marketing
activity, set of institutions, and process for creating, communicating, delivering, and exchanging offerings that customers value
how to meet customer needs, profitably
marketing concept
achieving organizational goals requires being more effective than competitors in creating, delivering, and communicating customer value to chosen target markets
what is the difference between marketing research and marketing stretegy?
marketing research
the process of designing, gathering, analyzing, and reporting information to solve a specific marketing problem
not continuous, has a beginning and end
marketing strategy
consists of selecting a target market and designing the proper âmixâ of the 4Ps to meet the wants and needs of consumers
good marketing research â good marketing strategy
when do you use marketing research?
to help identify marketing opportunities and problems
ex: zoom taking the opp. during covid vs. skype
to help generate, refine, and evaluate potential marketing actions
used inâŚ
selecting target markets
product/pricing/promotion/distribution research
to monitor marketing performance
tracking data at the point of sale
tracking social media
strengths + weaknesses (SWOT)
internal capabilities of the firmâs employees
company reputation
customer relationships
satisfaction, retention, recommendation behavior
downstream effectiveness
distribution, pricing, promotion, innovation
perceptions of quality
opportunity (SWOT)
buyer needs or interests that has a high probability of profitability satisfying (external)
threat (SWOT)
challenge posed by an unfavorable trend or development that, without counter action, would lead to lower sales or profit
types of research
basic research
expands general knowledge rather than solving a specific problem
results often canât be directly implemented
applied research
tries to solve specific problems
most marketing research by companies falls into this category
what is marketing information systems (MIS) and what are the 4 components
MIS
the people, equipment, and procedures used to gather, sort, analyze, evaluate, and distribute information to marketing decision makers
internal reports system
gathers information generated within a firm (orders, billings, inventory: accounting related)
daily transactions information (products purchased, payment methods, etc)
intelligence system
brings in information generated outside of the firm
magazines, trade publications, newspapers
decision support system
data collected that will be analyzed to generate decision-making insights
research system
gathers information for a specific situation (ex: what promotion to use or which logo will be more effective)
information not gathered by the other MIS
what are the values of marketing research?
decrease uncertainty
increase the likelihood of a correct decision
improve marketing performance, resulting in higher profits
what are the costs of marketing research?
research expenditures
time needed could delay a marketing decision
possible wrong research results
possible disclosure of information to rivals
when is marketing research not needed?
information is already available
past studies
internal reports in MIS
timing is wrong
do we need to act immediately
is the product at the end of its life cycle
what is the difference between symptoms and problems?
symptoms
observable signs that problems exist
problems
situations calling for managers to make choices among alternatives
problem statements
concise descriptions of problems or opportunities
iceberg principle
decision maker (top of iceberg) â symptoms
researcher (under water) â problems
what do KPIs provide?
measures how well a company is performing relative to an objective
situation analysis
gathers background information helpful in defining the problem
how do research objectives relate to hypotheses?
research objectives (RO)
specified what information is needed to solve the problem
specifies who to gather information from
a research study may have multiple ROs
can be a question or a statement
hypotheses
statements that are taken as true for the purpose of argument or investigation
Unidimensional variables vs. constructs
unidimensional
height, weight, etc.
constructs
multidimensional
abstract concept composed of attitudes or behaviors that are related
research design
specifies the methods that will be used to collect and analyze information for a research project
what are the objectives of a research design?
gain background information
develop hypotheses
measure a variable of interest
test hypotheses about relationship between variables
what are the 3 types of research design?
exploratory research
best when there is little known about the problem
descriptive research
best when problem is somewhat clear
causal research
best when the problem is very clear
exploratory research
unstructured, informal, and often conducted at the beginning of research projects
used to gain background information
used to define terms
used to clarify problems and hypotheses
used to establish research prioties
what are the different types of exploratory research methods?
secondary data analysis
search for and interpret existing relevant information
experience surveys
gather information from those knowledgeable on the relevant issue
leader-user survey
case analysis
viewing information about a past situation that has similarities to the current research problem
focus groups
utilize small groups of consumers guided by a moderator through an unstructured discussion to gain information
what is the purpose of descriptive research studies?
helps describe important market/consumer characteristics and function
process is more formal and well defined
examines who, what, where, and when
helps provide answers to broader questions
necessitates a representative sample
may be gathered with or without directly interacting with respondents
types of descriptive research studies
cross sectional studies
measures units from a sample of the population at only one point in time
sample surveys
longitudinal studies
repeatedly measure the same sample units of a population over time
continuous panels
(related to longitudinal studies)
ask panel members the same questions on each measurement occasion
brand switching studies
market tracking studies
discontinuous panels
(related to longitudinal study)
vary questions from one measurement to the next
causality
a conditional relationship in which a change in a variable(s) affects a change in one or more variables
experiment
(related to causal research)
a study in which one or more IV at a time are manipulated to see how they affect a DV
experimental design
(related to causal research)
provides the setting for us to examine if a change in a DV may be attributed solely to the change in an IV
why do we need control and treatment groups?
to tell if the difference in DV is the result of the change in IV or something else
why is random assignment important?
to ensure that we donât have groups that are fundamentally different
pretest
measures if the 2 groups (that got randomly assigned) are about the same ob an important variable before beginning
before-after testing
the DV is measured in both groups at two time points
(T2 - T1) - (C2 - C1)
A/B testing
we test 2 alternatives simultaneously to see which is better
there is no control group
internal vs. external validity
internal
the extent to which the change in the DV is actually due to the change in the IV
external
the extent that the relationship observed between the IV and DV during the experiment is generalizable to the âreal worldâ
lab vs. field experiments
laboratory
the IV is manipulated and DV is measured in an artificial setting
higher internal validity
field
the IV is manipulated and the DV is measured in its natural setting
higher external validity
what are the uses of databases?
identify prospects
identify customers who requested information and provide them with a personalized sale presentation
sending customized offers
send purchasers of a product an offer for a different one 2 weeks later
reactivate purchases
automated messages can increase customer awareness (on birthdays, after 6 months, etc.)
avoid customer mistakes
identify the most profitable customers can prevent treating them like âany otherâ customer
advantages and disadvantages of secondary data
advantages
quickly obtainable
inexpensive
readily available
can enhance primary data insights
disadvantages
in compatible or unmatched reporting units
ex: you want city-level data, only state-level is available
unusable class definitions
ex: you want data of a city with a population over 80,000, only 60,000+ is available
may be outdated or not credible
competition may have access to the same data
online user generated content
information created by online users that is and intended to be shared with others
social media monitoring
involves actively gathering, organizing, and analyzing social media data to gain consumer insights
3 main social media data platforms
online communities/forums
blogs
social networks
how do we analyze social media posts?
several dimensions of posts
post sentiment (positivity/negativity of post)
post emotions
post length
alsoâŚ
mean post characteristics
number of comments
3 categories of research
quantitative research
qualitative research
mixed methods research
quantitative research
uses structured questions with predetermined response options, response is 'quantifiedâ
qualitative research
involves collecting, analyzing, and interpreting data that is in the form of words or text
mixed methods research
integrates both quantitative and qualitative research methods
qualitative before quantitative
quantitative before qualitative
both at the same time
observation methods
techniques in which phenomena of interest involving people, objects, and/or activities are systematically observed and documented
types of observation methods
direct vs. indirect
overt vs. covert
structured vs. unstructured
in situ vs. invented
direct vs. indirect observation
direct
observes behaviors as it occurs in real time
indirect
observes the effects/results of behavior
archives
physical traces (like popcorn in movie theatre)
covert vs. overt observation
covert
subjects are unaware that they are being observed
overt
subjects are aware that they are being observed
structured vs. unstructured observation
structured
the behaviors to be observed (and recorded) are determined beforehand
unstructured
all behavior is observed and recorded
in situ vs. invented observation
in situ
approaches observe subjects in natural settings (higher external validity)
invented
uses a âsimulatedâ environment (higher internal validity)
advantages and disadvantages of observational techniques
advantages:
insight into actual consumer behavior, not just what they say they do
no chance of recall errors by consumers
applicable to most settings
disadvantages:
behavior observed needs to be relatively short
interpretations are more subjective than analyzing secondary data
does not examine causality
Purpose and objective of focus groups
generate new ideas
understand the vocabulary of consumers
reveal motives, perceptions, and attitudes
deepen understanding of quantitative studies (we see the âwhyâ)
describe (not predict) a phenomenon
advantages and disadvantages of focus groups
advantages:
great for generating new ideas
can be used to understand a wide variety of issues
allow fairly easy access to special respondent groups
disadvantages:
representativeness of target market may be low
depend on moderatorâs skill
interpretation of information sometimes is difficult
ethnographic research
descriptive study of a group and their behavior, characteristics, and culture
shopalongs
mobile ethnography
netnography
thematic analysis
thematic analysis
examines qualitative data to uncover themes (patterns that relate to the objective of research)
researchers look for substantiating examples from what participants said/wrote that provide evidence of a theme
word cloud
eye tracking
measures eye positions and movement
facial coding
measures expressions of emotions by facial appearances
why not just sample the entire populaion?
expensive
too many people
analyzing that much data is difficult
sampling error, sampling unit, sample, population, sampling frame, sampling frame error -- how are they related?
sample unit
the basic level of investigation
sample frame
a master source of sample units in the population (hopefully)
sampling frame error
the sample frame fails to account for all of the population
sampling error
any error in a survey that occurs because a sample is used
could be due to sample selection method
could be due to sampling size
probability vs. non probability sampling
probability sampling
members have a known probability of being selected for the sample
using an objective method to select sample units
nonprobability sampling
probability of selecting members from the population into the sample is unknown
subjective way of selecting samples and based on the knowledge of researcher
what are the 4 probability sampling methods
simple random sampling
systematic sampling
cluster sampling
stratified sampling
simple random sampling
the probability of being selected into the sample is equal for all members of the population
sample size / population size
advantage:
every population member has an equal chance to be selected, so representative
disadvantages:
creating a population list and randomly selecting from it may be time consuming
there still may be sample error if the population is listed incompletely or inaccurately
systematic sampling
a sample is selected systematically from a list using skip interval
population list size / sample size
advantages:
easy and quick way to draw samples
less costly
disadvantage:
if the sample frame doesnât include all members of the population, then they cannot be included in the sample
cluster sampling
the population is divided into naturally existing clusters (subgroups), each of which could represent the entire population
each cluster is assumed to be representative of the population
we take a subsample of a cluster
clusters can be created based on a variety of identifiers
area sampling divides demographic areas into clusters
advantages:
cost effective
easy to implement
the clusters are often readily available
disadvantage:
cluster specification error
when clusters are NOT homogeneous
stratified sampling
population is divided into different subgroups (called strata) and all subgroups are sampled
useful when we think that the units within each stratum are not âbalancedâ
must consider the sizes of the strata relative to the population size to calculate a weighted mean
(data %) + (data * %) âŚ
proportionate stratified sample
sample size scaled to population size
what are the 4 nonprobability sampling approaches
convenience sample
chain referral âsnowballâ sample
purposive âjudgmentâ sample
quota sampling
convenience sampling
draw at the convenience of the researcher
the selection of time, place, and situation is subjective
advantages:
can interview a high number of respondents quickly
good in early stages of research to pretest a questionnaire
disadvantages:
difficult to determine if the sample is representative
results are often not generalizable
often times not much variation in the sample
chain referral âsnowballâ sampling
the initial respondents provide names of other prospective respondents
advantages:
effective when the population is small or unique
helpful when conducting qualitative research
disadvantages:
the generalizability of the results will likely be limited
recommendations are based on the sample unit
purposive âjudgmentâ sampling
requires an âeducated guessâ made by an experienced researcher as to who should represent the population (ex: focus group)
advantage:
can help gather insights from key respondents who may have important insights about larger groups
disadvantages:
the sample likely wonât be representative
depends on the expertise (and possible bias) of the researcher
quota sampling
ensures that specified percentages of the total sample come from various types of individuals or subgroups and selects them in a non-random way
advantages:
can improve the representativeness of a sample, but it is still not random
useful when researchers have a detailed demographic profile of the respondents
disadvantages:
results may not be generalizable
the studyâs sample depends on subjective decisions by researchers
sample size general formula
margin of error
sample accuracy
how close a random sampleâs characteristics of interests (i.e., mean) is to the true populationâs value it represents
as our acceptable margin of error decreases (more precise), the sample size we need increases
the âeâ in the equation (denominator)
variability
refers to how similar or dissimilar responses are to a given question
as variability in the population increases, the sample size we need also increases
the âsâ in the equation (numerator)
how do we estimate variability? what are our options?
we can use data from a previous study on the same population that measured the population characteristic of interest
we can conduct a pilot study of the population
(1/4) * range
confidence level
how confident we want to be that the sample mean will contain the population mean
âzâ in the equation (numerator)
two types of major erros
nonsampling error
all sources of error other than sample selection method and sample size
the wrong problem is specified
the questions are biased
data is recorded incorrectly
the data analysis is wrong
sampling error
any error that occurs because a sample is used
could be due to sample selection method
could be due to sample size
the normal distribution
it is continuous
it is symmetrical
the distribution on each side of the mean is 0.5 (50%)
central limit theorem (CLT)
a sampling distribution derived from a random sample will be normally distributed
68-95-99.7 rule
68.27% of the data is within 1 SD of the mean
95.45% of the data is within 2SD of the mean
99.73% of the data is within 3 SD of the mean
what is the z score?
the number of SD that a value, x, is away from the mean
the z score for 95% is 1.96 because 95% of the area under the standard normal curve is within z scores of -1.96 and 1.96
95% of our data will be greater than or equal to z=-1.96 and less than or equal to z=1.96
calculating sample size with proportions
50 X 50 is a âsafe estimateâ
p = estimated % in a population
q = 100 - p
what are the 5 dimensions of service quality?
reliability
responsiveness
tangibles
empathy
assurance