MKT 360 exam 3

Subjects

The sampling units for an experiment, usually human participants in research who are subjected to some experimental manipulation.

Experimental condition

One of the possible levels of an experimental variable manipulation.

Blocking variables

Categorical variables included in the statistical analysis of experimental data as a way of statistically controlling or accounting for variance due to that variable.

Covariate

A continuous variable included in the statistical analysis as a way of statistically controlling for variance due to that variable. Alternative term => explanatory variable.

Main effect

The experimental difference in dependent variable means between the different levels of any single experimental variable.

Interaction effect

Differences in a dependent variable due to a specific combination of independent variables.

Experimental treatment

The term referring to the way an experimental variable is manipulated.

Experimental group

A group of subjects to whom an experimental treatment is administered.

Control group

A group of subjects to whom no experimental treatment is administered which serves as a baseline for comparison.

Cell

Refers to a specific treatment combination associated with an experimental group.

Test units

The subjects or other entities whose responses to the experimental treatment are measured or observed. (ex. individual consumers, employees, organizational units, sales territories, market segments, brands, stores, websites)

Systematic (non-sampling) error

Occurs if the sampling units in an experimental cell are somehow different than the units in another cell, & this difference affects the dependent variable. [ex. professor gives 3 types of snacks (fruit, cookies, & chocolate) over the course of a day. Error occurs bc peoples tastes react differently to different foods @ different times of the day]

Randomization

The random assignment of subject & treatments to groups; it is one device for equally distributing the effects of extraneous variables to all conditions.

Repeated measures

Repeated measures experiments in which an individual subject is exposed to more than one level of an experimental treatment.

Confound

Term means that there is an alternative explanation beyond the experimental variables for observed differences in the dependent variable.

Demand characteristic

Experimental design element or procedure that unintentionally provides subjects with hints about the research hypothesis.

Demand effect

Occurs when demand characteristics actually affect the dependent variable.

Placebo

A false experimental treatment disguising the fact that no real treatment is administered.

Placebo effect

The effect in a dependent variable associated with the psychological impact that goes along with knowledge of some treatment being administered.

Constancy of conditions

Means that subjects in all experimental groups are exposed to identical conditions except for the differing experimental treatments.

Counterbalancing

Attempts to eliminate the confounding effects of order of presentation by requiring that 1/4 of the subjects be exposed to treatment A first, 1/4 to treatment B first, 1/4 to treatment C first, & finally 1/4 to treatment D first.

Laboratory experiment

The researcher has more complete control over the research setting & extraneous variables.

Tachistoscope

Device that controls the amount of time a subject is exposed to a visual image.

Field experiments

Research projects involving experimental manipulations that are implemented in a natural environment.

Within-subjects design

Involves repeated measures bc with each treatment the same subject is measured.

Between-subjects design

Each subject receives only one treatment combination.

Internal validity

Exists to the extent that an experimental variable is truly responsible for any variance in the dependent variable.

Manipulation check

A validity test of an experimental manipulation to make sure that the manipulation does produce differences in the independent variable.

History effect

Occurs when some change other than the experimental treatment occurs during the course of an experiment that affects the dependent variable.

Cohort effect

Refers to a change in the dependent variable that occurs bc members of one experimental group experienced different historical situations than members of other experimental groups.

Maturation effect

A function of time & the naturally occurring events that coincide with growth & experience.

Testing effects

A nuisance effect occurring when the initial measurement or test alerts or primes subjects in a way that affects their response to the experimental treatments.

Instrumentation effects

A nuisance that occurs when a change in the wording of questions, a change in interviewers, or a change in other procedures causes a change in the dependent variable.

Mortality effect (sample attrition)

Occurs when some subjects withdraw from the experiment before it is completed.

External validity

Is the accuracy with which experimental results can be generalized beyond the experimental subjects.

Attention filters

Items that have known & obvious answers included just to see if participants are playing along.

Test-market sabotage

Intentional attempts to disrupt the results of a test-market being conducted by another firm. (ex. Hidden Valley Ranch & competitor buying up all new of a new flavor being tested)

Measurement

The process of describing some property of a phenomenon of interest, usually by assigning numbers in a systematic way that aims to be reliable & valid.

Concept

A generalized idea that represents something of identifiable & distinct meaning.

Operationalization

The process of identifying scale devices that correspond to properties of a concept involved in a research process.

Scales

A device providing a range of values that correspond to different characteristics or amounts of a characteristic exhibited in observing a concept.

Correspondence rules

Indicate the way that a certain value on a scale corresponds to some true value of a concept.

Construct

A term used to refer to latent concepts measured with multiple variables.

*R.O.N.I.*

1. Ratio

2. Ordinal

3. Nominal

4. Interval

What are the 4 levels of scale measurements:

Nominal scales

Represent the most elementary level of measurement in which values are assigned to an object for identification or classification purposes only; can be qualitative as no quantities are being represented. (ex. Blind taste testing 3 different soda recipes labeled X, Y, & Z; uniform numbers, airport terminals, school bus numbers)

*Name*

Ordinal scales

Ranking scales allowing things to be arranged based on how much of some concept they possess. [ex. teacher assigning grades between A-F; rank 1-5]

*Named + Ordered variables*

Interval scales

Scales that have both nominal and ordinal properties, but that also capture information about differences in quantities of a concept from observation to the next.

*Named + Ordered + Proportionate interval btw variables*

Ratio scales

Represent the highest form of measurement in that they have all the properties of interval scales with the additional attribute of representing absolute quantities; characterized by a meaningful absolute zero.

*Named + Ordered + Proportionate interval btw variables + Can accommodate absolute zero*

Discrete measures

Measures that take on only one of a finite number of values. Can possess ordinal & nominal properties, which are best measured by "mode."

(ex. yes-no response, matching, etc.)

Continuous measures

Measures that reflect the intensity of a concept by assigning values that can take on any value along some scale range. Continuous measures require at least interval level measurement. Can possess ratio & interval properties, which are best measured by "means & standard deviations."

Soft metrics

Social media measures such as "likes," downloads & followers that might NOT correlate to desired outcomes from a customer in the form of an action or a purchase.

1. Specific- Written in simple terms that are well-defined & understandable to all participants & stakeholders.

2. Measurable- Quantifiable progress in terms that are meaningful to the brand.

3. Attainable- Possible to achieve with the resources available to the organization, & in light of current internal & external conditions.

4. Relevant- Aligned with the brand's essential work & its place in the marketplace.

5. Time-specific-- Bound by a specific time frame.

List the S.M.A.R.T. acronym :

1. Goals

2. Objectives

3. Strategy

4. Tactics

5. Key performance indicators (KPI's)

Common social media framework, list 5 steps:

1. Conversation drivers- Reflects what people are talking about

2. Influence- Reflects who or what drives customer behavior

3. Sentiment- Reflects the tone of conversations about a brand, product, or idea.

3 examples of qualitative social media metrics:

1. Click-through rate (CTR)- (%) of visitors who click on a link.

2. Dwell time- Amount of time that a visitor actually spends on a page.

3. Conversions- The number of people who perform a desired action, such as buying a product, voting for a candidate, signing up for a trial service or completing a lead-generation form.

4. Engagement- Measures how well the bran is connecting with its followers or fans, "interactions per follower"

5. Followers- Amount of followers

6. Leads- The people who might purchase a brand's product or service.

7. Visitor frequency rate- Differentiates between new & returning visitors.

7 examples of quantitative social media metrics:

1. Aspirational- What are social leaders in the brand's industry doing?

2. Trended- What does previous activity for the brand tell marketers about establishing projections & standards for this effort?

3. Earned- What do previous campaigns tell a brand about reasonable goals for an upcoming campaign?

4. Competitive- What kinds of results are direct competitors getting from their social media marketing?

List the 4 main areas of social media Benchmarking:

Attribute

A single characteristic or fundamental feature of an object, person, situation, or issue.

Index measure

Assigns a value based on a mathematical formula separating low scores from high scores.

Composite scales

Assign a value to an observation based on a mathematical derivation of multiple variables to create an operational measure of a construct.

Summated scale

A scale created by simply assuming (adding together) the response to each time making up the composite measure. The scores can be but do not have to be averaged by the number of items making up the composite scale.

Reverse coding

Means that the value assigned for a response is treated oppositely from the other items.

Reliability

An indicator of a measure's internal consistency.

Internal consistency

Represents a measure's homogeneity or the extent to which each indicator of a construct converges on some common meaning.

Split-half method

A method for assessing internal consistency by checking the results of one-half of a set of scaled items against the results from the other half.

Coefficient alpha

The most commonly applied estimate of a multiple item scale's reliability. It represents the average of all possible split-half reliabilities for a construct.

Test-retest method

Administering the same scale or measure to the same respondents at two separate points in time to test for stability.

Validity

The accuracy of a measure or the extent to which a score truthfully represents a concept.

Face (content) validity

Extent to which individual measures content match the intended concept's definition.

Criterion validity

The ability of a measure to correlate with other standard measures of similar constructs or established criteria.

Construct validity

Exists when a measure reliably measures & truthfully represents a unique concept; consists of several components including face validity, convergent validity, criterion validity, discriminant validity & fit validity.

Convergent validity

Depends on internal consistency so that multiple measures converge on a consistent meaning.

Discriminant validity

Represents how unique or distinct is a measure; a scale should not correlate too highly with a measure of a different construct.