CONSUMER SURVEY RESEARCH Collecting Primary Data

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

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

What questions do you have? Selecting a survey research design should be based on the survey question(s) you are trying to answer

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

Properly conducted Surveys can be: Quick Inexpensive Efficient Accurate Flexible

Problems with Surveys come from: Nonresponse error Response bias Administrative error

NonResponse Error The difference between a survey that includes only respondents and a perfect survey that also includes nonrespondents

Response Bias Where respondents answer survey questions with a bias that misrepresents truth

Administrative Error - data processing error - sample selection error - interviewer error - interviewer cheating

Asking Consumers Questions

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

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

Two Main Types of Question: Closed Open

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

Dichotomous Description: Question offering two choices Example: Did you watch television at all yesterday? Yes / No

Multiple Description: Question offering three or more choices Example: Which of these shops do you prefer? Next / River Island / Gap Top Shop/ Top Man

Likert scale Description: Statement with which respondent shows the amount of agreement / disagreement Example: Assessment by course-work is easier than assessment by examination Strongly agree Agree Neither agree nor disagree Disagree  Strongly disagree

Semantic differential Description: Scale is inscribed between two bipolar words and respondent selects the point that most represents the direction and intensity of his / her feelings Example: The course I am taking is............. Interesting :_____:_____:_____:_____:_____: Boring Useful :_____:_____:_____:_____:_____: Useless Easy :_____:_____:_____:_____:_____: Difficult

Rank order Description: Respondent is asked to rate or rank each option that applies. This allows the researcher to obtain information on relative preferences, importance etc. Example: Please indicate, in rank order, your preferred chocolate bar, putting 1 next to your favourite through to 5 for your least favourite. Snickers Bar Dove bar Wispa Mars Bar Creme Egg

Numeric Description: Respondent specifies a particular value (can include decimal places) Example: How far (to the nearest kilometre) did you travel today to reach this College? ________km

Advantages of Closed-Ended Questions Quick to answer Easy to code No difference between articulate and inarticulate respondents Disadvantages of Closed-Ended Questions Can draw misleading conclusions because of limited range of options Researcher / interviewer cannot deal with qualifications to responses e.g. "Yes, but….." or "It depends" where only Yes/No are given as options

Open-ended questions Unstructured Word Association Sentence completion Story completion

Unstructured Description: Question that respondents can answer in an unlimited number of ways? Example: Why did you enrol for this course at HAUT? ……………………………………………………………………………… ………………………………….. …………………………………………………………

Word Association Description: Words are presented one at a time and respondents give the first word that comes to mind Example: What is the first thing that comes to mind when you hear the following? Lecture Interesting  Computer Exciting  Exam Challenge  Tutorial Rewarding

Sentence completion Description: Incomplete sentences are presented, one at a time, and respondents are asked to complete the sentence Example: My worst shopping experience while visiting ZhengZhou happened when……………….

Story completion Description: An incomplete story is presented and respondents asked to complete it Example: I sat down at the kitchen table, picked up a spoon, then looked at the Chicken and Mushroom flavour Instant Noodles in front of me……. NOW COMPLETE THE STORY

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

Questionnaire Layout Always Introduce questionnaire Move from general to specific Use “filter” questions

Checklist for Questionnaires 1. Have you avoided all leading questions? 2. Is the question as specific as possible? . 3. Are the questions going to be understood by all respondents? 4. Is each question applicable to all respondents? 5. Are any of your questions double - barreled?

SAMPLING

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.

Bias The one thing above all to avoid. There is usually no way to fix a biased sample and no way to salvage useful information from it. The best way to avoid bias is to select individuals for the sample at random. The value of deliberately introducing randomness is one of the great insights of Statistics

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

Probability Sampling Methods Probability or random sampling gives all members of the population a known chance of being selected for inclusion in the sample and this does not depend upon previous events in the selection process. 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

Randomize 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. There are tables and books of random digits available for random sampling. Statistical software can generate random digits (e.g., Excel)

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

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.

Simple Random Samples To select a sample at random, we first need to define where the sample will come from. The sampling frame is a list of individuals from which the sample is drawn. E.g., To select a random sample of students from a college, we might obtain a list of all registered full-time students. When defining sampling frame, must deal with details defining the population; are part-time students included? How about current study-abroad students? Once we have our sampling frame, the easiest way to choose an SRS is with random numbers.

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 Consumer Research the most frequently-adopted form of non-probability sampling is known as quota sampling.

Quota Sampling Similar to cluster sampling in that it requires the definition of key subgroups. Main difference lies in the fact that quotas (i.e. the amount of people to be surveyed) within subgroups are set beforehand (e.g. 25% 16-24 yr olds, 30% 25-34 yr olds, 20% 35-55 yr olds, and 25% 56+ yr olds) Usually proportions are set to match known population distributions. Interviewers then select respondents according to these criteria rather than at random. The subjective nature of this selection means that only about a proportion of the population has a chance of being selected in a typical quota sampling strategy.