Advanced Marketing Research v3.0

8/3/2019 Advanced Marketing Research v3.0

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Sridhar Mudhan

MBA 2nd Semester2011

Advanced MarketingResearch

Sridhar Mudhan

MBA 2nd Semester2011


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The KRAs:

I. Internal Exams 2 10 Marks each 20

II. Group activities and Class

participation Below normalized to 10

1. 20 Group activities 5 Marks each 1002. Two Individual field exercises 15

marks each30

3. Class participation 20 20

10

III. Final Exam 70


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UNIT I

Marketing Research - IntroductionWhat is Marketing ResearchBasic and applied researchValue and limitationsOverview of research processUsers and doers


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Life after Death by Powerpoint

http://www.youtube.com/watch?v=lpvgfmEU2Ck


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"The systematic gathering, recording andanalyzing of data about problems relating tomarketing of goods and serviceso Systematic :

Orderliness Impartiality in analysis and interpretation

Definitions


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Basic versus Applied research

"I would say basic research answers questions,whereas applied research solves problems. Sowhere an applied researcher is looking toproduce something useful, a basic researcher is

trying to better understand or at leastcharacterise what's going on.

Readmore: http://wiki.answers.com/Q/What_do_you_un

derstand_by_applied_and_basic_research#ixzz1A8mphwkh"


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Examples of Applied Research

FMCG

Durables

Services


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Steps in Market Research

Problem Definition

Specify Information Needs

Present findings to DM

Identify sources of Info

Decide Techniques forgetting info

Gatherand process info

Analyse and interpret


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Users and Doers

CME

Brand Manager

MR dept

M.RAgency

AD Agency

Syndicated dataservices

Supportservices

Gov Agencies


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Filling a Gap Tata nano

Competition Vodafone zoozoo

Strategic info foodles and maggi

DMT

ool Updating the Org SBI pariwartan

Marketing Orientation Kellogs

Impact assessment KFC ZINGER BURGER

Marketing Mix

Marketing Strategies

Control Techniques

Values and Limitations of MR


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Research can add immense value to

strategic business decision making and result

in a measurable return on investment. The

value of market research is not just aboutmaking more money; it can also be used to

significantly save money. It does save you the

cost of"getting it wrong.

Values and Limitations of MR.


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Values and Limitations of MR.

Further questioning and analysis of the marketers showed that market research is more

necessary in a slow economy than ever- particularly with non-profits and associations who rely

heavily on donations and memberships. Highlighting the importance of market research for

corporate, association and non-profit marketers, they listed key findings andrecommendations:

1. Shape the message; dont slash the price.

2. Focus on who NOT to target.

3. Stand apart from the crowd.

The implications of these show that marketers, particularly in hard economic environment, will

fare better in the long run and in the current market if they invest in knowing what to say and

who to say it to.

http://www.w-r-s.com/blog/2008/08/29/the-value-of-market-research-in-tough-times/


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Market Research -Limitations

http://managementstudyguide.com/limitations-marketing-research.htm

Marketing Research (MR) is not an exact science though it uses the techniques of science

The results ofMR are very vague asMR is carried out on humans who tend to behave artificiallywhen they know that they are being observed

NOT a complete solution to any marketing issue as there are many dominant variables

between research conclusions and market response

M

R is not free from bias.

Many business executives and researchers have ambiguity about the research problem and its

objectives.

They have limited experience of the notion of the decision-making process.

Huge cost is involved inMR as collection and processing of data can be costly.


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Market Research gone wrong?

http://phillygrrl.com/2009/03/13/more-marketing-research-gone-wrong/


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MR Gone Wrong ?

http://www.jokatimes.com/2009/02/11/marketin

g-gone-wrong/

New Coke

RJ Reynolds Smokeless Cigarettes

Harley Davidson Perfume


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MR Gone wrong ?

ExerciseAlpro Soya milk- The company changes the product to remove beanytaste based on research and look at what customers say.

Based on available information:

interpret how research was conducted

how consumers on FB are reacting andPresent what you think the company should do

http://www.facebook.com/topic.php?uid=140939319471&topic=11930


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The bottomline

MR does not go wrong

The practitioners do

Physics is not wrong because the

space craft crashed


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Nature of MR

MR is Input to DMs

A continuous process

Interdisciplinary ( Psychology, social studies, statistical tools, management

principles )

Descriptive

Exploratory

Evaluatory

Predictive

Gives meaning to data

Gathering info internal and external sources Teamwork

A Profession


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UNIT II

Application of Marketing ResearchVariety of applicationsThe Client/ Researcher interface

Articulation with decision stages

Information systems and Marketing Research


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MR- Variety of Applications

Market Size, growth, segments

Products

Sales Force

Channel studies

Advertising

Business expectations/ short term forecasts


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Group Activity Each team to take up one of the following Industry Research type combo and

present a contemporary example

Geography Industry Type of research

1 Global FMCG Consumer

attitudes

2 India Hospitality Customer loyalty

3 Global Consumer

Durables

New product

feasibility4 India Media Consumer habits

5 Global Any category Industry Analysis


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Client Interface

Client Responsibilities

Clear Problem definition

How decisions will be made

Cost/ Budget Context to the problem

Available data

Changes while study is underway

Support to expedite project

Decide priorities

Implementation based on research findings

Feedback


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Client Interface

Researchers responsibilities

Articulate meaning and limitations of exp.findings

Articulate conclusions

Get a good brief

Eliminate Client biases creeping into conclusion


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Client Interface

Sine qua non

Trust

Transparency

Ethical conduct


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Objective Setting

Problem Definition

Problem Environment analysis

Implementation

Decision

Find and evaluate alternatives

Prelim Research

Exploratory

Conclusive

Monitoring

Articulation with decision stages


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Integration with IS

Some Parts of MR could become part of Routine

MIS of the Org

MR agency may need certain routine data with the Org

A good partnership requires good management of

Information flow between organsiation and MR agency


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UNIT III

Research Objectives and Plan :

Research Objectives

Research Plan


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What constitutes a Decision

Research plan and design depends upon

Decisions to be made

Decision definition covers

Decisions objective

Hypothetical solutions to be tested

Payoff criteria for go/nogo

Any constraints


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Types of Research

Monitoring

Preliminary

Exploratory

Conclusive


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Research Objectives

Monitoring Research

Helps discern problems as they emerge early

premptive action

Changes in trends suggest new directions


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Exploratory Study

Deals with C&E relating to number of alternatives

Objective is to generate a set of possible options

Check with

Statistics

Informed Specialists

Consumers orUsers

Research Objectives


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Research Objectives

Preliminary Research

Problem defn to be operational ready to use

How serious is the problem under consideration

compared to other problems

Used when need is to

Improve problem definition

Understand environment and context

Validation of initial feedback data that triggered

research


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Conclusive Research

These are major studies

Objective statement to cover

Scope- All aspects of the study

Constraints ( Time, budget)

Level of detail and sophistication acceptable to client

Data characteristics necessitated by decision needs

Research Objectives


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Research Plan

Research design ( Choice from a menu of

experimental and non-experimental designs)

Research Proposal:

Research Plan

Cost-Benefit

Client Evaluation , Approval

Implement/ Discard / Rework proposal


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UNIT IV : Experimental Designs

The Setting of Experiments True Experimental DesignExtension ofTrue Experimental Design How to select an Experimental Design


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Research Designs

Design- A Pattern or an outline of a Research

Projects working and has

Statement of Objectives, Exp. Output, In Conclusive studies

this shd. Solve problem

Statement of Data, Inputs

Analysis methods

Why Design :

Avoid dependence on researchers memory

Being on same page with Client on all aspects

Refer back to at data analysis and interpretation stage


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Design Types

Descriptive

Experimental

Quasi Experimental


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Causal Relationships influence on

Design

Applicable only in Conclusive Research

Is there a cause-effect relationship between an

action and the objective

Not certainties high or low probabilities can be

assigned


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Conditions for Causal relationships

Strong evidence of connexion between an

action and observed outcome

Non concomitant variation

Action happens before outcome ( Pause)

No other valid explanation

Measured outcome to be identical to Client

objective ( not a weak proxy)


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Cause and Effect

Concommitant variation C & E happen

together

Time sequence of variables C happens

before or simultaneously with effect

Absence of other possible causal factors


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Cause Questions.. Examples

What effect have recent price increases had onproduct class sales?

Does the number of sales calls per month affect the size of the order placed?

Can a new three-class airfare (including a budget or no-frills category)

generate sufficient new passengers to offset the revenue loss of existing

passengers switching to the cheaper category?

What effect has the new sales training program had on sales performance?

Has the new nutritional information disclosure requirement changed

consumer purchasing habits?

http://exporters-sources.com/experimentation-what-are-causal-relationships-2/


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Types of Research Design

Descriptive Describes Phenomena as is

without establishing association between

factors

Experimental Intended to demonstrate causeand effect

Quasi Experimental Yields some quanti

indicators of association between variables


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Descriptive Design

Accurate description of variables relevant to design

Does not demonstrate any relationship between

variables

Only inferences can be drawn about cause and effect Sub types:

Cross Sectional At a point in time across segments

Focus Groups- Better suited for Prelim and Exploratory

studies

Descriptiveesearch case F and

Cross sectionaludy food habits in

Focus Group


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Quasi Experimental Design

One-shot case study - X1 O1 Subjects selected on some basis

Exposed to causal variable

Measurements taken afterwards Example Sales people given training program and

tested on knowledge afterwards ( was program

effective??)

One group- pretest/post test design O1 x1 O2 Measures conditions before test as well

Fails to account forHistory, Maturation and other internal

validity issues


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Longitudinal designs Repetitive measures of

same kind of event over times

Quasi Experimental Designctd

http://www.google.co.in/images?um=1&hl=en&client=firefox-a&hs=ofm&rls=org.mozilla%3Aen-

US%3Aofficial&biw=1024&bih=574&tbs=isch%3A1&sa=1&q=time+series+graph+marketshare&aq=f&aqi=&aql=&oq=


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Static group comparison : Uses control group

versus Test group

Simulation Imitation of a real world situation

Quasi Experimental Designctd

static groupcomparison

Time Series cross

sectionalresearch


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Experimental Designs

Setting of experiments Lab experiments, FieldExperiments

Lab Experiments:

Artificial environment , contrived

Minimizes unwanted effects of extraneous variables

Could use one-way mirrors, cameras, lightingcontrol, temp. control etc.

Need to assess

Internal validity

External Validity


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Lab Expts External validity Issues

Lab population Representative?

Environment at Test time Vs. Environment at

decision time

Treatment in test versus actual application

Measures over a say a 4 week study

extendable to 12 weeks in reality?


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Field Experiments

Conducted in real world

Extraneous factors could affect int.val;idity

More expensive and complex?


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Test Marketing

A special form of Field experiment

Expensive

Could happen over severalmonths

Invites attention and pre-emptive action from

competitors

Test market versus national

representativeness??


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Sources of Error in experimentation

Extraneous factors

History

Maturation

Mortality

Testing Effect

Instrumentation

Selection Bias


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Experimental design notations

X Exposure ofTest group to experimentaltreatment

O Observation of Dependent variable on Test units

R- Random assignment ofTest units as subjects

Left to Right indicates a sequence ( R O1 x O2 ) All notations in one line Subject belongs to that

group

Vertical Notations Simultaneity of events

R O 1 x O2

R O3 O4


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True Experimental Designs

Pre Test Post Test control group design

Solomon 4 group design

Post test only control group design


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Pretest Post Test Control group

Expt. Grp R O1 x O2

Ctrl Group - R O3 O4

Assumes all extraneous factors work equally in bothgroups

Sensitizing aspect present in expt. Group not in

Ctrl grp.

Treatment effect = ( O2 O1 ) (O4 - O3)


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Solomon 4 group Design

http://www.infolizer.com/d41artmouti8a15ed4u/Types-of-experimental-

designs.html


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Used when it is felt pre-testing distorts post-test

results

Pre-measurement for second expt & ctrl group

= (O1 + O 3 )

Treatment effect =

[ { O3 (O1+O3)/2 } - { O6 (O1+O3)/2 }]

Interaction = O2 - O1 { O5 - (O1+O3)/2 }

Solomon 4 group Design

2


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Solomon Group 4

Used when it is felt pre-testing distorts post-test

results

Referred to as Ideal controlled experiment

Isolates most major sources of error in

experiment

Some times impractical

Expensive


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Post Test Only Control Design

Exp Grp R X O1

Ctr Grp - R O2

Treatment Effect = O1 O2 Extraneous factoreliminated


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UNIT V : Measurement and scaling

Managerial Considerations for measurement error avoidanceThe development of Measurement Scaling methodsSelecting the appropriate scaling to use


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Measurement Scales

http://people.math.sfu.ca/~cschwarz/Stat-301/Handouts/node5.html

# Nominal Data

* classification data, e.g. m/f

* no orde

ring, e.g. it makes no sense to state that M > F

* arbitrary labels, e.g., m/f, 0/1, etc

# Ordinal Data

* ordered but differences between values are not important

* e.g., political parties on left to right spectrum given labels 0, 1, 2

* e.g., Likert scales, rank on a scale of 1..5 yourdegree of satisfaction

* e.g., restaurant ratings


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Principles of questionnaire design

http://www.analytictech.com/mb313/principl.htm


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Scales.. Contd

# Interval Data

* ordered, constant scale, but no natural zero

* differences make sense, but ratios do not (e.g., 30-20=20-10, but

20/10 is not twice as hot!

* e.g., temperature (C,F), dates

# Ratio Data

* ordered, constant scale, natural zero

* e.g., height, weight, age, length

Documents

Advanced Marketing Research v3.0