Marketing research is "the process or set of processes that links the consumers, customers, and end users to the marketer through information -? information used to identify and define marketing opportunities and problems; generate, refine, and valuate marketing actions; monitor marketing performance; and improve understanding of marketing as a process. Marketing research specifies the information required to address these issues, designs the method for collecting information, manages and implements the data collection process, analyzes the results, and communicates the findings and their implications.

It is the systematic gathering, recording, and analysis of qualitative and quantitative data about issues relating to marketing products and services. The goal of marketing research is to identify and assess how changing elements of the marketing mix impacts customer behavior. The term is commonly interchanged with market research; however, expert practitioners may wish to draw a distinction, in that market research is concerned specifically with markets, while marketing research is concerned specifically about marketing processes.

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DATA COLLECTION Data collection is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes. The data collection impotent of research is common to all fields of study including physical and social sciences, humanities, business, etc. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same.

The goal for all data collection is to capture quality evidence that then translates to rich data analysis and allows the building of a convincing and credible answer to questions that have been posed. Data Collection in Marketing Research is a detailed process in which a planned search for all relevant data is made by researcher. It is very much prone to errors ND hence is the most expensive step in marketing research. However, thanks to the development in the field of computers and electronics, data collection methods are improving immensely.

Data collection involves a field force or staff that operates either in the field, as in the case of personal interviewing, from an office by telephone, or through mail. The Marketing Research Process is comprised of the following steps: 1: Problem Definition 2: Development of an Approach to the Problem 3: Research Design Formulation 4: Field Work or Data Collection 5: Data Preparation & Analysis : Report Preparation & Presentation Data Collection Methods Qualitative Research- Qualitative Research is generally undertaken to develop an initial understanding of the problem. It is non statistical in nature.

It uses an inductive method, that is, data relevant to some topics are collected and grouped into appropriate meaningful categories. The explanations are emerged from the data itself. It is used in exploratory research design and descriptive research also. Qualitative data comes into a variety of forms like interview transcripts; documents, diaries and notes made while observing. There are two main methods for collecting Qualitative data Direct Collection Method-when the data is collected directly, it makes use of disguised method. Purpose of data collection is not known.

This method makes use of- Focus Groups Depth Interview Case Study Indirect Collection-Method Projective Techniques Quantitative Research- Quantitative Research quantifies the data and generalizes the results from the sample to the population. In Quantitative Research, data can be collected by two methods Survey Method Observation Method In a workplace like a super market, qualitative research would not be possible since he number of people to collect data from would be huge and no one would have the time or more over, willing to take part in any discussion group or interview.

So for data to be collected in a super market, one would have to use quantitative research. For this, the best way in my opinion would be through questionnaire and surveys. But despite being the most ideal ways of data collection, every method has its own weak points and disadvantages that must be considered. Advantages and Disadvantages of Surveys Advantages of Surveys 1. High Representatives Surveys provide a high level of general capability in representing a large population.

Due to the usual huge number of people who answers survey, the data being gathered possess a better description of the relative characteristics of the general population involved in the study. As compared to other methods of data gathering, surveys are able to extract data that are near to the exact attributes of the larger population. 2. Low Costs When conducting surveys, you only need to pay for the production of survey questionnaires. If you need a larger sample of the general population, you can allot n incentive in cash or kind, which can be as low as RSI. 0 per person. On the other hand, other data gathering methods such as focus groups and personal interviews require researchers to pay more. 3. Convenient Data Gathering Surveys can be administered to the participants through a variety of ways. The questionnaires can simply be sent via e-mail or fax, or can be administered through the Internet. Nowadays, the online survey method has been the most popular way of gathering data from target participants. Aside from the convenience of data gathering, researchers are able to collect data from people around the globe. Good Statistical Significance Because of the high representatives brought about by the survey method, it is often easier to find statistically significant results than other data gathering methods. Multiple variables can also be effectively analyzed using surveys. 5. Little or No Observer Subjectivity Surveys are ideal for scientific research studies because they provide all the participants with a standardized stimulus. With such high reliability obtained, the researcher's own biases are eliminated. . Precise Results As questions in the survey should undergo careful scrutiny and standardization, they revive uniform definitions to all the subjects who are to answer the questionnaires. Thus, there is a greater precision in terms of measuring the data gathered. Disadvantages of Surveys 1. Inflexible Design The survey that was used by the researcher from the very beginning, as well as the method of administering it, cannot be changed all throughout the process of data gathering.

Although this inflexibility can be viewed as a weakness of the survey method, this can also be a strength considering the fact that preciseness and fairness can both be exercised in the study. 2. Not Ideal for Controversial Issues Questions that bear controversies may not be precisely answered by the participants because of the probably difficulty of recalling the information related to them. The truth behind these controversies may not be relieved as accurately as when using alternative data gathering methods such as face-to-face interviews and focus groups. . Possible Inappropriateness of Questions Questions in surveys are always standardized before administering them to the subjects. The researcher is therefore forced to create questions that are general enough to accommodate the general population. However, these general questions may not be as appropriate for all the participants as they should be. ANALYSIS OF DATA AND INFERENCES With the data in a form that is now useful, the researcher can begin the process of analyzing the data to determine what has been learned.

The method used to analyze data depends on the approach used to collect the information (secondary research, primary quantitative research or primary qualitative research). For primary research the selection of method of analysis also depends on the type of research instrument used to collect the information. Essentially there are two types of methods of analysis - descriptive and inferential. Descriptive Data Analysis Not to be confused with descriptive research, descriptive analysis, as the name implies, is used to describe the results obtained.

In most cases the results are merely used to provide a summary of what has been gathered (e. G. , how many liked or dislike a product) without making a statement of whether the results hold up to statistical evaluation. For quantitative data collection the most common methods used for this basic level of analysis are visual representations, such as charts and abeles, and measures of central tendency including averages (I. E. , mean value). For qualitative data collection, where analysis may consist of the researcher's own interpretation of what was learned, the information may be coded or summarized into grouping categories.

Inferential Data Analysis While descriptive data analysis can present a picture of the results, to really be useful the results of research should allow the researcher to accomplish other goals such as: Using information obtained from a small group (I. E. , sample of customers) to make Judgments about a larger group (I. E. , all customers). Comparing groups to see if there is a difference in how they respond to an issue. Forecasting what may happen based on collected information. To move beyond simply describing results requires the use of inferential data analysis where advanced statistical techniques are used to make Judgments (I. . , inferences) about some issue (e. G. , is one type of customer different from another type of customer). Using inferential data analysis requires a well-structured research plan that follows the scientific method. Also, most (but not all) inferential data analysis techniques require the use of quantitative data collection. As an example of the use of inferential data analysis, a marketer may wish to know if North American, European and Asian customers differ in how they rate certain issues. The marketer uses a survey that includes a number of questions asking customers from all three regions to rate issues on a scale of 1 to 5.

If a survey is constructed properly the marketer can compare each group using statistical software that tests whether differences exists. This analysis offers much more insight than simply showing how many customers from each region responded to each question. Applications of marketing research can be divided into two broad areas: 1 . Strategic 2. Tactical Among the strategic areas, marketing research applications would be demand forecasting, sales forecasting, segmentation studies, identification of target markets for a given product, and positioning strategies identification.

In the second area of tactical applications, we would have applications such as product testing, pricing research, advertising research, promotional research, distribution and logistics related research. In other words, it would include research elated to all the As of marketing: how much to price the product, how to distribute it, whether to package it in one way or another, what time to offer a service, consumer satisfaction with respect to the different elements of the marketing mix (product, price, promotion, distribution), and so on.

In general, we would find more tactical applications than strategic applications because these areas can be fine-tuned more easily, based on the marketing research findings. Obviously, strategic changes are likely to be fewer than tactical changes. Therefore, the need for information would be in proportion to the frequency of changes. The following list is a snapshot of the kind of studies that have actually been done in India. 1 . A study of consumer buying habits for detergents-?frequency, pack size, effect of promotions, brand loyalty and so forth. 2.

To find out the potential demand for ready-to-eat chapattis in Iambi city. 3. To determine which of the three proposed ingredients-?Tulsa, coconut oil or nee, the consumer would like to have in a toilet soap. 4. To find out what factors would affect the sales of Flue Gas Discontinuation equipment 5. To find out the effectiveness of the advertising campaign for a car brand. In conclusion, if I was working in a super market, I would collect data through Quantitative methods like surveying among my customers, handing them out friendly, time-saving and to the point questionnaires.

This way it will save both my time and the time of my customers. I will use both descriptive and inferential statistics to analyses my results and draw conclusions. This way I could present my findings both roughly for the quick understanding of the situation, as well as in detail for decisions to be made. The more you understand your potential customers, the more effective you can be in reaching them and convincing them to buy. The more you know about which customers are the easy targets, the less communications resources you waste trying to sell to the harder targets.

It follows then that the more you understand how your customers buy, the more you can focus your sales and marketing efforts. Evidence is a critical component in every owner's or manager's toolkit. Yet, too often, gut feeling is relied on instead of informed decisions shaped by good research. This is particularly the case with smaller businesses and those Just starting out; it can be difficult to gain access to funds for research, and stretched budgets are a real