3 Ways to Present Surveys to Your Audience One of the first things to decide when setting up a survey is the general design and presentation style for your questions and answers. In this context, you have to choose the format for displaying your survey. Essentially, this means you can either show your entire survey on one page, which is called scrolling survey design in the research world.  You can show your survey on multiple pages, i.e., one question per page, which is called paging survey design.   You can alternatively use a hybrid format offered exclusively by LimeSurvey that allows you to show one question group per page consisting of several questions, which we will call categorizing survey design. What seems like an easy decision at first will require some further consideration when looking closer at this design topic.  In light of the availability of different technical devices to take surveys on nowadays, such as desktop computers, tablets, or smartphones, formats may appear more advantageous on one device, yet more disadvantageous on another device. This adds extra complexity to the survey design. Researchers have been testing and evaluating this design question for years now by examining key metrics such as bounce rates, completion times, and rates, as well as item nonresponses. Insights indicate that surveys taken on desktop computers do not differ significantly for scrolling and paging designs with regard to completion and bounce rates. Merely, a tendency to skip certain questions was discovered for scrolling survey designs which could have had any number of reasons such as a mental overload, boredom, or other problems connected to survey fatigue.   Tips For Different Survey Design Formats One thing has to be stated clearly: there is no general best strategy that will apply to any type of survey. Ultimately, it comes down to the survey characteristics with regard to survey length in terms of time and number of questions, as well as technical equipment and connectivity. Nevertheless, scenarios can be created within which a certain design format may be more suitable than others due to the underlying survey conditions. This leads to the following tips for the usage of different survey design formats: In general, if your survey is short in terms of the time it requires to be completed, as well as a low number of questions, the recommendation will always be to use a scrolling design to keep the survey short, regardless of the device used. A paging or categorizing design will spread questions over several pages and require respondents to click on the next button as well as to adjust to the subsequent page(s), which prolongs a survey. This will almost always exhaust or lower respondents’ interest potentially resulting in lower completion or higher bounce rates. A paging design usually only makes sense if you have a long survey that is to be taken on either a desktop computer or a laptop, as these devices possess larger screens, as well as allow for faster cursor movements and clicks. This way, surveys can be completed in a more convenient manner when shifting from page to page. Obviously, the aforementioned paging design can also be replaced by a categorizing design which is the more elegant way as it groups question subtopics to facilitate respondents recognizing logical connections between questions. Because tablet and smartphone devices have smaller touchscreens, a categorizing design should be used with long surveys, as it would minimize the negative effects of both pure paging and scrolling designs. In the categorizing design, fewer clicks and new page loads are required than with the paging design, as well as less scrolling and information overload are present than with the scrolling design. The advantage of paging and categorizing design is perfectly clear: every time a respondent completes one or a few questions on a page and clicks the next button, this data is submitted and saved, even if the respondent drops out on the subsequent page. If a respondent completes the same amount of questions in a scrolling design and drops out without submitting, all that data is lost. In this scenario, paging and categorizing designs are more valuable as partial data may still deliver important insights.       Conclusion   All in all, we do, however, recommend that you try to avoid creating long surveys with many questions, as these will oftentimes lower completion rates and increase bounce rates due to survey fatigue. Try and split longer surveys by subtopics into multiple shorter surveys. This way, you will make sure to increase survey relevance to your target audience and earn more valuable data to analyze.In the end, it all comes down to how well you know your target audience. The more you find out about devices used and survey perseverance, the better you can suit your survey design to achieve the best results.  

Take a look at the following assortment of the most popular and widely used chart types to get a good idea for evaluating and reporting on your own survey data.   When to Use a Pie Chart single choice questions mask questions (e.g. Gender, Yes/No) Pie charts are best used when you are presenting a share of something, ideally, items explaining a single variable to benefit readability and assessment. Logically, all shares in a pie chart should thereby add up to 100%. For example, when you have binary survey responses, e.g., yes/no question types, or questions with only a few answer options/categories. Overloading a pie chart with too many categories, i.e., 6 or more, makes it hard to identify labels as well as shares and should be avoided. When it comes to data types, nominal data such as demographics, i.e., data without an order or ranking, as well as ordinal data such as Likert scale ratings, i.e., data with an order or ranking, can be visualised using pie charts. Nominal data can be arranged clockwise from largest to smallest share and ordinal data can be arranged clockwise according to ranking or rating scale. In order to increase the distinction between shares in a pie chart, strong colour contrasts or colour shades can help to achieve this. Pie charts are a nice and visually appealing solution if you are trying to show general trends rather than specific accurate data. General Tip: Avoid including "Other" as an option choice, as an answer as different responses will not be displayed in a pie chart, but will be shown as "Other".   When to Use a Donut Chart single choice questions mast questions (e.g. Gender, Yes/No)  Donut charts work similarly to pie charts. Donut charts have a circular cutout in the middle whereas the shares within pie charts completely fill out the middle.  Despite these seemingly small differences, the way these chart types are viewed and interpreted from a psychological standpoint vary substantially. Shares of a pie chart all run to the middle and focus a viewer's attention to the centre where all pieces are processed as by the size of their areas. Shares of a donut chart however focus the viewer's attention to the length of each piece, thereby demonstrating a more linear approach of processing results. The latter way of interpreting data is naturally easier for people. Apart from that, donut charts can be used in the same way as pie charts, i.e., assessing shares of a whole.   When to Use a Bar Chart single choice questions multiple choice questions arrays mask questions (e.g. Gender, Yes/No) There are several different ways to visualise data with bar charts. Most commonly used are the vertical and the horizontal bar charts. Both vertical and horizontal bar charts are composed of columns which are either aligned vertically or horizontally to the x-axis respectively. Furthermore, they are suitable to visualise nominal and ordinal data.  The vertical bar chart is helpful when displaying percentages or means of only a few categories. Otherwise, too many categories would increase the width of the entire chart across a screen and make it hard to read or even display. The rule of thumb here is to reduce the categories included in a vertical bar chart to only about a handful. Compared to pie charts, bar charts facilitate direct comparison between categories, especially when ordinal data is arranged from largest to smallest column or vice versa. Furthermore, bar charts can easily display negative values which is impossible with pie charts and makes the former superior and more flexible in most cases. The horizontal bar chart comes in handy where the vertical bar chart falls short. If you have more than a handful of categories, select the horizontal bar chart as it extends vertically and improves readability.Stacked and grouped bar charts are great solutions when displaying subcategories, i.e., break down categories for a more detailed view of your data. The only difference between stacked and grouped bar charts is the way subcategories are displayed, namely subcategories in the same bar versus in different bars. General Tip: Make sure to display your bar labels horizontally, otherwise viewers have to tilt their heads to read them. Also, don't include the answer option "Other" for the same reason disclosed for pie charts.   When to Use a Line Chart Single choice questions Multiple choice questions Arrays Mask questions (e.g. Gender, Yes/No) Line charts consist of data values that correspond to individual answer options and are best used to display trends, comparisons or peaks over time, therefore are great when running surveys repeatedly. General Tip: Reduce the number of labels on the x-axis to a maximum such as 5 to ensure readability; however, make sure to have enough data points to enable proper extraction of trends. Also, adjust the relative height of the y-axis to match your highest value point within the line chart to improve the visual appeal of the chart. Furthermore, do not include the answer option "Other" for the same reason disclosed for pie charts.   Chart Types in LimeSurvey In LimeSurvey, for each question that is created in a survey, a chart type can be predefined in the statistics options of the respective question. If not changed, it will be set to a bar chart by default. Not to worry though, in the statistics overview after collecting survey responses, you can simply and flexibly switch back and forth between all available chart types. Besides bar, pie, donut and line charts, LimeSurvey offers a few more chart types that are not as mainstream: radar (spider) chart and polar chart. Radar charts are a great way of visualising multivariate data, i.e., data with multiple variables, on two dimensions while the variables are represented by axes starting from the same point. Thus, radar charts are beneficial when other chart types such as bar charts become rather cluttered with an increasing number of variables. Polar charts are essentially radar charts since both display data as circular graphs and can be used nicely for visualising multivariate data. However, while radar charts connect the variable results to a "web", the polar charts display results in adverse bars within the circular diagram. General Tip: Keep the number of variables in your radar or polar chart to a maximum number of 8 to avoid chart overload and confusion. Advanced Tip: If you are dealing with large amounts of survey data in general, we recommend you consider creating pivot tables to get more efficient and structured data filtering options when generating flexible and powerful pivot charts.   Conclusion Learning how to use these different chart types effectively will be of great benefit not just when presenting survey results, but also and more importantly when deriving actionable measures from these results. It is always important for you to consider that your audience may not be familiar with the survey setup, i.e., structure, variables and items in detail, which makes it essential to facilitate the readability and interpretation of your survey results by choosing the most suitable chart to get your point across. Always remember: There is no one right chart to visualise your survey data. It ultimately comes down to weighing the pros and cons of each chart.  

What is the Net Promoter Score (NPS)? The Net Promoter Score is an index that is a direct indication of the likelihood that a customer will recommend an organization, product, or service, and an indirect indication of customer satisfaction with an organization, a product, or a service. It provides alternative insights to traditional means for determining customer relationships, as special emphasis is placed on the aspect of word-of-mouth marketing.   It is said that the NPS value is heavily linked with revenue growth and, therefore, a key metric to establish customer loyalty by a provider of a product or service. The Net Promoter Score consists of a single powerful question that simply asks “How likely is it that you would recommend company/product/service XYZ to a friend or a colleague?”. It offers an array of answer options ranging from values 0 (“Not at all likely”) to 10 (“Extremely likely”).It was developed by Fred Reichheld and introduced in 2003.* How to calculate the Net Promoter Score First, your survey respondents are divided into three groups: Those that chose answer options 0 to 6 are categorized as detractors, i.e., people who are not particularly satisfied with your products or services. Respondents who chose 7 or 8 are labeled passives who are neutrally motivated users and later ignored when calculating the Net Promoter Score. Lastly, those who chose 9 or 10 are your promoters, i.e., your loyal and satisfied customers who would gladly recommend your company and its products and services to other people. The actual NPS calculation is done in two steps. First, you need to determine the percentage of promoters and detractors: Number of promoters / Number of total respondents * 100 Number of detractors / Number of total respondents * 100 Example: You have received a total of 100 responses on your survey. 30 respondents (detractors) chose 0 to 6, 30 respondents (passives) chose 7 and 8 and 40 respondents (promoters) chose 9 and 10. 40 promoters / 100 total respondents * 100 = 40% promoters 30 detractors / 100 total respondents * 100 = 30% detractors The second calculation step is the respective NPS equation: % promoters - % detractors = Net Promoter Score The Net Promoter Score can reach a maximum value of +100(%) if you receive 100% promoters and 0% detractors and passives or a minimum value of -100(%) if you receive 100% detractors and 0% promoters and passives.Let’s take a look at our previous example and calculate the Net Promoter Score.Example: We had 40% promoters and 30% detractors.   40% promoters – 30% detractors = 10(%) Net Promoter Score Note: There is broad uncertainty about whether the Net Promoter Score is displayed as a percentage or not. The fact is, there is no specific evidence so far to determine which is better. However, there are publications by the inventor of the NPS himself, Fred Reichheld, who specifies the NPS in percent, for example, see here which is why I decided to stick to percent. What is Considered a Good Net Promoter Score? This question is not easily answered or assessed in a standardized way despite being purely numeric in determination.As mentioned before, the NPS can range from -100 to +100. If you have an equal number of promoters and detractors, you will always end up with an NPS of exactly 0. Therefore, it makes sense to treat 0 as the mean NPS, making it an average score, neither very good nor bad. Anything below 0 should sound an alarm since it indicates customer satisfaction levels are tending towards negative values, and an organization’s products, services, or processes require considerable improvement to avoid substantial customer churn.Obviously, strategy and efforts should be aimed at achieving the highest possible positive NPS score. According to global NPS standards, a score from 0 to 49 is considered “good”, a score from 50 to 69 is considered “excellent”, while a score of 70 and higher is considered “world-class”.For benchmarking reasons, pages such as Customergauge.com offer great insights into well-known brands’ NPS results. For example, Tesla Motors currently has an NPS of 97, while Apple has an NPS of 89, and Samsung, however, only manages an NPS of 70. Interestingly, the Apple iPhone has an NPS of only 55 and the Samsung Galaxy only 45, hence, making the overall brands more satisfactory from a consumer perspective than the companies' products. Tip: If you are able to retrieve information on competitors’ or industries’ Net Promoter Scores, this may give you a good starting point to work towards gaining a competitive edge. Advantages and Disadvantages of the Net Promoter Score There are plenty of advantages of conducting a Net Promoter Score survey to gain knowledge on how satisfied your customers are: Setup and processing are easy and fast due to user-friendliness. NPS question is intuitive for most respondents. The shortness of the survey reduces survey fatigue and results in a better response rate. Studies by Satmetrix and Bain & Company have shown that NPS and revenue growth are correlated. There can be good benchmarking possibilities. Customer classification can be undertaken easily.   There are also disadvantages to the Net Promoter Score: It is criticized as being too general and unspecific, as it doesn’t reflect the reasons for the low satisfaction of the detractors. It’s a snapshot of the general satisfaction level but lacks natural motivation and a plan for what to do with the attained data. It fails to predict future loyalty trends. Tip: if you feel you are not getting enough information out of your NPS question data, simply extend your survey by questions such as ”Would you elaborate on why you chose {0,1,2,3,4,5,6,7,8,9,10}” and ”Which changes would have to be implemented regarding company/product/service XYZ in order for your recommendation to increase by just one point?”, each with an open text box. These additional questions extend your NPS status quo by asking customers specifically for improvement areas and enabling concrete action to spur growth.  *Net Promoter Score is a trademark of Satmetrix Systems, Inc., Bain & Company, and Fred Reichheld  

Online versus offline surveys When using surveys for data collection, you are facing multiple decisions. One of them is to choose a delivery medium.   The evolution of surveys has kept up with the development of technology: going from door to door, mailing questionnaires out, calling people to complete phone interviews, using portable computers – and finally online surveys.Online surveys provide some obvious advantages such as reduced paper and administration costs. However, it makes sense to look a bit deeper into the differences between the two general options, online and offline surveys, especially with respect to the quality of the collected data. Quality of data The quality of survey results is made up of the right questions, the representativeness of the examined group of interest, and the validity and depth of the answers. Error in your data can occur systematically due to biases, like researcher bias, survey bias, respondent bias, and non-response bias, or randomly by misrepresentation.But it’s not just the accuracy of the data: Especially when surveying feedback on customers or an event experience or gathering new ideas and suggestions for improvement, the quality of free text fields is crucial for usable data. All those aspects are notably influenced by your choice of survey format. Response time and rates Online surveys most certainly produce quicker responses, since you can share the link to your survey immediately after creating it without having to call people, mail it to them or meet them in person. Offline surveys, on the other hand, usually produce higher response rates with in-person surveys being the most effective, followed by mail surveys. Online and email surveys still have a better response rate than telephone surveys.The height of response rates doesn’t necessarily translate to representation: If you want to represent the whole population of one country, you’ll need a much lower response rate than when you wish for feedback from a defined group. In a smaller group, you’ll get much smaller sample sizes and it’s much more likely to miss neutral responses and get more positive and negative results. Target group selection Most of the time, the lower response rates of online surveys can be compensated by being able to reach more people – even worldwide if you wish. With the right software, you can run a survey in multiple languages which the participants can select.If the survey has a specific target group or needs a certain frequency distribution in order to be representative, quota setting is a solution that can be used in survey software.A downside to online surveys is that random sampling is more difficult since generating random email addresses like phone numbers is not possible. That is not a problem if the group of interest consists of the members of a club, the students of a certain university, or registered customers of a shop. Otherwise, panel companies can offer a solution to getting the wished sample size.The benefits of offline interviews include going to specific places after an event to reach specific people and also reaching the computer-illiterate population. Though the “online population” used to have special characteristics like being younger, better educated, and more tech-savvy, the computer literacy has drastically increased in the last 15 years. Online surveys are thus reaching more and more people, whereas phone surveys, being still a popular medium of choice, are reaching fewer and fewer people, since households that have no landline are increasing, in particular with younger people. (Perceived) anonymity Especially upon addressing sensitive topics like smoking, drinking, sexual behavior, cheating on taxes, or gambling, self-protective answering can be observed. This means the participant is not answering honestly, downplaying, or exaggerating his or her answer. It occurs especially with an interviewer present and even depends on factors like age, gender, and ethnicity. But also when asking less sensitive questions, and instead about the experience with a product or event, the results might be biased by the presence of the interviewer in in-person interviews, since people may be more polite and less honest. This also applies to situations with an existing relationship of dependence, as often observed at universities, where the professor to be rated is present at the evaluation. Oftentimes people mistrust online surveys, when they are unsure of their data safety. Particularly if you want to prevent multiple participation, you either have to select setting cookies, saving the IP address, or only allow access with a personalized token. All those options might prevent the participants from answering upfront or from answering at all if you neglect to assure the participants of their anonymity and also choose a software tool that allows anonymization as needed.This not only concerns the data accessible to the survey creators but also to the software provider. This is why the hosting and data storage should be at best on servers within countries with high data protection legislation like Iceland, Germany, the Netherlands, or Spain.       Other technical advantages Although the readability of black ink on white paper goes unchallenged, online surveys still win the victory in the design category. By not being restricted in space, it is not only possible to create a more appealing appearance with more coloring and implementation of pictures and videos but also to provide unlimited space for free text entries.To keep participants interested, online surveys allow many options for personalization, including branching to only show relevant questions, piping to reuse answers, or defining different end URLs. Though readability might be better in paper surveys, online surveys grant access to people with disabilities such as poor eyesight by being compatible with screen readers. On the researcher’s side deciphering handwriting is being skipped and fewer errors in data entry occur with online surveys. Interaction A special benefit of personal interviews arises when you want feedback on an event taking place or to ask for customer feedback immediately after the experience: Since the experience (and the excitement at best) is still fresh in their mind, the motivation to fill in a questionnaire might be higher, particularly in regards to open text fields.The interviewer bias, which has already been mentioned, can be utilized in a good way: From my own experience, face-to-face interaction can be beneficial when you are looking for answers in the form of free text fields. I learned that people often do not think of their opinion or thoughts as relevant, and so they’d rather skip a question than enter something they deem wrong. In personal interviews, you can encourage those to share their experiences. If required, you can give further explanations or ask further questions when fitting. Although offline surveys immediately after the examined experience make a lot of sense, online surveys are still superior when it comes to time management. People are often reluctant to answer at all or fill out their questionnaires as quickly as possible if they feel pressured.Did you know? When creating questionnaires with LimeSurvey, you can have respondents take your questionnaire offline with no need for internet availability. The free Android app OfflineSurveys enables caching any LimeSurvey survey and collecting your data offline. Once the Internet is available again, the app can automatically synchronize the collected responses with your LimeSurvey system. Feel free to check it out here. Conclusion The question of whether to choose an online or offline survey cannot be answered conclusively – and it does not need to be. The choice has to be made based on the particular cause depending on the survey goal and type, employee or customer feedback, academic research, or feedback to an event.In many cases, a combination of both might make the most sense, because that way you can also combine the benefits of both: broadly speaking, the number of online surveys with the quality of paper surveys and the combined accessibility of different target groups. LimeSurvey provides a convenient way to combine both: questionnaires that have been created online can be easily converted into a Word document or a PDF file. The question display is thereby adjusted in order to be used in a written or personal interview. Afterwards, the collected data can be entered manually into LimeSurvey, so that in the end both data sets can be analyzed collectively. All aforementioned features like multiple languages, data security, choosing the degree of anonymity, and personalization of the survey design are also provided by LimeSurvey.