Research Marketing Exam 1

Marketing

he activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large

Marketing Research

• the process of gathering and analyzing data to solve marketing problems, including:

  • identifying marketing problems and opportunities

  • generating, refining, and evaluating marketing actions (the 4 Ps/Markeitng Mix)

  • monitoring marketing performance

  • improving marketing as a process

where does marketing research belong?

• in every stage of the strategic marketing process:

  • situation analysis (SWOT)

  • STP (segmentation, targeting, positioning)

  • marketing mix (4 Ps)

What are the 4 Marketing Eras?

• Production (to 1930)

• Sales (1920-1970)

• Marketing Concept (1950-2000)

• Customer Relationship (1990-now)

Production Marketing Era

• to 1930

• focus and driver:

  • quantity and quality (production first); mass production after the industrial revolution

• Role of marketing research

  • little use, except to learn about distant markets

Sales Marketing Era

• 1920-1970

• Focus and Driver:

  • pushing products (sales first); Great Depression, supply>demand

• Role of Marketing research:

  • forecasting demand, evaluating ads and salesforce performance; research firms (Nielsen, Gallup) are born

Marketing Concept Marketing Era

• 1950-2000s

• Focus and Driver:

  • discovering and satisfying needs (customer need first); consumers defensive to ploys

• Role of Marketing:

  • understanding needs, designing the 4Ps, measuring satisfaction; computerization

Customer Relationship Marketing Era

• 1990-now

• Focus and driver:

  • long term relationships (relationship first);power shifts to buyers

• Role of Marketing research:

  • digital tracking, CRM, AI, big data

The Marketing Research Process (11 Steps)

1. establish the need for marketing research

2. define the problem

3. establish research objectives

4. determine research design

5. identify information types and sources

6. determine methods of accessing data

7. design data collection forms (questionnaire)

8. determine sample plan and size

9. collect data

10. analyze data

11. prepare and present the final research report

Remember that this is a problem solving process that doesn’t have to happen in this order

Step 1: When is marketing research not needed?

• the informatio is already available

• the timing is wrong: a decision must be made now (ex. competitor is rising at an alarmingly fast rate)

• costs outweigh the benefits

• funds aren’t available

Step 2: define the problem (Problem)

• situations that call for managers to choose among multiple decision alternatives. If there are no alternatives, there is no problem

• Problems arise from a gap:

  • supposed/expectations

  • Did/reality

  • could/Ideal

• Supposed vs. Did: something went wrong (satisfaction below expectations)

• did vs. Could: an opportunity (how can Best Buy raise awareness by 40%)

• AVOID: don’t define problem too broadly/narrowly

Step 3: Research objectives

• goal oriented statement of what the researcher must do to solve the problem

  • what information is needed

  • from who it’s gathered

  • the unit of measurement

  • the wording of questions used

Step 4: Research Design

• a master plan, decided in advance, specifying the methods and procedures for collecting and analyzing the needed information. It cannot be skipped, there is no single best design, and it’s chosen after consideringn the problem and research objectives

Exploratory Objectives

• Purpose: background information, clarify the problem, generate hypothesis

• When: early stage, high uncertainty

• Methods: secondary data, experience surveys, case studies

• Findings: tentative, needs follow up

Descriptive Objectives

• Purpose: describe a population or market; the 5Ws

• When: after background is known

• Methods: cross sectional or longitudinal studies

• Findings: conclusive

Causal Objectives

• Purpose: test cause and effect-why (If,then)

• When: problem clearly degined

• methods: experiments (A/B test, test markets)

• Findings: conclusive and casual

Exploratory Research

• unstructured, informal research to clarify the nature of the problem. Its four uses are to gain background information, degine terms, clarify problems and develop hypotheses, and establish research priorities

• Methods

  • Secondary Data Analysis

  • Experience Surveys

  • Case Studies

Secondary Data Analysis

magazines, literature review, industry reports

experience surveys

talk to knowlgeable people (executives, experts, market mavens, focus group)

case studies

examine past situation analogous to the current problem

descriptive research

• descibes characteristiccs of a population or market and produces numbers (market share, customer profiles, sales qutoas by district, satistfaction scores)

  • cross sectional study

  • longitudinal study

cross sectional study

measure a smaple once, at one point in time

longitudinal study

measure the same sample units repeatedly over time; produce panel data. Only panel data can show change over time within the same people, such a brand loyalty

Casual Research

uses experiments: the researcher manipulates the cause and uses random assignment or a control group to isolate the effect (color vs. B/W —> brand awareness)

data types and sources

always examine secondary data first, then collect primary data to fill the gap

Secondary Data

• information collected for purposes other than the current problem.

• Almost every project uses some; some projects rely on it entirely, and it can solve a problem by itself. It is widespread and quick to search.

• researcher use it at the start of a project tolearn about a new client’s industry

Internal Source

• inside the firm

• accounting data, sales reports, inventory, data, customer databases

• Pros: organized around the business and current

• Cons: massive and hard to analyze and internal policies

Database Marketing

• using customer databases to identify prospects, target offers, deepen loyalty, reactivate customers, and avoid service mistakes

Published

• external source

• government data (U.S. Census, ACS) and non government data (trade associations, journals, databases such as ABI/INFORM, Factivia)

• Pros: widely available, inexpensive

• Cons: overwhelming, fixed format, hard to verify, may not fit your situation

Syndicated

• external source

• collected with standardized measure and sold to many clients (not free)

• Pros: standard format, shared cost, high quality, current

• cons: commitment cost, competitors can buy it too

U.S. Census

every 10 year, entire population; demographic and consumption data at levels from city block to nation

american community Survey (ACS)

conducted every year on about 3 million people; timely social, economic, demographic, and housing data

Syndicated panels

• Purchase Panels

• Media Panels

• Retail Panels

Purchase Panels

• households’ purchase recorded by diary, then scanner/barcode, then RFID

• Used to measure brand loyalty and best promo strat

Media Panels

viewing behavior by diary, Nielsen set top boxes, portable people meters

Retail panels

retailers’ product sales

Pros and cons of secondary data in general

Pros: quick, inexpensive, may solves the problem alone, supplements primary data

Cons: incompatible reporting units, mismatched units of measurements, unusable class definitions, outdated data, and lock information to assess credibility

Primary Data

gathered specficially for the project at hand: observation (mechanical such as eye tracking or personal), questionnaires, interivews, social media, panels, experiements

Social Media Data (user generated content)

Pros: current and fast, inexpensive, unpromted and authentic, good for tracking trends

Cons: comments may not represent the target audience; demographics may be unknown or falsified, reviews can be manipulated; much content is shallow or irrelevant; unstructured and needs special skills

Survey

• an internview with many respondents using a predesigned questionnaire

• Survey Design = questionnaire design + sampling design

• Advantages: standardization, easy to administer, get beneath the surface, easy to analyze, reveal sub group differences

The 4 survey methods

• Person administered

• Self administered

• computer assisted

• computer administered

Interviewer

• no computer

  • person administered

  • reads questions, records on paper

• computer

  • computer assisted

  • interviewer uses computer to record

no interviewer

• no computer

  • self administered

  • respondant writes on paper

• computer

  • computer administered

  • online survey, Qualtrics

Person administered

• Advantages: feedback, rapport, quality control, adaptability

• Disadvantages: human error, slow, high cost, fear of interviwer evaluation

Self Administered

• Advantages: reduced cost, respondant control, less evaluation apprehension

• Disadvantages: respondent control, no monitoring, high questionnaire requirements

computer assisted

• advantages: speed, fewer errors, pictures and graphics, immediate data capture

• Disadvantages: technical skills, possibly high setup cost

computer administered

• Advantages: user friendly features, inexpensive, less evaluation concern

• Disadvantages: requires computer literate, internet connected respondents

What we measure in measurement scaling

• behavior

• state of being

• state of mind

Behavior

• objective properties

• observable actions (ex. how often yoy buy cereal)

State of being

• objective properties

• physically verifiable facts (demographics, age, income)

state of mind

• subjective and not directly observable

• attitudes, perceptions, intentions, image

natural scales

• already exist (dollars, years, times/month)

• measure behavior

• measure state of being

• natural metric questions

synthetic scales

• must be created to measure state of mind

• synthetic metric questions

The 5 synthetic scales

1. one way labeled

2. n point

3. semantic differential

4. stapel

5. likert

one way labeled

• How to recognize it:

  • label scale

  • labels from one extreme to the other

  • not satisfied at all … very satisfied

• generic, easy for responents; ordinal only

Semantic Differential

• How to recognize it:

  • Bipolar adjective pairs:

    • Easy —- Difficult

• Brand/store/product image; quick comparisons; bipolar pairs hard to write

N Point Scale

• How to recognize it:

  • number scale

  • numbers from on extreme to the other (1-N)

  • anchored if the endpoints have labels (1=lowest and 5=highest)

Stapel

• How to recognize it:

  • one adjective with numbers from -X to +X

• image; easier to build; negative numbers; no neutral point possible

Likert

• How to recognize it:

  • Degree of (dis)agreement with statements

• attitudes, values, lifestyles; 7 points is a good upper limit

Questionnaire Design

a systematic process: consider question formats, word questions carefully (together, question development), and organize the layout

Questionnaire Organization

• covers three aspects:

  • introduction

  • logic

  • flow

• strongly affects response rate and data quality

Introduction

• what respondents read or hear before answering

• Functions:

  • identify the surveyor/sponsor (undisguised survey; hide the sponsor in a disguised survey)

  • indicate the purpose of the survey

  • explain how the respondent was selected

  • request partcipation and mention incentives or anonymity

  • express appreciation

Screening questions

• remove unqualified respondents

• skip logic function

• screening lowers the response rate because only those who pass are kept

filtering (branching) questions

• send respondents down different path based on their answers

• Display Logic function

• Branch Logic Function

Flow: the funnel approach

• move from easy to difficult, general to specific, the sensitive

  • Screens First: select the right respondents

  • Warm Ups: easy behavioral questions that build interest

  • transitions: signal a change in topic or format

  • complicated scales in the middle: respondent is committed by then

  • demographics last: personal and possibly offensive

the 7 Tips

1. keep it short, simple, and clear

2. add logic

3. use scales whenever possible

4. limit scale levels to 4-7

5. explain unexpected questions and justify sensitive ones

6. speak the respondent’s language: no jargon; write for the least informed respondent

7. always test drives: pretesting on a small sample (5 ppl) to find and fix the problems before launch

4 Question Formats

• open ended

• categorical

• metric

• closed ended

open ended

• unaided

  • ex. what ads do you recall?

• aided

  • do you recall any other ads you saw on TV?

• Pros: no bais from offered choices; respondent control

• Cons: costly to code; idiosyncratic language; favor articulate respondents

categorical

• dichotomous (2 options)

  • ex. yes/no; male/female

• multiple choice

  • ex. which brand do you wear most often?

• closed ended question

• give nominal data (no scale needed)

metric

• natural

  • ex. how many times did you…? Monthly bill: $___

• synthetic

  • ex. rate its performance: poor…excellent

• closed ended question

• gives oridnal, interval, or ratio data along an underlying continuum

Close Ended

• includes categorical and metric questions

• Pros: uniform treatment, simple coding and analysis, quick and easy

• Cons: must know the option in advance; respondents less involved

4 Do’s in Questionnaire Wording

• focused: one issue per question

• simple: one subject and predicate; split long sentences

• brief: cut unnecessary words

• clear: precise, everyday words; most important

6 Dont’s to Questionnaire Wording

• ambiguous: no extemes or vauge wording

• leadning: cues the right answer: emotional words, answer built in, social pressure

• overstated: exaggerates one side of the issue

• loaded: built on an unverified assumption, fact, or belief

• double barreled: two questions in one

• ill defined: asks for what people can’t recall or can’t imagine