Survey data analysis involves taking all that raw data you’ve just collected - comments, numbers in spreadsheets, etc. - and turning them into real, actionable information. The kind of information you can use to achieve your business goals.
The two broad categories of data are numerical and text (or written) data. Today, we will be going into greater detail about the types of text data you can gather using simple online surveys and polls.
Surveys are flexible tools that marketers use to gather pertinent consumer data for cheap. Instant surveys provide users with their test results as soon as they arrive, allowing designers to make changes to their products quickly and with consistency. Using a mixture of these two question formats will allow you to uncover intimate and surprising consumer data from your target audiences.
Close-ended questions are those that can only be answered using a predefined set of choices. “True/false” questions as well as “yes/no” questions are common types of closed-ended questions. There are, however, many other types of closed-ended question formats, namely: multiple choice, drop down questions, and ranked choice questions.
Close-ended questions are the best format for capturing quantitative data - that is, data related to numbers and figures. Quantitative data is extremely useful for researchers looking to make informed, factually-accurate decisions. Not only is the data provided by these types of questions very easy to visualize and display (in the forms of infographics or charts) - they enable you to delve deep into whatever subject you’re researching.
Questions like “How many times have you purchased our products in the last 3 months?” or “Which of the following elements of our product do you value the most?” can shed light on some powerful consumer insights. The biggest brands are always looking to survey their customers with these exact types of questions. The reasons are obvious; the results they garner provide immediate benefits, and allow marketers to keep abreast of changing consumer trends.
Conversely, open-ended questions are those designed to capture qualitative data. Open-ended-questions are sometimes referred to as being the “CEO’s favorite question” because they provide valuable insight into the minds of your consumers and to learn how they view your brand.
Open-ended questions - in lieu of pre-selected answer sets - provide survey respondents with an open-form text box for them to record their thoughts. Free-response text boxes often provide respondents with 500 characters or more to share their true feelings about and experiences with your product.
Open-ended questions can be used to address a broad range of research queries and concerns. “How has our product impacted your life?” or “What can we do to improve our customer experience?” can provide you with extremely nuanced and unique looks at your product and the way customers interact with it.
To get the most out of your survey results, start by asking yourself some important questions. If you can plan out your survey ahead of time - conducting it with clearly defined goals and with purpose - you will find that the data practically visualizes itself.
Every survey should be designed to tackle one clearly identified subject. When it comes to gathering customer sentiment through surveys, your customer’s time is more valuable than gold. Writing concise survey questions with focused direction is the best way for you to show you respect your customers’ time; in return, they will be more likely to answer your survey promptly and in its entirety.
Having a clear goal in mind when you design your survey increases the clarity of your results tremendously. When all of your data pertains to one specific subject, or answers one small part of a greater question, you will have a far easier time putting that data into a pragmatic context. A context that derives a greater understanding of your audience because of it.
Your variables are any value, object, or event that your testing seeks to explore or manipulate. Your independent variable is the subject of your testing - the outlier that you want to observe. The values that change when you manipulate the independent variables are therefore known as dependent variables.
You could measure the efficacy of your product elements or business designs by running multiple iterations of the same concept test, tweaking design elements (the independent variable) slightly each time and recording how audiences perceptions’ (the dependent variable) changes with each run. Alternatively, you can attempt to extract the most amount of useful information from your existing data-set through strategic analysis.
Using existing surveys and experimental research and comparing it to your most recent tests can prove to be a fruitful endeavor for researchers looking to keep research costs low. Survey data analysis methods like data visualization can give new context to your variables, and aid in your interpretation of the questions you’re trying to explore. We will explain how to visualize your data sets later on in this guide.
Identifying patterns or “trends” in your data will enable you to forecast and predict certain changes in the behavior of your core buying audience. Businesses that can stay on top of developing trends in their target market will find themselves at a competitive advantage vs. their more out of touch, slow-to-adapt competitors.
When you are combing through your research data, try to extrapolate the gaps in your results using what you already know about your audiences’ taste. Even if you are a new entrant into this market, there are a myriad of ways one can gather information about consumer trends.
Sampling errors occur whenever there is a deviation between a sampled audience and the population at large. These types of errors are significant in the way that they can invalidate the results of your survey - making your test worthless.
There are several varieties of sampling errors, all stemming from different problems originating from the audience sampling process. These errors can be controlled by taking steps to ensure the right target demographics are being surveyed - and in a sample size that is properly significant.
Data visualization is a key component for any survey analysis. You’re going to want an idea for how you’re going to organize your data ahead of time, as it will make the process much easier later down the line.
Your audience is one important factor that shapes the overall design of your data visualization. Who do you plan on sharing these results with? Investors, customers, co-workers? These are all very distinct groups. Take your audience’s familiarity with the subject matter and their relationship to the survey into account when you organize your data. This strategy will ensure that your results have a far better chance of being properly communicated to your audience.
The best and most affordable way business owners can generate quality, reliable consumer feedback is through conducting consumer response surveys. Digital survey platforms like Survicate, SurveyMonkey, and Helpfull enable their users to not only run tests, but also manage and interpret their results. The ideal platforms for surveys are those that offer real-time feedback or instant surveying.
Helpfull is a living, growing platform built around the core principles of accessibility and usability. A community of thousands are ready and waiting to test your products; giving you the feedback you need to turn your project into a resounding success.
An intuitive user-interface, coupled with the ability to gather hundreds of consumer responses in just minutes, are just a few of the features that make Helpfull the ultimate tool for any artist, designer, marketer, or inquisitive spirit.
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