4110 Exam 2

ex: survey

characteristic to be measured: attitude towards gun control scaling: scale on seven-point scale (favor or oppose gun control) measurement: .1-3 favorable attitude .4 neutral .5-7 oppose

recomputing cluster centroids

cluster centroid simply the average of all the points in that cluster

tradeoff matrix

different people could have different tradeoff matrices

simple random sampling

each population element has an equal chance of being selected -simplest method observations: x could be attitudes, market share, value of customer, voting... law of large numbers- given enough time, the house always wins

modern conjoint analysis

establishes contribution of each attribute to a customer's overall evaluations to: -predict market share of a proposed new product, given the current offerings of competitors -predict the impact of a new competitive product on the market share of any given product in the marketplace -determine consumers' willingness to pay for a proposed new product -quantify trade-offs customers or potential customers are willing to make among the various attributes or features that are under consideration in the new product design -identify consumer segments

one stage cluster sampling

ex: we want beer consumption of students -choose blocks of dorms/apartments -find beer consumption of all students in sampled blocks

two stage cluster sampling

ex: we want candy preferences of all kids in US -treat zipcodes as clusters -first stage: random sampling of zipcodes -second stage: random sampling of households in each zipcode selected in first stage

why firms use conjoint

firms want to increase profits by providing the product features that consumers value

randomized response approach

flip the coin...

when not to use exploratory research

for conclusive results

how surveys are answered

interpret question: -retrieve info form judgment -map judgments onto response scale

Summary of scales

look at chart

communication methods of data collection

mail, fax, telephone, in home interview, mall intercept, internet

convenience sample

-accidental, based on ease of accessibility -mall intercept -radio station asked people to call in disadvantage: not representative

Profiling Clusters

-how big is the segment -how fast is the segment growing -where do they shop -how do they buy -how often do they buy -how much do they buy -how do they use the product

profile analysis (snake plot)

-application of semantic differential scale -overall comparison of brands hard to grasp with many brands and attributes -not all attributes are independent -plot mean ratings for each object on each scale for visual comparison -a snake plot connects the mean value on each attribute -typically place positive descriptors on the right

actionability

-are customers in the segment and the marketing mix necessary to satisfy their needs consistent with goals and core competencies of the firm -will segmentation help develop effective marketing message?

Cluster Limitations

-assumes that the clusters are in circular way, if they are thin and long then it tends not to work well -comparing python clustering algorithms

k means clustering

-belongs to non-hierarchical class of clustering algorithms -aims to partition n observations into K clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster

accessibility

-can managers reach the identified segments -how to reach through promotion and distribution

identifiability

-can managers recognize segments (profiling) -through demographics

number of clusters: elbow criterion

-choose a number of clusters so that adding another doesn't add sufficient information -minimize the within cluster variance and maximize the between cluster variance -ratio of within to between cluster variance is plotted against the number of clusters -the point at which a sharp bend occurs indicates the number of clusters

setting up focus groups

-define research objective -communication with moderator -define target participants

types of primary data

-demographics -psychographics -awareness -intentions -motivations/benefits -behavior

deciding on order, wording, and layout

-do any words have vague or ambiguous meanings -are there any questions double barreled -leading or loaded questions -potentially confusing instructions -applicable to respondents -appropriate length -order bias

sustainability

-do the segments represent a large enough portion of the market -are segments big enough for marketing programs to be profitable

ideal characteristics of cluster sampling

-each cluster is a small scale representation of target population -each cluster is as heterogeneous as the population -clusters should be as similar to each other as possible

probability samples

-each unit has a known probability of being included in the sample -simple random sample -sampling error can be inferred often more expensive

conjoint: new products

-estimate market share of brands that differ in attribute levels -determine attribute composition of most preferred brand

qualitative research characteristics

-exploratory research -less structured than other types of research --high degree of flexibility -number of respondents is typically small --usually not representative of population

non-probability sampling: circumstances

-exploratory research -pre-testing a questionnaire -when probability samples are almost impossible --difficulty in acquiring a suitable sampling frame -generalizability of research

Horizontal attributes

-features that can't be ordered in an objective way -ex: design

conjoint overview: objective

-find importance of attributes and levels of attributes -conduct what-if analysis (sales, market share)

when to use exploratory research

-gain background information -problem formulation aid -identify alternative courses of action -develop hypotheses -isolating key variables -defining terms -establishing priorities for future research -help interpret conclusive research -for dependable estimates of market characteristics -for establishing cause and effect relationships

cluster analysis is a means of segmenting markets

-goal: find groups of similar consumers -group them together -describe each group for subsequent targeting and positioning

takeaways: sampling

-a badly chosen big sample is much worse than a well-chosen small sample -be careful about selection bias and nonresponse bias

qualitative research purposes

-access consumers' mind --experience, concerns, perceptions, feelings, thoughts, intentions, motivations -understand range and complexity of consumer thoughts --develop consumer vocab

qualitative approach unstructured approach: advantages

-individual's organization of a relatively unstructured stimulus indicates individual's basic perception/feelings -the more unstructured the stimulus, the more individual has to project his/her own emotions, needs, attitudes, values -questionnaire: highly structured (choose from a set of alternatives) -record feelings as you watch this ad: unstructured (choose own interpretation)

focus groups v. quantitative research

-insights not rules -social not individuals -homogenous not diverse -flexible not standardized -words not numbers

survey

-involve questioning -yield primary data -all primary data don't come from surveys

disadvantages: observation

-may not be representative -subjective interpretation -inability to learn why

one-on-one interviews

-more in-depth than focus groups -enhances discussion and independent thought -criteria for success --establishing relaxed sympathetic relationship --ability to probe/clarify without biasing results

advantages: observation

-natural environments -no recall error -sometimes it's the only way

conjoint overview: how it works

-new (hypothetical) products are created as profiles (combo) of attributes and attribute levels -consumer respondents rate new products in a survey -regression analysis applied to ratings

interval scale

-numbers used to rank objects also represent equal increments of the attribute being measured -differences can be compared -entire range of statistical operations can be employed for analysis what can you identify -distribution of brand preferences -most popular brand -second most preferred item for each person -mean rating of each brand

nominal scale

-objects are assigned to mutually exclusive, labeled categories -no necessary relationships among categories -only possible arithmetic operation is a count of each category -which of the following brands do you prefer what can you identify -distribution of brand preferences -most popular brand -no ordering or spacing is implied

formulating questions

-open ended v. close ended open ended -important to measure the salience of an issue to a respondent -there are too many responses to be listed or cannot be foreseen -verbatim responses are desired to give the flavor of people's answers or to cite examples close ended -information requirement is clear and known

disadvantages of asking

-people may not know what group they belong to -people may believe they belong to multiple groups -researcher often doesn't know what groups exist in the market

survey characteristics

-population has been defined correctly -sample is representative of the population -respondents selected are able and willing to cooperate -questions are understood by the respondents -respondents have the knowledge, opinions, attitudes or facts required -interviewer correctly understands and records the response

non-probability samples

-probability of units being included in the sample is unknown -mall intercept -sampling error cannot be inferred often less expensive

judgment sample

-purposive -elements are hand picked to obtain better results -swing states in election -classify types of ads -identify strengths and weaknesses

ordinal or rank scale

-ranks objects or arranges them in order by some common variable -does not provide info on how much difference there is between objects -arithmetic operations are limited to statistics such as median or mode what can you identify -distribution of brand preferences -most popular brand -have ordering but no spacing is implied

focus groups: disadvantages

-recruiting problems -group peer pressure -dominant personalities -hard to quantify results -small sample size -can't generalize to target population

focus groups: advantages

-relatively quick info -stimulate new ideas -relatively inexpensive -very flexible -very spontaneous -group interaction

nonresponse bias

-respondents differ in meaningful ways (systematically) from nonrespondents (the differences are not random)

planning what to measure

-revisit the research objectives -decide on the research issue of your questionnaire -get additional information on the research issue from secondary data sources and exploratory research -decide on what is to be asked under the research issue

K means advantages

-robust to different types of variables -appropriate for large data sets common in mktg -less sensitive to some customers who are outliers

disproportionate samples

-sample sizes are not proportional to stratum sizes -more heterogenous group --> more samples

drawbacks: non-probability samples

-sampling units elected by interviewer, usually those who are most accessible, at home, with time, acceptable appearance -sample may not represent target population (convenience) -difficult to project sample results to target population

selection bias

-selection of individuals groups or data for analysis such that proper randomization is not achieved -sample obtained is not representative of the population intended to be analyzed

Vertical attributes

-several levels that are present can be ordered according to their objective quality from highest to lowest -it's possible to say in this case that one good is "better" than another ex: MPG, Price etc

typical focus group

-size 8-12 -length 1.5-2 hrs -data collection 1. transcribe 2. audiotape -moderator (flexible yet focused) (use interview guides) -reporting formats (selected quotations) (analysis of repeated themes)

focus groups

-solicit opinions, ideas, and emotional responses to particular topics or issues -discussion between small groups of people selected from a demographically relevant population (target market) -moderator facilitates and guides discussions -need video recording for further analysis

semantic differential scale (opposites)

-subjects asked to check the cell between a set of bipolar adjectives that best describes their feelings -most popular way in marketing research to obtain attitude toward an object -anchored at each end by an adjective --often bipolar (inconvenient-convenient) --sometimes monopolar (sweet-not sweet) -sometimes difficult to find bipolar opposites -colorful (colorless), emotional (rational), calm (excitable)

how to study attitudes

-surveys: measure of attitudes -measurement: assigning numbers to reflect the relative or absolute amount of some property --scales: creation of a continuum on which measured objects are located --scales are measurement tools -Goal is to achieve objectivity: "when description gives way to measurement, calculation replaces debate"

key concepts: sampling

-target population: entire body of interest -sampling error: from sampling -non-sampling error: systematic error

analysis of features considered jointly

-technique that enables a researcher to estimate consumers' valuations of different attributes -allows us to understand how consumers make trade-offs among attributes/characteristics of products and services -how much are consumers willing to pay/give up to get/avoid different attributes

quota sample

-to ensure representativeness (chi square) -sample is similar to population on a number of variables -age and gender disadvantages: units selected or discarded by interviewer to fit quota`

ratio scale

-type of interval scale with meaningful zero point -possible to say how many times greater or smaller one object is than another -only scale that permits comparisons of absolute magnitude what can you identify -distribution of brand preferences -most popular brand -second most preferred item for each person -mean purchase intention quantity

basis for stratification

-use criteria that are related to whatever you are measuring -ex: gender as strata for average height -income of tulane grads, by major

conjoint: pricing/valuation

-use info about consumers valuation of attributes to guide pricing strategy for a product line (iPod) -brand name equity: what's in the name?

sensitive questions

-use less threatening terminology -use counterbalancing statements -ask about others -ask after a chain of diffusing questions -ask from a range of responses (frame of reference)

conjoint overview

-useful marketing research technique to develop new products -experimental, using surveys

segmentation fails

-using same segmentation scheme for different objectives (dif. advertising or dif. products) -too much focus on techniques -using only psychographic or demographic variables -not focusing on differences in customer needs -static segmentation schemes -lack of senior managment Judgement and speculation = critical because you will never have all the info you want -usually not enough time to collect info -costs a lot to collect all info -someone will often prevent you from collecting it -consumers can't give it to you -consumers won't give it to you -collecting may tip off competitors

how to get consumer evaluations

-very nice but we don't know consumers valuations of attributes -consumers prbly don't know own values -Solution: force consumers to rank different bundles of attributes

implications for big data

-very reason why they are available is technology -users of technology are typically not representative sample of the population

trade-offs

-would consumers pay 35 cents more for a plastic bottle? -what is more important: texture or flavor? -who would be willing to have a heavier laptop in order to double the processing speed? -what do I care more for in a potential boyfriend: looks or brains?

K means: How to

1. choose number of clusters K 2. generate K random points as cluster centroids 3. assign each data point to the nearest cluster centroid 4. recompute the new cluster centroid 5. repeat steps 3-4

popular scales

1. constant sum scale 2. likert scales (agree-disagree) 3. semantic differential scale (opposites) 4. profile analysis (snake plot)

6 steps of drawing a sample

1. define the target population 2. identify sampling frame 3. select sampling plan 4. determine sample size 5. select sample elements 6. collect data from sample

examples of basis of segmentation

1. demographic characteristics 2. psychographics (lifestyle) 3. desired benefits from products/services 4. past-purchase and product-use behavior

stage 2 conjoint

1. design a data-collection procedure 2. select a computation method for obtaining part-worth

steps: cluster analysis

1. formulate the problem and select the variables you want to use as the basis for clustering 2. compute the distance between customers along the selected variables 3. apply the clustering procedure to the distance measures 4. decide on number of clusters 5. map and interpret clusters and draw conclusions

effectiveness of a segmentations scheme

1. identifiability 2. sustainability 3. accessibility 4. actionability

what can go wrong with predictions

1. initial sample bias (selection bias) 2. low response rate combined with a nonresponsive bias

types of qualitative methods

1. observation 2. focus groups 3. one-on-one interviews 4. projection techniques

why stratification

1. obtain more reliable results 2. to guarantee minimum sample sizes so analyses can be done at the stratum level

designing questionnaires

1. plan what to measure 2. formulate questions to gather the needed information 3. formatting: decide on order, wording, and layout 4. pretest 5. correct the problems

stage 3 conjoint

1. segment customers based on part-worth 2. design market simulations 3. select choice rule

stage 1 conjoint

1. select attributes relevant to product/service 2. select levels for each attribute 3. develop product bundles to be evaluated

evaluating segmentation scheme

2 acid tests -is there heterogeneity between segments? is there homogeneity within segments -are these differences and similarities based on how the customers will respond to your value proposition

recruiting

3-4 sessions 8-12 people homogenous group screening interviews incentives (if you pay) avoid professional focus group participants

observation (ethnography)

4 elements 1. directness (att and wendy's ex) 2. disguise (bose ex) 3. structure (researcher previously knows what research will occur) 4. observation system (state of Florida and tourism)

Grouping consumers

Goal: find similar and different groups -what is close and what is far

snowball sampling

I go to vegas and would like to study the nefarious business of prostitution -sample prostitutes (not legal) -sample pimps -brothels

elements of strategic marketing

Segmentation: dividing market into groups of buyers who are -similar in meaningful ways -dissimilar from other groups Targeting Product positioning

why conjoint analysis

asking direct questions about preferences often leads to unenlightening answers -what load would you like to pay on your mutual fund -what annual fee would you like -would you like online access to funds -CONSUMERS WANT EVERYTHING AND WANT IT FREE

measurement scales

assigning numbers -to subjects (customers) -regarding attributes (attractiveness) -objects (brands)

cluster analysis

a class of statistical techniques that can be applied to data that exhibit natural groupings -no distinction between dependent and independent variables -sort through the raw data on customers and groups them into clusters

cluster

a group of relatively homogeneous data points -primary input is an analysis of similarity between customers -correlation coefficients -distance measures -association coefficients

sampling frame

a list of elements from which the sample is drawn (physical representation of target population) -individuals, households or institutions -every unit is uniquely identified -all units can be found in the frame -no units not in the population of interest are in the frame -data is up-to-date

part-worth model

a simple but very useful representation of preferences -suppose there are K attributes describing the different brands. The "utility" or "worth" of any given brand j is then assumed to be total utilities ex: worth of (Austin, $130K) = Worth (Austin) + Worth ($130K)

closed ended responses

advantages -easier to answer -require less effort by interviewer -tabulation and analysis is easier -less potential error in the way the question is asked and the way it is recorded -the responses are directly comparable from respondent to respondent disadvantage -answer to a closed response will be received no matter how relevant the question is -may not produce meaningful results -dichotomus questions are prone to a large amount of measurement error -provides fewer opportunities of self expression -alternative responses not considered by the respondent, leading to selection of a reasonable response

likert scales (agree-disagree)

ask respondents the extent to which they agree or disagree with a statement -usually 5-7 point scale -typically used item by item and also a summed scale comparing two options across all measurements -easily understood but can take a long time complete when a large number of attitudes are being measured -items for measuring patients' attitudes about interactions with physicians' service staff (all with same scale)

attitudes

mental states used by individuals to structure the way they perceive their environment and guide the way they respond to it -attitudes drive behavior components: -cognitive or knowledge component -affective or liking component -intention or action component

why recovering importance works

more realistic questions -if you choose left you prefer portability, right you prefer processing power -rather than ask directly whether you prefer portability over speed, we present realistic tradeoff scenarios and infer preferences from product choices -when respondents are forced to make difficult tradeoffs, we learn what they truly value

conjoint: services

mutual fund = past returns + fees + brand name + online access value of aircraft = capacity + max range + fuel efficacy + price + service contract

constant sum scale

often used to measure importance -generally do not want to have more than 5-7 features or the allocation process gets too hard

segmentation

organizing customers into groups with similar traits, product preferences, or expectations Goal: homogenous segment

laddering example

personal value benefit product attribute

cluster sampling

population is divided into "clusters" -clusters are drawn randomly and units are observed in clusters 1. parent population is divided into mutually exclusive and exhaustive subsets -same as stratified sampling -different criteria 2. random sample of subsets is selected -sometimes there is reason to draw groups (clusters) and observe units within the sampled cluster why: 1. reduce costs of interview 2. more convenient when complete sampling frame is missing, but a sampling frame of clusters is available

stratified sampling

population is divided into "strata" a simple random sample is drawn from each subset -divided into mutually exclusive and exhaustive subsets -a simple random sample of elements is chosen independently from each subset ideal characteristics: homogenous within strata and heterogeneous across strata

sampling

population, census, and sample -population = any complete group with at least one characteristic in common -population may be studied using one of two approaches: taking a census, selecting a sample -census: survey every member of population -sampling: selection of a part of the population -both provide info to draw general conclusions about entire population standard error decreases as we increase the number of samples

consumers are heterogeneous

poses a challenge for the development and marketing of profitable products and services

relative importance of attribute

range of part-worths for attribute/sum of ranges of all attributes

laddering

seeks to discover relationship between product attributes and customer benefits and personal values 1. ask questions about attribute level -what product attributes/features are important -what product attributes/features make them buy (not buy) like (not like) the brand 2. ask why these attributes/features are important (functional and psychological consequences benefits) 3. ask why these consequences are important and what are the ultimate goals that are being satisfied

probability sampling

simple random sampling stratified sampling cluster sampling

Conjoint study process

stage 1: design conjoint study stage 2: obtain data from a sample of respondents stage 3: evaluate product design options

cluster v. stratified sampling

strata- all groups included; homogenous cluster- random selection of groups; heterogeneous

structured & undisguised

typical questionnaire: what is your age +easy to store in a dataset +frame of reference is clear from alternatives +alternatives help to make question clearer -loss of info through response categories: -forced to reply -no accurate category listed -no opinion

why use laddering

ultimately, consumers want to know what's going on -enhance communication strategies -enhance product development

projective techniques

vague stimulus = unbiased consumer response -word association (brand names, slogans) -sentence completion -storytelling -respondents projected into simulated activities -useful when respondents may be hesitant/unable to answer direct questions

pretesting

variation meaning task difficulty respondent interest and attention -test flow of questionnaire for clarity and logic -ensure that skip patterns are clear and well laid out -time each section so it's not too long -capture and maintain respondent interest and attention

conjoint: directly asking can also be misleading

when people are directly asked, they want -durability + quality + reliability but from conjoint consumers really care about -Price + Design

unstructured & disguised

when respondents have reason to hide their feelings or when they cannot express them accurately 1. ask respondent about what others think 2. projective techniques: respondent is given a vague task, response is used to deduct respondents feelings