Data Processing and Preliminary Data Analysis in Marketing Research. MBA Marketing study material

Data Processing and Preliminary Data Analysis is a point of doing marketing research at first place in order to collect raw data and transform it into a knowledgeable form for analysis and interpret the final result. Initially, after designing a suitable Questionnaire, researcher need to take a field survey to collect the data. This blog comprise the practice of transformation of data into a logical and expressive content.

Data Processing:

Data processing simply the process of produce a data that can be convertible into knowledge. Data processing is a first step of final marketing research. After taking hundreds and thousands of survey, researcher need to check out the data that can be convert into some meaningful form. There are several steps involved in this process as below:

·         Questionnaire examination:

Researcher need to check the question formation, incorrect questions, rejection of unacceptable questions, removal of incomplete questions and also need to check past cut-offs date or missing pages. 

·         Editing:

Editing is a process of generate data which is correct and accurate. It corrects the errors detected from the data where ever possible. The purpose of editing is to ensure that each questionnaire is accurately completed. It confirms that the information collected from questionnaire is error free and ready to transfer into final analysis.

·         Coding:

Coding is nothing but assignment of numbers, symbols, or alpha to various data categories through some measurement and scaling techniques. Some information need to take into a featured category and so it need to record it by its number or symbol. Coding is a process of ensuring every category is in numerical form accurately to push into final analysis. It is usually applied on open-ended questions.

·         Transcribing:

Transcribing is entering a data into various software that can be accessible to people. Data entry software in this process should be user friendly to easily reachable to people. There are various methods and statistical formats for entering data easily.

·         Cleaning:

While doing a transcribing, cleaning of raw data is very important step of data processing. Raw data may have defective logins, number of errors which need to fix it with the step of entering data. Purpose of cleaning process is to make sure the consistency of the data which is transcribed.

·         Statistical Adjustment:

Some data need to represent visually by graph or statistical chart to show the result more effectively. Statistical adjustment is a step to ensure the graphs, charts or tables involves in data are correctly entered. Researcher also need to check the graph or chart are exactly placed on assigned location. 

Researcher can take these above steps according to the need of research.

Preliminary Data Analysis:

Preliminary data analysis is the first stage of research which mostly concerned with descriptive statistics. Descriptive statistics is the process of describing the characteristics of primary data which provides initial analysis of assumptions. This is important process for detecting any violation of assumptions in data. It gives a clear vision to researcher as to where the violation occurs. It embraces some statistical and arithmetical terms like Mean, standard deviation, range of score, skewness etc.

Nowadays, SPSS (Statistical Product and Service Solutions, SPSS Statistics) is a commonly used statistical analysis software package as well as SAS, Stata, Minitab are also widespread for descriptive statistical analysis.

In usual preliminary research process, there are three mainstream stages:

1.      Exploratory Analysis: This analysis shows a limitations to the primary data analysis and convert it into an evidence. It helps to resolve the difficulties by taking questions as a proof for final result.

2.      Developing the findings: It is a process of clean the data set from violations and generate the summery, relationship, narratives, and interpretations also recommendations for research users.

3.      Archiving: In archiving stage, data processor can keep the record of non-transient data for further analysis. Due to vast and complicated process of research analysis, researcher can only take fraction of content. So this step helps to save other inconsequential sets of data.

Hope this blog helps you to understand Primary stage of marketing research that is data processing and preliminary data analysis.

What is Hypothesis Testing in Marketing Research? MBA Marketing study material.

Marketing research process involves collecting of information through a questionnaire from a selected sample size and measuring this data by various techniques to record it systematically for further study. Now before heading forward let’s look into the most important topic that is Hypothesis. Hypothesis testing in marketing research helps to give a direction towards the study by making and testing an uncertain statements. It is a process of getting direction through the predictions.

What is Hypothesis Testing?

Hypothesis testing is a process of making an assumption or predictions of an uncertain events or statements to study the relationship between two or more variables and test it whether the assumptions are specific and correct to achieve the purpose of research. Benefits of hypothesis testing are:

·         Clear the purpose of research.

·         Gives the direction to re-analyse and rethink towards the research efforts.

·         It stats the relationship between two or more variables which are considered in research.

·         Gives opportunity to different industries to have debates.

How to write a Hypothesis?

Writing a hypothesis is very important and complex procedure. It is very vital to consider the relationship between two variables while writing a hypothesis. Let’s consider the below example:

“Girls and boys have different grades in school.”

In above statement, there is no existence of generic relationship between variables.

“Girls have more grades than boys in school”

This statements shows some measurable values that girls have “more” grades than boys. It gives you the clear direction towards the research as:

Why the girls have more grades than boys in school?

After getting a direction toward a research, let’s write a hypothesis by assuming some uncertain facts about previous statements:

“Girls have more grades than boys because girls are more attentive than boys in school.”

Now researcher have to test the above hypothesis to make sure whether it is correct or not.

How to test a Hypothesis?

There are two types of testing a hypothesis:

1.      Null Hypothesis (H₀):

Null hypothesis is the statement to believe as correct throughout the research. Null hypothesis is assumed to be true unless it has some proof to reject it. It is subjective by random cause. It is statement of equality. Null hypothesis represent as “H₀”. Let’s look an example:

“Average fare charges of a car in city is $50”

In this example, Null hypothesis can be indicate as:   H₀ = $50

If the data represent the fare charges is less than or more than $50 then null hypothesis reject the statement. So it comes to second type of hypothesis that is alternative hypothesis.

2.      Alternative Hypothesis(H₁):

The name itself states the alternatives or options for the Null hypothesis. Alternative hypothesis statements shows every possible alternatives other than null. This statement influenced by non-random cause. It accept all expect null statement. Alternative hypothesis represent as “H₁” or “H_a”. If we consider the above example:

“Average fare charges of a car in city is $50”

In this case, Alternative Hypothesis can be indicate as:  H₁ < $50; H₁ > $50 but H₁≠ $50

Both the Null Hypothesis and alternative hypothesis should be considered and stated in research before collection a data. It gives you desire and expected conclusion of marketing research.

Hope this blog helps to clear your idea about Hypothesis Testing.

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.

How to design a Questionnaire for Marketing Research? MBA marketing study material.

Every organization needs a valuable and truthful information to take a decision about future of the organization. Correct information leads to influence the marketer to take a right decision.

The previous article explained types of market research and how information can be collected for research. Primary/qualitative type of marketing research consist a survey method to collect data. In the survey, Organization needs to make a Questionnaire. Here is the answer of How to design a Questionnaire for Marketing Research?

What is Questionnaire???

A questionnaire is a series of questions with a choice of answers devised for the purpose of research or statistical study.

Therefore, the decisive part of good research is allied with making sure that the questionnaire design as per the need of the research.

How to design a Questionnaire for Marketing Research??

Designing a questionnaire is not as simple as it at first sight. A research team has to plan for collecting information is required to be extremely careful in deciding vital queries like:

What kind of data/information should be collected?

What kind of questions to be formed?

What type of wording should be used in questions?

Arrangement of sequence of questions

How to present a form of questionnaire?

Finalization of Questionnaire etc.

Let’s look into this step by step:

1.      Determine what information is required:

The basic step is to determine exactly what kind of information is required to accomplish the goal of a survey. An organization needs to make a list of objectives of the survey.

2.      State sample size:

This is a step of selecting a set of people or respondent of questionnaire or sample size. It means Organization should select a target customer’s sample size to whom the questions to be asked.

3.      Choose a question type:

The organization should be specific about what question type to choose, whether it will be multiple choice questions or open-ended questions or projective type questions like fill in the blacks and word association etc.

4.      Decide content of questions:

This is a very important step in which organization should develop each question with a specific purpose. Each question should be logical, easy to understand and answerable. The content of questions should be addressed to need of market research.

5.      Arrange sequence of questions:

An arrangement of questions plays a vital role in designing a questionnaire. Neutral questions should be arranged at the beginning to set an empathy to set a person at ease. The questions should be in order to bring logic and flow to the interview.  

6.      Finalise the questionnaire:

After the arrangement of questions, the form needs to format with instructions to respondents with the good introduction. It will give a clear idea to the respondent about organization’s objectives.

7.      Test and review:

After making it finalize, Questionnaire should be tested on small sample size (probably on associate or friends). Pre-test of questionnaire aims to detect faults and correct where ever it needs before going through the main survey.

And finally, your questionnaire has been designed to work. It all set to collect information/ data from a respondent.