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Before you can begin thinking about how to analyze survey data and the best way to present survey results, you need to understand how you will measure each question and what type of analysis is necessary for making sense of the raw data and responses.
Data visualization is an increasingly popular term, especially for those that are routinely analyzing their data. Data visualization is the process of taking your data and translating it into something visual, like a chart or map.
When you’re trying to detect patterns, trends, outliers, and other events in data, visualizing the numbers is the most effective strategy. By turning raw, statistical figures into something visual, it becomes easier for the human brain to comprehend complex data sets.
In other words, good data visualizations put meaning and context to your collected data, even when the information is complicated in nature. This is also very useful when presenting or reporting your findings to others. You want audiences to quickly reach the desired conclusion.
If you’re analyzing and presenting survey results, data visualizations are the best way to present data. Typically, you’re forced to sift through the survey results and pick out key trends and behaviors by hand. Then, you need to decide how to use the results and present the findings to your sales, marketing, and customer service teams.
If this process sounds familiar, then it may be time to look for a new approach.
In this blog you will learn:
In the following video, you will learn how to present your survey results to your stakeholders in the best way. Visualizations that will make it easy for you to present your survey results as they are very easy to create and interpret.
If you want to learn more about customizing this chart, setting properties, header, footer, and labels you can read our guide on How to Present Likert Scale Data.
This discussion will focus on the impact that data visualizations can have on analyzing and presenting survey findings and what ChartExpo can do to help.
There are a number of unique challenges that analysts face when trying to make sense of survey results. These challenges can make it difficult to visualize and present the findings. Again, surveys often deal with text and other forms of unstructured data. These insights can’t be effectively displayed with the traditional line, bar, and pie charts. You need data visualizations specifically built to present survey results.
That’s where ChartExpo enters the picture. ChartExpo is a tool used in business intelligence to visualize and present data. While there are other data visualization tools on the market, ChartExpo is specifically built to be intuitive and simple to use. After all, you don’t want to use a complex tool to solve your already-complex data issues!
With ChartExpo you can:
If you’ve tried to visualize survey findings in the past with traditional charts, you likely ran into a lot of problems and obstacles. Some of these roadblocks you were not able to overcome. That’s because survey data can be very tricky if you aren’t using the right visualization type. There is a number of visualizations that you can use as the best option to analyze and present survey results which are as follows:
We will explain all of these visualizations separately in detail in the next section. The minds behind ChartExpo understand these challenges well and have developed several charting options that are specifically designed for survey results. To demonstrate these options, let’s look at a mock use case.
Scenario: You are running a hospital or managing hospital data, you need to gain feedback from customers and patients. You have created a questionnaire and asked that patient/attendant to fill out a number of multiple-choice questions. Your survey consists of the following questions:
Once you have gathered the results, there are a lot of ways that ChartExpo can help you display and make sense of the responses you receive.
Likert Scale Charts have become a common favorite for analysts working with customer satisfaction, employee engagement, and/or employee satisfaction data. It’s a great way to obtain accurate opinions, impressions, and attitudes from respondents, especially across a spectrum of possible answers.
| Questions | Rating | Response Count |
| How do you rate the cleanliness of the hospital? | 1 | 324 |
| How do you rate the cleanliness of the hospital? | 2 | 176 |
| How do you rate the cleanliness of the hospital? | 3 | 230 |
| How do you rate the cleanliness of the hospital? | 4 | 278 |
| How do you rate the cleanliness of the hospital? | 5 | 0 |
| How do you rate the performance of the doctors? | 1 | 138 |
| How do you rate the performance of the doctors? | 2 | 186 |
| How do you rate the performance of the doctors? | 3 | 176 |
| How do you rate the performance of the doctors? | 4 | 230 |
| How do you rate the performance of the doctors? | 5 | 270 |
| How do you rate your overall experience? | 1 | 0 |
| How do you rate your overall experience? | 2 | 138 |
| How do you rate your overall experience? | 3 | 186 |
| How do you rate your overall experience? | 4 | 176 |
| How do you rate your overall experience? | 5 | 500 |
| How do you rate the quality of the hospital staff? | 1 | 0 |
| How do you rate the quality of the hospital staff? | 2 | 138 |
| How do you rate the quality of the hospital staff? | 3 | 186 |
| How do you rate the quality of the hospital staff? | 4 | 176 |
| How do you rate the quality of the hospital staff? | 5 | 500 |
| How do you rate the hospital costs? | 1 | 138 |
| How do you rate the hospital costs? | 2 | 186 |
| How do you rate the hospital costs? | 3 | 176 |
| How do you rate the hospital costs? | 4 | 238 |
| How do you rate the hospital costs? | 5 | 270 |
| How do you rate the services offered by the hospital? | 1 | 324 |
| How do you rate the services offered by the hospital? | 2 | 176 |
| How do you rate the services offered by the hospital? | 3 | 230 |
| How do you rate the services offered by the hospital? | 4 | 270 |
| How do you rate the services offered by the hospital? | 5 | 0 |
After collecting the data and organizing it with the above table, you can now turn the raw data into a Likert chart visualization, such as the one pictured below:
With this chart, it is much easier to see the breakdown of positive and negative scores, both in an overall view and for each individual survey question. This chart will help you to analyze Likert scale data.
Here are some helpful tips to follow when constructing survey questions using the Likert scale and the charting method.
Be careful with adjectives: Survey questions need to be straightforward, precise, and leave nothing up to question. This is particularly important when using a scale. It should be very clear and obvious which option is where on the scale. If your scale options are too ambiguous, survey participants may not choose the answer that actually corresponds to how they feel.
For example, if your scale is Excellent – Great – Okay – Poor – Bad, it may be unclear what the difference between poor and bad is or how excellent and greatly differ from one another. The best option is to choose extremes on both ends of the spectrum and use adjectives that reflect this (extremely satisfied / extremely unsatisfied, very happy / very sad, exceptionally good / exceptionally bad). Then, you can fill in the rest of the scale between these points with lesser degrees of the extreme.
Ask, Don’t Tell: Studies have found that human beings respond better to questions instead of statements. When developing your surveys, be sure that you are asking questions instead of making statements. Not only will this encourage more participants in the survey, but it will also better ensure that the results are accurate.
The score bar chart uses rectangular bars to measure how many respondents chose each option. The length of the bar is proportional to how many respondents selected that answer. This style of the bar chart is more reflective of the survey data. It displays each possible metric or answer with the given number of responses. This allows you to easily see which options see the most responses and whether those responses are mostly negative or positive.
For example, you want to see how people feel about the following subjects:
You use a 0-10 scale to allow survey participants to rate each metric.
| Questions | Rating | Response Count |
| Doctors | 0 | 50 |
| Doctors | 1 | 50 |
| Doctors | 2 | 450 |
| Doctors | 3 | 90 |
| Doctors | 4 | 450 |
| Doctors | 5 | 650 |
| Doctors | 6 | 950 |
| Doctors | 7 | 1050 |
| Doctors | 8 | 350 |
| Doctors | 9 | 1750 |
| Doctors | 10 | 1650 |
| Services | 0 | 250 |
| Services | 1 | 55 |
| Services | 2 | 50 |
| Services | 3 | 90 |
| Services | 4 | 450 |
| Services | 5 | 650 |
| Services | 6 | 950 |
| Services | 7 | 1050 |
| Services | 8 | 350 |
| Services | 9 | 375 |
| Services | 10 | 550 |
| Care | 0 | 250 |
| Care | 1 | 550 |
| Care | 2 | 40 |
| Care | 3 | 950 |
| Care | 4 | 540 |
| Care | 5 | 650 |
| Care | 6 | 950 |
| Care | 7 | 100 |
| Care | 8 | 350 |
| Care | 9 | 1750 |
| Care | 10 | 550 |
| Emergency | 0 | 1250 |
| Emergency | 1 | 550 |
| Emergency | 2 | 450 |
| Emergency | 3 | 950 |
| Emergency | 3 | 950 |
| Emergency | 4 | 450 |
| Emergency | 5 | 1650 |
| Emergency | 6 | 950 |
| Emergency | 7 | 150 |
| Emergency | 8 | 350 |
| Emergency | 9 | 1750 |
| Emergency | 10 | 2550 |
| Nurses | 0 | 1250 |
| Nurses | 1 | 550 |
| Nurses | 2 | 450 |
| Nurses | 3 | 950 |
| Nurses | 4 | 450 |
| Nurses | 5 | 650 |
| Nurses | 6 | 950 |
| Nurses | 7 | 1050 |
| Nurses | 8 | 350 |
| Nurses | 9 | 1750 |
| Nurses | 10 | 2550 |
| Availability | 0 | 1250 |
| Availability | 1 | 550 |
| Availability | 2 | 450 |
| Availability | 3 | 950 |
| Availability | 4 | 2450 |
| Availability | 5 | 1650 |
| Availability | 6 | 1950 |
| Availability | 7 | 2050 |
| Availability | 8 | 1350 |
| Availability | 9 | 1750 |
| Availability | 10 | 2250 |
| Staff | 0 | 1250 |
| Staff | 1 | 450 |
| Staff | 2 | 950 |
| Staff | 3 | 550 |
| Staff | 4 | 1650 |
| Staff | 5 | 450 |
| Staff | 6 | 950 |
| Staff | 7 | 1650 |
| Staff | 8 | 1450 |
| Staff | 9 | 350 |
| Staff | 10 | 2250 |
| Unsatisfied | 0 | 3250 |
| Unsatisfied | 1 | 550 |
| Unsatisfied | 2 | 450 |
| Unsatisfied | 3 | 1950 |
| Unsatisfied | 4 | 450 |
| Unsatisfied | 5 | 1650 |
| Unsatisfied | 6 | 950 |
| Unsatisfied | 7 | 350 |
| Unsatisfied | 8 | 1050 |
| Unsatisfied | 9 | 1750 |
| Unsatisfied | 10 | 2250 |
Instead of limiting yourself to a traditional bar chart, you can visualize your data with the score bar chart to see added dimensions of data that would not normally be visible.
A rating bar chart is very common in consumer reviews. Like the five-star rating system, the rating bar chart also relies on at least five points to choose from. It is typically used to measure the quality (like customer satisfaction in reviews) of a brand, product or service. This is a very familiar method for respondents to quantitatively express their feelings and perceptions about a given subject.
Let’s say that you want to check patient satisfaction at the hospital. A five-point scale is a very useful method to rating satisfaction. Similar to the scale discussed in the LiKart chart, the five-point system reflects two extremes (scores 1 and 5), two lesser extremes (2 and 4), and a neutral midpoint (3).
| Rating | Response Count |
| 2 | 210 |
| 3 | 120 |
| 4 | 120 |
| 5 | 112 |
| 1 | 205 |
When you display the survey data into the ChartExpo rating bar chart, the results look as follows with proper ordering as well:
With this visualization, you can quickly understand the results and begin making the necessary questions to alleviate your lower customer satisfaction scores.
The survey score summary chart reflects the average scores collected in a survey, particularly between Yes/No options. It displays whether the majority of respondents answered positively or negatively. When you compile multiple Likert Scale questions and the data from results into a single visualization, it can help you gain a full understanding of how customers feel about a range of topics.
For example, you pose a number of questions to hospital guests about the performance and overall experience. These questions include:
Medical lab conditions, positive or negative?
The scale is a simple positive-negative, +1 versus -1. That said, you can include more than two options with the survey score summary model and adjust accordingly
Due to the simple yes/no, positive/negative scale, the collected data is very easy to organize.
| Questions | Rating | Response Count |
| How do you rate the cleanliness of the hospital? | 1 | 324 |
| How do you rate the cleanliness of the hospital? | 2 | 176 |
| How do you rate the cleanliness of the hospital? | 3 | 230 |
| How do you rate the cleanliness of the hospital? | 4 | 278 |
| How do you rate the cleanliness of the hospital? | 5 | 0 |
| How do you rate the performance of the doctors? | 1 | 138 |
| How do you rate the performance of the doctors? | 2 | 186 |
| How do you rate the performance of the doctors? | 3 | 176 |
| How do you rate the performance of the doctors? | 4 | 230 |
| How do you rate the performance of the doctors? | 5 | 270 |
| How do you rate your overall experience? | 1 | 0 |
| How do you rate your overall experience? | 2 | 138 |
| How do you rate your overall experience? | 3 | 186 |
| How do you rate your overall experience? | 4 | 176 |
| How do you rate your overall experience? | 5 | 500 |
| How do you rate the quality of the hospital staff? | 1 | 0 |
| How do you rate the quality of the hospital staff? | 2 | 138 |
| How do you rate the quality of the hospital staff? | 3 | 186 |
| How do you rate the quality of the hospital staff? | 4 | 176 |
| How do you rate the quality of the hospital staff? | 5 | 500 |
| How do you rate the hospital costs? | 1 | 138 |
| How do you rate the hospital costs? | 2 | 186 |
| How do you rate the hospital costs? | 3 | 176 |
| How do you rate the hospital costs? | 4 | 238 |
| How do you rate the hospital costs? | 5 | 270 |
| How do you rate the services offered by the hospital? | 1 | 324 |
| How do you rate the services offered by the hospital? | 2 | 176 |
| How do you rate the services offered by the hospital? | 3 | 230 |
| How do you rate the services offered by the hospital? | 4 | 270 |
| How do you rate the services offered by the hospital? | 5 | 0 |
As you look at the visualization below, you can really see the story behind the data unfold. Each question is listed sequentially and the simple +/- scale gets right to the point of the data.
Would the majority of customers recommend the hospital? Yes
Do doctors give enough time to patients? No
Is there enough seating? Yes
Is management’s behavior okay? No
Etc.
Displaying these questions in such a way really lets you see where improvements need to be made and where you are delivering a successful experience to patients. It’s a very fast and effective way to reach actionable insights with broad data.
Whenever you ask survey participants to rate something on a scale, you can use the score detail chart to visually depict the results. The chart will calculate the NPS (net promoter score) and also display the breakdown of responses.
For the scenario, let’s say you want to dig deeper into whether or not patients would recommend the hospital to their friends and family. It wasn’t enough to just look at Yes/No responses. You want to broaden the available options to a 0-10 scale.
| Questions | Rating | Response Count |
| Would you recommend our hospital to your family or friends? | 1 | 45 |
| Would you recommend our hospital to your family or friends? | 2 | 61 |
| Would you recommend our hospital to your family or friends? | 3 | 80 |
| Would you recommend our hospital to your family or friends? | 4 | 123 |
| Would you recommend our hospital to your family or friends? | 5 | 75 |
| Would you recommend our hospital to your family or friends? | 6 | 41 |
| Would you recommend our hospital to your family or friends? | 7 | 88 |
| Would you recommend our hospital to your family or friends? | 8 | 45 |
| Would you recommend our hospital to your family or friends? | 9 | 134 |
| Would you recommend our hospital to your family or friends? | 10 | 209 |
| Would you recommend our hospital to your family or friends? | 0 | 10 |
With these results, you can quickly segment your customers into fans, neutral, and detractors. Plus, you can see how significant the swing between negative and positive sentiments is. You can immediately see that negative satisfaction vastly outweighs neutral or positive responses. Now, you can start making changes to fix these negatives in time for your next round of surveys.
The rating score chart is another visualization to look at close-ended survey questions and responses. It is very similar to the rating bar chart, but it displays results as parts of a whole. The size of each section of the bar corresponds to the percentage of all responses. If the one-star bar is the largest section of the chart, then you can see right away that there is a problem.
Rating score charts are extremely effective when you want to quantify qualities or traits that are usually difficult to bring numerical values to. For instance, rating different features of a product, evaluating various elements of the customer experience, etc.
| Rating | Response Count |
| 2 Star Rating | 210 |
| 1 Start Rating | 205 |
| 3 Start Rating | 120 |
| 4 Star Rating | 120 |
| 5 Star Rating | 112 |
This is what the data looks like with the ChartExpo rating score chart in an ordered way:
Thanks to the chart, it is easy to see relative information about the given subject and compare and analyze the results from each response. Then, you can see which metrics or components of the hospital experience need attention.
All of the charts included so far deal primarily with structured, quantitative data. What do you do with survey results that are not structured, such as open-ended responses? At the core of open-ended responses are sentiments.
Sentiments are the thoughts, feelings, and attitudes that respondents share about different dimensions of your business. For example, “I was happy that my doctor was so knowledgeable.” “Happy” is the sentiment being shared about the expertise of the doctor.
Open-ended survey responses are rich with incredibly actionable feedback. You need to know what types of sentiments and opinions customers are feeling and expressing towards your business.
The challenge is that long survey responses are difficult to analyze. Apart from reading each response individually, there are not many options. Sentiment analysis alleviates this problem by using text analytics to detect feelings and emotions in language. This allows the analyst to get right to the important parts of the survey responses.
Sentiment data can be visualized in many different ways. You can look at the trend of your overall sentiments.
For a deeper look into sentiments, you can use a Sankey or treemap chart. This shows how often certain subjects are discussed in either a positive or negative light.
These visualizations are a great way to grasp what’s really going on behind all of your open-ended survey responses. They can also be used to analyze reviews and other text-based feedback forms.
Your customers are a key piece in the marketing puzzle. Market research is an ongoing task that is focused on learning about the feelings and behaviors of your customers and seeing how to best approach these individuals.
One of the best strategies for learning about your customers is to get out and ask them. This is where the value of surveys comes into play. This research tactic allows you to ask your target audience members direct questions and receive valuable responses in return. With these insights, you can stay ahead of the competition and achieve greater marketing success.
There are a number of important goals you can achieve by conducting surveys:
While survey data can offer businesses plenty of valuable insights to further organizational goals, actually acquiring these insights from the survey results can be a real challenge. The main problem is that you can’t rely on the responses of a small sample of your audience. To ensure that your findings are accurate, you need a large sample size.
This means that you need to establish a lot of survey data for your results to be accurate enough to truly be actionable. The problem is that the more data you collect, the more tedious it is to analyze. It’s much easier to look at 30 survey responses than 3,000.
To make matters worse, survey data is often unstructured, which is especially hard to analyze.
Unstructured data comes in the form of text responses and other inputs that aren’t strictly number-based. Here is the difference between unstructured and structured responses:
A 7/10 score on a customer service feedback survey is much easier to analyze than the unstructured, open-ended response. The trade-off, however, is that your open-ended survey questions can lead to some very insightful responses. You just need to commit the time to analyze these unstructured responses.
This difference between unstructured and structured responses has a lot to do with your approach to surveying customers. Do you opt for structured questions that are easy to analyze, or do you create more open-ended survey questions that let customers share their complete thoughts and feelings? You can also mix the two approaches together.
Once you’ve developed your approach and conducted the survey, you need to have a consistent strategy for analyzing the results. There are a few things to consider at this stage of the analysis.
Before you can begin thinking about the best way to present survey results, you need to understand how you will measure each question and what type of analysis is necessary for making sense of the raw data and responses.
Before you conduct your research and develop any questionnaires or survey sheets, you should think about your goal. What do you hope to get out of this project? There are many goals that survey research can complete, which one best suits your business at this stage? It could be developing a stronger understanding of how people feel about your brand, or you may want to conduct research to develop stronger products and services. Whichever goal you choose, it needs to be the absolute focus of your survey.
Qualitative data can lead to interesting insights and feedback but its unstructured nature makes it harder to analyze. For this reason, it is best to draw conclusions from your statistical data first. This will provide a foundation of understanding that will help you derive insights from your qualitative data and even assign numerical values to open-ended responses to identify common trends in responses and behaviors.
Despite your best efforts, it is common to have survey participants that fall outside of your target audience. Since these respondents are not your target, their responses can skew your results and create wrong conclusions about the individuals that are your ideal customer.
To remedy this problem, it’s important to segment your responses using cross-tabulation. This method analyzes how audiences responded and then groups answers based on similarities. For example, you may segment your survey responses to group non-customers, new customers, returning customers, and loyal customers into their own segments.
This allows you to pay close attention to what your actual customers are saying, while also putting less emphasis on what non-customers are saying.
The data you gather through a survey is a good reflection of the current status and sentiments of audiences. It’s a good idea to compare the responses to past surveys to see how feelings and attitudes have changed. This gives you great insight into how your marketing and other strategies have helped (or hurt) shape customer perceptions about your company and offerings.
If this is your first time analyzing survey data, you can use these findings as the benchmarks. The next time you conduct a survey, use the findings you’ve just acquired to measure the changes that have occurred between now and the future.
As mentioned, data visualization is a helpful tool that provides a visual summation of the data you’ve gathered. The brain is built to receive visual signals. It’s actually performing visual analysis every moment that your eyes are open! This means that, since you were born, your brain has been building a stronger and stronger acuity for digesting visual information. Some studies have found that the brain is 60,000 times better at processing visual information than text.
The goal of any analysis, survey or otherwise, is to gain insights. If you can’t manage to obtain insights from your survey results, then the data is no longer valuable. Data visualization is incredibly useful for this because it is much faster and much easier to extract insights from survey data when you can actually see the results.
Data visualization also makes it extremely easy and effective to present results to others. Often, an analyst will uncover an insight in their spreadsheets, but then struggle to convey that finding to others.
Charts are an effective communication tool for presenting data findings to others, whether it be a colleague, a manager, stakeholder or client. Your audience will be able to grasp the insights you’re presenting and understand why they are important to the company.
No matter what visualization type you use for your survey data, your results will depend on the strength of the survey itself. To close, here are some helpful tips and best practices to consider when creating surveys and analyzing the results.
Don’t overload a single survey with too many questions. Instead, focus on asking the specific questions you want to know at this moment. This will ensure that all of the data you collect will be useful right away.
While adding extra questions may seem useful and you may think that you can use this data later on, data is always changing. The answers you receive now, but don’t use right away, will lose their relevance and value. By the time you’re ready to look at the extra survey data you’ve gathered, the sentiments shared have likely changed.
Shorter surveys also ensure greater accuracy of responses. The time of survey participants is valuable and the more you ask of it, the less engaged they will be. If they begin to feel that the survey is too long and their time is being wasted, they will submit an incomplete survey or stop putting any thought into their answers.
Continuing with this idea that the longer the survey, the less accurate the responses, it’s also important to consider how you order your questions. You want the most pressing items at the top of the list to ensure that you capture the most accurate responses to those questions.
It can also be a wise strategy to lead with open-ended questions. Not only is this feedback typically the most valuable, but it also creates a more inviting survey experience. Open-ended questions invite the respondent to share their thoughts and feelings, which makes their time and feedback seem valuable. Putting it at the top of the list is like a warm invitation that will carry through the result of the survey.
You should also aim to vary the types of questions you are asking in your order. This will help keep participants engaged and ensure that they thoroughly read each question. If every question is in the same format, respondents will begin to skim the text, which can lead to misunderstandings that hurt the accuracy of their responses.
You may already be aware of some of the issues or problems being mentioned in survey responses. For instance, if your hospital has an issue with having enough seating in the waiting room, it’s likely a concern you’re already aware of. When this is the case, surveys can be used to present possible solutions and determine the most suitable option.
This approach will show customers that you’re already aware of the areas that your business needs to improve, which can help validate their own feelings. Then, by presenting possible solutions to remedy these problems, you are including them in the process. They will feel like part of the fix!
You can create engaging and insightful presentations from survey results to share it with management to make impactful decisions and with customers to show them that their feedback is important to your organization.
When you approach your target audience with surveys, it is also important to consider the timing. Participating in your survey should be convenient for the customer. You don’t want to ask for their feedback during a time that doesn’t suit them.
For instance, retail companies rarely ask for survey responses during the holiday shopping season because they know that customers are way too busy to respond. Instead, holiday shopping surveys are conducted before or after this busy period.
You also need to align the placement of your surveys to correspond with the timing of conversions. If you are asking questions specific to your checkout process, then you only want the survey to appear in front of people that have experienced this.
It’s common for business owners to assume certain things about their business and why things are the way they are. For instance, if customer service scores are low, an owner may assume it is because they don’t have enough support staff. In reality, the issue may be more complex than that.
Don’t fall into believing your own assumptions. Instead, test them directly in your surveys. When people with different perspectives and backgrounds respond to the same subject, their answers may be totally opposite from what you’ve assumed. It’s good to bring these viewpoints into a light and consider everything.
One of the main reasons that people participate in surveys is to voice their feedback and feel like they are part of the solution. After surveys are completed, respondents want to know what impact their voice had on the results. They want to know how their feedback is making a difference.
You should be prepared to share the results with customers and survey participants, including what actions you are taking as a result of their time and feedback. This is an often neglected part of the survey process, but it can be a great way to let customers know that they’ve helped improve your business.
Not only does this encourage participation in future surveys, but it can also stimulate brand loyalty. When customers feel that a company really values and utilizes their feedback, it creates a stronger brand-client relationship. You can build different survey analysis reports for your customer to show you are working on their feedback.
It may not seem like it, but you’re actually asking a lot of your customers when you approach them with a survey. Everyone’s time is important to them and many potential participants will feel that there should be something in it for them.
By incentivizing participants in some way, you’ll receive a greater number of responses and the feedback provided will be more thorough. An incentive could be a discount offer on a future purchase, a free item or something else. Sometimes, the only incentive you need is a promise to share the results with respondents!
Surveys are an important strategy for acquiring audience feedback and identifying areas of promise and concern within your business. The drawback is that survey data can be painstaking to work with. Luckily, data visualization tools, like ChartExpo, provide useful charting options that are easily the best way to present survey results.
If you want to spend less time analyzing survey data for insights and more time actually making improvements based on survey feedback, then ChartExpo will be a welcomed addition to your team. You can try ChartExpo here.
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