What is Sampling in Marketing Research? MBA Marketing study material.

In Marketing Research, recognize and select the sample is very crucial part to collect information. This article helps to understand what is sampling? And How to identify and select a correct sample size?

What is sampling?

It’s a process of identifying and selecting a number of units from a whole population for our marketing research. Sample is a subgroup of larger population of individuals or objects.

In short, it is a process of selecting small amount of people from whole large population for study. It is more feasible, less time consuming and cost-effective to analyse or study of smaller amount of individuals rather than to study large population. Sample size is a group of an individuals for whom the questionnaire is to be designed aims marketing research.

Sampling Methods:

Generally, sampling is classified into two groups that are probability sampling and non-probability sampling. Let’s have a look how it work:

1.      Probability sampling:

In this method, every object or an individuals has an equal chance of getting selected for research. This method of sampling have many types as follows:

• Simple Random sampling: This is a basic type of sampling in which every individual or object has an equal probability to get selected. Lottery method is the best example of Simple random sampling. This type is simplest, cheapest and fastest but unreliable in some points because of its uneven population.

• Systematic Random sampling: It is modification of simple random sampling. In systematic random sampling, Object or an individual is to get selected by calculating desired sampling fraction. E.g. Every 5^th person or object, every 15 mins, every 15 houses, every 2 kilometers, every 3^rd shop etc.

• Stratified Random sampling: In this type of sampling, Whole population is divide into strata according to its characteristics and then sample is going to select randomly. In this type, stratification can take place even of selecting an Individuals. Stratification of population can be done by age group of people, income of people, and number of dependents accordingly.

• Cluster Random sampling: ‘Cluster’ is the name itself shows the meaning of this type of sampling. It is a process of forming a group or bunch of an individuals or object according to their features and within this group we can choose a set of sample randomly. E.g. there are 2000 schools in one town for research, if we apply this method, we cluster the geographic area of town where each area has 50 schools and within 50 schools we have to select every 10^th school as our sample set.

2.      Non-probability sampling:

As the name stated, non-probability sampling is a process of identifying and selecting sample set not by randomly but as a subjective.  It is much less formal than probability sampling method. It involves:

• Convenience sampling: This non-probability sampling method is used to select set of sample from those who willing to involve in research or who are volunteers to get selected.

• Judgement sampling: Judgement sampling is exactly opposite of simple random sampling. This method involve the process of selecting sample by own personal judgement and opinion.

• Quota sampling: It is a process of selecting a representative sample by dividing whole population into quotas according to their variables like age, income, location etc. Sample is getting selected by drawing its quota from each variables.

• Snowball sampling: In this method, selected sample size gives the references from their personal network with same features and characteristics. This method is supportive for organisation to get additional samples for its research.

Measurement and Scaling techniques in Marketing Research. MBA Marketing Study Material

After getting a knowledge of Marketing research and how to collect data/ information in the previous post, here is the blog on Measurement and Scaling techniques in Marketing Research.

Initially, we have to look into the meaning of Measurement and Scaling in marketing research

Measurement: It is a process of observing, recording and assigning numbers or other symbols to a characteristic of the object according to certain rules.

Scaling: It is a process of assignment of objects to a number. Scaling is developing a continuum/range/series upon which measured objects are located.

In simple words,

There are two forms of data, first comprise of quantitative variables which can be measured in terms of numbers like price, income, expense etc. and second comprise of qualitative variables which cannot be measured in numbers like emotions, feeling, sense, intelligence etc. For further analysis, the organisation needs to convert this qualitative data into the numerical form. Here, measurement and scaling techniques help to convert the data into the measurable form. Here is how:

Measurement and Scaling techniques:

1.      Nominal Scale:

This scaling technique is basic and simple to understand. It is a technique of assigning labels or numbers to the variables. In this type, there is no existence of numerical significance. There is no link between the variables and numbers or labels allocate to them. It can be called as a “Label Scaling technique”.

e.g.

Gender-    1. Male   2. Female

Marital Status-    A. Married   B. Unmarried

2.      Ordinal Scale:

Ordinal scaling is a process of ranking the objectives according to their characteristics or features. Ordinal scale helps to convert the data from unmeasurable to measurable one, so that researcher can analyze the particular value of responses and rank it as per its feature. This scale is basically used to measure non-numerical concepts like emotions, satisfaction, intelligence etc.

e.g.

How would you rank our product? -   1.Satisfied   2.Unsatisfied   3.Delighted

3.      Interval Scale:

Interval scale can be measured an absolute value or difference of values between scale points. This scale not only can rank the data but also can convert the difference in numerical form so that researcher can find correct figure to record it properly. This type of scale gives a strong figure for non-numerical responses in numbers.

e.g.

Rate our performance on a 0-10 scale- The answers can be 8.2, 9.2. 1.3, 5.6.3, 4, 6.6 etc.

4.      Ratio Scale

The ratio scale is the ultimate level of scale by its use as it allows the researcher to find or classify the object, rank the object as well as compares the difference between the intervals and gives the result in ratio form. In short, Ratio scale includes nominal, ordinal as well as interval scale pattern to measure and record the data in sequence.  It compares both distinctions in rating.

e.g.

What is the average temperature measured in the USA in last three months?-

In the first month- 20 degree- 2^nd rank

In the second month- 22.5 degree- 3^rd rank

In the third month- 10 degree- 1^st rank

Above explained techniques are the basic in measurement and scaling the research which can be used on collected data through Questionnaire as described in the previous post.