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Business growth all boils down to tweaking and evolving to meet the demands of your customers. To do that, you’ve got to understand what your customers want — what’s their pain point, and what are they looking for? Well, that’s where data analysis of survey results comes into play.
A good survey is paramount to your business growth. And it goes beyond coming up with some questions and blasting them to everyone on your email list. That’s not to say that you need to be a tech lord or be a whiz in quantum physics before conducting good surveys. It’s an easy process — and you will discover how to do just that.
Data analysis of survey results means making meaning of the information gotten from your surveys. With survey data analysis, you get to dive into the thoughts of your customer, distill their intentions, and make informed decisions that will be of much benefit both to you and your loyal customers.
Let’s face it; random, biased, and skewed data is of no use. To get the best, you need to perform accurate survey data analysis. You will also learn about a tool in this tool which provides good visualizations for survey analysis. But before diving into how to conduct survey data analysis. Here is a brief overview of survey data analysis.
In this blog, you’ll learn the following:
Whatever industry you are in, you would have to make decisions. Good decisions are not a product of your imagination. Far from it, it should be from a reliable source — comprehensive data gotten from your customer. Here’s where survey data analysis comes into play.
Survey data analysis is the process of drawing insights and reasonable conclusions from data gathered from your clients. The gathered data could be in the form of qualitative statements, hard percentages, or anything in between.
By carefully keeping a close eye on your data, you can identify patterns. This will, in turn, help you have an overview of what the entire data set entails. For instance, if you manage a digital marketing agency, and notice that your customers mention the slow load time of your website. You would get a good grasp of why you’ve been experiencing a high bounce rate on your website. And a high bounce rate will pretty much affect your sales — your sales would tank!
To get data analysis of survey results, you’ve got to use standard procedures to get surveys from your audience. This way, you get to minimize the level of biased opinions, and pretty much get data that would help you make informed decisions.
One sure way of getting reliable data from your audience is by using questionnaires — whether it’s online or offline, the results gotten from questionnaires will do just fine. But you can step up your game by getting data using social networks, QR codes, or emails.
Now you have a good understanding of what survey data analysis is, you’ve got to take a look at what makes up an international online survey.
If you’ve seen or completed a digital questionnaire over the internet, then you’ve probably seen an international online survey. It’s structured questions where the target audience (or respondents) gets to fill out a form. The process is quite natural and less time-consuming.
Traditional methods of gathering data are good. But if you are looking for a less expensive and more engaging way of gathering data, then an international survey is probably your best bet. To get started, you would have to work with a team of experts who would evaluate the data stored in your database.
To boost the level of participation in an international online survey, you’ve got to offer something — an incentive in the form of discounts, reward points, or gift cards — anything that would be of much value to the respondents. This way, you get to mine data from your audience, while they gain physical rewards. It’s a win-win situation for everyone.
If you come across two international online surveys, which would you most likely complete — the one with an attached reward, or the one without a reward? It’s probably the one with a reward — and that’s how your customers think.
Simply put, having a reward attached to an online survey would likely help you generate more data from your target audience. There are no two ways about it.
Moving on, international online surveys could come in various formats — they could come as complex questions or simple ones.
Hypothetically, if you’ve got data on how people from different countries spend their spare time, the survey data analysis will be similar to the image below.
Visualization Source: ChartExpo
You can either opt to combine multiple charts to report your results or go for a single chart.
Visualization Source: ChartExpo
In a nutshell, survey analysis helps you to draw meaningful conclusions about your audience. By merely asking for opinions or feedback about your company, you would dive into the minds of your audience, and pretty much know their thoughts. This will, in turn, help you make relevant adjustments and boost the overall service delivery of your business.
Now, here is how to create surveys using good designs.
You probably know that surveys help individuals, companies, or organizations extract meaningful data from the public. Here are some things you’ve got to know before creating surveys.
You will gain nothing if your result (or aims) are unplanned at the beginning of your survey. Your methods and plans should be thoroughly represented as milestones. Furthermore, you should have a good grasp of the right distribution channels for your survey samples.
There is nothing fancy in using complex, not-easy-to-comprehend language — that’s a recipe for disaster. To help your audience get a good grasp of what your survey is about, you’ve got to use simple language.
Surveys come in various ways and formats — and the question type influences the engagement you would likely receive. To get the most out of your survey, figure out the best question type that suits your audience and use it.
Also, the question type should fully extract the kind of information you desire from your audience. Generally, multiple-choice questions or Net Promoter Score questions boost the response rate of surveys.
Ideally, the survey objectives should pretty much determine the number of questions used in the survey. Every question should count, and the questionnaire length should pretty much be dependent on the vital data metrics needed in the survey.
Logic dictates almost everything in your survey design. Flawed logic interrupts the flow of effective communication, and your audience will seldom supply the data you desire. To get the best out of your survey design, the logic has to be tested. If not, you are on a failed mission.
If you are using rating scales, then it has to be consistent. The consistency must be maintained throughout the survey work. Let’s say you use a scale range of -5 to +5 for one question, using a different scale range in another question may be a deal-breaker — you would likely get your respondent confused.
Surveys come with varying question types. It would be best if you use the question type that best fits your audience. Also, the question type has to be easy to understand. But if you desire more responses from your survey, then you should opt for multiple-choice or Net Promoter Score questions.
Regardless of how good you are, or how skilled your survey data analysis is, if there are flaws in your data, it won’t do you much good.
Here’s the thing; whatever results you get from your survey pretty much reflect how your customers feel about your business. To get usable and accurate survey data, here are some things you need to observe.
Your metrics are a vital piece of the whole puzzle. To get the most out of it, it has to be consistent. For instance, if you send out a survey in January to men below 30 years, and another one in August to men above 30 years, both surveys should have the same metrics system — it should be consistent. Anything short of that will do you no good in the long run.
Binary scales like yes or no responses will do you no good in the long run. It provides little to no insight into the subject matter at hand, and that’s why you should opt for a more robust scale system like the numerical ranking system.
Scale range of 1 to 10 seems okay. It provides more depth and allows for a more meaningful analysis of the subject. You can also opt for other scaling systems like the strongly agree to strongly disagree scale.
As a general rule of thumb, binary systems like yes or no response, thumbs up or thumbs down, and other similar systems are good but do not provide much insight.
If you desire a more robust system where you get quality feedback, then the numerical scale is your sure bet.
Your wordings should not be set in stone. Use wordings that would best communicate your thought process to your target audience. And if you want to communicate to a different set of audiences, use wordings that would best suit them.
All in all, your questions should help you get the right feedback from your audience.
If you want to dive more into the mind of your customers, then open-ended questions are the way to go. Close-ended questions are good but do not provide the flexibility and freedom that comes with open-ended questions.
Close-ended questions have a way of narrowing down your response, and you will most likely not get a robust response from your audience. For instance, “Please tell us about your experience while using our product” is open-ended, and gives the customer room to pour out their hearts to you.
Closed-ended questions like “what do you enjoy about our product” are flawed, and pretty much assume that the customer enjoyed the product.
Assumptions are faulty — don’t fall into it. Never assume the response (or experience) of your audience. Let them respond by themselves.
Your choice should be dependent on the depth of the insight you are looking for. If you desire more robust answers from your customers, then freeform is the right choice for you. With freeform, you get to dive more into the minds of your customers, and also get a hold of their thought processes.
How do they feel about your product, and how has their customer experience been so far? Freeform offers answers to all these and more.
With multiple-choice questions, you risk losing your audience halfway. After all, not everyone will be patient enough to go through a long process that goes into providing answers in a multiple-choice question type.
To get the most out of your survey, you’ve got to provide freedom by allowing your audience to supply answers to your freeform questions.
The next step is to analyze your survey data.
Survey data analysis is the hallmark of the whole exercise. You have to analyze, get the right insight, and move on to the next thing. Here is how to perform survey data analysis.
First things first, what is your primary objective, and what do you want to gain from your survey data analysis? Before launching your survey, or running data analysis of survey results, you’ve got to figure out what you want to accomplish in the first place.
Do you desire to figure out the primary reason why you are experiencing a high bounce rate on your website, or if your customers are satisfied with your service experience? Whatever your reasons may be, you’ve got to know your objectives before starting.
Like anything worth doing in life, you’ve got to do your homework, and figure out what you want to accomplish in the first place.
Here, you get to figure out what your audience is saying. By merely taking a close look at the cross-section of your audience, you get to figure out the categories that have positive things to say about your product and those who have negative things to say as well.
By merely taking a close look at your variables, you would see patterns. These patterns are vital pieces of your survey data analysis. When you pinpoint trends in your data and confirm the authenticity of your data sample, then you can proceed to apply what you’ve discovered. After all, there is a reasonable confidence level in your survey data analysis, and drawing conclusions from it seems like the way to go.
Regardless of the technical skills of your audience, data visualization tools are easy ways of showcasing your data. Without good visualization tools, you run the risk of boring your audience to death — well, not literally, but you get the point.
For starters, you can opt for infographics. Infographics are compelling visuals that make graphs and charts engaging. By using infographics, you would get a good mix of charts, texts, and some graphics. It’s an ideal way of spicing up the work that goes into the data analysis of survey results.
Regardless of your industry, or the kind of data you are working on, using data visualization tools is one of the best ways of showcasing data analysis of survey results.
Now you’ve got your data ready, it’s time to look into it to see if you can identify patterns that tally with your original thoughts or ideas.
If there are patterns, you’ve got to double down on your data to see if you can identify other high-level patterns. Finally, you’ve got to narrow down your search to see if you can figure out more insights about the data at hand.
Launching a survey is good, but it’s of no benefit if you can’t analyze it. To curb the stress and hard work that goes into manually analyzing your results, you have to opt for tools like ChartExpo.
Here is how to perform data analysis of survey results using ChartExpo.
Let’s say you’ve gathered survey results, and you want to analyze them. The first thing is to click on the ChartExpo add-on to launch it.
Next, click on the create chart icon, and choose the Likert Scale chart.
Highlight your datasheet, choose your metrics and dimensions, and hit the create chart icon.
The displayed result will be similar to the screenshot below.
Excel helps in performing data analysis of survey results without losing much sweat. You can start by opening the Excel application on your desktop.
Next, open your worksheet and hit the insert menu where you get to see the My App option. After that, click on it and also click the See All option.
A screen will be displayed where you get to see the ChartExpo for Excel add-in. If there is nothing of such, click on the Refresh icon. Next, select the add-in and hit the Insert button.
To log in, you have to create a new account or use your existing Microsoft account. The add-in comes with a first-time login policy where you get to log in just once — you won’t have to go through a login process next time you try accessing the add-in.
Users with Excel 2013 version should install the pack 1 service into their computer.
To get started, click the create Chart icon.
The next screen displays a list of various charts.
Click on the Specialized Survey Charts, and the drop-down menu, click on the Customer Satisfaction Chart option.
A screen showcasing your customer satisfaction will be displayed.
Finally, click on the Explore Sample Data to create your chart.
The sample data is not yours, replace it with your data and click the Create Chart from sheet data.
You will get a result similar to the one shown below.
If you manage a restaurant like the one shown above, you would see what your customers think about your service delivery. From the results, you can come up with ways of revamping your service offering.
Survey analysis is the series of work that goes into analyzing (or studying) your survey results obtained from your target audience. The survey could be Net Promoter Score surveys sent out to your customers.
Online, paper, telephonic, and one-to-one interviews are the four types of surveys. Online surveys are pretty much the most popular kind of survey. In paper surveys, you get to use traditional tools like pen or pencil, while telephonic surveys are done over the telephone.
After a good survey process, you would get results outlined in a report, and such a report is called a survey summary. Survey summaries are studied by a manager (or leader in the industry), and it helps them identify their next move.
With a survey summary, the manager (or leader) pretty much gets a good grasp of the background behind your survey and also identifies the objective(s) of the questionnaire. All in all, a survey summary helps provide a robust survey data analysis.
Business boils down to providing satisfactory products (or services) to your customers. Simply put, a good business serves the customers well. To serve your customers, you’ve got to understand them — and that’s where data analysis of survey results comes into play.
Gathering data that you cannot analyze will do you no good. What’s the essence of carrying out a survey if you don’t have the necessary tools to translate it into digestible information? It’s a lose — lose situation.
The good news is, you can avoid such a situation through survey data analysis.
The best part, you don’t have to be a data whiz to perform survey data analysis. By merely launching out surveys with open-ended questions, you get to dive deep into the minds of your audience.
Furthermore, you can use visualization tools like an infographic to study the results.
Now you have a good grasp of how to perform data analysis of survey results, what kind of data will you be analyzing using ChartExpo?
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