Exam 1 Flashcards
Marketing concept
focuses on how a firm provides value to customers more than on the physical product or production process
A marketing oriented firm must…. (3)
be customer oriented
emphasize long run-profitability
adopt a cross functional perspective
Applied marketing research
conducted to address a specific marketing decision for a specific firm or organization.
example: should green mountain coffee add cola to its pod-based beverages? How much should I charge for this new feature?
Basic marketing research
conducted without a specific decision in mind and usually does not address needs for a specific organization. Can test the validity of a general marketing theory or learn more about market phenomenon (ex: social networking)
product research
desinged to evaluate and develop new products and to learn how to adapt existing product lines.
product research examples
concept testing
product testing
brand-name evaluation
package testing
pricing research
involves finding the amount of monetary sacrifice that best represents the value customers perceive in a product after considering various market constraints
integrated marketing
all promotional efforts (advertising, PR, personal selling, event marketing) are coordinated to communicate a consistent image
performance-monitoring research
research that regularly, sometimes routinely, provides feedback for evaluation and control of marketing activity. most common forms: market share analysis and sales analysis
marketing metrics
quantitative ways of monitoring and measuring marketing performance.
Backward marketing research
start with the end in mind, peel the onion until you can articulate a feasible business decision, start with small and initial decisions and build more specific insights.
2 tips tightly connected in backwards marketing
ask the right questions right away will lead to decisions made and implemented
steps on how to ask the right questions
symptoms, problem, options, decision, information needed, the right question.
data strategy
data inventory and describe characteristics
data readiness
integrated designs
what does smart use of big data provide?
more data means more insight
more opportunities to validation
more opportunities for real-timeliness
4 components for data value
relevance, quality, timeliness, completeness
Decision support system
help decision makers confront problems through direct interaction with computerized databases and analytical software programs
what are two functions of DSS?
store data and transform them into organized information that is easily accessible to marketing managers
Marketing analytics
general term that refers to efforts to measure relevant data and apply analytical tools in effort to better understand how a firm can enhance marketing performance
Predictive analytics
a system linking computerized data mined from multiple sources to statistical tools that can search for predictive relationships and trends
geolocation technologies
allow whereabouts and/or movement of a consumer or object to be known through digital identification of some kind
interpolation
method of constructing new data points within the range of a discrete set of known data points.
extrapolation
is the process of estimating, beyond the original observation range, the value of a variable on the basis of its relationship with another variable
Market dynamics
what markets will grow/shrink and what drives this?
Market share dynamics
how can I take market share from my competitor
marketing dynamics
how well do the various advertising channels work
customer dynamics
what customer are most likely to defect/respond to my offer
The analytical process
- review data quality
- univariate and bivariate analysis
- multivariate analyses
- integrate across data sources
Integrate with qualitative insights
Types of market research (experimental)
Nonexperimental, quasi experimental, experimental
Explorative
qualitative focus groups idea generation observation problem scoping ambiguous situations: from symptom to problem
descriptive
U&A, segmentation, tracking studies, we have considerable understanding of the situation
conformity, predictive and causal
driver models, forecasting, causal analysis, groups, marketing mix models, conjoint, experiments, list segmentation.
3 main types of descriptive research
U&A’s, segmentation studies, tracking
Nonexperimental market research
survey, qualitative, observation
Quasi experimental
field experiment, conjoint
Segmentation
dividing people in distinct groups with distinct characteristics to target them with different makreting mixes
key criteria for segmentation
exist, distinctive, targetable, profitable, respond, stable
Criteria (EXIST)
the segment must represent a real situation that exists in the market, not a data only situation
Criteria (DISTINCTIVE)
are sufficiently different on the relevant variables
Criteria (TARGETABLE)
Can be reached by a market intervention
Criteria (PROFITABLE)
segments need to be big and valuable enough to go after
Criteria (RESPOND)
respond differently to a different marketing mix
Criteria (STABLE)
presents an on going situation which lasts for a sufficient amount of time such to allow to extract value from it
Difficulty of segmentation
scale often very large (thousands of survey respondents, 30+ questions)
Not a well-defined process
How to find actionable business outcomes
Confirmatory and predictive research
factor analyses, driver modeling, list segmentation/customer base analysis, experiments
Brand funnel
Preference, consideration, awareness
causality requirements
allows causal inferences to be made–they identify cause and effect relationships.
Temporal sequence
the appropriate causal order of events
concomitant variation
two phenomena vary together–>there needs to be a relationship
nonspurious association
an absence of alternative plausible explanations
types of relationships
non-linear effects indirect effects lagged effects interaction effects surround sound effects feedback effects secondary effects
indirect effects
product quality–> overall satisfaction. BUT could be a middle factor like quality of technical support being an effect
reverse causility
dependent variable (customer satisfaction) causes independent variables
dependent variable
the variable you are trying to predict
independent variable
variables that you want to use to make the prediction
coefficient or regression coefficient
weight given to a variable to make the prediction
statistical significance
whether or not the coefficient statistically speaking is not zero
fit of the model or R-squared
the amount of explained variance in the dependent variable
best fit line is used to
minimize the sum of errors and the line can predict what we can interpolate and what we can extrapolate
