Ethnography is the most rustic form of observation where all the participants are observed in a natural environment. The aim here is to gain insight into how users naturally interact in regular ways. This method includes direct observation, video recordings, diary studies, and a variety of other methods. Note that this method of research is a popular field-based research method used widely in social research.

Collecting video feedback has become popular over the years. It’s also another great way to collect qualitative data for the research. Mostly, companies and brands are using video responses as a medium to capture feedback at scale. One thing you must note here is that video responses show more authentic and natural insights. Researchers can also observe the participants through the video for further research purposes (mostly to find intention).

You can find a range of moderated discussions in focus group studies. Similar to focus group observation, researchers use online forums or any other platform to share the topic of discussion. Thereafter, the researcher collected dynamic data from the discussion. One thing is different here is that the researchers can flex their level of input during moderated discussion.

Last in qualitative data, you have enquired “why” through the research. But in quantitative data, you need to inquire “what” through the research.

Basically, quantitative data is more statistical data, which is based on numerical data. This type of data helps you understand “hard” facts about the research topic.

Suppose you want to develop your content strategy. Therefore, using quantitative data helps you understand the latest trends, consumer behavior, and other forms of vital data insights that can make your content worthy and engaging.

Similar to qualitative data, quantitative data can also be collected via different methods and processes. Some of the most important methods are;

Assess the level of depth towards a data value using ordinal data. It follows a natural order to detail the datasets. The application where ordinal data can be found is a survey. It helps uncover agreement levels towards certain statements and assess preferences.

For example, a respondent can choose “strongly agree” instead of “agree” to show the level of desperation. Ordinal data strikes a balance between objective and subjective preferences and reveals data or responses in a uniform format. That’s why you can observe that ordinal data is being widely used in hypothesis testing or in advanced analysis tools.

Some sorts of data cannot be measured in any meaningful way for data analysis. Nominal data represent those data types. You cannot place these data types in any order or perform any sorting work. For example, somebody is sharing his favorite food items like sandwiches, tahini, burgers, gialto, etc., you can categorize them into food items for the sake of quantitative data. And that’s it.

Consider the amount of profit a company makes in a random month of a specific year to understand discrete data. This data type only represents particular values, not necessarily using whole numbers.

Sometimes, continuous data is referred to as “infinite” data. It gets its name from a continuous range of datasets. For example, continuous data can include temperature, weight, or distance. Continuous data changes over time, and that’s the very nature of it. Continuous data uses a scale to measure, as the highest range is infinite.

As we have seen in the previous sections, questionnaires are a part of a broad survey process. Whereas surveys are quite a big part of the research process. There are plenty of research methods available to conduct surveys and questionnaires. Let’s have a look at them to understand each one of them.

With an aim to collect data that is useful for decision-making, qualitative research is conducted. It includes in-depth questioning of respondents to bring detailed survey data. Each response can be unique from another. Differences of opinions and thoughts are welcome and recorded in this qualitative research method.

To collect qualitative research, researchers need to carry out interviews, focus group studies, one-to-one or moderated group discussions, and other methods.

It’s all about gathering statistical insights from the data. Collecting statistical data (i.e., numbers) is the sole aim of quantitative research. It helps uncover the trends that help researchers make decisions. Plus, it also helps predict the future as it reveals the current trends.

Collecting data through customer satisfaction surveys or employee retention surveys is the prime example of quantitative research. It will showcase the main issues through a subjective lens of the researcher.

Rather than focusing on “why”, descriptive research focuses more on finding answers to “who”, “where”, “what”, and “when”. Descriptive research helps researchers to find out unique characteristics of a population, situation, or phenomenon that they’re studying.

Understand why certain things happen and the order of their occurrence using analytical research. Conducting analytical research is excessively useful for making strategic decisions. Applying critical thinking is a part of the process under this research method, and that’s the reason the research demands analytical support.

Researchers choose a topic of research that has not been previously covered. Exploratory research helps researchers use different ranges of quantitative and qualitative methods to explain and explore a topic.

Finding practical solutions to get away with real-life problems is the main purpose of applied research. For example, organizations can conduct research to find our workplace issues, productivity measures, etc, to tactically handle the challenges.

SurveyMoney (a widely popular survey platform) conducts 3.5 million plus surveys each year. They stress designing the surveys, too, as a part of the process. Setting up a questionnaire is also a part of the same process.

Asking great questions matters the most if you want to conduct a survey that stands out. Therefore, you need to take the responsibility of adding relevant and conscious questions to your questionnaire.

That’s what it’s been said that whether your questionnaire stands on its own or is part of a survey, to acquire great responses or results, you have to ask great questions.

Keep the length of your questionnaire in mind while writing it. Many research organizations have realized that the survey response rate decreases when the number of questions in the questionnaire increases. More than 10 questions in a questionnaire can decrease the response rate up to 40%. Without any rewards, you cannot keep people for more than 5 minutes answering your questionnaire.

Questions can make the entire picture different. Asking relevant questions can make people stay on the platform. That’s why you need to frame and ask good questions as a part of your questionnaire strategy.

Questions can make the entire picture different. Asking relevant questions can make people stay on the platform. That’s why you need to frame and ask good questions as a part of your questionnaire strategy.

It’s always better to ask more questions than you really need to. That is applicable in your life, not when it comes to research. Striking a balance between what you need to ask and how well you can ask is there.

All your questions should be kept short to get more responses. We are not limiting the tips only to this. The following tips can help you frame good questions as part of your survey procedure.

✒️ Keep your language simple: All your questions should remain in short format. If you need to explain anything, just write it in brief like an instruction. Avoid explaining it in big.

✒️ Be specific: When you ask about factors such as “daily”. You can add phrases like “more than once a week”, rather then adding ‘regualry’ in your questionnaire.

✒️ Avoid using jargon: Jargon weakens the sentence’s matter. Keep your questions to the point in order to maximize the responses. Sometimes jargons make questions confusing and forces people to leave the survey in the middle.

✒️ Avoid negative phrasing: Place “not” in the right location in the question to make it visible easily. Sometimes a simple “not” causes issues in response. It’s better to keep the negative phrases out of your scope.

✒️ Do not put double-barreled questions: Avoid using two questions at the same time. One questions should reflect one intention.

✒️ Test your questions: before sending your questionnaires, you need to test it well. Preferably, go for multiple times.

Running a successful survey isn’t just about throwing a few questions together and hoping for the best. It’s about strategy, clarity, and purpose.

Whether you’re collecting customer feedback, employee opinions, or market insights, the way you design and manage your survey determines how valuable your results will be. Here’s how to do it right.

Before you write a single question, define what you want to learn. Are you trying to improve a product, measure customer satisfaction, or explore a new business idea? A clear goal keeps your survey focused and prevents unnecessary questions. Think of it like a GPS; without direction, your survey will wander aimlessly, and your data will lead nowhere.

Understanding who you’re surveying is just as important as knowing what you want to ask. Tailor your tone, language, and questions to fit your audience’s profile. For example, questions for tech professionals will differ from those for students or older citizens. The more relatable your survey feels, the more genuine responses you’ll receive.

No one likes a marathon survey. Keep it concise — 10 to 15 questions are usually enough. Use simple, direct language and avoid jargon or confusing phrasing. Make sure each question serves a purpose. If it doesn’t tie back to your goal, cut it out. The easier it is for respondents to complete, the higher your completion rate will be.

A successful survey mixes question types strategically. Use multiple-choice for quick insights, rating scales for satisfaction levels, and open-ended questions for qualitative feedback. Avoid leading or biased questions like “How amazing was your experience?” they skew results. Instead, stay neutral and let respondents share their honest opinions.

Before sharing your survey widely, test it on a small sample of people. This helps identify confusing questions, technical issues, or errors. A pilot test also shows if your questions actually capture the data you need. It’s far easier to fix mistakes early than after responses start rolling in.

Your survey’s success depends on where and how you share it. Email, social media, website pop-ups, or direct messages all can work, but pick the one your audience uses most. For business clients, email might be best; for younger demographics, social media links could be more effective.

A small incentive like a discount, free resource, or entry into a giveaway can significantly boost participation. People love to feel rewarded for their time, and even small gestures can make a big difference in response rates.

Collecting responses is only half the job; analyzing them is where the real value lies. Look for patterns, trends, and actionable insights. Share results transparently and use them to make informed decisions. Let participants know how their feedback is making an impact; it builds trust and encourages future participation.

Understanding the differences between a questionnaire and a survey is important when it comes to market research.

Always think about your audience first and plan how you can efficiently communicate with them. Using simple language is the best way to get close to them. Do not use any jargon or acronyms, as these elements make your questions unnecessarily complex.

People will open your survey link on a small screen. So think about it also. How your survey will look on a small screen should be taken care of during this course. Further, you need to reduce the load on the responders’ working memory. Asking too many difficult questions or some questions that go against their beliefs can trigger them.

Getting survey bounce is not our aim. Thus, we have to be meaningful when asking questions. Avoid visual triggers; keep questions plain and simple.

Getting reliable data from survey responses requires choosing the right type of survey. Choosing the right mix of question types can help. Asking too many open-ended questions can increase the survey drop-out rate. People do not like to think too much. They like to answer multiple-choice questions when it comes to responding to surveys.

Therefore, if you have a total of 9 questions in your questionnaire, you can ask 1 or 2 open-ended questions. Not more than that.

From clicking your survey link to clicking the submit button, your survey should take less than 10 minutes. If it takes a longer time, you’ll end up increasing bounce rates. Participant engagement generally drops if the survey consumes more time. Hence, keep your survey as short as possible.

If you require any help regarding survey design or processing, please feel free to reach us. We have relevant expertise and experience handling everything related to surveys.