These questions have a broad range, covering different topics, with people inquiring through various methods. For organizations that use surveys to their advantage, the questions must be strategically designed and structured for the results to be accurate. When creating the survey, consider the goals of the survey, the process of application, and the decisions that follow once the survey results are available. Afterwhich, the organization produces a survey analysis report. What is a survey analysis report, and what is its purpose in the operations of a business? The article presents valuable information about the report, including its definition, components, and how-to guide. A dedicated section also answers frequently asked questions about the document stemming from various industries and sectors.

What Is a Survey Analysis Report?

A survey analysis report provides a better visual representation of the gathered data. It is a document that conveys critical information to the readers. The business must emphasize and give special attention to the survey analysis report as it can make or break other processes and operations. After completing the survey process with all the essential information and data from target groups, the next step is the survey analysis report. It contains all relevant detail from the survey and data analysis through a creative and comprehensive data story. The document serves as a tool to persuade readers to look over the information regarding the survey, whether it is to secure funds or to represent relevant information. Data without appropriate visualizations will find it difficult to communicate significant insight. Provide the best way to communicate survey data that complements a story. The best way to express a survey analysis report is using a creative and well-organized narrative containing visual representations to deliver clarity.

According to the United States Census Bureau, there are more than 130 surveys and programs a year they execute. The surveys include the nation’s two largest surveys, including the household survey, the American Community Survey, and the business survey, Quarterly Services Survey. These surveys range from opinions from different target groups that influence different sectors and industries.

Tips to Analyze Survey Data Results

Before an individual or a team can write a comprehensive survey analysis report, they must first collect and analyze the results from the survey questionnaire. Getting the right amount of information is already hard as it is, and providing inaccurate data analysis makes things worse. Below are helpful tips that can help with analyzing data results.

Understand the four measurement levels: Before analyzing the survey data, the researcher must understand the four available measurement levels. These measurement levels help the team or individual determine the process of measuring survey questions and the statistical analysis method to use. The four measurement levels are ordinal scale, interval scale, ratio scale, and nominal scale. The ordinal scale determines the order of values. In using the scale, there is a quantitative value as there is one element is higher than the other. Ranking or ordering items on a grocery list is an example of an ordinal scale. Researchers can analyze the median and mode and use the cross-tabulation analysis for this measurement scale. The interval scale describes the order of values and their differences. The scale consists of quantitative values with data intervals remaining equivalent in the scale without a true zero point. Many psychological tests make use of the interval scale. Researchers analyze the mean, median, and mode and utilize the ANOVA, t-test, and correlation analysis in this type of scale. The ANOVA test measures the significance of the results, while the t-test and correlation analysis determine relationships between sets. The ratio scale depicts the difference and order of values with a zero point. There is quantitative value in this type of scale as it provides information despite the lack of attributes. An example of the ratio scale is writing the amount of time spent on social media applications. The ratio scale also analyzes the mean, median, and mode and uses the same tests similar to the interval scale. The last measurement level is the nominal scale. It classifies data without quantitative values. An example is selecting the phone brand that people use. The choices present have no relation with each other, and the only way to get data is to count the number of respondents with their corresponding selections.Select survey questions: After knowing how to analyze the survey questions using the four measurement levels, take note of the overarching questions that the research is trying to solve. Segmenting questions help the researchers to isolate the vital information relevant to achieving the target goals. For survey questions, it is essential to incorporate close-ended and open-ended questions. Close-ended questions are those that contain a limited number of answers. It includes yes or no questions, multiple-choice questions, checkboxes, scale questions, and dropdowns for online survey questionnaires. Respondents can only choose from pre-determined answers. Various questions are necessary to retrieve accurate data from the survey. When it comes to open-ended questions, respondents explain their views and opinions to answer a survey question. Analyze the quantitative data first: Quantitative data is necessary as it provides statistical information to produce viable conclusions. Qualitative data produces interesting and unique interpretations, making them subjective and hard to analyze. Most quantitative data comes from close-ended questions that can be convertible into numerical data. Once it becomes quantifiable, researchers can compare and contrast information and identify market and business trends for customer behavior. It is ideal to start with quantitative data when performing survey analysis because quantitative data provides a better understanding of the survey results. It helps researchers to easily pinpoint roadblocks during the customer journey and solve the pain points that respondents identify.Cross-tabulate to better understand information: It is not as effective to analyze all the responses of respondents to gain accurate information. Instead, segment the responses from ideal customers and target audiences using cross-tabulation to receive the most precise information. The process provides data about the relationship between variables, comparing data from one chart to another. It reveals specific information from audience responses to various questions. Using the cross-tabulation process, researchers can narrow down on survey results to only get the responses from the target audience. Understand the statistical significance of the data: Not all the data from the survey is reliable, and everything is relative. Random sampling is an effective way to gain more accurate results as it utilizes a larger group of individuals. Random sampling allows the researcher or research group to utilize an arbitrary group from a larger population, creating diverse survey responses. Running information through software like IBM’s SPSS states the significance of data using the p-value. If the p-value is lower than 0.05 percent, it means that the degree of error is more than 5 percent. If the p-value is less than 0.01 percent, it means it has a high statistical significance with only 1 percent of probable error.Consider causation and correlation: A significant factor of survey analysis is knowing if the conclusions are accurate. Just because there is a correlation between two factors does not equate to causation. Usually, there is a third variable, or an independent variable, that influences the two factors. When concluding, make sure that there is sufficient evidence through data analysis before assuming what the target market thinks, feels, or acts.Compare past and present data: If it is the first time that researchers are conducting a survey analysis, make the results the benchmark for future survey results. Compare the future results to the current record, and track the necessary changes that happen over months, years, quarters, and other intervals. Researchers can also utilize the records to improve the experiences of sub-groups in the future.

How To Write a Survey Analysis Report

If a researcher presents data to stakeholders, executives, and business partners, there must be a full report of the findings you have from the data analysis. It is necessary to keep track of all the information that you currently have, maintaining all past and future records for reference. It is so you will not waste time duplicating research and lessen the number of errors. Below are helpful steps to write a survey analysis report.

  • 1. Indicate the Outcome of the Survey

    For the audience to focus on the specific outcome you wish to relay after reading the document, start to explain the survey outcome in great detail. The survey outcome comes in the middle of the survey analysis report, but it is a valuable roadmap when writing the report, especially if it is lengthy. The section describes the probable scenarios if stakeholders are on board after reading the survey results. The ideas for outcomes consist of new product offers due to critical customer feedback, price increases or price adjustments to increase business revenue, and exploring new markets for expansion. Guarantee that collected data supports the outcome and avoid ideas that do not stem from the results of the report.

  • 2. Write the Research Summary

    The next step is to summarize the research findings. Indicate all the notable outcomes and all the information that shows the correlation with previous research on record. The research summary becomes an essential part of the survey analysis report that the readers focus on as it contains a brief description of all the essential details of the document. In writing the research summary, ensure that it is no longer than a single page. For readers to find it easier to read, indicate headers before paragraphs as a guide through the contents.

  • 3. Draft a Rough Report Outline

    The average length of a survey analysis report ranges from eight to ten pages. Therefore, a researcher must find a way to make the contents concise and comprehensive, highlighting information that the stakeholders need to know. The outline consists of an introduction that sets the stage for the report. It also includes a summary detailing the key findings and elements of the research. The methodology section explains the research process. The results section describes the data from research, while the outcome section analyzes the results according to organizational goals and objectives. Finally, the limitations and conclusion describe the research oversights for future research and a summary of the survey analysis.

  • 4. Select a Layout To Use

    A survey analysis report can be in landscape or portrait format, depending on the choice of the researcher. It is ideal to use a portrait format when the report focuses on text elements. It is also best to avoid entire pages for images or infographics as it takes away the space for necessary text-based information. A researcher should utilize the landscape format if the report aims to be design-heavy. It means that the report consists of high-quality images, charts, graphs, and infographics as text-based content is best set on the sides or below these visual elements.

  • 5. Indicate the Methodology and Limitations of Research

    The methodology details the procedures and processes of conducting the research. It also indicates the participants and the types of tests that the researchers used. The researcher can indicate a pie chart or line graph to represent and communicate the data. Use as much detail as possible as readers will want to know the research outcomes. Indicate the number of respondents, selection method, and demographical data. Describe the process of selection survey questions and the test selection. The limitation section sets up future research. It also provides future researchers to continue the study or correct mistakes in the present survey.

  • 6. Indicate Appendices as Necessary

    In cases where the report cannot hold all the data used for the research, the truncated versions of the graphs, charts, and tables that are present in the document must be a part of the appendix section in their raw forms. Throughout the survey analysis report, reference the appendix in order for the reader to review the information and have a better understanding of the content.


How important is a survey report?

A survey report is essential to many businesses and organizations that provide solid and factual numbers, deliver essential benchmarks, uncover precise data, and give an encouraging voice to customers.

Which tools can be used for data analysis?

There are different types of data analysis tools. The most common of all is Microsoft Excel. Aside from Excel, applications like KNIME, SAS, Python, and RapidMiner.

What is the best data analysis method?

Depending on the type of data, various data analysis methods will help arrive at the most accurate results. For qualitative research, content, discourse, and narrative analysis are useful. For quantitative data, researchers use regression, factor, and cohort analysis.

Survey analysis reports are relevant in different organizations as it relays vital information about target markets, including trends and feedback. Businesses must conduct surveys regularly, whether it is monthly, quarterly, or annually. Research surveys allow organizations to collect honest and critical feedback, responses, and opinions from consumers and clients and utilize the information to improve the business. Start conducting surveys to the target market and perform data analysis to produce reliable and accurate information. Afterward, construct a detailed survey analysis report, and choose from the 13+ SAMPLE Survey Analysis Report in PDF from the article above.