You want to provide your customers with top-notch service, test the waters for a new product launch, or get an idea of how you can improve your products.
And you’ve decided to conduct a survey because you know the results will help you move your business forward. But do you know how to interpret the survey results?
Start by using an online survey tool that will provide you with the data you need to make better business decisions and build stronger relationships with your customers.
Understand your data to make better business decisions
Surveys can help you get honest feedback from your customers.
And while interpreting survey results can seem like a hassle, you don’t need to spend months reading surveys and entering them into a database nor do you need to pay someone to do statistical analysis for you.
With a little knowledge and planning, you can analyze the results yourself and use the information you gain to tailor your marketing and customer service to connect to more customers and keep the ones you have.
The basics of survey data
If you’ve never done survey analysis before, the terminology can be a little confusing.
Survey analysis includes a lot of references to statistics, which might sound complicated. But you don’t have to have a math degree or a business degree to analyze survey results. You just need to know some key terms.
Qualitative data helps you understand why people choose you over your competitors or what they value about your product or service.
It refers to information you can’t put into numbers. It’s descriptive and helps you classify or characterize parts of your business. If you think of your survey as answering the “who,” “what,” “where,” “why,” and “how” of your business, qualitative data would answer the “what,” “why,” and “how” parts of your products or services.
You can collect qualitative data in a variety of ways, including focus groups, customer interviews, social media listening, and open-ended questions on surveys, among others.
On the other hand, quantitative data is data that can be easily put into numbers — in short, it’s quantifiable.
This is measurable information like how many units you sold, how much a customer spent in each transaction, your average number of returns, and other important information.
You can ask quantitative questions on a customer survey to help identify your most valuable customers. You can also look through your sales records to supplement survey data.
Quantitative data also helps you see trends and recognize potential trouble before it becomes too big to manage. For example, you might notice an uptick in sales when you release a special offer through social media. Alternatively, a large volume of people may have left your company in a short timeframe. In this case, a customer satisfaction survey can help you see why.
Cross tabulations, or cross-tabs, are a key element of how to interpret survey results. A cross-tab is a table that compares data. You might have a column that includes answers from all survey respondents, another for those aged 18–34, and another for those aged 34 and older.
This sample from Wikimedia Commons shows a cross-tab of soda preferences among survey respondents. It’s been grouped by age and then by gender. This particular cross-tab shows that people under the age of 30 are more likely to drink soda than their parent’s generation. In response to the information, the company could ramp up marketing to the older generation or stick to focusing on its core customers.
Demographics refer to population data broken down by groups. Examples of questions to include in your demographic survey are your customers’ age, gender, race, marital status, income, and employment. If your customers aren’t comfortable providing this information, they can leave it blank. But when they do fill it out, demographic information can help you see trends in certain customer groups.
The mean refers to the average number in all quantitative responses. For example, if you ask your customers to rate your product from 1 to 10, the mean would be the average of scores given by everyone who took the survey. To find the number, add all of the responses and then divide the result by the number of surveys you received.
If you received 150 surveys, you would add up all the customer ratings and then divide the result by 150 to find your mean score. Although this is one of the more technical parts of survey data analysis, it will help you paint a broad picture of how your customers perceive your business.
Survey data analysis starts with the right questions
Another key element of interpreting survey results is asking the right questions in the first place.
Before you write your survey questions, set goals for your survey. Knowing what you want to get out of your survey will help you tailor your questions to gather relevant data.
You may start the client satisfaction survey process with the goal of improving customer satisfaction. But this goal is too broad and won’t help you focus your questions to get relevant data. Your survey questions will look very different when they’re written with specific goals in mind, such as aiming to:
- Improve the number of customers who buy after a free trial
- Determine how our products meet customer needs
- Improve the customer service process to reduce wait times
- Measure the overall customer experience
Setting specific goals will help you ask the right questions. From there, you’re in a better position to meet them.
Once you know why you want to survey your customers, you can start writing survey questions that will give you helpful information. Also, after you’ve found your goals, include some demographic questions so that you can see if responses are similar among people in the same age group, income group, etc.
Determine the types of questions you will ask
A good survey includes a mix of multiple-choice questions, rating questions, and open-ended questions. Ask yes or no questions for topics that need a solid answer. If you want to figure out what people think is the most important part of your customer service process, include a multiple-choice question.
Asking customers to rate topics on a scale from 1 to 7 helps you see how satisfied they are. For example, asking a customer, “Were you satisfied with your experience?” only tells you how many people were completely satisfied. If you ask the same group of people to rate their experience from 1 to 7, you get a better idea of how you are doing with your customers.
Open-ended questions can’t be answered with a yes or no. Your customers have to give you details. Use them to find out why your customers were or weren’t satisfied with their experience. Ask what you can do better or which parts of the service experience can be improved.
Don’t get too complicated
Ask questions that are clear and short. Keep your language simple. Your customers should be able to finish the survey quickly. If they can’t understand your questions, you will probably end up with bad data. Or they won’t answer your survey at all.
Stay away from vague language like “many” or “several.” Ask for specific information whenever possible. But don’t try to point your customers in a certain direction by writing leading questions. Instead of saying, “What did you enjoy most about your experience?” aim to be neutral. “Tell us about your experience” is a simple way of asking the same question without leading your respondent in a certain direction.
When you’re done writing your survey, read it over and see if there are questions you can simplify. If you’re not sure, share it with a coworker or another person to make sure the meaning behind each question is clear.
How to distribute the survey
Now that you have a survey with great questions to help you meet your goals, you need to send it out. One of the easiest ways is to tap your email list. Create a brief email invitation with a link to the survey.
You can also use QR codes posted at cash registers or on windows to encourage in-person customers to take a survey. Include a link to a satisfaction survey at the bottom of paper and electronic receipts. You can encourage participation by offering an incentive like a chance to win a free product or a special discount code.
To engage people on your website, add a link to your satisfaction survey on your homepage. Use tools like SMS messages and chatbots to distribute your survey. Leave the survey open for a set period and then close it and analyze the results.
How to analyze your survey data
Keep your goals in mind when you start to analyze your survey results. Part of knowing how to interpret survey results is your ability to pull out the most important information.
Get rid of bad data
When responding to customer satisfaction surveys, it’s common for people to skip some questions, particularly those asking for demographic data. If someone skipped a few questions, you likely still have enough information to interpret their answers and compare them to others. But if a lot of the questions are blank, it could skew the data.
You may also find some comical answers to open-ended questions. While these are good for a few laughs, they won’t help you meet your customer service goals. If it’s obvious that the respondent wasn’t being serious, take their survey out of the set.
Break your results down by metrics
It’s easiest to start with the quantitative data. You can create cross-tabs of multiple-choice questions and numerical rankings to break survey results into groups and compare them. Start with those that are most important to your goal.
Most online survey tools automatically track data for you. You don’t have to manually input hundreds of surveys into a spreadsheet. But you do have to tell the program which reports to run, particularly when you’re creating cross-tabs or other data visualization tools.
Look at your data
Use different features of your online survey tool to create charts and graphs along with your cross-tabs. These charts can help you picture your data and compare results without looking closely at the numbers.
This sample from Venngage shows how charts and graphs can make data easier for you and your team to understand.
Find trends in the open-ended questions
While open-ended questions provide valuable insight, they can also be tricky to interpret. Some people may be more long-winded than others, and you have to sift through all the answers to find similar answers.
Some online survey platforms have tools that let you generate word clouds or find common words in your open-ended responses. The task of reading all open-ended responses may seem tedious, but this is a great way to catch a glimpse into our customers’ minds.
Your customers might offer insights you never considered. Maybe they see a benefit to your product that you’ve overlooked. You can use this information to tweak your marketing campaigns and emphasize different features of your product or service.
How to understand and share the story
Using cross-tabs and other tools to compare answers is one of the best ways to notice trends and highlights in your survey data. These tools help you see which topics resonate with multiple people. When you group the data by demographics or other characteristics, you can start seeing similarities within different groups.
If you’re doing a customer satisfaction survey to measure changes you made as a result of a previous survey, these tools help you measure your progress. For example, if your goal is to improve the number of people who sign up after a free trial, you can use charts to compare your current numbers with previous data.
Use the quantitative data to give you the facts
Your quantitative data will give you hard answers like how many people have signed up for your service after a free trial or your average customer satisfaction rating on a scale of 1 to 7. This numerical data will give you a high-level overview. Display the facts in charts and graphics to easily communicate with your team.
Round out the information with qualitative data
Include graphics built around qualitative data, so your team has the full picture. You can use a word cloud or the analytical charts you generated to find trends in your data. Or you can pull insightful answers to open-ended questions and include them in your report as quotes.
Remember that you’re not distilling the data for yourself. You’re probably going to share it with people so that they can use it to make decisions. Use a combination of qualitative and quantitative results to present data and to help the reader understand the why behind the numbers.
Make it relevant
Since you’ve been working on the survey since the beginning, you probably think all the data is interesting. But not everyone on your team will be interested. Use your survey goals to prioritize how you present your data. Put information that addresses your goals in the front of the report, and use charts, graphs, and infographics to make it interesting.
Remember to use your data
Once you’ve finished your customer satisfaction survey, use it to drive your decisions. You could create a report that ends up on a shelf, or you can use what you’ve learned to inform your team and help improve.
Whatever your goal, your survey likely featured valuable information your team can use. For example, if your goal was to improve your customer service process, the survey may show that customers are frustrated with long wait times.
This data could show you that you need to experiment with different customer service tools. You might use AI or chatbots to handle easy customer inquiries, freeing up your representatives to deal with more complex issues.
Survey your own customers
If you haven’t done a customer satisfaction survey, you could be missing out on valuable data. These surveys give you a chance to check in with your customers and identify potential problems before they spin out of control.
Start by outlining your most pressing goals, and use them to write a variety of questions. Include a mix of multiple-choice, ranking, and open-ended questions to get the best data. Use a variety of methods to distribute your survey, including your email list, QR codes, and links on your website.
Next, know how to interpret survey results. Use cross-tabs and graphs to compare answers from survey respondents. Take your numbers from the quantitative data and use the qualitative data to fill in the missing information. Finally, use your goals to determine how to present the information to others in your company, and use the report to make decisions.
Want to know what your customers, prospects, or donors really think? Start by creating an online survey.