Customer Relationship Management in Retail Marketing. MBA Marketing study material.

Maintain and upturn the long-term relationship with the customers is a vital course for the retailers to increase the footfall of the store which eventually converts into the sales. But to make this win-win situation, how the customer relationship management in retail marketing can help the retailers? Let’s have a look further:

Customer Relationship Management (CRM) in Retail Marketing:

It is set of business strategies and system or software which focuses on customer satisfaction and building loyalty with a retailers’ most valued customers. A process or a system which constantly engage the customers by delightful offerings of retailers is called as a customer relationship management in the retail marketing environment.

It aims to convert the end users into the loyal customers at first visit to the retail store by satisfying their needs with attending their attitudes and feelings at very first purchase.

Components of Customer Relationship Management (CRM):

·         Customer Service:

Identifying, collecting and analyzing the customers’ needs and wants is the main goal of customer service support applications. Also, it is very important to analyze the customers’ complaints and suggestions to cater the business in high level. In the modern era, retailers are using various customer database software to integrate the information about every customers’ purchasing pattern their needs and behavior. Customer service is a part of front desk service which directly communicates with the customers promote the products and services and receives the information to maintain a customer database.

·         Sales Force Automation:

Salesforce automation is a very useful tool for customer relationship management. It is primarily designed for sales personals to manage their each and every customer’s records.  It includes the functionality to maintain the sales cycle such as lead generation, lead distribution, follow-ups, tracking records, design work calendar for the sales team, analysis of sales data etc. This tool also helps to forecast the sales which lead to expanding the future opportunities for the retailers. It is beneficial for managing the help-desk or customer care services such as call centers to quickly solve the customers’ problems and complaints.  

·         Market Research:

Market research involves the process of campaigning management which provides support for a marketing budget, promotional campaigns, ad placements, target market, recording customers’ response and analyze the performance of these campaigns. Market research for customer relationship management also helps to provide marketing analysis tools which give the accurate statistical and systematic data analysis.

·         Data Mining and Analytics:

Data mining is a useful process of collection, sorting, analyzing, organizing the data and use this data for identifying future demographic cross-selling opportunities and chance to improve the pattern and modify the process to maintain customer loyalty.

Analytics is an immense study of available data and represent it in a specific logical form to spot the trend or condition of the market. It shows a graphical presentation such as chart, histogram, figures, diagrams etc. of the market situation through analyzing the data. It helps to calculate the progress in customer relationship management accurately.

All of above components of customer relationship management is important to improve the work around the customer satisfaction and loyalty as well as finding the different opportunities to maintain a long-term relationship with customers.

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.

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.

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.

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.