1. Module
Review

3. SURVEY RESEARCH

4. Based on simple idea:
“”… the best way to find out what consumers think is to ask them.”
Zikmund

5. Survey Research
A method of collecting primary data by communicating with a representative sample of people

6. Survey Research Design
• The way the environment is controlled or
organized
• Environmental variables to control
When the survey is given
How the survey is given
▫ The sample size
▫ Number of groups
• The more environmental control, the more
accurate the results will be

7. Properly conducted Surveys can be:
Quick
Inexpensive
Efficient
Accurate
Flexible

8. Problems with Surveys come from: ERRORS
Non-response error
Response bias
Administrative error

9. Types of Sampling:
Personal Interviews
Intercepts
Telephone interviews
Self administered questions
Mail questionnaires

11. Qualitative Research...
Is any research conducted using an observational technique or unstructured questioning.
Conducted:
when structured research is not possible,
when true response may not be available [embarrassing “touchy questions”]
to explain quantitative research results.

12. Qualitative research Observation techniques
Classification of Observation
Direct vs indirect:
Direct > observing behavior as it occurs
Indirect > observing the effects of behavior
Disguised vs nondisguised
Nondisguised >Direct
Disguised > Indirect
Structured vs unstructured
Structured >predetermine what to observe
Unstructured>monitor all behavior
Human vs Mechanical
Human>observation done by human beings
Mechanical>observation by machine

13. Observation Appropriate Conditions
The event must occur in a short time interval,
Avoid lag affect
Must occur in a setting where the researcher can observe the behavior
Praying, cooking are not suitable things to observe
Necessary under situations of faulty recall
Faulty recall - remembering things such as how many times one looked at his wristwatch.

14. Observation: Advantages and Limitations
Greater data accuracy than direct questioning, in natural settings people behave naturally,
Problems of refusal, not at home, false response, non-cooperation etc. are absent,
No recall error,
In some situations, only way
Number of customers visiting a store
Studying children’s behavior
Limitations
Time consuming, too many things to observe,
may not be representative,
difficulty in determining root cause of the behavior.

15. Focus Groups Objectives: - Generate new product or service ideas
Understand consumer vocabulary
Useful for ad campaigns
Reveal consumer needs, motives,
perceptions and attitudes,
Generating future research objectives
Facilitate understanding of the
quantitative studies 15

16. Other Qualitative Techniques
Depth Interview: An unstructured interview that seeks opinions of respondents on a one-to-one basis. Useful for sensitive issues, politics etc.
Protocol Analysis: Involves placing a person in a decision making situation and asking him/her to state everything he/she considers in making a decision. Useful in 1. Purchasing involving a long time frame (car, house) and 2. Where the decision process is too short (greeting card).
Projective technique: Involve situations in which participants are placed in simulated activities hoping that they will divulge information about themselves that are unlikely to be revealed under direct questing. 16

17. Main advantage is that is capable generating rich data on WHY?
Qualitative research can be used alone or as part of mixed research
Main advantage is that is
capable generating rich data on WHY?
Useful when looking at NEW
things
Rich data may be difficult to
analyse

18. SAMPLING
(Zikmund,
Chapter 12)

19. Examine a Part of the Whole
In most surveys access to the entire population is near impossible,
The results from a survey with a carefully selected sample will reflect extremely closely those that would have been obtained had the population provided the data.

20. Bias The one thing above all to avoid. - no way to fix a biased sample
- no way to salvage useful information from it.
Best way to avoid bias is to select individuals
for the sample at random.
Deliberately introducing randomness
is one of the great insights of Statistics

21. There are essentiality two types of sampling:
probability
non-probability
sampling.

23. Probability Sampling Methods
Probability or random sampling gives all members of the population a known chance of being selected for inclusion in the sample
The selection of individuals does not affect the chance of anyone else in the population being selected. Many statistical techniques assume that a sample was selected on a random basis

24. Randomise - can protect against factors that you know are in the data.
- can help protect against factors you are not
even aware of.
Randomising makes sure that on the average the sample looks like the rest of the population

25. Randomisation - Individuals are randomly selected.
- No one group should be over-represented.
- Sampling randomly gets rid of bias.
Random samples rely on the absolute objectivity of random numbers.

26. Four basic types of random sampling techniques:
Simple Random Sampling
Systematic Sampling
Stratified Sampling
Cluster or Multi-stage Sampling

27. Simple Random Sampling
This is the ideal choice as it is a ‘perfect’ random method.
Using this method, individuals are randomly selected from a list of the population and every single individual has an equal chance of selection.

28. Systematic Sampling
Systematic sampling is a frequently used variant of simple random sampling. When performing systematic sampling, every kth element from the list is selected (this is referred to as the sample interval) from a randomly selected starting point.
For example, if we have a listed population of 6000 members and wish to draw a sample of 200, we would select every 30th (6000 divided by 200) person from the list. In practice, we would randomly select a number between 1 and 30 to act as our starting point.

29. Cluster or Multi-stage Sampling
Is particularly useful in situations for which no list of the elements within a population is available and therefore cannot be selected directly.
As this form of sampling is conducted by randomly selecting subgroups of the population, possibly in several stages, it should produce results equivalent to a simple random sample

30. Cluster samples are generally used if: - No list of the population exists.
- Well-defined clusters, which will often be
geographic areas,exist.
- A reasonable estimate of the number of
elements in each level of clustering can be
made.
- Often the total sample size must be fairly
large to enable cluster sampling to be
used effectively.

31. Non-probability Sampling Methods
Non-probability sampling procedures are much less desirable, as they will almost certainly contain sampling biases. Unfortunately, in some circumstances such methods are unavoidable.
In Marketing Research the most frequently-adopted form of non-probability sampling is known as quota sampling.

32. Voluntary Response Sampling:
Individuals choose to be involved.
These samples are very susceptible to being biased because different people are motivated to respond or not.
Often called “public opinion polls.”

33. It’s the Sample Size!!
How large a random sample do we need for the sample to be reasonably representative of the population?
It’s the size of the sample, not the size of the population, that makes the difference in sampling.
Exception: If the population is small enough and the sample is more than 10% of the whole population, the population size can matter.

34. Calculating a Sample Size:
Calculation of an appropriate sample size depends upon a number of factors unique to each survey and it is down to the researcher to make decisions regarding these factors. The three most important are:
- How accurate you wish to be - How confident you are in the results - What budget you have available

35. The required formula is: s = (z / e)2 Where: s = the sample size
z = a number relating to the degree of confidence you wish to have in the result. 95% confidence* is most frequently used and accepted. The value of ‘z’ should be 2.58 for 99% confidence, 1.96 for 95% confidence, 1.64 for 90% confidence and 1.28 for 80% confidence.
e = the error you are prepared to accept, measured as a proportion of the standard deviation (accuracy)

36. (re. Zikmund,
Chapter 14)

37. Why we need Statistics
The main purpose of statistics is to accurately summarise the data into easily interpretable fewer numbers

38. Descriptive statistics:
Convergence
- Divergence
Measures of:
- Association

39. The Standard Deviation
In principle, the standard deviation (often shortened to ‘sd’) is very similar to the mean deviation. 
It summarises an average distance of all the scores from the mean of a particular set.

40. Normal Distribution

41. Attitude Scaling
and
Measurement
(Zikmund,
Chapter 10)

42. Attitude: 
An enduring disposition to consistently respond in a given matter

43. Measuring Attitudes  
Ranking
Rating
Sorting
Choice

44. The Attitude Measuring Process: 
Ranking - Rank order preference
Rating - Estimates magnitude of a
characteristic
Sorting - Arrange or classify concepts
Choice - Selection of preferred
alternative

45. Physiological measures of attitudes …
provide a means of measuring attitudes without verbally questioning the respondent. for example, galvanic skin responses, measure blood pressure etc.

46. Simple Attitude Scaling: 
In its most basic form, attitude scaling requires that an individual agree with a statement or respond to a single question.
This type of self-rating scale merely classifies respondents into one of two categories;

47. Questionnaire Design
(re. Zikmund
Chapter 11)

48. Major Decisions What to ask How questions are phrased
Sequence of questions
Layout
Pretesting

49. What Questions? … will be determined by Type of Marketing Decision
Problem definition
Primary research objectives

50. Two Main Types of Question:
Closed
Open

51. Closed-ended questions can be:
Dichotomous
Multiple
Likert scale
Semantic differential
Rank order
Numeric

52. Open-ended questions Unstructured Word Association Sentence completion
Story completion

53. Advantages of Open-Ended Questions Greater freedom of expression
No bias due to limited response ranges
Respondent can qualify their answers
Disadvantages of Open-Ended Questions
Time consuming to code
Researcher / interviewer may misinterpret
and therefore misclassify) a response

54. Questionnaire Layout (see Zikmund – page 265)
Always Introduce questionnaire
Move from general to specific
Use “filter” questions

55. PILOTING QUESTIONNAIRE
Any questionnaire, should be "piloted" (i.e. test it) to check that it is going to function effectively. There are a number of reasons why it is important to pilot a questionnaire:
To test how long it takes to complete
To check that the questions are not ambiguous
To check that the instructions are clear
To eliminate questions that do not yield usable data