Start with the end in mind – what are your top research questions? This table also shows you that 18% say they are planning to return and 11% say they are not sure. Congratulations are in order! We receive feedback from many places: our in-product NPS, Many organisations, large or small, gather customer feedback to improve their CX efforts and ultimately their bottom line. Open-ended questions also tend to be more objective and less leading than closed-ended questions. This booklet … Firstly, you need to plan for survey design success. Hopefully, some of our other questions will help you figure out why this is the case and what you can do to improve the conference for administrators so more of them will return year after year. Let’s say on your conference feedback survey, one key question is, “Overall how satisfied were you with the conference?” Your results show that 75% of the attendees were satisfied with the conference. You can count different types of feedback (responses) in the survey, calculate percentages of the different responses survey and generate a survey report with the calculated results. Thus, 60% or your respondents (1098 of those surveyed) are planning to return. Here, you can see that most of the enterprises and the self-employed must have liked the conference as they’re wanting to come back, but you might have missed the mark with the small businesses. In analyzing our survey data we might be interested in knowing what factors most impact attendees’ satisfaction with the conference. On a large scale, software is ideal for analyzing survey results as you can Survey data collection uses surveys to gather information from specific respondents. It’s quite simple to install the Data Analysis … In survey analysis and statistics, significant means “an assessment of accuracy.” This is where the inevitable “plus or minus” comes into survey work. If that is the case, the big bucks spent on the speaker might be best spent elsewhere. Now it’s time to actually do something useful with them. Customer feedback doesn't have all the answers. So, 71% of your survey respondents (852 of the 1,200 surveyed) plan on coming back next year. Research: if you did the planning of your survey well, it means that you already know what its objective is.Once you have the purpose of your survey in mind, what you have to … Have customers noticed our efforts in solving issue Z? How to analyze survey data in Google Sheets. The social events? Say for example that satisfaction rates are increasing year over year for students and teachers, but not for administrators. Analyzing this sort of data is called qualitative data analysis or QDA for short. If you can nail the “what’s in it for me”, you automatically solve many of the possible issues for the survey, such as whether the respondents have enough incentive or not, or if the survey is consistent enough. https://www.proprofs.com/c/customer-support/how-to-analyze-survey-data To connect your survey data, you have one of three options: Upload new responses in an Excel or CSV file to conduct batch analysis Use Monkeylearn’s integrations with Google Sheets, Zapier, Zendesk, and … You’ll do yourself a disservice. Now is when that planning pays off. Categorical data is the easiest type of data to analyze because you're limited to calculating the share of responses in each category. This can, for example, be Net Promoter Score surveys that you send a few times a year to your customers. If your survey sample is a random selection from a known population, statistical significance can be calculated in a straightforward manner. Here’s how you can do it in just a few simple steps. Your results will give you raw numbers of actual respondents and, when div… You dig deeper to find out what’s going on. In the below example, any comment about friends and family both fall into the second category. Closed-ended questions are the equivalent of being offered milk or orange juice to drink instead of being asked: “What would you like to drink?”. What caused this increase in satisfaction? As a respondent you want to know your responses count, are reviewed and are making a difference. You’d be able to make a trend comparison. He needs no introduction in industry-wide circles, but in case you’re not familiar with his name: Shep is an award-winning customer service and customer experience speaker, a New York Times and Wall Street Journal best-selling author, A.K.A. The average reported here is the mean, the kind of average that’s probably most familiar to you. You might think there are lots of questions that seem useful, but they can actually negatively affect your survey results. You most often will not be able to, and shouldn’t for practicality reasons, collect data from all of the people you want to speak to. Customer surveys can have a huge impact on your organization. Take a look at your top research questions. What insight am I hoping to get from this question? To have multiple survey writer can be helpful, as having people read each other’s work and test the questions helps address the fact that most questions can be interpreted in more than one way. Below, we’re inserting the positive and the negative layer under customer service theme. In the first snippet, there’s a code frame. Code frames can also be combined with a sentiment. The best part of analyzing survey results is that you will find surprising insights … We will illustrate the use of Survey Monkey, but we do not mean to suggest that it should be preferred over any other online survey service. How to get meaningful, actionable insights from customer feedback, 4 Steps to Customer Survey Design – Everything You Need to Know, The Buyer’s Guide for feedback analysis software, Best practices for analyzing open-ended questions, How to use AI to improve the customer experience, How to measure feedback analysis accuracy, Product Feedback Collector (Chrome extension), How we use our own platform and Chrome extension to centralize & analyze feedback, Text Analytics Software – How to unlock the drivers behind your performance, 10 insider customer experience tips according to Shep Hyken. Is it a matter of the number of sessions? The percentages in this example show how many respondents answered a particular way, or rather, how many people gave each answer as a proportion of the number of people who answered the question. In this case the answer is six. Our visualizations tools show far more detail than word clouds, which are more typically used. This is called longitudinal data analysis. There’s a transcription tool for quick transcription of voice data. Most survey questions fit into one of these four categories: Categorical data… The software includes polling, tablet and smartphone research, and data visualization for analysis. And your results look like this: You might want to analyze the average. Another reason is that often we ask redundant questions that don’t contribute to the main problem we want to solve. There are many online services one could use for collecting survey data. An open-ended question feels more inviting and warmer – it makes people feel like you want to hear what they want to say and actually start a conversation. (More on survey planning below). But if, for example, your Detractors in an NPS survey mention something a lot, that particular theme will be affecting the score in a negative way. Steps to Analyze Survey Data. What are the most common responses to questions X? In this case, they don’t allow the respondent to provide original or spontaneous answers but only choose from a list of pre-selected options. Part 3: Generate a survey … For example, drinking hot chocolate and wearing mittens are two variables that are correlated — they tend to go up and down together. If you take the time to carefully analyze the soundness of your survey data, you’ll be on your way to using the answers to help you make informed decisions. Filtering means narrowing your focus to one particular subgroup, and filtering out the others. Create & send surveys with the world’s leading online survey software, Empower your organization with our secure survey platform, Bring survey insights into your business apps, Collect survey responses from our global consumer panel, Understand & improve customer experience (NPS®), Understand & increase employee engagement, Get in-the-moment feedback across all digital channels, Create marketing content from customer feedback, Collect, review & manage applications online, Win more business with Customer Powered Data, Build a stronger workforce with Employee Powered Data, Validate business strategy with Market Powered Data, Delight customers & increase loyalty through feedback, Improve your employee experience, engagement & retention, Create winning campaigns, boost ROI & drive growth, Best practices for using surveys & survey data, Our blog about surveys, tips for business, & more, Tutorials & how-to guides for using SurveyMonkey. As you may recall, there are three different kinds of averages: mean, median and mode. I am currently doing my dissertation and am collecting data from a survey i put out. Confused about what to do next and how to achieve the optimal survey analysis? Drawing an inference based on results that are inaccurate (i.e., not statistically significant) is risky. A larger sample size does often equate to needing a bigger budget though. Filter results by cross-tabulating subgroups. Thus, you need to make sure your survey analysis produces meaningful results that help make decisions that ultimately improve your business. Good surveys start with smart survey design. Closed-ended questions can be answered by a simple one-word answer, such as “yes” or “no”. Technically, the data created by this type of question is Categorical (see below) data. An idea is to check the list of existing clients of the product, which is often listed on their website. That is part of the story right there — great conference overall, lousy choice of locations. The mode is the most frequent response. To make sure your results are statistically significant, it may be helpful to use a sample size calculator. It’s important to pay attention to the quality of your data and to understand the components of statistical significance. Did you feature empirical research questions? If so, next year you’ll want to get a great keynote speaker again. However, one does not cause the other. Now it’s time to look at the information gathered through the survey questions. They often consist of pre-populated answers for the respondent to choose from; while an open-ended question asks the respondent to provide feedback in their own words. For a technical overview, see this article. When it comes to reporting on survey results, think about the story the data tells. To always make sure you have a sufficient sample size, consider how many people you need to survey in order to get an accurate result. Thematic is a B2B SaaS company. How does it compare to other conferences? You may think of this as the most economical solution, but in the long run, it often ends up costing you more (due to time it takes to set up and analyze, human resource, and any errors or bias which result in inaccurate data analysis, leading to faulty interpretation of the data. Notice that in the responses, you’ve got some percentages (71%, 18%) and some raw numbers (852, 216). Qualitative data is information that is in language form. collected your statistical survey results, Take a look at your top research questions. Just be sure to let your audience know when you are showing them findings from statistically significant research and when it comes from a different source. As an incentive, you can share the results with the participants, in the form of a benchmark, or a measurement that you then report to the participants. Which group of respondents are most affected by issue Z? Which responses are affecting/impacting us the most? How to Present Survey Results 1. This is called benchmarking. Or, look at a particular issue or a theme, and ask questions such as “have customers noticed our efforts in solving a particular issue?”, if you’re conducting a continuous survey over multiple months or years. Here you simply set up a table that places each survey question in its own table field, then count up the number of respondents that chose each particular answer. Using a filter is another useful tool for modeling data. Open-ended questions often begin with words such as “Why” and “How”, or sentences such as “Tell me about…”. But gathering feedback alone can’t make much of a difference. So, you multiply all of these pairs together, sum them up, and divide by the total number of people. Regression analysis is an advanced method of data visualization and analysis that allows you to look at the relationship between two or more variables. Did you consider probability sampling? But wouldn’t you like to have some context? When presenting your insights, to your stakeholders or board, it’s always helpful to use different data points and which might include even personal experiences. Suppose the satisfaction rate for your conference was 50% three years ago, 55% two years ago, 65% last year, and 75% this year. Fifty (50) is a small sample size and results in a broad margin of error. For example, if you held an education conference and gave attendees a post-event feedback survey, one of your top research questions may look like this: How did the attendees rate the conference overall? For instance, you could limit your focus to just women, or just men, then re-run the crosstab by type of attendee to compare female administrators, female teachers, and female students. Survey data analysis—aggregating the numbers The first step when analyzing survey data is to turn your individualized responses into aggregated numbers. Clearly, you do not have the sophisticated features of an online software tool, but for simple tasks, it does the trick. For more pointers on how to design your survey for success, check out our blog on 4 Steps to Customer Survey Design – Everything You Need to Know. Collecting and analyzing this feedback requires a different approach. Based on these two facts you might think that having a fabulous (and expensive) keynote speaker is the key to conference success. Then, there is no other option but to use software”. Now take a look at the answers you collected for a specific survey question that speaks to that top research question: Do you plan to attend this conference next year? Calculate impact of NPS on cost of customer acquisition. You know how many people said they were coming back, but how do you know if your survey has yielded answers that you can trust and answers that you can use with confidence to inform future decisions? But it has critical insights for strategy and prioritization. There are numerous tools on the market, and they all have different features and benefits. Build a survey analytics team for deeper insights. Crucially, you’ll want to test the tool, or at the least, get a demo from the sales team, ideally using your own data so that you can use the time to gather new insights. When presenting to your stakeholders, it’s imperative to highlight the insights derived from your data, rather than the data itself. One-way tables are typically the quickest and easiest way to analyze quantitative data in a short amount of time. The last kind of average is mode. So, next, you apply this code frame. Analyze a survey data in Excel. Analyzing … — When you ask employees to complete a survey, they expect that their responses will be put to good use. Survey data collection can replace or supplement other data collection types, including interviews, focus groups, and more. Collected all of your survey data? There a many types of regression analysis and the one(s) a survey scientist chooses will depend on the variables he or she is examining. Your surveys will reveal what areas in your business need extra support or what creates bottlenecks in your service. In the second snippet, you can see the actual coded data, where each comment has up to 5 codes from the above code frame. There are two main approaches to choose from here: Grounded theory / emergent coding / inductive (data driven) This is… For tips on how to analyze results, see below. If the answer to all those questions is yes, only then new opportunities and innovative strategies can be created. First, let’s talk about how you’d go about calculating survey results from your top research questions. In the same vein, we are analyzing the data … What all types of regression analysis have in common is that they look at the influence of one or more independent variables on a dependent variable. So instead of comparing subgroups to one another, here we’re just looking at how one subgroup answered the question. It’s designed to produce a meaningful answer and create rich, qualitative data using the subject’s own knowledge and feelings. To avoid enforcing your own assumptions, use open-ended questions first. In particular, it means that survey results are accurate within a certain confidence level and not due to random chance. First, all qualitative survey data … Then you apply the cross tab to look at different attendees to look at female enterprise attendees, female self-employed attendees etc. Plus, software has the added benefit of additional tools that add value. Whether that impact is positive or negative depends on how good your survey is (no pressure). Here are a few tips: Only include questions that you are actually going to use. But say the regression shows that, while everyone liked the speaker, this did not contribute much to attendees’ satisfaction with the conference. For example, say you wanted to see how teachers, students, and administrators compared to one another in answering the question about next year’s conference. So just look at how one subgroup (women, men) answered the question without comparing. Choosing a tool that is right for you will depend on your needs, the amount of data and the time you have for your project and, of course, budget. She speaks four languages fluently and has lived in six different countries. Favoured by government agencies and communities, it’s good for employee engagement, public opinion and community engagement surveys. that you can use the answers with confidence as a basis for your decision making? The median is the middle value, the 50% mark. Cold weather is the independent variable and hot chocolate consumption and the likelihood of wearing mittens are the dependent variables. In the table above, we would locate the number of sessions where 500 people were to the left of the number and 500 to the right. The first two lines of code we write will allow us to get our data … Use this post as a guide to lead the way to execute best practice survey analysis in 2019. So you’d take a sample (or subset) of the people of interest and learn what we can from that sample. Suppose 50 of the 1,000 people who attended your conference replied to the survey. The first factor to consider in any assessment of statistical significance is the representativeness of your sample—that is, to what extent the group of people who were included in your survey “look like” the total population of people about whom you want to draw conclusions. This is the time to go back to those and check how they (for example the subgroups; enterprises, small businesses, self-employed) answered, with regards to attending again next year. To figure this out, you want to delve into response rates by means of cross tabulation, where you show the results of the conference question by subgroup: From this table you see that a large majority of the students (86%) and teachers (80%) plan to come back next year. So, the question is: When you’re dealing with large amounts of data, it is impossible to manage it all properly manually. If you have personal experience with the topic, use it! Either because there’s simply too much of it or if you’re looking to avoid any bias, or if it’s a long-term study, for example. Many businesses don’t actually think about this when they send out their surveys. If something is very common, it may not affect the score. The site? Here’s how our Survey Research Scientists make sense of quantitative data (versus making sense of qualitative data), from looking at the answers and focusing on their top research questions and survey goals, to crunching the numbers and drawing conclusions. Analysis gets a bit more complicated if you’re creating surveys with open-ended questions. The data collected from surveys can be used to boost employee engagement, understand buyer behavior, and improve customer experiences. The best approach is to use a mix of both types of questions, as It’s more compelling to answer different types of questions for respondents. Of course, these are just a few examples to illustrate the types of functions you could employ. Miami or San Diego might be a better choice for a winter conference. Nvivo lets you store and sort data within the platform, automatically sort sentiment, themes and attribute, and exchange data with SPSS for further statistical analysis. Often, we start with a few checkboxes or lists, which can be intimidating for survey respondents. You can see two different slices of data. Longitudinal data analysis (often called “trend analysis”) is basically tracking how findings for specific questions change over time. You can benchmark not just attendees’ satisfaction, but other questions as well. An error occurred, please try again later. Fact is, most Google Sheets formulas are either identical … If last year’s satisfaction rate was 60%, you increased satisfaction by 15 percentage points! In the table above, the average number of sessions attended is 6.1. Something to compare it against? It’s important to think about the timing of your survey. Bias is also avoided as it is a software tool, and it doesn’t over-emphasize or ignore specific comments to come to unquantified conclusions. Then, you can have a large enough sample size to draw meaningful conclusions, without wasting time and money on sampling more than you really need. Your longitudinal data analysis shows a solid, upward trend in satisfaction. We aren't swimming in feedback. This is the majority of people, even though almost a third are not planning to come back. Don’t stop at the survey data alone. Would you bet your customer insights on something that’s at best 50 accurate? Categorical data is popular because it is the easiest type to analyze. At the start of your survey, you will have set up goals for what you wanted to achieve and exactly which subgroups you wanted to analyze and compare against each other. Below we give just a few examples of types of software you could use to analyze survey data. Part 2: Calculate the percentages of all feedbacks. On a large scale, software is ideal for analyzing survey results as you can automate the process by analyzing large amounts of data simultaneously. Now it’s time to dig in, start sorting, and analyze the data. 260 survey participants attended six sessions, more than attended any other number of sessions. In everyday conversation, the word “significant” means important or meaningful. The median is, in this case, six sessions. You have a problem if 90% of conference attendees who completed the survey were men, but only 15% of all your conference attendees were male. Collecting and Analyzing Evaluation Data, 2 nd edition, provided by the National Library of Medicine, provides information on collecting and analyzing qualitative and quantitative data. Now, I talk about the steps about analyzing survey data and generate a result report in Microsoft Excel. Clearly, if you are working with a larger sample size, your results will be more reliable as they will often be more precise. If you have qualitative research that supports the data, use it! Does your survey analysis deliver clear, actionable insights? In other words, it is the survey data that is obtained in response to open-ended questions. First, let’s talk about how you’d go about … However, the administrators who attended your conference look different, with under half (46%) of them intending to come back! … This sounds complicated but really it just means … For best practice on how to draw conclusions you can find in our post How to get meaningful, actionable insights from customer feedback. 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