Exam 1 Flashcards

1
Q

Marketing concept

A

focuses on how a firm provides value to customers more than on the physical product or production process

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

A marketing oriented firm must…. (3)

A

be customer oriented
emphasize long run-profitability
adopt a cross functional perspective

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Applied marketing research

A

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?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Basic marketing research

A

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)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

product research

A

desinged to evaluate and develop new products and to learn how to adapt existing product lines.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

product research examples

A

concept testing
product testing
brand-name evaluation
package testing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

pricing research

A

involves finding the amount of monetary sacrifice that best represents the value customers perceive in a product after considering various market constraints

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

integrated marketing

A

all promotional efforts (advertising, PR, personal selling, event marketing) are coordinated to communicate a consistent image

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

performance-monitoring research

A

research that regularly, sometimes routinely, provides feedback for evaluation and control of marketing activity. most common forms: market share analysis and sales analysis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

marketing metrics

A

quantitative ways of monitoring and measuring marketing performance.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Backward marketing research

A

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.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

2 tips tightly connected in backwards marketing

A

ask the right questions right away will lead to decisions made and implemented

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

steps on how to ask the right questions

A

symptoms, problem, options, decision, information needed, the right question.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

data strategy

A

data inventory and describe characteristics
data readiness
integrated designs

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

what does smart use of big data provide?

A

more data means more insight
more opportunities to validation
more opportunities for real-timeliness

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

4 components for data value

A

relevance, quality, timeliness, completeness

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Decision support system

A

help decision makers confront problems through direct interaction with computerized databases and analytical software programs

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

what are two functions of DSS?

A

store data and transform them into organized information that is easily accessible to marketing managers

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Marketing analytics

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Predictive analytics

A

a system linking computerized data mined from multiple sources to statistical tools that can search for predictive relationships and trends

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

geolocation technologies

A

allow whereabouts and/or movement of a consumer or object to be known through digital identification of some kind

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

interpolation

A

method of constructing new data points within the range of a discrete set of known data points.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

extrapolation

A

is the process of estimating, beyond the original observation range, the value of a variable on the basis of its relationship with another variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Market dynamics

A

what markets will grow/shrink and what drives this?

25
Market share dynamics
how can I take market share from my competitor
26
marketing dynamics
how well do the various advertising channels work
27
customer dynamics
what customer are most likely to defect/respond to my offer
28
The analytical process
1. review data quality 2. univariate and bivariate analysis 3. multivariate analyses 4. integrate across data sources Integrate with qualitative insights
29
Types of market research (experimental)
Nonexperimental, quasi experimental, experimental
30
Explorative
``` qualitative focus groups idea generation observation problem scoping ambiguous situations: from symptom to problem ```
31
descriptive
U&A, segmentation, tracking studies, we have considerable understanding of the situation
32
conformity, predictive and causal
driver models, forecasting, causal analysis, groups, marketing mix models, conjoint, experiments, list segmentation.
33
3 main types of descriptive research
U&A's, segmentation studies, tracking
34
Nonexperimental market research
survey, qualitative, observation
35
Quasi experimental
field experiment, conjoint
36
Segmentation
dividing people in distinct groups with distinct characteristics to target them with different makreting mixes
37
key criteria for segmentation
exist, distinctive, targetable, profitable, respond, stable
38
Criteria (EXIST)
the segment must represent a real situation that exists in the market, not a data only situation
39
Criteria (DISTINCTIVE)
are sufficiently different on the relevant variables
40
Criteria (TARGETABLE)
Can be reached by a market intervention
41
Criteria (PROFITABLE)
segments need to be big and valuable enough to go after
42
Criteria (RESPOND)
respond differently to a different marketing mix
43
Criteria (STABLE)
presents an on going situation which lasts for a sufficient amount of time such to allow to extract value from it
44
Difficulty of segmentation
scale often very large (thousands of survey respondents, 30+ questions) Not a well-defined process How to find actionable business outcomes
45
Confirmatory and predictive research
factor analyses, driver modeling, list segmentation/customer base analysis, experiments
46
Brand funnel
Preference, consideration, awareness
47
causality requirements
allows causal inferences to be made--they identify cause and effect relationships.
48
Temporal sequence
the appropriate causal order of events
49
concomitant variation
two phenomena vary together-->there needs to be a relationship
50
nonspurious association
an absence of alternative plausible explanations
51
types of relationships
``` non-linear effects indirect effects lagged effects interaction effects surround sound effects feedback effects secondary effects ```
52
indirect effects
product quality--> overall satisfaction. BUT could be a middle factor like quality of technical support being an effect
53
reverse causility
dependent variable (customer satisfaction) causes independent variables
54
dependent variable
the variable you are trying to predict
55
independent variable
variables that you want to use to make the prediction
56
coefficient or regression coefficient
weight given to a variable to make the prediction
57
statistical significance
whether or not the coefficient statistically speaking is not zero
58
fit of the model or R-squared
the amount of explained variance in the dependent variable
59
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