitive bias where
respondents are more likely to select the most recent
options presented in a list.
Reminders (Follow-Ups): Messages or
notifications sent to survey participants to encourage
them to complete the survey if they haven't yet
responded.
Representative: A sample that
accurately reflects the characteristics of the broader
population being studied.
Respondent Burden: The perceived effort
or time required from participants to complete a survey,
which can affect response rates and data quality.
Response Rate: The percentage of people
who respond to a survey out of the total number invited,
used to assess the survey’s reach and participation.
Response Sample: The group of
individuals who actually respond to a survey, as opposed
to the entire population invited to participate.
Response Set: A pattern of answers in
which respondents consistently choose the same type of
response (e.g., always choosing "Agree"),
regardless of the actual content of the questions.
Reverse Coded Questions: Survey
questions where the direction of the scale is reversed
to ensure respondents are paying attention and not
selecting the same response by habit.
Routine: Standardized, repeated survey
practices that are regularly conducted, such as
quarterly or annual surveys.
Saturation: The point at which no new
information or insights are being generated from
additional responses in qualitative research.
Screener Questions: Preliminary
questions used to determine respondents'
eligibility to participate in a survey.
Semantic Differential Scale: A survey
scale that measures respondents' attitudes towards
a subject using bipolar adjectives.
Skip Logic: A feature in surveys that
directs respondents to different questions based on
their previous answers.
Sociodemographic Data: Data that
describes the social and demographic characteristics of
respondents.
Statistical Significance: A measure of
whether survey results are likely due to chance or
represent true differences in the population.
Sample, Sampling: The process of
selecting a subset of individuals from a population to
participate in a survey.
Sample Bias: A bias that occurs when
the sample is not representative of the population,
leading to skewed or inaccurate survey results.
Sample Size Equation: A mathematical
formula used to determine the number of respondents
needed to achieve reliable survey results with a
specific confidence level and margin of error.
Sample Statistics: Data collected from
a sample that is used to estimate the characteristics of
the larger population.
Sampling Error: The error that arises
due to the fact that a sample, rather than the entire
population, is used to collect data, resulting in
potential differences between the sample and the
population.
Sampling Frame: A list or database of
the population from which a sample is drawn.
Satisficing: A behavior where
respondents choose an answer that is good enough or
satisfactory rather than the most accurate or optimal
answer, often due to survey fatigue or complexity.
Scales: Tools used in surveys to
measure attitudes, preferences, or behaviors, often
using rating systems (e.g., Likert scale).
Scatter Plots: Graphs used to display
the relationship between two variables, with data points
plotted along two axes.
School-Grade Scale: A type of rating
scale where respondents evaluate items in terms of
traditional school grades (e.g., A, B, C, D, F).
Section Headings: Titles used in
surveys to separate different parts of the
questionnaire, helping respondents navigate through the
survey more easily.
Segmentation Analysis: The process of
dividing respondents into distinct groups based on their
responses to identify patterns or insights.
Selection Bias: A bias that occurs when
the sample selected for the survey is not representative
of the population due to a flawed sampling process.
Self-Selection Bias (Non-Response or Participation
Bias): A bias that occurs when individuals with a particular
interest in the survey topic are more likely to
participate, leading to skewed results.
Semi-Structured Questionnaire: A survey
format that combines fixed-response and open-ended
questions, allowing for more detailed feedback while
retaining structure.
Sequencing: The order in which
questions are presented in a survey can impact the way
respondents answer subsequent questions.
Service Recovery: Actions taken to
address customer dissatisfaction after a service
failure, which can be measured through surveys to assess
the effectiveness of the recovery.
Skip and Hit (Branching, Conditional Branching): A survey feature that directs respondents to different
questions based on their answers, creating a customized
path through the survey.
Spam Trigger Words: Words or phrases in
emails or surveys that may be flagged by spam filters,
reducing the likelihood that survey invitations reach
respondents.
Standard Deviation: A statistical
measure of the spread or variability of a dataset,
indicating how much individual data points differ from
the mean.
Statistic: A numerical value derived
from survey data that summarizes a specific
characteristic of the population or sample.
Statistical Confidence: A measure of
how certain researchers are that their findings reflect
the true population characteristics, often expressed as
a confidence level (e.g., 95%).
Stratified Random Sampling: A sampling
technique where the population is divided into subgroups
(strata), and samples are drawn from each subgroup to
ensure representation.
Survey: A method of collecting
information from a group of people, usually by asking
questions, to gather insights on specific topics.
Survey Administration: The process of
distributing and collecting surveys from respondents,
including the method and mode of distribution.
Survey Instrument (Questionnaire): The
tool used to collect data from respondents, consisting
of the survey questions and prompts.
Survey Fatigue: A condition where
respondents become tired or bored of completing surveys,
leading to lower response rates or lower-quality
data.
Survey Manipulation: The intentional
alteration of survey questions or data to produce a
desired outcome or result.
Survey Question: An individual item or
prompt in a survey designed to elicit information from
respondents.
Systematic Sampling: A sampling
technique where every nth member of the population is
selected after a random starting point, ensuring equal
representation across the population.
Target Population: The specific group
of individuals that a survey aims to study.
Tenure Bias: A tendency for respondents
to favor answers that align with their length of
association or experience with a subject.
Testing Effects: The potential
influence of prior exposure to survey questions on
respondents' subsequent answers.
Telephone Surveying: A method of
conducting surveys over the phone, where respondents are
asked questions verbally by a survey administrator.
Tests of Independence: Statistical
tests used to determine whether two variables are
related or independent of each other.
Textual Data: Information collected in
the form of written responses, often from open-ended
survey questions.
Threaded Branch: A survey technique
where questions are organized in a logical sequence
based on previous answers, allowing for personalized
paths.
Top Box Scoring: A method of analyzing
survey data by focusing on the most positive or highest
rating (e.g., "5" on a 5-point scale), used to
assess overall satisfaction or sentiment.
Trade-Off Analysis: A survey method
that asks respondents to evaluate multiple attributes of
a product or service to determine which features they
value most.
Transactional Surveys (Event or Incident Surveys): Surveys conducted immediately after a specific event or
transaction to gather feedback on that experience.
Truncated Scales: Scales where certain
responses are omitted or condensed, typically to
simplify the response options.
T Test: A statistical test used to
compare the means of two groups to determine if they are
significantly different from each other.
Unobtrusive Measures: Data collection
techniques that do not disturb or influence respondents’
natural behavior.
User Experience (UX): The overall
experience of a person using a product, especially in
terms of how pleasurable or efficient it is.
Ulterior Motive: Hidden intentions or
goals behind asking certain questions in a survey, which
can influence the responses received.
Unit of Analysis: The main entity being
studied in a survey, such as individuals, households, or
organizations.
Validity: The extent to which a survey
measures what it claims to measure, ensuring accurate
results.
Variance: A statistical measure that
indicates the degree of spread in a set of data points
around the mean.
Verbal Scale: A rating scale where the
response options are described using words rather than
numbers (e.g., "Very Satisfied,"
"Neutral," "Dissatisfied").
Verbatims (Comments, Open-Ended Questions): Direct, unstructured responses provided by participants
in surveys, often gathered through open-ended
questions.
Verbatims (Comments, Open-Ended Questions): Direct, unstructured responses provided by participants
in surveys, often gathered through open-ended
questions.
Weighting: Adjusting survey results to
compensate for sample imbalances or to ensure
representation of various population segments.
Webform Surveying: A method of
conducting surveys through web-based forms, where
respondents complete the survey online.
Yearning for Consistency: The desire
to maintain a coherent belief system often leads us to
interpret new information in a way that aligns with our
existing views, even if it distorts reality.
Zero-Involvement: A term that describes
respondents who do not actively engage with survey
content, often leading to low-quality data.