Surveys are the most widely used tools you can use to gather market insights. Whether your firm is new on the market or an old player, collecting data on customers or on the market movements in pertinent to your business. However, all data you collect is not equal.
Data which misinforms you not only wastes your time and resources but can also waste your money. Ultimately, you make decisions misguided by your data and hamper your company’s end goal.
Even as a student, spotting the signs when your data is misguiding your academic paper is crucial. By recognizing unreliable responses early in a survey can save you a lot of time. That way, you will not be working late into the night before a thesis submission, just to correct those mistakes.
Let's walk through the most common indicators of low-quality survey data and practical ways to fix them.
Excessive Straight-lining for Every Question
When you present respondents with repetitive questions with similar patterns, they often get bored. This ends up in a collection of straight-line responses. For example, someone might check ‘Strongly Agree’ for multiple questions, even when they vary in meaning. This happens when the one giving the answers does not put much thought into it.
Though sometimes it is the respondents who want to rush through the survey without paying attention, it is not always their fault. The surveys often have questions that are consistent with each other in meaning, providing a high rate of identical answers.
So how can you figure out whether it is an authentic response or it is a flaw in your survey? Sometimes automated tools like an AI checker can flag patterned responses for you, but that happens much later in the survey.
Where you want to start is the very beginning; the design of the survey. Break up the continuous flow with different types of questions. Mix ‘Yes’ or ‘No’ questions with an open-ended question.
You can even include diagrams to direct the visual responders. The more variety you bring will change your survey from low to high quality.
Relatively Fast Completion Times
Sometimes when faced with, let's say, a 20-minute survey, respondents will finish it within 5 minutes. How is that possible, you may wonder. But the answer is clear; they simply were not paying attention.
Respondents click through options without a thought when the survey is long or confusing to them. When a survey is completed extremely fast, it signals poor responses. The key here is to analyze the survey completion time before releasing it to the candidates.
How do you tackle this issue? First of all, do not estimate. Different respondents might take any range of time to complete the same survey. Rather, you should set a realistic completion time based on test runs you have done with early responders. If your survey is computer-based, you can then easily track unusually fast responses.
You can also add a progress checker at intervals, something to remind your survey-takers that their response is valid and meaningful to you. Improving the clarity of your questions by removing unnecessary long paragraphs will hold their interest and give you promising data in return. You can go through survey question examples to fix your data and make it high-quality.
High Skip Rates on Important Questions
Surveys often come with optional questions. You may leave it to the respondents to decide whether they want to provide an answer and they might skip it. However, problems arise when you notice a pattern in people skipping questions that are most relevant to your survey.
Key questions can be skipped for various reasons. Let’s say you ask a question on an overly sensitive topic, such as personal income or religious preference, the respondents might not feel comfortable to answer them.
Occasionally, the ones providing the answers can skip your key questions because of poor user experience. This often happens when people use mobile phones to complete surveys.
If multiple respondents skip the same questions, you are not only losing data, but you are also creating a bias in your end result. A crucial part of your findings will be missing.
You can definitely research the different types of survey questions that you can insert in your questionnaire. Once you have a satisfactory set of questions, do a random test run.
Analyze the pattern of questions which your responders have intentionally skipped. Examine whether the questions are cluttered together, which may indicate an issue with the user experience.
Patterns of Random or Contradictory Answers
Imagine you have asked the two following questions in your survey- “Do you often exercise?” and “How often do you exercise?”
Now, if a series of respondents choose ‘No’ for the first question and ‘2-3 times a week’ for the second, then the logical alignment of their answers will contradict each other. How can you not exercise often and also do it two to three times a week?
This miracle can happen when the respondents do not pay attention to your questions, or they are simply guessing. If random answers fill your survey, you will have a confusing set of data to work with. Misinformation will cloud what you were ultimately trying to achieve with your questionnaire.
A plausible reason can be how you have framed the question’s options. If you only allow ‘Yes and No’ choices to answer whether they exercise or not and follow that up with the next question without allowing them to choose ‘0 times a week’, naturally people will choose whatever the next best alternative is.
So how to exclude redundancy? Do consistency checks on your survey and remove any questions that reveal contradicting information.
Even during your analysis, notice the patterns of answers that do not make sense at all and leave them out of your final output. If you help your respondents with a shorter, more logically framed questionnaire, ultimately you will receive a higher-quality result from them.
The Importance of Maintaining Low Response Variance
The best and worst part about working with humans is that they truly vary in opinions. A healthy data set will show the variance, lets for example say in their preferences or experiences. If most of your respondents' answers fall into the same narrow range of options, it automatically indicates low variance in their choices.
But why does similarity in responses occur? It may be because of your question set. You might have used questions or provided options that push respondents to choose a type of answer. Suppose you fill the survey with mostly positive options and very few negative ones, then your scale of choices will be unbalanced.
If you want to draw a meaningful conclusion from your audience, you should review your survey thoroughly before the final draft is released. You can do this by having a few test respondents fill out the questionnaire first. During the checking process, you should change any language that can deter them towards a certain answer.
If you put too many ‘neutral’ options, people tend to lean towards those. Provide full anonymity to your respondents so that they can freely choose what they feel without feeling like they will be judged. If you can show them that their opinions will be valued, you will achieve a good data set with healthy variance.
The Imbalance in Presenting All Demographics
The best surveys you create will have a healthy representation of the population you want to study. Let’s say you want to survey the homeless community of an area on their daily struggles, and your questions only represent the males and do not address the females. Naturally, the results will be a bad representation of the actual picture.
You will face a sample bias when your questionnaire does not target your audience accurately. If you, for example, post your survey on a website that does not have high traffic from the older population, then you will miss out on their insights if it is valuable to you.
On the other hand, if you make extremely long surveys with many questions, you will unwillingly force people with less time to give you their honest feedback.
The best thing you can do is have a clear definition of who your target audience is, before actually initiating the survey. Once you have that set in, prepare a questionnaire that accurately represents them. Take time to go through your questions again and again to make any necessary changes.
When you release your survey, monitor the response rates of your audience. Release them during a time period when they will not be at a rush.
You do not want to catch a university student in between their classes, rather target their lunch breaks. When you ensure their comfort you will automatically achieve the best results.
Improve Retention by Reducing Mid-Survey Participant Dropout
Previously, we had talked about how respondents can fill out surveys half haphazardly. However, another issue arises when participants completely stop answering the questions.
If breakoff continuously happens at the same spot, that means there is something in your survey that is driving away the responders. This can happen mostly due to long sections of reading before the questions come.
Sometimes, their devices may restrict them from viewing extended paragraphs on the same page. As a result, they just tend to drop out of the survey.
Something you can do to fix that is mapping out the dropout rates and find where in the questionnaire is this happening the most.
At those points, avoid elongated paragraphs and overly complicated questions. Instead, give them visual intervals and it will make your data high-quality.
Final Thoughts
To get reliable data, watch for "straight-lining" where bored users pick the same answer; you can fix this by mixing up question types like open-ended prompts. If people finish way too fast, they aren’t paying attention, so use test runs to set realistic time limits. High skip rates on sensitive topics or clunky mobile designs also hurt results, but a quick check and better phrasing can bridge those gaps.
Contradictory answers usually mean your options are too restrictive, so keep it simple to ensure consistency. Also, avoid pushing people toward "neutral" or positive answers to maintain a healthy variety of opinions. Finally, make sure you are reaching the right demographic and keep sections short to prevent people from quitting halfway through.
