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1
Q

Classification of Market Research

A

Problem Identification & Problem Solving Research

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2
Q

Market Research Process

A
  1. Defining the Problem [MDP & MRP]
  2. Developing an Approach to the Problem [How it will be addressed - Framework/Model, Research Q’s & Hypothesis, Specification of Information]
  3. Formulating a Research Design [Framework for conducting research- Explorator, Descriptive, Casual]
  4. Doing Field Work or Collecting Data
  5. Preparing and Analysing Data
  6. Preparing & Presenting the Report
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3
Q

Problem Definition & Approach Development Process

A
  1. Initial Research: Discussion with DM’s, Interviews with Experts, Secondary Data analysis, Qualitative Research
  2. Environmental Context of Problem
  3. Problem Definition - MDP & MRP
  4. Approach to Problem - Framework/Model, Research Q’s & Hypothesis, Specification of Information
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4
Q

Defining the Problem

A

Conduct problem audit:
Events lead to decision that action needed
Alternative Caourses of Action available
Criteria for evaluation of alternative actions
potential actions that are likely to be suggessted
information needed to answer DM’s questions
ENVIRONMENTAL FACTORS:
past info & forecasts
resorces and constraints that restrict scope definition
objectives of the organisation and decision maker
buyer behaviour
legal context
economic environment
marketing and technological skills.

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5
Q

MDP

A

ASKS: What the DM needs to do
IS: Action Oriented
FOCUSES ON: Symptoms

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6
Q

MRP

A

ASKS: What information is needed
IS: Information Oriented
FOCUSES ON: Underlying causes

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7
Q

Approach to Problem

A
  1. Analytical Framework and Models - Verbal, Graphical, Mathematical
  2. Research Questions and (possible answers) Hypotheses
  3. Specification of Information Needed
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8
Q

Research Design Framework

A
  1. Define Information Needed
  2. Design the research phases - exploratory, descriptive and/or causal
  3. Specify the measurement and scaling procedures
  4. Construct & Pretest questionnaire
  5. Specify sampling process and size
  6. Develop a plan of data analysis
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9
Q

METHODS: Exploratory Research

A

Survey of experts, Pilot Surveys, Case Study, Secondary Data Analsyis, Qualiative Research

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10
Q

Exploratory vs Conclusive Research

A

Objective: To Provide Insighs and Understanding vs To test specific Hypotheses.
Characteristics: Loose definition of information needed, flexible and unstructured process, small size, qualitative analysis vs Clearly definined information needs, formal and structure dresearch process, large sample, quantiative analysis.
Findings: Tentative vs Conclusive

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11
Q

METHODS: Descriptive Research

A

Secondary Data analysis, surveys, paels, observational data.

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12
Q

Cross Sectional Research

A

Designs involve the collection of information from a sample population at a single point

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13
Q

longitudinal research

A

Design involves collection of information from a fixed sample population repeatedly.

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14
Q

PURPOSE: Descriptive Research

A

To describe the characteristics of relevant groups/population

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15
Q

PURPOSE: Causal Research

A

To establis cause-and-effect impacts of relationships

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16
Q

METHODS: Causal Research

A

Expirements.

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17
Q

DESIGN Acryonym

A

D-Data Analysis Pln
E - Exploratory, descriptive, causal design
S - Scaling and Measurement
I - Interviewing forms: Questionnaire Design
G - Generating the needed information
N - Number: Sample size and plan

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18
Q

DEFINITION: Secondary Data

A

Data that already exisits and that is collected for the purpose other than need at hand.

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19
Q

Secondary Data Classification

A

Internal - Customer Databases, Data Warehousing & Mining, CRM & Database Marketing, Social Media
External - Syndicated Services, Government, Business/Nongovernment, Social Media

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20
Q

PROS/CONS: Secondary Data

A

PROS: Helps identify MRP, Helps develop an approach to problem, Answers questions and tests hypotheses, Cheaper and faster than primary Research
Cons - May be collected for other problems, may not be useful or irrelevant, may not be collected appropriately for this purpose, may be inacurate

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21
Q

CRITERIA: Evalating 2ndry Data - SECOND

A

S - Specifications: Data collection methodology
E - Error: Accuracy of Data
C - Currency: When the data was collected
O - Objective: Purpose for collection
N - Nature: Content of the data
D - Dependibility: How dependable is data

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22
Q

Secondary Data: Overcoming Disadvantages

A

Use Reliable Sources
Evaluate the primary source research Design
Assess the purpose of publication
Use multiple sources to help verify the quality of Secondary Data
Use information that is as relevant as poss.
Use original Source
Use most current data.

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23
Q

PROS/CONS: Surveys

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A

PROS: Easy, Reliable Results, Simple codifying and Analysis
CONS: Respondents Unable or unwilling to respond, Fixed results may mean loss of data validity, question wording difficult

24
Q

Modes of Survey Admin

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A

Telephone
CATI
Personal interview at home
Mall intercept Personal Interview
CAPI
Mail Interview
Mail Panel
Email Survey
Internet Survey

25
DEFINITION: Syndicated Data
Common pools of data that have a known commercial value that is collected and sold
26
CLASSIFICATION: Syndicated Data
HOUSEHOLD/CONSUMER Surveys: Physographic/Lifestyles, advertising evaluation, general Panels: Purchase & Media electronic Scanner Services: Volume Tracking Data, Scanner Panels, Scanner Panes with Cable TV INSTITUTIONS Retails/Wholesales: Audits Industrial Firms/Organisations: Direct inquiries, Clipping Services, Corporate Reports
27
SYNDICATED DATA: Panels
PROCESS - Record purchases and behaviour in diary/over internet. MAKEUP - Representative of the target population in terms of demographics. Electronic recording methods have made more accurate. Useful for estimating market share, forecasting sales, assessing brand loyalty.
28
SYNDICATED DATA: Surveys
Can be used for marget segmentation, consumer profile development or determining consumer preferences. PROS: Very flexible regarding content and aids, enables targeting of respodnents with specific characteristics CONS: Data may not be accurate, ncorrect recollection or pressured answering from respondents, questions may be biased, results misinterpreted. PANELS ARE BEST
29
SYNDICATED DATA: Purchase Panels
Physical recording of purchase habits.
30
SYNDICATED DATA: Media Panels
Electronic recording of media consumption. Television, Radio, Internet, Mobile.
31
SYNDICATED DATA: Pros & Cons
PROS: accuracy of datam generation of longitudinal data, reduce recall errors and human error CONS: might not be representative of larger population, response errors inherent in maintaining a panel. Underrepresented society groups, time committment of participant.
32
SYNDICATED DATA: Scanner Data
PROS: prompt feedback, most accurate, less response bias and recall error, store variables recorded. CONS: lack of representiveness of WHOLE industry Only as good as scanning process
33
SYNDICATED DATA: Audit Data
PROS: Relatively accurate information of many products at wholesale and retail levels CONS: Limited retail coverage, delay due to compiling and reporting, not linkd to consumer characteristics.
34
Criteria for selecting Survey Method
If no method is clearly superior - consider overall consideration of advantages and disadvantges. __________ complex and diverse or physical stimuli: personal methods are preferable (Capi, In-home, Mall intercept) sample control issues: cold mail, fax and electronic may not work high Data quantity: in-home and mail panels low response rates: cold mail and electronic disadvantages social disarability issues: Mail, mail panel and internet are best interview bias problems: mail, electronic are favoured Speed: Internet, email & telephone Cost: Cold mail, electronic, mail panels, telephone, mal intercept, capi and in-home (IN THAT ORDER)
35
SURVEY: improve response Rates
Prior Notification, Incentivisation (Money/Nonmonetary), Follow-Up
36
Measurement
The assignment of numbers to characteristics according to pre-specified rules so that statistical data analysis is possible.
37
Scaling
creation of a continuum upon which measured objects are placed. Allows classification of consumers according to attitudes.
38
Scale Types
Nominal : numbers serve only as labels for indentifying or classifying objects (do not reflect amount of characteristics) Ordinal: which numbers are assigned to objects to indicate the relative xtent to which some characteristic is possessed. Interval scale: numbers used to rank objects which are numerically equal distances on a scale. (i.e. time/temp) ratio : identify or classify objects, rank order the objects and compare intervals/differences
39
Scaling Techniques: Comparative
Comparative: direct comparison of stimulus objects with one another. Done in relative terms - Ordinal/Rank only. Methods: Paired Conmparison Scaling (select one object of two on offer). Rank order scaling ( presented with several objects, asked to order or rank them)
40
Scaling Techniques: Non-Comparative
Non-Comparative: Does not compare against another object or standard. One object evaluated at a time - monadic scales Continuous rating Scale: rate objects by placing at an approproate position on a line that runs from one criterion to another Itemised Rating scale: Have number or brief descriptions associated with each category. Required to select which best describes - Likert, Semantic Differential Scale, Stapel all this type.
41
Likert Scale
Indicate degree of agreement or disagreement with a series of statements.
42
Semantic differential scale
Rating scale with end points associated with bipolar labels that have semantic meaning
43
Questionnaire Design Process
1. Specify the information needed 2. Specify the type of intervew method (will effect nature of qustions) 3. Determine question content (do you need some double-barrelled) 4. Desin Questions to overcome unwillingness or inability to answer 5. Decide on Question structure (Unstructured (at start) vs Structured) 6. Determine quesiton wording 7. Arrange the question in proper order 8. Identify the form and layout 9. Reproduce the questionnaire 10. Eliminate Bugs by Pretesting.
44
Overcome unwillinness and inability to respond
Factos that limit ability: Are they Informed? Can they Remember? Can they Articulate Combating Unwillingness - manipulate context for appropriateness of request, Explain legitimate purpose of data collection, assure security of data.
45
Wording Question
Define the Issue Use Ordinary Words Avoid ambigious words avoid leading questions avoid implicit aassumptions avoid generalisations and estimates
46
Question Order
Start with interesting, simple and non threatening questions before moving into more difficult, complext, sensitive or dull questions --> USE a FUNNEL approach
47
General Question Order
Qualifying/Screening Questions Inroductory Questions Main Questions Easy Main Questions More Difficult Psychographics/Lifestyles Demographics Iedntification information
48
DEFINITION: Census
A complete enumeration of the elements of a population or study of objects
49
DEFINITION: Sample
A subgroup of the elements of the populaton selected for participation in the study.
50
DEFINITION: Population
The aggregate of all of the elements that share some common set of characteristics and that comprise the universe for the purpose of the MRP.
51
Sampling: Defining the target population
The collection of elements or objects that possess the information sought by the researcher and about which inferences are to be made. Define in terms of: Element - is the object about which or from which the information is desired. Sampling Unit: is an element or a unit containing the element that is available for selection Extent: Geograpic Boundaries Time: Time period under consideration
52
Sampling Design Process
1. Define the Population 2. Define the Sampling Frame 3. Select Sampling Technique 4. Determine the Sample Size 5. Execute the Sampling Process
53
Sampling Frame
Consists of a list of directions for identifying the elements of the target population
54
Sample Frame Error
A survey error caused when the sample frame is not a perfect representation of the population. (false respondents)
55
Reducing Sample Frame Error
1 - Redfining the population in terms of the sampling frame (turning te frame into the population) 2 - Screening respondents through qualifying questionnaires 3 - Applying a weighting scheme to counterbalance errors (statistically adjust the sample by weighting over or under represented segments).
56
Sampling Techniques
Non-Probability: relies on personal judgement of reseacher to arbitrarily/consciously decide which elements to includez. Probability: selected by chance - everyone has a non-zero chance of being selected (evenly) - requires precise definition of target population and specificatin of sampling frame
57
Sampling Types
Non Probability --> Convenience Sampling, Judgement Sampling, Quota Sampling, Snowball Sampling Probability --> Simple random, Systematic, stratified, cluster

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