Know About Statistical Surveys For Marketing

What Are Statistical Surveys In Marketing?

Statistical surveys are used to conduct quantitative research about items in a population. Surveys of human populations and institutions are common in political polling and government, health, social science, and marketing research. A statistical survey is any structured inquiry designed to obtain aggregated data, which may be qualitative or quantitative where the individual or corporate identities of the respondents are in themselves of little significance. A survey may focus on opinions or factual information depending on its purpose, and many surveys involve administering questions to individuals (Hamzehpour 2021). When the questions are administered by a researcher, the survey is called a structured interview or a researcher-administered survey. When the questions are administered by the respondent, the survey is referred to as a questionnaire or a self-administered survey. It is an efficient way of collecting information from a large number of respondents (Gajanova, Nadanyiova, and Moravcikova 2019). Very large samples are possible. Statistical techniques can be used to determine validity, reliability, and statistical significance. Surveys are flexible in the sense that a wide range of information can be collected. They can be used to study attitudes, values, beliefs, and past behaviors. Because they are standardized, they are relatively free from several types of error. There is an economy in data collection due to the focus provided by standardized questions. Only questions of interest to the researcher are asked, recorded, codified, and analyzed. Time and money are not spent on tangential questions (Sallis et al. 2021).

What Are The Advantages of Statistical Surveys In Marketing?

Advantages of Surveys

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 an incentive in cash or kind, which can be as low as $2 per person. On the other hand, other data gathering methods such as focus groups and personal interviews require researchers to pay more (Udriyah, Tham, and Azam 2019).

High Representativeness

Surveys provide a high level of general capability in representing a large population. Due to the usual huge number of people who answers the 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 (Papadas et al. 2019).

Convenient Data Gathering

Surveys can be administered to the participants in 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 (Lipkind, Kitrar, and Ostapkovich 2019).

Good Statistical Significance

Because of the high representativeness brought about by the survey method, it is often easier to find statistically significant results than other data gathering methods. Multiple can also be effectively analyzed using surveys (Udriyah, Tham, and Azam 2019).

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 (Lipkind, Kitrar, and Ostapkovich 2019).

Precise Results

As questions in the survey should undergo careful scrutiny and standardization, they provide 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. They are less expensive than interviews and they do not require a large staff of skilled interviewers. They can be administered in large numbers all at one place and time (Papadas et al. 2019).

Why Are Statistics Surveys Important For Business And Industry?

A survey is a crucial tool used by businesses to gather relevant data from different directions to gauge customer expectations and also reflect on how good their products and services are doing in the current market scenario. Surveys allow a business to efficiently collect honest feedback, opinions, and responses from customers and use that information to improve different areas of the business (Novak, Bennett, and Kliestik 2021).  Survey responses can confirm or provoke discussions on strategic business decisions and provide unbiased data to guide decision-making Surveys can help gauge the representativeness of individual views and experiences. When done well, surveys provide hard numbers on people's opinions and behaviors that can be used to make important decisions. A market survey can help build an effective marketing and advertising strategy as well as contribute to enhancing the features of a new concept before entering the product or service into the market (Jarmin 2019).

How Statistical Surveys Quantitative Track Things helpful in Marketing?

Quantitative Market Research is a technique to ask questions to the target audience in an organized manner using surveys, polls, or questionnaires. Received responses can be analyzed to make well-thought decisions for improving products and services, which will in turn help increase respondent satisfaction levels. Surveys provide businesses with feedback and information about customers' wants and needs. Surveys can have different goals. For example, one survey might gauge your target audience's familiarity with your brand, while another might serve to drum up new leads. Choose the right survey type for your goals. Quantitative research will help to tell you Whether customers are looking for or need a product like yours, Who your target population should be and what convinces them to buy, What, if anything, your target population knows about your market or your product, and whether your target market’s attitude or perception is changing, which can give insights into how you should respond (Fisher and Kordupleski 2019). 

Organizations are dependent on quantitative analysis for the statistical evaluation of data because it gives systematic, detailed information about the problem at hand or the target audience. This market research technique revolves around surveys, questionnaires, and polls, and the data collected is evaluated numerically, statistically, and mathematically to form better strategies and marketing plans. A critical factor of surveys is that the responses collected should be such that they can be generalized to the entire population without significant discrepancies (Mooi, Sarstedt, and Mooi-Reci 2018).

Analyzing quantitative results is easier now with survey tools like Survey Monkey, Survey Gizmo, and Qualtrics. But those tools won’t be able to remove outliers or include questions that will weed out people who didn’t understand the question and people who rushed through without reading (Lipkind, Kitrar, and Ostapkovich 2019).

Why Are Statistics Used For Quantitative Research?

Quantitative research methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Statistics allow you to evaluate claims based on quantitative evidence and help you differentiate between reasonable and dubious conclusions (Sheard 2018). That aspect is particularly vital these days because data are so plentiful along with interpretations presented by people with unknown motivations. It enables us to maximize our interpretation, understanding, and use. This means that statistics help us turn data into information; that is, data that have been interpreted, understood, and are useful to the recipient. Statistical analysis is the main method for analyzing quantitative research data. It uses probabilities and models to test predictions about a population from sample data. What's the difference between descriptive and inferential statistics? Descriptive statistics summarize the characteristics of a data set. Cross-tabulation is the most widely used quantitative data analysis method. It is a preferred method since it uses a basic tabular form to draw inferences between different data sets in the research study. Quantitative analysis involves the quantifying of data with the help of some form of statistical analysis. Quantitative analysis generally involves statistical techniques like significance testing, regression analysis, multivariate analysis, etc. (Pyrczak and Oh 2018).

References

Fisher, N.I. and Kordupleski, R.E., 2019. Good and bad market research: A critical review of Net Promoter Score. Applied Stochastic Models in Business and Industry, 35(1), pp.138-151.

Gajanova, L., Nadanyiova, M. and Moravcikova, D., 2019. The use of demographic and psychographic segmentation to create a marketing strategy of brand loyalty. Scientific annals of economics and business, 66(1), pp.65-84.

Hamzehpour, M., 2021. Identify and explain the entrepreneurial marketing model for startups. Commercial Surveys.

Jarmin, R.S., 2019. Evolving measurement for an evolving economy: thoughts on 21st century US economic statistics. Journal of Economic Perspectives, 33(1), pp.165-84.

Lipkind, T., Kitrar, L. and Ostapkovich, G., 2019. Russian business tendency surveys by HSE and Rosstat. In Business cycles in BRICS (pp. 233-251). Springer, Cham.

Mooi, E., Sarstedt, M. and Mooi-Reci, I., 2018. Market research. The process, data, and methods using stata.

Novak, A., Bennett, D. and Kliestik, T., 2021. Product decision-making information systems, real-time sensor networks, and artificial intelligence-driven big data analytics in sustainable Industry 4.0. Economics, Management and Financial Markets, 16(2), pp.62-72.

Papadas, K.K., Avlonitis, G.J., Carrigan, M. and Piha, L., 2019. The interplay of strategic and internal green marketing orientation on competitive advantage. Journal of Business Research, 104, pp.632-643.

Pyrczak, F. and Oh, D.M., 2018. Making sense of statistics: A conceptual overview..

Sallis, J.E., Gripsrud, G., Olsson, U.H. and Silkoset, R., 2021. Research Methods and Data Analysis for Business Decisions: A Primer Using SPSS. Springer International Publishing.