50 data collection questionnaire examples
18 min read
Are you still unsure about how to structure your research? Finding good data collection questionnaire examples is one of the first steps to creating surveys that can generate relevant information and support more strategic decisions.
In this article, you will learn about different questionnaire models, understand which questions to use in each situation, and discover how to transform responses into valuable insights for your business.
What is a data collection questionnaire?
A questionnaire for data collection is a tool used to gather information from a group of people in a structured and organized way.
It is composed of a set of questions developed with a specific objective, such as understanding customer opinions, evaluating satisfaction with a product or service, identifying consumption habits, or collecting information for academic and market research.
The main function of the questionnaire is to transform perceptions, behaviors, and experiences into data that can be analyzed later. When well-planned, it allows obtaining reliable information, identifying patterns, and generating insights that support decision-making.
What are the types of questionnaires?
There are different types of data collection questionnaires, and choosing the ideal model depends on the research objectives, the target audience, and the information desired. See some of them:
Questionnaire with open-ended questions
Questionnaires with open-ended questions allow participants to respond freely, using their own words. This format is ideal for understanding opinions, perceptions, experiences, and suggestions in more depth.
For example:
“What could be improved in our service?”
Although they provide more detailed responses, open-ended questions usually take more time to answer and analyze.
Questionnaire with closed-ended questions
In this model, participants choose an answer from previously defined options. It is one of the most used formats in market research, satisfaction, and consumer behavior surveys.
For example:
“How often do you use our service?”
- Daily
- Weekly
- Monthly
- Rarely
Closed-ended questions facilitate participation and make data analysis faster and more objective.
Mixed questionnaire
The mixed questionnaire combines open-ended and closed-ended questions in the same survey. This approach allows collecting quantitative and qualitative data at the same time.
For example, a survey might ask for a rating for the service and then provide a space for the participant to explain their evaluation.
This is one of the most complete formats used by companies.
Satisfaction questionnaire
It is used to measure customer perception of products, services, or experiences offered by a company. Its main objective is to identify strengths, opportunities for improvement, and satisfaction levels.
This type of questionnaire is widely used in NPS, CSAT, and service evaluation surveys.
Market research questionnaire
The market research questionnaire seeks to understand consumption habits, preferences, behaviors, and trends of a specific audience.
The information collected helps companies develop products, validate ideas, analyze competition, and identify growth opportunities.
Demographic profile questionnaire
This model aims to collect information about the characteristics of participants, such as age, gender, education, income, profession, and geographical location.
This data is important for segmenting the audience and analyzing research results more strategically.
Product evaluation questionnaire
Used to collect opinions about physical or digital products, this type of questionnaire helps identify positive points, difficulties of use, and opportunities for improvement. It is very common in concept tests, product launches, and user experience research.
Academic or scientific questionnaire
Widely used in final papers, scientific research, and academic studies, this model follows specific methodologies to ensure data reliability and result validity.
Depending on the research objective, it may include both open-ended and closed-ended questions.
Online questionnaire
The online questionnaire refers to the survey application format. It can be used in different contexts and is usually distributed by email, social media, websites, or specialized research platforms.
Its main advantage is practicality, in addition to the possibility of reaching a large number of respondents in a short time.
In-person questionnaire
In this model, questions are applied directly by an interviewer. Although it requires more resources and time, it allows for deeper responses, clarification of doubts, and closer interaction with participants.
What should a good questionnaire have?
To generate reliable and relevant data, it is important that each question has a clear purpose and contributes to the research objectives. Below, check out the main elements that a good questionnaire should have.
Well-defined objectives
Before writing any question, it is essential to know exactly what you want to discover. A questionnaire without clear objectives can generate interesting but not very useful answers for decision-making.
Defining the research objective helps select the most relevant questions, avoid unnecessary information, and keep the questionnaire more concise and efficient.
Clear and objective questions
Participants should easily understand what is being asked. Confusing, ambiguous, or overly technical questions can lead to different interpretations and compromise the quality of the collected data.
Whenever possible, use simple and direct language, appropriate to the profile of the audience that will answer the survey.
Organized structure
The order of questions directly influences the respondent's experience. The ideal is to start with simpler and more general questions, gradually moving to more specific issues.
A logical structure helps maintain participant interest and reduces the chances of abandonment during completion.
Appropriate length
Very long questionnaires usually have lower completion rates. Therefore, it is important to include only questions that truly contribute to the research objectives.
When the questionnaire is objective and respects the respondent's time, the quality of the answers tends to be higher.
Appropriate question types
The choice of question format also makes a difference. Closed-ended questions facilitate data analysis and increase response speed. Open-ended questions, on the other hand, allow for more detailed opinions and deeper exploration of certain topics.
The ideal is to find a balance between the two formats, according to the research needs.
Neutral language
Questions should be formulated impartially, without inducing or influencing responses. When a question suggests a specific answer, the results can become biased and less reliable.
Neutrality helps ensure that the data reflects the real opinion of the participants.
Well-defined target audience
An efficient questionnaire is built considering the characteristics of the people who will answer it. Age, professional profile, level of knowledge, and context of use are factors that influence how questions should be formulated.
The more aligned the questionnaire is with the target audience, the better the results obtained.
Ease of results analysis
In addition to thinking about the respondent's experience, it is important to consider how the data will be analyzed later. Well-structured questions facilitate the organization of responses, the identification of patterns, and the generation of relevant insights for the research.
What types of questions can be used in a questionnaire?
It is worth remembering that the type of question will depend on the objective of your research. However, to choose the best one, it is important to know the options. Here we have selected the main ones:
Open-ended questions
Open-ended questions allow respondents to express their opinions, perceptions, and experiences in their own words, without limitations of predefined alternatives. They are useful for obtaining deeper answers and understanding the reasons behind a choice or behavior.
Example: “What do you value most in customer service?”
This type of question generates qualitative insights, but may require more time for analysis, as responses need to be interpreted and categorized.
Closed-ended questions
Closed-ended questions present previously defined answer options, allowing the participant to choose an alternative. They are widely used in quantitative research, as they facilitate data organization and analysis.
Example: “Have you used our product before?”
- Yes
- No
They allow for easier comparison of results and identification of patterns among different groups of respondents.
Multiple-choice questions
Multiple-choice questions offer a list of alternatives, allowing the respondent to select one or more options, depending on the survey configuration.
Example: “What factors influence your purchasing decision?”
☐ Price
☐ Quality
☐ Brand
☐ Service
☐ Recommendation from others
They are ideal for mapping preferences, habits, and characteristics of the audience.
Rating scale questions
Scale questions allow measuring opinions, perceptions, and satisfaction levels through a sequence of values. They are widely used to evaluate consumer experiences and feelings .
Example: “On a scale of 1 to 5, how satisfied are you with our service?”
1 – Very dissatisfied
5 – Very satisfied
Some common scales include satisfaction, importance, agreement, and likelihood of recommendation.
Ranking questions
Ranking questions ask the respondent to organize options according to their preference or importance. They help identify priorities and factors most relevant to the audience.
Example: “Rank the factors below in order of importance when choosing a car:”
1st Price
2nd Fuel consumption
3rd Technology
4th Design
They are useful when it is necessary to understand which attributes have the greatest weight in the consumer's decision.
Matrix questions
Matrix-format questions present several items evaluated using the same response scale. They make the questionnaire more organized and allow for comparing different aspects of an experience.
Example: Rate your satisfaction with the following aspects:
| Aspect | Very dissatisfied | Dissatisfied | Satisfied | Very satisfied |
|---|---|---|---|---|
| Service | ☐ | ☐ | ☐ | ☐ |
| Delivery time | ☐ | ☐ | ☐ | ☐ |
| Product quality | ☐ | ☐ | ☐ | ☐ |
They are widely used in satisfaction and customer experience surveys.
Single-choice questions
In this format, the participant can select only one alternative from the available options. They are indicated when there is a single correct or main answer.
Example: “What is your primary payment method?”
- Credit card
- Pix
- Bank slip
- Cash
This model facilitates results analysis and avoids duplicate responses.
Multiple-choice questions
Multiple-choice questions allow the participant to choose more than one alternative. They are indicated for situations where different options can be true at the same time.
Example: “Which social media networks do you use frequently?”
☐ Instagram
☐ TikTok
☐ LinkedIn
☐ YouTube
They are useful for understanding audience behaviors, preferences, and habits.
Demographic questions
Demographic questions collect information about participants' profiles, such as age, gender, location, education, and income. This data helps segment the analysis and compare responses across different groups.
Example: “What is your age group?”
- Up to 18 years old
- 19 to 30 years old
- 31 to 45 years old
- Above 45 years old
They should be used carefully, requesting only information relevant to the research objective.
Filter or screening questions
Filter questions are used to direct the respondent to specific parts of the questionnaire or to identify if they belong to the research's target audience.
Example: “Have you purchased any beauty products in the last 6 months?”
- Yes → continue survey
- No → end survey
They help ensure that only people with the appropriate profile answer certain questions.
Intent questions
Intent questions seek to understand the likelihood of a future action, such as buying, recommending, or continuing to use a product or service.
Example: “How likely are you to buy this product again?”
- Very likely
- Likely
- Unlikely
- Very unlikely
They are widely used to predict behaviors and evaluate business opportunities.
Comparison questions
Comparative questions present two or more options for the respondent to choose a preference or evaluate differences between alternatives.
Example: “Which cell phone brand do you consider most reliable?”
- Brand A
- Brand B
- Brand C
This type of question helps understand brand positioning, value perception, and consumer preferences.
What are the main errors in preparing a data collection questionnaire?
Something important you need to know is that some errors can compromise the quality of responses and even invalidate the research results. Therefore, understanding these problems helps avoid biases, improve participant experience, and obtain more reliable data.
Not defining a clear objective
One of the most common errors is starting to formulate questions without a well-defined objective. When the research lacks a clear purpose, the questionnaire tends to be long, confusing, and full of questions that do not generate useful information.
Before creating any question, define exactly what you want to discover and what decisions will be made based on the results.
Asking confusing questions
Questions with complex language, technical terms, or multiple interpretations can generate inconsistent responses. If participants do not clearly understand what is being asked, the collected data will lose quality.
The ideal is to use simple, objective language appropriate to the profile of the surveyed audience.
Creating biased questions
Questions that suggest a specific answer can influence participants and generate biased results. For example:
“Do you agree that our service is excellent?”
In this case, the question already induces a positive perception. A more neutral alternative would be:
“How do you rate our service?”
Neutrality is fundamental to obtaining genuine responses.
Asking double-barreled questions
Another frequent error is combining two different topics into a single question. For example: “Are you satisfied with the quality and price of the product?”
The respondent may be satisfied with the quality but not with the price. In this case, it will not be possible to know which aspect influenced the answer.
Whenever possible, each question should address only one topic.
Creating overly long questionnaires
Extensive questionnaires tend to increase abandonment rates and reduce the quality of responses. When participants get tired, they often answer quickly just to finish the survey.
Therefore, include only questions truly necessary to achieve the defined objectives.
Ignoring the order of questions
The sequence of questions directly influences the respondent's experience. Sensitive or complex questions at the beginning can cause discomfort and reduce engagement.
A good practice is to start with simple questions and gradually move to more specific topics.
Not offering adequate response options
In closed-ended questions, poorly formulated options can make it difficult to answer and harm data analysis. Alternatives should be clear, comprehensive, and, whenever possible, mutually exclusive.
It can also be useful to include options like “Other” or “Prefer not to answer” in certain situations.
Not testing the questionnaire before application
Many surveys are sent out without any prior validation. This increases the risk of typos, poorly formulated questions, logic problems, and navigation difficulties.
Conducting a test with a small group before launch helps identify flaws and make important adjustments.
Disregarding the target audience
An efficient questionnaire must be designed for those who will answer it. Using inappropriate terms, irrelevant questions, or language incompatible with the participants' profile can significantly reduce the quality of the results.
The more aligned the questionnaire is with the target audience, the higher the response rate and the reliability of the collected data will be.
Not planning data analysis
Many people create surveys without thinking about how the results will be analyzed later. This can generate information that is difficult to interpret or impossible to compare.
How to create a data collection questionnaire?
When well-structured, a questionnaire increases the quality of responses and helps transform data into more assertive decisions. Therefore, it is important to follow some steps, such as:
Define the research objective
The first step is to understand exactly what you want to discover. Before creating the questions, ask yourself: what problem needs to be solved? What information is needed to make a decision?
Having a clear objective avoids unnecessary questions and helps maintain the research's focus.
Identify the target audience
Knowing who will answer the questionnaire is fundamental to defining the language, the format of the questions, and even the survey application channel.
A questionnaire intended for end customers, for example, may require a different approach than a survey aimed at managers or professionals in a specific area.
Choose the types of questions
Depending on the research objective, you can use open-ended, closed-ended, or a combination of both types of questions.
Closed-ended questions facilitate data analysis, while open-ended questions allow for a deeper understanding of opinions and perceptions. A balance between these formats usually yields more complete results.
Organize the questions in a logical sequence
The respondent's experience also influences the quality of the answers. Therefore, questions should follow a natural and intuitive order.
A good practice is to start with simpler, general questions, gradually moving to more specific or sensitive issues.
Use clear and objective language
Complex questions can lead to different interpretations and compromise research results.
Try to use short sentences, simple language, and terms that make sense to the target audience. The easier it is to understand the question, the higher the quality of the answer will be.
Avoid biased questions
Questions should be neutral and not induce answers. When the participant perceives an implicit expectation in the question, the data can become biased.
The goal is to understand the respondent's real opinion, not to influence their answer.
Limit the number of questions
Overly long questionnaires can cause fatigue and increase the abandonment rate. Furthermore, tired participants tend to answer with less attention.
Include only questions that truly contribute to achieving the research objectives.
Conduct a test before application
Before making the questionnaire available to the public, test it with a small group of people.
This step helps identify interpretation errors, navigation problems, confusing questions, and other points that could harm data collection.
Choose the best application method
The questionnaire can be applied in different ways, such as online forms, email surveys, in-person interviews, phone, or social media.
The choice of channel should consider the audience's profile and participants' ease of access.
Analyze the results and transform data into insights
After collection, it's time to organize and analyze the responses. Look for patterns, trends, and opportunities that can generate practical actions for your business or research.
Check out 50 examples of questionnaires for data collection
If you still have doubts about how to create a good questionnaire, here are some examples that can help you:
Examples to identify the audience profile
- What is your age group?
- In which state do you reside?
- What is your education level?
- What is your profession?
- What is your monthly income bracket?
Examples for customer satisfaction survey
- How do you rate your experience with our company?
- Did the product or service meet your expectations?
- How do you rate the quality of the service received?
- Was the response time satisfactory?
- What can we improve?
Examples for product evaluation
- How do you rate the quality of the product?
- Was the product easy to use?
- Which feature did you like the most?
- Was there any difficulty during use?
- Would you buy this product again?
Examples for market research
- How often do you buy products in this category?
- What factors influence your purchasing decision?
- Which brand do you currently use?
- How much do you usually invest in this type of product?
- What would make you switch brands?
Examples for consumer behavior research
- Where do you usually research before making a purchase?
- Which channel do you use most for shopping?
- Does price influence your purchasing decision?
- Do you usually read reviews from other consumers?
- What criteria are most important in your choice?
Examples for service evaluation
- How do you rate the team's cordiality?
- Was your problem resolved?
- Was the service provided within the expected timeframe?
- Did you feel well-served during the process?
- What score would you give our service?
Examples for NPS surveys
- On a scale of 0 to 10, how likely are you to recommend our company?
- What was the main reason for your score?
- What could we do to improve your experience?
- What do you value most about our company?
- Is there anything that caused dissatisfaction?
Examples for organizational climate research
- Are you satisfied with your work environment?
- How do you rate the company's internal communication?
- Do you feel valued by the organization?
- Do you have the necessary tools to perform your job?
- What could be improved in the company?
Examples for event research
- How do you rate the event's organization?
- Was the content presented relevant?
- Did the event venue meet your expectations?
- Would you participate again?
- What stood out most to you during the event?
Examples for collecting suggestions and feedback
- What was your main difficulty?
- Is there any feature you would like to see available?
- What did you like most about your experience?
- What improvements do you suggest?
- Are there any additional comments you would like to share?
These examples can serve as a starting point for different types of research. The most important thing is to adapt the questions to the context of your data collection and ensure that each answer contributes to the research objectives.
How to send questionnaires for data collection?
After structuring the questionnaire, defining the questions, and identifying the target audience, the next step is to choose the best way to send it to participants. The choice of distribution channel can directly influence the quantity and quality of responses received.
A survey platform is one of the best options for those seeking more efficient, organized, and cost-effective data collection. These tools allow you to create online questionnaires, distribute them to the right audience, monitor responses in real-time, and analyze results more practically.
If you are looking for a simple, efficient, and accessible solution, the tip is to use VisionCX. The platform offers resources for different types of research, helping companies collect data, better understand their customers, and transform responses into insights to support strategic decisions.
How to find respondents for a data collection questionnaire?
Currently, one of the simplest and fastest ways to find respondents for a data collection questionnaire is by using a respondent panel. These platforms allow access to a database of previously registered participants, segmenting the audience according to research criteria, and collecting responses more quickly.
If you want to find qualified respondents practically and efficiently, the tip is to use PainelTAP. The platform helps companies and researchers reach the ideal audience for their surveys, ensuring faster data collection and higher quality responses.
With a respondent panel, you reduce the time needed to find participants and increase the chances of obtaining relevant insights to make more strategic decisions. Want to know how it works? Schedule a demonstration.