You may think you’re done once you receive the feedback. It is important to then analyze the survey results. Create a data-analysis plan to help you analyze the data.
How can you make a plan to analyze your data? To begin with, you need to know the objectives that you had for your survey. This guide will assist you in creating a data-analysis plan that makes the most of the information provided by your respondents.
What is the purpose of a data-analysis plan?
Consider your data analysis plan a roadmap to help achieve your ultimate goals. A good analysis plan will help you to get answers for your key questions, including “How do the customers feel about the new product?” By asking specific questions. This will allow you to separate the respondents and see how their opinions differ based on demographics.
Making a Data Analysis Plan
You can create a data analysis plan following these simple steps.
Check your goals
Usually, when you design a survey, there are specific goals you want to achieve. It could be to answer a question in academia, measure customer satisfaction, or for another purpose.
You may want to ask potential customers how they feel about your new product if you’re beta-testing it. You likely had several topics in mind, including:
- What are the typical experiences with this product?
- What demographics show the greatest positive response? What demographics are responding most positively?
- Is there anything specific that needs to be addressed before the launch of your product?
- What features should you add to the product before it launches?
Use these survey objectives to organise your data.
The results will help you to determine the most important questions.
You’ll probably include at least two questions in your survey that relate directly to your main goals. In the example of beta testing above, you might have two top questions:
- How satisfied are you with the overall product?
- Would you buy this product?
These questions will give you a good idea of what your customers think. This information is crucial for your business. It is important to understand why beta testers react the way that they do.
Questions can be grouped according to their specific goal
You’ll then organize your survey responses and questions by the research question that they address. If you want to assign questions for the “overall” section, such as:
- What is your opinion of the product?
- Do you have any complaints about the product that you purchased?
- What was your favorite/least favourite feature?
- How helpful did the product prove to be in reaching your goal?
Answers to demographic questions include:
- Period of life
- Gender
- Place
- Education level
- Industry
- Occupation
This allows you to decide which questions or answers will best answer your larger questions. For example, “which demographics most likely had a good experience?”
Demographics is a key factor to consider
The demographics of a target market are very important for a data-analysis plan. You’ll obviously want to find out what your testers think of the product, but you also need to identify your target audience. Demographics can provide a lot of insight into the responses.
If you want to target the over-65 demographic, you can use survey data to refine your product before it launches. You can refine your product to appeal to the over-65s demographic by using the survey data.
It can also be useful to separate people by demographics. You may find that the product you’re selling is more popular with those who work in the tech sector, as they are used to a simpler user interface. Those from other sectors, such as education, might have trouble using it effectively. If your product is targeted at the tech community, it may not require any modifications. However, if its primary purpose is to be used by educators, changes will need to be made.
You can also compare the experiences of different groups by comparing factors such as location, education, income, and many other demographics. You may compare different demographics to gain accurate insights into your survey results, depending on the ultimate goals of your survey.
Consider correlation vs. causation
Remember to distinguish between correlation and cause when creating your data-analysis plan. As an example, having a user experience that is difficult might be correlated with being older, but it could also be caused by something entirely different. You may discover that users over 65 tend to have certain educational backgrounds, or they might struggle with reading the user interface text. Consider all of the data and their impact on the results.
The next step is analysis
You can then move to data analysis once you’ve assigned your survey questions to research questions. If you already use a survey tool that allows quantitative or qualitative analyses, it’s possible that the software is already included. Use the software that you have to perform the quantitative and/or qualitative analysis.
After the research process is complete, you should have the answers to your main questions.
Voiceform: a powerful tool to analyze data
Voiceform will collect and analyze data once you’ve established your survey objectives. The feature-rich platform includes an easy to use interface, multiple-channel surveying tools, multimedia question formats, and powerful analytical capabilities. We can assist you in creating and implementing a data-analysis plan.