Recent trends in Marketing Research. MBA Marketing study material.

This is an era of technology, instant communication, huge data. In this era, more businesses are realizing the need to pull the knowledge of market researchers in bringing the voice of the customer to the organization. This post is focused on the recent trends in Marketing Research to explore more business opportunities with emerging drifts in a competitive marketplace. Let’s have a look:

·         Artificial Intelligence(AI):

Thanks to the google home and amazon echo, Artificial Intelligence has entered in consumer landscape. It also is known as Machine Intelligence which is basically a machine learning problem-solving techniques in contrast to Natural Intelligence (NI). Apart from machine learnings, AL will come up with a transformation in many aspects of research including survey and questionnaire development, field management, big data analytics and advanced computing power. Al transformation will not be able to replace the traditional research methodology of a survey and qualitative research, in fact, it is an elementary part of AL.

·         Automation:

Recent survey stats that the trend of future of research will be automation. Researchers are going to be faster, cheaper and standard. Automation abilities are constantly growing and this leads to a big change in the industries. Sometimes, the researcher’s need is to get research done only with the help of automated processes. Along with Artificial Intelligence, Automation can transform the future of research. Automation helps to provide an opportunity to take more evidence-based decision making in marketing research.

Sometimes, automation may give a bad result as it picks a speed of doing it, but it will never make you compromise with enhancement of quality as it provides relevant answers with minimum cost.

·         Turning insight into an action:

In the current scenario, data is getting cheaper and vast in quantity. But the techniques to find what research need in data is called a process of finding insights. Data handling is a fancy name for insight finding. There is so many organization are involved and newly emerging in data handling process such as official reports and e-tabs etc.

Finding insights is not only the work to deal with research but these insights have to be converted into an action to reach the goal.  Many of consultants such as Brainjuicer and Insite consultancy are engaged and becoming widespread in turning insights into an action.

·         Big Data and Data Integration:

It is possible nowadays to store a massive amount of data and information at the cheapest cost. Data collection devices have evolved the pace of data creation. In a survey, IBM estimates 90% of the data in the world has been created in the last 2 years. It is possible to be logged in and recorded every transaction or event for study.

No doubt, big data trend is useful for future without replacing a traditional market research process but larger data represents enormous challenges for marketing research. Here, the data Integration plays a very important role. Integration between two or more type of data from different resources into one useful insight is a recent trend of marketing research.

        

·         Going Digital:

Undeniably, Smartphones are the best example of a recent trend in marketing research. Smartphones work as not so far from computers or laptops in all around the world. In this phase, mobile marketing is a new drift of current scenario of the global market. Researcher uses the smartphone as a data collection tool which is handy, easy, user-friendly and fastest.

As the globe has connected to the internet, everything is not so far from us. Internet covered a range of topics and information for research. We can see in future evolution in mobile-only research, in particular, app and message-based solutions for using smartphones for market research will grab the world rapidly.

Applications of Marketing Research. MBA Marketing study material.

Marketing Research plays a significant role where the organization and people associates to each other through the process of data collection and data analysis to identify the scope of the market for product or services. Applications of marketing research is an instinctual interface which provides statistical or graphical practices for market research analysis. It does not only help to identify the target market but focuses on evaluating choices and preferences of potential consumers.

Application of Marketing Research Process:

·         Product Research:

Product research usually conducts to calculating possible acceptance of a new product, upgrade or additions to existing products, making wise decisions on product packaging and determining product acceptability over market competition. Product research mainly focuses on how customers might react to a product.

·         Pricing Research:

Pricing research is dealing with the decisions on pricing strategies of a product according to the cost of production and profit margin for the organization. It helps to determine the acceptability of price of product or services where consumers feel that it is worth to pay for it. It makes you understand the variety of price level as per the competitive market to achieve desired profit.

·         Concept Testing:

Concept testing comprises of assessing new product concept, brand names, advertising concept etc. It basically focuses on the process of generating a new product and its concept behind developing it with pricing concept, ad appeals, and positioning.

·         Positioning Research:

Positioning Research covers all the study of how the existing product or services has been positioned in the competitive marketplace and how to launch and presenting a new product in the potential market. This research helps to define the consumer’s responses or reviews about the product or services so that organization can find out the scope for its positioning.  

·         Advertising Research:

It consists a set of decisions on advertising a product or services, ads developments or advertising campaigns to find out the scope where the organization can apply advertising practices to influence the customers. An organization often conducts a campaign in advertising research to find out whether it is really beneficial to invest in advertising platform for its product and if it's beneficial then this research helps to find out from how many ways the organization can invest to achieve its advertising goals.

·         Market Segmentation:

A market segment is a research process of dividing a market into sub-categories according to the special characteristics. It is normally divided potential consumers into segments by looking at features such as shared needs, common interests or similar lifestyles. This research helps to recognize the high yield segment or profitable segment of the market.

·         Branding Research:

In this type of research, an organization makes an opinion about the product value by reviewing the consumer’s statements on the product. Branding is what are the opinions of people about the product and, what people think about the organization. It assists with the creation, development, and ongoing management and strengthening of brands. Branding research conducts to understand the landscape and develop a launch strategy in the competitive market.

·         Sales Analysis:

Sales Analysis is a research to conduct and analyze the customer records and other available data to identify the sales opportunities in the market. Sales research also analyze whether the sales presentation is effectively moving over the competition in market or not. It helps to record and calculate percentage of sales, stock inventory sales force and other sales related activities.

Applications of marketing research demand the forecasting of the studies in every area such as product, sales, price, advertising etc. which has explained in above process.

What is Data Interpretation and Report Writing in Marketing Research? MBA Marketing Study Material.

Data Analysis is a very crucial step to fulfill the purpose of research but researcher needs to represent this outcome of analysis in a meaningful way by summarizing it in short sentences, this is the step of Data interpretation and report writing in marketing research. Data Interpretation and report writing is simply the overall conclusion of marketing research. The purpose of research is not well served unless the findings are made known to others.

Data Interpretation:

Data Interpretation is a process of illustrating of inferences from the analysis study in a very meaningful way.  Interpretation is concerned with relationships within the collected data, partially corresponding analysis. Interpretation also covers beyond the data analysis to comprise the results of other research, theory, and hypotheses.

Techniques of Data Interpretation:

Data Interpretation often involves following techniques:

·         Explanation:

The researcher needs to give reasonable explanations of the relations which has found and needs to interpret the lines of relationship in terms of the underlying processes and try to find out the thread of consistency that falls under the surface layer of expanded research findings.

·         Extraneous Information:

During the study, if the researcher has extraneous information which seems unnecessary at that time then it must be considered while interpreting the final results of marketing research.

·         Guidance:

Before boarding upon final interpretation, it is advisable to consult someone having perception into the study who will not vacillate to point out the errors in logical argumentation. This guidance will result in correct interpretation which will enhance the value of research.

·         Relevant Factors:

The researcher needs to finish the task of interpretation only after considering all relevant factors affecting the study to avoid false generalization.

Report Writing:

A report is a page or a document which consist of summery and interpretation of research done based on factual data, opinions of individuals or group. As a matter of fact, even the most intense hypothesis, well-designed research study, and the most outstanding generalizations and findings will have little value unless they are successfully communicated to others. Report writing is the last step in a research study and requires skills beyond earlier steps.

Steps involved in report writing:

·         Logical analysis of the subject-matter:

There are two ways to analyze subject matter logically that are Logical treatment and Chronological treatment. Logical treatment frequently contains in developing the material from the simple possible to the most complex arrangements. Chronological treatment is based on a connection or sequence in time or occurrence. 

·         Preparation of the final outline:

Outlines are the structure upon which long written works are erected. It is an aid to the logical organization of the material and a reminder of the points to be stressed in the report.

·         Preparation of the rough draft:

This step involves the process of analysis of the subject and the preparation of the final outline. The researcher will write down in this rough draft about the procedure adopted of data collection along with its limitations, data analysis techniques adopted in this research etc.

·         Rewriting and polishing:

Usually, this step takes more time than previous steps of report writing. This step involves the careful revision of outline draft revising it very carefully to make it a good piece of writing. The researcher needs to polish the draft by checking the grammar, spellings etc.

·         Preparation of the final bibliography:

A bibliography is the list of books, magazines, and references etc. which are used to study in this research. The bibliography should be organized alphabetically and may be divided into two parts. The first part may cover the names of books and the second part may cover the names of magazine and newspaper articles. 

·         Writing the final draft:

This is the step where the final draft should be written in a brief and objective style and in simple language, avoiding unclear expressions such as “it seems”, “there may be”. A research report should not be dull, should maintain interest and show originality. The report should be an attempt to solve some intellectual problem and must contribute to the solution of a problem and must add to the knowledge of both the researcher and the reader.

Steps involved in this post may vary from research to research, depends on its usage in a study.

What is Data Analysis in Marketing Research and how to deal with it? MBA Marketing study material.

Before going into a conclusion part, Data Analysis is a mainstream process of getting an end result of marketing research. It is an obvious process in which the researcher can reach the final stage of the marketing research. This is time to examine the amount of data and information collected and draw a final conclusion from it.

Once the data has prepared for analysis as shown in the previous post, there are some basic steps which include some statistical procedures. A wide range of collected data should be accurately measured and recorded for analysis to get an accurate conclusion.  Data analysis can be done in two way that are descriptive statistics and inferential statistics. Let’s sort it out one by one:

A.    Descriptive Statistics:

Descriptive statistics is a process of describing and summarising the data in knowledgeable conclusion. This method does not allow a researcher to go beyond the information collected or assumed hypothesis. It simple describe the data to the point as it is. Following are the types of descriptive statistics:

·         Measures of Central Tendency:

Measures of central tendency tools are used to calculate an average value of data or sample. There are three types of widely using averages for research as explained below:

1.   Mean: This is the most popular average type of central tendency. The mean is to be calculated by the sum of all values of data divided by a number of values in data. It is a basic calculation of central tendency.

2.  Median: Median can be calculated by arranging the data in ascending or descending order and selecting a middle value from the arrangement as an average. In an even set of data, the average of two middle numbers can be a Median.

3.   Mode: Most frequently appeared number in data can be a mode average. In a data set, it can be possible that researcher finds more than one mode due to scattered data.

·         Measures of Variability:

Central tendency represents the single value of an average but it cannot describe the data observation fully. Measures of variability can calculate the reliability of the data observation. It also can be used to measure the differences between variable. It is more consistent than a central tendency. Types of measures of variability are:

1.    Range: Range is a basic measure of calculating an average for data set. The range can be calculated by defining a difference between smallest value and largest values from data.

2.    Mean Deviation: Mean Deviation is an average calculated from mean and median of data. It also called for an average deviation. The average can be a mean or median in this type of measure of variability.

3.    Standard Deviation: Standard deviation is very popular in and mostly used a method of getting an average of data. It is a value or an average value calculated from overall data which differ from a mean value.

B.     Inferential Statistics:

In Descriptive statistics, we have seen how to make data analysis with the data or set of data available to us. But in Inferential statistics, we can calculate, measure and analyze the information to check out the reliability and consistency to look into beyond the descriptive statistics. It allows us to compare the group of data and tests hypothesis.

In marketing research, we need the information or data for analysis, but we cannot study the whole population, so we choose a sample size as per a sampling theory. After this process, we need to make some hypothesis. In this case, a sample should be perfect which can represent the whole population. The final stage of inferential statistics is to compare the analysis of data and hypothesis to study the difference between them and make some decision about the research.  

As we can see, Descriptive and Inferential Statistics are two main steps of Data analysis which allows making a decision on research.

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.