It is no secret that data can be beautiful when the right strategies are applied. The challenging part is converting your survey analysis into a comprehensive report that individuals can easily read and comprehend the message. Survey analysis and reporting are considered technical by most people who conduct surveys and analyze the data collected. The truth is that this process can be simplified and made easier by applying the right tools and techniques.
Survey analysis and reporting are basic components that every business owner needs to invest in for them to access meaningful information that can help them in decision-making. Even though the process involves some technical aspects that you need to comprehend, there is a simple route that you can follow to extract meaningful information from your survey data.
This article discusses the art of survey analysis and reporting that every business owner and data professional needs to learn and master. Let’s get into the details!
What is Survey Data Analysis?
Survey data analysis refers to converting your survey results materials into meaningful insights and information that you can use when making fundamental decisions within the business. Note that this is the most important part of any type of survey that allows you to generate meaningful information from the survey data and use it to achieve your goals. There are different methods used in the process to make the analysis task easier and save time.
After conducting a survey and collecting data from the respondents, the information collected needs to be converted into actionable insights to guide you when making valuable decisions. The data collected from the survey is arranged in an organized manner that individuals can easily read and comprehend the information delivered. Data visualization is also used to help convert survey data into attractive visuals that are easier to read and grasp.
Steps to Analyzing Survey Data
Analyzing survey data involves different stages that you need to navigate through before collecting the information you need. These steps include:
Review the Research Questions
The research questions refer to the underlying questions you intend to answer using the survey. Note that the research questions are not similar to whatever is outlined in the questionnaire. However, all these questions can be similar since they operate on similar grounds to collect information that can help you achieve your objectives. You need to start by reviewing your research questions before analyzing the survey data generated from the questionnaire.
Cross-Tabulate the Data
Cross-tabulation is sifting through your data sets to uncover the hidden meaning. This process involves breaking data into different groups, making it easier to visualize the data sets and extract the hidden insights. It helps you to compare the relationship in the datasets, which helps you in making meaningful decisions from the survey data. All your focus should be channel on research questions that help to address your objective and can collect the exact information you need.
Review and Investigate the Results
The next step is to place your survey data into the right context and compare it with your industry benchmark. In addition, you can compare the data conducted with the past survey data that is available. Evaluate how the respondents from different demographics have answered the survey questions and use the data to group the information collected. When you evaluate the survey data closely, you will realize that it tells a particular story about customers from different demographics.
Incorporate Statistical Analysis to Evaluate Your Findings
Statistical analysis is made to help you evaluate the statistical significance of the data collected from your survey questions. Statistical analysis tools are involved in the process to help you better understand the survey areas that matter the most. It pinpoints the significant areas of focus and specific data type that has more weight toward the topic of discussion.
Survey Data Reporting
When analyzing data from your surveys, you will realize that it is not friendly to the reader’s eye. Reporting allows you to turn the data into attractive visuals that you can easily read. Below are the factors to consider during survey data reporting.
Make it Visual
The easiest way to present survey data is to turn it into attractive visuals using different types of charts and graphs. You can also tabulate the results in a format that readers can easily recognize their existing relationship in the data sets. Identify the best graphic format that reciprocates the nature of your data and the audience you intend to address. There are multiple options available that you can easily choose from to help you to address your pain points.
Maintain a Human Language
Utilize a language that your readers can easily comprehend without calling for any form of interpretation. Ensure that the language you are using it is well familiarized by the readers to avoid conflict of interest. Incorporate direct quotes your readers can easily comprehend to ensure they receive the message you want to deliver. Use a language that readers can easily illustrate the points in the best way possible.
Tell the Story Behind Your Research
The power of storytelling can help you to convey data to your target audience in a context that they can all grasp. You need to present your data in the form of a story that readers can easily relate to the objective that you want to achieve with your survey. People need to understand why you decided to conduct the research and some of the goals you want to achieve in the long run.
Incorporate Your Insights
Apart from sharing the numbers collected with your market audience, also share their insights collected from the data. The insights shared should be easier to grasp compared to the data displayed. This will help you to attract the attention of your readers and eliminate technical boundaries.
Survey analysis and reporting help you to extract meaningful information from your survey data and use it to achieve your preferred goals. The data collected from a survey is always disorganized, and you need to implement various strategies to extract the information you need. Data visualization helps you to extract the hidden meaning from your survey data and display it in a context that readers can easily read and translate.