Analyze the consequences of poor survey design and discover seven common errors that potentially ruin the reliability of your results. A blunder in survey design spells disaster, lowering the accuracy of your data and the subsequent extrapolations that can be made using that information.
Unfortunately, the line between “good” and “bad” survey design isn’t always clear. A double-barrelled question is just a question to the untrained eye. A double-barrelled question, on the other hand, is a missed opportunity to reliably gauge a consumer’s opinion, according to a market researcher grounded in survey design best practises.
What Exactly are Survey Errors, and Why do they Matter?
Simply put, survey errors are errors that occur during the design and implementation of a surveying instrument. A redundant questionnaire, for example, may cause straight-lining, which occurs when respondents lose motivation and begin providing similar answers to all questions.
Because the goal of surveying is to draw conclusions about a larger population of interest using a sample, straight-lining and other types of response bias reduce the predictive power of a data set. This means you could spend a lot of time, effort, and money on a survey only to have it fail.
What Causes Survey Errors?
What common survey design mistakes contribute to survey errors?
1. Survey Question Errors
Question errors are the most common type of surveying error in the world. A survey question is not the same as a real-life question. These questions must be precise and well-thought-out. Here are some of the mistakes people make when preparing survey questionnaires. For example, if a question asked respondents to estimate how much money they had spent on alcohol products in the previous six months, most would only be able to make an educated guess. Even if they are aware, they may be too embarrassed to provide an honest response.
Instead of asking survey participants to reflect on their own behaviour, ask them to report on the behaviour of others they know. For instance, you could ask respondents to forecast how much money a friend will spend on alcohol on a night out.
This method is based on a classic psychology experiment. One group of students was asked if they expected to clean up after a meeting. Half of them stated that they would. Another group was asked to predict how many students would clean up after a meeting, and they guessed 15%. The actual number of students who cleaned up was 13%. In summary, this projective technique can assist you in getting closer to the truth.
2. Not Catering To Mobile Responders
Surveys were once completed on desktop computers by respondents. Today, 30 to 40% of people answer questionnaires on their mobile devices.
In short, if you do not optimise your surveys to engage mobile responders, you will only collect feedback from a small portion of your audience. This is an illustration of sampling bias. Distribute mobile-friendly surveys that are design and screen agnostic to ensure complete representation.
3. Ignoring Best Practices for Survey Length
The battle for consumer attention has reached a fever pitch. The proliferation of smartphones has brought with it a slew of distractions: a cacophony of social media notifications, emails, and phone calls that easily divert respondents’ attention.
What is the solution? Keep surveys brief – preferably under 12 minutes, but 10 minutes is preferable. The higher the dropout rate, the longer the survey.
4. Data Collection Errors
Finally, you want reliable data from your surveying exercise. However, there are numerous potholes along the way. Avoid these survey data collection mistakes for dependable results.
Consider the following: If you ask respondents to rate a grocery product on a Likert scale based on “Healthy” and then another scale based on “Nutritious,” the results will be very similar. Similarly, if you ask a respondent to rate an online retailer on “Convenience” and “Ease of Use” separately, you will get similar results.
Having options with overlapping meanings creates redundancy. In this case, the survey becomes unnecessarily long, and the survey-taker is likely to become frustrated and abandon the survey entirely.
5. Design Errors
Improper survey design is another major source of survey errors. Spade survey is dedicated to creating the best survey design for you. Here are some common survey design mistakes to avoid when creating your survey:
You’re conducting an employee engagement survey across your entire company. You have specific questions about the accounting department in there, but it has been distributed to all departments. That is a coverage mistake. You don’t want a human resources employee answering questions for that department.
Survey coverage errors frequently result in skewed results. Make a plan for any specific questions that may or may not be relevant to your entire sample size. You can have those questions appear only if the respondent says they’re from accounting in Spade Survey. This type of branching can assist you in avoiding coverage errors.
Inadequate Response Options
This is yet another of those common survey mistakes. The survey creators ask closed-ended questions and come up with a set of responses that they believe will work for everyone. However, there are times when you want to respond in a way that is not one of the options. What does this imply? You choose the closest thing in the responses, which is still not your correct answer.
Inadequate response options skew the results and prevent honest responses. These types of survey errors are frequently related to design. Perhaps an open-ended response would have been more appropriate for that specific question. Avoid these survey mistakes when creating your survey.
Estimating an entire population’s preferences based on a small sample size is a difficult task. There are numerous ways to go wrong, one of which is simply selecting the wrong sample, whether based on size or demographics. The following are the sample-related survey errors.
Incorrect Sample Size
This is one of the most common surveying errors, second only to survey question errors. Choosing a sample size should not be done intuitively. It entails taking into account a variety of factors, such as your target population, the margin of error, and other figures. There are sample size calculators available to assist you in determining your ideal sample size.
If your sample size is too small, the results will most likely not be representative of the larger population. If your sample size is larger than necessary, that’s not a bad thing, but it still costs you more money to collect that data. It is critical to have a well-defined sample size and enough responses to meet that number for a variety of factors.
If you include a certain number of people in your sample size and some of them do not respond to certain questions, it can lead to critical survey errors. What you want is for each question to have enough responses to represent a larger population. If you don’t get that many responses, your data will be skewed and thus not representative of the actual population.
Non-response errors can be avoided by making all critical questions mandatory, so that respondents cannot choose and choose. It is also beneficial to have a larger sample size than your sample size in case some participants drop out. It is critical to consider the possibility of nonresponse bias when conducting a successful survey free of sampling errors.
7. Using Biased and Leading Language
‘Did you like our delectable ice cream?’ This question appears to be unimportant. After all, who wouldn’t want to buy something described as “delicious”? However, when subjective adjectives are included in surveys, they prime the respondent to provide a positive response. Worse, leading questions can make survey participants feel as if they are being manipulated into providing a specific response.
Instead, consider taking an empathic approach to survey design. Make respondents feel more at ease telling the truth. Instead of using adjectives like ‘delicious,’ use simple, easy-to-understand language.
Kudos on deciding to conduct your survey! You’re on your way to gaining insights that will allow you to channel your energy more effectively. However, as previously stated, a lack of knowledge is dangerous. Avoid these 7 common survey errors at every stage of your survey to gain useful insights. We hope that being aware of these flaws will assist you in creating more reliable surveys.
The data you obtain from an error-ridden survey will be at best useless and at worst misleading. A half-hearted survey exercise has real, tangible risks. Avoiding these types of survey errors will ensure that your data is robust. Follow these guidelines to conduct a thorough survey that will help you face the future of your organisation with confidence!