A questionnaire is more than just a set of questions. In market research, a questionnaire reveals people’s thought process and experiences. It serves as foundational pillars for survey research. In this blog, we will learn the meaning, types and benefits of using a questionnaire. We will also discuss how to design one for better research.

What are Questionnaires?

A questionnaire is a structured set of questions designed to gather information from respondents across various segments. It is used to collect quantitative or qualitative research and may include closed-ended or open-ended questions depending on the objective.

Questionnaires are a go-to method for researchers across fields like academia, market research, and social sciences.

Questionnaires can be administered via:

• Online survey tools
  
• Printed forms
  
• Face-to-face interviews
  
• Telephone (CATI) surveys
  
• Messaging apps like WhatsApp surveys & Facebook messenger

In various research methodologies, it facilitates the systematic collection of information on specific topics. Organisations can gather large volumes of data efficiently. In customer experience, questionnaires are used for understanding customer needs, preferences, and to measure satisfaction metrics. 

Why are questionnaires important?

• Data rich: Useful for statistical analysis, insights, and segmentation.
• Versatile: Use in academic studies, market research, or employee feedback.
• Data Accuracy: A uniform format reduces errors and simplifies analysis.
• Anonymity: Encourage honest responses, especially on sensitive topics. It can also avert response bias.
• Cost-Effective: Gather data from any number of respondents without expensive logistics.
• Scalable: Reach diverse audiences, from local communities to global markets.
• Flexible: Use online, paper-based, or omnichannel formats (e.g., WhatsApp, chatbots).

Who is responsible for designing a questionnaire?

Research states that there are 5 people responsible to design a questionnaire.

• A client may capture market trends and get answers based on on-ground statistics. This will help them identify pain points that they can improve.  
• A researcher has to identify the right kind of questions for the specific respondents. They need to know if the interviewer can get most out of the questionnaire. Their main task is to design questions that are unbiased and align with the needs of the client and capture valuable user data. 
• The interviewer has to collect answers from the target respondents at a specific time. Since they are in direct contact with the respondents, the interviewer can give insights on how easy or difficult the questionnaire was.
• The data analyst will collect and analyze the responses based on certain filters and requirements. Their main aim is to identify if the respondent data can be processed efficiently.

What is the difference between a questionnaire and a survey?

A questionnaire is a tool used for qualitative and quantitative data collection.  A survey is a comprehensive research methodology that uses questionnaires as one of its components.

Types of Questionnaires in Research [+ Examples] 

Questionnaires come in various formats, each suited to different research goals. Here are the main types used in research, with examples to spark ideas:

1. Structured questionnaire:

Structured questionnaires have fixed response options (close-ended questions). People have to choose from options they agree with. The answers will be noted by the interviewer and ideal for quantitative research.
Example: Net Promoter Score surveys where people have to indicate their brand advocacy over a 0 to 10 rating scale of recommendation.

2. Unstructured questionnaire: 

Unstructured questionnaires do not follow a predefined structure. It contains open-ended questions where respondents can answer freely offering qualitative insights. However, qualitative data does not mean free flowing without direction. The aim is to understand a respondent’s experience based on a specific situation. Unstructured questionnaires are ideal for customer interviews and brand perception research.

Examples:

• “What challenges do you face when studying remotely?”
• “Describe your experience with our product.”

3. Semi- structured questionnaire:

Semi-structured questions combine close-ended questions and open-ended questions for a balanced approach. In this format, respondents can answer a question based on a scale.They are given the opportunity to explain the reason behind the ratings or selection. Ideal for exploratory studies.

Example:  Customer feedback surveys with a rating scale and an open-ended response section. 

4. Close-ended questionnaire

Closed ended questions follow a structure and restricts the responses to a few options or selections. There are various types of closed ended questions used in customer experience surveys: 

Dichotomous questions:

Dichotomous questions only offer two response options- Yes/ No, True/False, Satisfied/ Unsatisfied . It is a straightforward way to analyze data. Just like most quantitative data, dichotomous questions are suitable when situations need precise information.

Multiple choice questions

Multiple choice questions enable people to choose multiple options under a single question. For example: 

1. Choose your preferred mode of transportation in the city:

1. Uber
2. Private car
3. Public bus
4. Metro
5. Others (please specify)

5. Likert scale questionnaire:

Likert scale is a type of rating scale commonly used to measure attitudes, satisfaction levels, and behaviours pertaining. There are various types of Likert scale: 3-point rating scale, 5-point rating scale, 7-point rating scale and 10-point rating scale. The Net Promoter Score is also a type of a rating scale.
Respondents will indicate their level of agreement or disagreement with the question.

Example: On a scale of 1 to 5, how satisfied are you with our product? 

1. 1: Extremely unsatisfiedUnsatisfied 
2. Neutral
3. Satisfied 
4. Extremely Satisfied

6. Semantic differential scale

A semantic differential scale will measure the attitudes and perception of people that are mapped on extreme ends of the scale. It contains polar opposite options on a question spectrum. 

Semantic differential scale is useful to map psychological influence in a marketplace or to identify how customers make a purchasing decision. 

Example:  How would you rate our new skincare product?

Unpleasant — Pleasant 

Cheap — Premium

Artificial — Natural

Abrasive — Soft

7. Self-administered questionnaires

Self-administered questionnaires are fulfilled by respondents when they undergo an interaction without the intervention of the interviewer or a customer support team. This type of questionnaire reduces bias and offers genuine responses from people who can share authentic experiences based on an interaction.   

A customer will purchase a product from an ecommerce website. She will receive order details on her email ID along with an automated email survey. This survey aims to capture her experience with the entire transaction. Example: customer satisfaction score (CSAT) survey automated via email.  

8. Interviewer-administered questionnaire

Interviewer administered questionnaires are conducted via face-to-face interviews. This can occur via telephonic surveys or CATI surveys. This method is useful for complex surveys that need in-person clarification. Interviewer administered surveys are applicable to gauge product usage, to understand purchasing behaviour across retail stores or to collect census data.

When Should You Use a Questionnaire?

Use questionnaires when:

• You need quantitative insights from a large population.
• You want to measure opinions, satisfaction, or behaviors to identify factors that influence purchase or brand selection.
• You plan to segment audiences based on demographics for comprehensive market research.
• You need a repeatable, scalable and measurable method for data collection.
• You aim to improve products and services for customers
• You aim to understand the internal working of an organisation or for employee satisfaction.

How to Design a Good Questionnaire for Research?

Designing a questionnaire involves several critical steps to ensure its effectiveness:

1. Stick to the survey goal:

Clearly define the purpose and objectives of the research questionnaire. Know the end goal – understanding customer satisfaction, gathering feedback on a new feature, or conducting market research. This will guide the entire design process.

2. Choose the right type of question:

For quantitative data, multiple-choice questions, rating scales, and Likert scales are some choices depending on survey channel and research goal. For qualitative insights, open-ended questions are more suitable. Customer satisfaction metrics come with a pre-defined question frame. 

Example: Share a CSAT scale after a purchase on an ecommerce application. The CSAT scale will gauge the experience of a customer during the transaction.

3. Keep the language simple:

Use simple, non-technical language and avoid complex terms that may confuse survey respondents. Example, instead of “What is your perception of our user interface?” a simpler version could be, “How easy is it to use our website?“.

4. Maintain survey logic to avoid confusion:

Organize questions in a logical sequence. Start with general questions to prepare respondents for upcoming questions. Warm up respondents with simple demographic survey questions: Example: What is your email address?
This can be followed by asking questions on the brand or current experience.

5. Run a pilot test to keep it error-free

Run a pilot test to identify bugs, typos or format errors. This also includes errors across operating systems while running interactive surveys. A seamless customer feedback questionnaire can significantly improve the final version.

6. Customize questions for respondents:

Tailor questions to suit the demographic, cultural, or professional background of the respondents. Customized questions resonate better with the audience and improve response rates.

7. Use visual aids:

Where appropriate, include images, charts, or scales ( emoji faces for satisfaction levels) to make the questionnaire more engaging and intuitive. Ensure that the font and its sizing is apt and easy to read across screens. Provide clear guidance on how to answer each section

Tips to Maximize Questionnaire Response Rates

• Consider survey length to maintain respondent engagement. Short surveys can be conducted in 3 to 5 questions. For long surveys, Aim for a completion time of 10-15 minutes. For short surveys, aim for a completion time of 3 to 5 minutes. 
• Offer apt survey incentives to participants. Keep the incentives relevant to the target audience. Incentives such as a free gift, membership requests, or free upgrades can encourage people to respond to surveys.
• Opt for multiple survey channels. Channels of WhatsApp, Facebook messenger, chatbots and dynamic emails. Diversifying survey channels can encourage participation rate from customers who already use those channels.  
• Nudge participants in case of any unanswered surveys. With Merren’s CRM integrations, you can create scheduled nudges to increase survey participation rate.    

Pros and Cons of Questionnaires for Research

Pros

• Fast, cost-effective data collection
  
• Responses are easy to compare and analyze
  
• Questions can be anonymous
  
• Research questionnaires have a flexible format. It runs swiftly across survey channels
  

Cons

• Self-administered or automated questionnaires can be misunderstood questions. This means skewed data
  
• Complex questionnaires can get low engagement if poorly designed
  
• No room for clarifying misunderstandings (unless interviewer-led)
• Certain formats can be interrogative. This can deter participants.
  

How to Run a Questionnaire? 

There are various offline and online methods to run a questionnaire for research. 

Offline channels: 

• In person administration: An interviewer can share questions in person either individually or in a group. The researcher will ask questions directly to the respondent. 
• Telephone survey: Computer Assisted Telephone Interviewing (CATI) is a popular telephone survey administration method. Here the caller will narrate the questions and seek answers over the phone. 
• Pen and paper surveys: Pen and paper surveys are popular in restaurants or cafes where the establishment seeks to collect responses on dining experiences.

Online channels:   

• Messenger surveys: WhatsApp and Facebook messenger are dynamic and interactive platforms that can collect a high survey response rate.  . 
• Dynamic emails: Dynamic emails collect survey responses from within the inbox. Here customers are not directed into an external link (to avoid friction points).
• Chatbots: Chatbots are AI-driven robust survey mediums popularly used across multiple industries. These chatbots can administer question surveys and collect responses at speed.  

How to Analyze Questionnaire Responses?

Step 1: Categorize your data

Begin by sorting your questionnaire responses into two distinct categories: Qualitative and Quantitative.

• Qualitative Data includes open-ended responses that offer insights into emotions, opinions, or experiences.
• Quantitative Data comprises close-ended responses with numerical or categorical values, such as ratings, percentages, or counts.

Step 2: Organize the responses

Start by filtering out incomplete or irrelevant responses—such as skipped questions or off-topic answers. Next, classify the remaining data into close-ended and open-ended questions.

For deeper organization, use techniques like cross-tabulation, which allows you to identify relationships and trends between variables. If you’re using a survey tool, this process can often be automated for efficiency.

Step 3: Analyze quantitative data first

Tackle the numbers before diving into the more nuanced qualitative data. Quantitative data often lays the groundwork, providing context for the qualitative insights.

• Descriptive Analysis: Begin by calculating key metrics such as mean, median, and mode to understand central tendencies. Add measures like standard deviation or variance to gauge data spread. Merren offers visual tools like bar graphs, histograms, or pie charts to make your findings more accessible.
• Inferential Analysis: If you’re exploring relationships or testing hypotheses, apply statistical techniques like T-tests, Chi-square tests, ANOVA, or regression analysis. These methods help uncover patterns or significant differences in your data.

Step 4: Analyze qualitative data

Qualitative data requires a deeper dive, often involving advanced text-analysis tools.

• Sentiment Analysis: Use tools to evaluate the tone of responses, such that you can gauge frustration or satisfaction metrics.
• Thematic Analysis: Identify recurring themes and patterns in open-ended responses.
• Keyword Analysis: Highlight frequently used terms to understand customer priorities or concerns.

Merren’s AI-powered analytics can simplify this process by categorizing and summarizing qualitative data quickly.

Step 5: Interpret and present your findings

Consolidate your quantitative and qualitative insights into actionable conclusions. Highlight key findings in a clear and structured report. Choosing the right analytics tool ensures your data not only informs but transforms your strategies.

• Visualization: Use charts, tables, and infographics with Merren CX to make your data engaging and easier to understand.
• Actionable Insights: Summarize what the data reveals and how it can drive decision-making.

Examples of Questionnaires in Research

To inspire your next project, here are three examples of questionnaires in action:

• Academic Research
  A psychology professor used a structured questionnaire to study stress levels among students. Questions like “How often do you feel overwhelmed? (1-5)” provided clear data, while open-ended questions like “What’s your biggest stressor?” added context.
• Market Research
  A startup launched a product feedback questionnaire with NPS and ranking questions. Results showed 80% of customers valued price over design, shaping their next product iteration.
• Social Research
  A nonprofit used an unstructured questionnaire to explore community needs post-pandemic. Responses like “We need more childcare options” guided their funding priorities.

Use Questionnaires to Power Smart Decisions with Merren

Questionnaires are simple yet powerful. But their effectiveness depends on how well they’re designed, distributed, and analyzed.

Don’t just collect data—collect insights.

With tools like Merren, you can:

• Create multichannel questionnaires (email, WhatsApp, in-app)
  
• Launch in minutes with AI survey builder
  
• Use AI to auto-analyze text responses
  
  

📌 Ready to launch your next research project?
👉 Try Merren Now – No coding, just insights.