Open-ended questions often begin with words such as “Why” and “How”, or sentences such as “Tell me about…”. Qualitative data is information that is in language form. In the first snippet, there’s a code frame. 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? How should I analyze qualitative survey data? Interpreting the Survey Results Do a quick overview of the results to familiarize yourself with the … Simply collect, count, and divide. Every piece of feedback counts. In the below example, any comment about friends and family both fall into the second category. Code frames can also be combined with a sentiment. Make sure you incorporate these tips in your analysis, to ensure your survey results are successful. 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. Causation is when one factor causes another, while correlation is when two variables move together, but one does not influence or cause the other. Did you feature empirical research questions? 260 survey participants attended six sessions, more than attended any other number of sessions. When presenting to your stakeholders, it’s imperative to highlight the insights derived from your data, rather than the data itself. The blue bars are United Airlines 1 and 2-star reviews, and the orange bars are the 4 and 5-star reviews. The percentages are just that–the percent of people who gave a particular answer. In the case of our conference feedback survey, cold weather likely influenced attendees dissatisfaction with the conference city and the conference overall. First, let’s talk about how you’d go about … But say the regression shows that, while everyone liked the speaker, this did not contribute much to attendees’ satisfaction with the conference. Have customers noticed our efforts in solving issue Z? We need to analyze our feedback to discover insights that inspire us to drive action at our organisations. Thus, you need to make sure your survey analysis produces meaningful results that help make decisions that ultimately improve your business. It’s a fantastic airline, but you can identify the biggest issue as mentioned most frequently by 1-2 stars reviews, which is their flight delays. Calculate impact of NPS on cost of customer acquisition. You’ll do yourself a disservice. You’ll be able to track, year after year, what attendees think of the conference. In the same vein, we are analyzing the data … Part 1: Count all kinds of feedbacks in the survey. It also shows that your respondents “look like” the total population of people about whom you want to draw conclusions. Then, there is no other option but to use software”. It’s crucial to challenge your assumptions, as it’s very tempting to make assumptions about why things are the way they are. Survey analysis refers to the process of analyzing your results from customer (and other) surveys. The median is the middle value, the 50% mark. It’s quite simple to install the Data Analysis … So, if you can overlap qualitative research findings with your quantitative data, do so. For tips on how to analyze results, see below. Remember that you should have outlined your top research questions when you set a goal for your survey. The median is, in this case, six sessions. It’s a no-frills online tool, great for academics and researchers. Of course, these are just a few examples to illustrate the types of functions you could employ. In analyzing our survey data we might be interested in knowing what factors most impact attendees’ satisfaction with the conference. You can see two different slices of data. Favoured by government agencies and communities, it’s good for employee engagement, public opinion and community engagement surveys. 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. 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. It’s usually a cumbersome process involving some combination of clunky analysis … Take a look at your top research questions. However, the administrators who attended your conference look different, with under half (46%) of them intending to come back! Cold weather is the independent variable and hot chocolate consumption and the likelihood of wearing mittens are the dependent variables. How to analyze survey data in Google Sheets. Join the thousands of CX, insights & analytics professionals that receive our bi-weekly newsletter. As you may recall, there are three different kinds of averages: mean, median and mode. Regression analysis is an advanced method of data visualization and analysis that allows you to look at the relationship between two or more variables. So, you multiply all of these pairs together, sum them up, and divide by the total number of people. Survey data collection can replace or supplement other data collection types, including interviews, focus groups, and more. 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. Surveys can be a great source of information about your customers or your employees. 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. Professional pollsters make poor comedians, but one favorite line is “trend is your friend.”. You might want to look at administrators’ responses to various questions to see if you can gain insight into why they are less satisfied than other attendees. Getting Our Survey Data Into Python. Survey data analysis is the process of drawing conclusions from what you’ve gathered. 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?”. Fifty (50) is a small sample size and results in a broad margin of error. Consider how much margin of error you’re comfortable working with first, as your sample size is always an estimate of how the overall population think and behave. If you’re a DIY analyzer, there’s quite a bit you can do in Excel. Great. Below is an example we’ve taken from the tool, to visualize some of Thematic’s features. However, we can in general, treat it as Ordinal data. Then you apply the cross tab to look at different attendees to look at female enterprise attendees, female self-employed attendees etc. Another reason is that often we ask redundant questions that don’t contribute to the main problem we want to solve. This can, for example, be Net Promoter Score surveys that you send a few times a year to your customers. 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. It’s important to think about the timing of your survey. Suppose the satisfaction rate for your conference was 50% three years ago, 55% two years ago, 65% last year, and 75% this year. 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. 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. Or rather, that your results are not based on pure chance, but that they are in fact, representative of a sample. 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. So just look at how one subgroup (women, men) answered the question without comparing. Go back to your main research questions which you outlined before you started your survey. How to Present Survey Results 1. Developed by QRS International, Nvivo is a tool where you can store, organize, categorize and analyze your data and also create visualisations. 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. On a large scale, software is ideal for analyzing survey results as you can automate the process by analyzing large amounts of data simultaneously. Does your survey analysis deliver clear, actionable insights? Say you asked your survey respondents how many of the 10 available sessions they attended over the course of the conference. 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. 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. (More on survey planning below). 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. 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. If you don’t have data from prior years’ conference, make this the year you start collecting feedback after every conference. Cross-sectional surveys are an observational research method that analyzes data of variables collected at one given point of time across a sample population or a pre-defined subset. Suppose 50 of the 1,000 people who attended your conference replied to the survey. 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. Did you consider probability sampling? This is the majority of people, even though almost a third are not planning to come back. Add analysts to any team plan for even bigger impact. Miami or San Diego might be a better choice for a winter conference. Now, I talk about the steps about analyzing survey data and generate a result report in Microsoft Excel. At least when it comes to gender, you’re feeling pretty good if men make up 15% of survey respondents in this example. Don’t be. Now it’s time to actually do something useful with them. One aspect of data analysis and reporting you have to consider is causation vs. correlation. Technically, the data created by this type of question is Categorical (see below) data. So you’d take a sample (or subset) of the people of interest and learn what we can from that sample. Your surveys will reveal what areas in your business need extra support or what creates bottlenecks in your service. You might think there are lots of questions that seem useful, but they can actually negatively affect your survey results. These two questions are important to take hand in hand. Closed-ended questions can be answered by a simple one-word answer, such as “yes” or “no”. It’s designed to produce a meaningful answer and create rich, qualitative data using the subject’s own knowledge and feelings. Means–and other types of averages–can also be used if your results were based on Likert scales. Always think about what customers (or survey respondents) want and what’s in it for them. Longitudinal data analysis (often called “trend analysis”) is basically tracking how findings for specific questions change over time. 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. Look at your survey questions and really interrogate them. Lattice makes it easy to view engagement and performance data using heat maps, nine-box scatterplots, and other visuals. 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. But gathering feedback alone can’t make much of a difference. Data on its own means nothing without proper analysis. 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. This can help you eliminate the influence of outliers, which may adversely affect your data. Various issues can easily crop up with this approach, see the image below: Out of 7 comments, here only 3 were categorized correctly. Categorical data is the easiest type of data to analyze because you're limited to calculating the share of responses in each category. This booklet … The results are back from your online surveys. Traditional survey analysis is highly manual, error-prone, and subject to human bias. What’s different about this month/this year? You’d be able to make a trend comparison. Now it’s time to look at the information gathered through the survey questions. Maybe there’s something you can do to convince the 11% who are not sure yet! You can find more features, such as Thematic’s Impact tool, Comparison, Dashboard and Themes Editor here. 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. You can imagine that it’s actually quite difficult to analyze data presented in this way in Excel, but it’s much easier to do it using software. This is called benchmarking. 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. In this example, you have 100 people saying they attended one session, 50 people for four sessions, 100 people for five sessions, etc. If something is very common, it may not affect the score. Participants gave this speaker and the conference overall high marks. This table also shows you that 18% say they are planning to return and 11% say they are not sure. Using a filter is another useful tool for modeling data. 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. Analyze four types of survey questions. So instead of comparing subgroups to one another, here we’re just looking at how one subgroup answered the question. Part 3: Generate a survey … Categorical data is popular because it is the easiest type to analyze. 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. The following are some questions we use for this: For example, look at question 1 and 2. Graphs and charts are a visually-appealing way to share data. Once a benchmark is established, you can determine whether and how numbers shift. But wouldn’t you like to have some context? By looking at other questions and interrogating the data further, you can hopefully figure out why and address this, so you have more of the small businesses coming back next year. The data collected from surveys can be used to boost employee engagement, understand buyer behavior, and improve customer experiences. In this case the answer is six. — When you ask employees to complete a survey, they expect that their responses will be put to good use. Good surveys start with smart survey design. Well, say you did ask this question in your conference feedback survey after last year’s conference. … In this regard, the “significant” in statistical significance refers to how accurate your data is. This is called longitudinal data analysis. There are multiple ways of doing this, both manual and through software, which we’ll get to later. On a large scale, software is ideal for analyzing survey results as you can So, the question is: When you’re dealing with large amounts of data, it is impossible to manage it all properly manually. Is it a matter of the number of sessions? It has numerous features, for example automatically detecting and categorizing themes. As a respondent you want to know your responses count, are reviewed and are making a difference. 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. Don’t wait for your team to create insights out of the data, you’ll get a better response and better feedback if you are the one that demonstrates the insights to begin with, as it goes beyond just sharing percentages and data breakouts. Interpris is another tool from QRS International, where you can import and store free text data directly from platforms such as Survey Monkey and store all your data in one place. Other tools worth mentioning (for survey analysis but not open-ended questions) are SurveyMonkey, Tableau and DataCracker. 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. You can benchmark not just attendees’ satisfaction, but other questions as well. You’ve collected your survey results and have a survey data analysis plan in place. Use this post as a guide to lead the way to execute best practice survey analysis in 2019. Drawing an inference based on results that are inaccurate (i.e., not statistically significant) is risky. Clearly, if you are working with a larger sample size, your results will be more reliable as they will often be more precise. For this, you can cross-tabulate, and show the answers per question for each subgroup. Below, we’re inserting the positive and the negative layer under customer service theme. Use your surveys as a way of presenting solutions to your audience and getting direct feedback on those solutions in a more consultative way. If the answer to all those questions is yes, only then new opportunities and innovative strategies can be created. Which responses are affecting/impacting us the most? You might find that the popularity of the keynote speaker was a major driver of satisfaction with the conference. Our visualizations tools show far more detail than word clouds, which are more typically used. In fact, they are both caused by a third factor, cold weather. Cold weather influences both hot chocolate consumption and the likelihood of wearing mittens. We update you on our new content authored by business professionals. Categorical data is sometimes referred to as "nominal" data, and it's a popular route for survey questions. 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? But the 4 and 5-star reviews have frequent praise for the friendliness of the airline. Collected all of your survey data? There’s a transcription tool for quick transcription of voice data. A top research question for a business conference could be: “How did the attendees rate the conference overall?”. Say your conference overall got mediocre ratings. 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. When it comes to reporting on survey results, think about the story the data tells. There are many online services one could use for collecting survey data. 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