Understanding Surveys: What They Are, Survey Types, How to Conduct Them, and the Best Survey Tools

Surveys are a cornerstone of data collection in various industries, from marketing and education to healthcare and social sciences. They offer a structured way to gather insights, measure opinions, and inform decision-making processes. In this article, we’ll explore all the fundamentals of a survey — what surveys are, their different types, how to conduct them effectively, how to write questions, which survey tools to use and how to use the results.

What is the Definition of a Survey?

A survey is a research method used to collect information from a specific group of people. It involves asking respondents a series of questions to gain insights into their opinions, behaviors, experiences, or preferences. Surveys can be conducted online, offline, or through a combination of methods, depending on the target audience and research goals.

What is the Difference between a Survey and a Questionnaire?

Survey is a broader process that involves collecting, analyzing, and interpreting data from respondents. It often includes a questionnaire as its primary tool for gathering information but also encompasses designing the study, choosing a sample, administering the questions, and analysing the results. Surveys aim to draw insights, make decisions, or identify trends.
Questionnaire is a specific tool or instrument—a set of structured questions designed to gather information from respondents. It is just one part of a survey and can be used independently without a broader research process, for example, to collect basic feedback or opinions.

In short: a questionnaire is the "what" (a set of questions), and a survey is the "how" (the process of gathering and analysing data).

Types of Surveys and Research: Understanding Methods and Data

Understanding the basics of research, surveys, methods and data

Before jumping into the best practices in survey design, let's first figure out what different survey formats are, learn the difference between types of research they support, and the distinction between qualitative and quantitative data. The knowledge of these survey basics will help make informed decisions when designing a survey.

Types of Surveys

Surveys can be categorised based on their purpose, format, or delivery method. Here are the most common types

By Purpose:

Market research surveys: Understand customer preferences, buying habits, and satisfaction levels.
Employee satisfaction surveys: Measure workplace morale, engagement, and productivity.
Customer feedback surveys: Assess customer satisfaction and identify areas for improvement.
Academic surveys: Gather data for research purposes in education or social sciences.

By Format:

Open-ended surveys: Allow respondents to provide detailed, qualitative answers.
Close-ended surveys: Offer predefined answer choices, such as multiple-choice or rating scales.
Mixed surveys: Combine open and close-ended questions for comprehensive data.

By Delivery Method:

Online surveys: Delivered via email, social media, or survey platforms.
Telephone surveys: Conducted over the phone for real-time responses.
Face-to-face surveys: Allow for personal interaction, often used in focus groups.
Paper-based surveys: Traditional method using physical questionnaires.

Types of Research in Surveys

Before diving into survey creation, it’s essential to understand the type of research you’re conducting. Why? Because the purpose of your research determines the kind of questions you should ask, the structure of your survey, and the data you’ll collect. A well-designed survey tailored to your research type ensures that the insights gathered are relevant, actionable, and aligned with your goals.

1. Exploratory Research

This type of research is used to investigate an issue that is not well understood. Exploratory surveys focus on gathering preliminary insights or uncovering patterns, without seeking definitive answers.

Example: a startup may survey potential users to understand their needs before developing a product.
Data type: typically qualitative, using open-ended questions to encourage detailed responses.

2. Descriptive Research

Descriptive research aims to systematically describe characteristics of a population or phenomenon. It answers "what" questions but doesn’t establish cause-and-effect relationships.

Example: a company may survey customers to find out their preferred product features.
Data type: can involve both qualitative and quantitative data, with structured questions like multiple-choice or Likert scales to quantify responses.

3. Causal Research

Causal research seeks to identify cause-and-effect relationships. Surveys in this context are used to test hypotheses about the impact of one variable on another.

Example: a business might survey to test whether offering discounts leads to increased customer loyalty.
Data type: mostly quantitative, focusing on measurable data to confirm or refute hypotheses.

Qualitative vs Quantitative Data in Surveys

Surveys can collect two main types of data, each serving different research needs:

Qualitative Data

Purpose: captures non-numerical insights, such as emotions, opinions, or motivations.
How it's collected: through open-ended questions like “What challenges do you face with our product?”
Use cases: ideal for exploratory research, understanding customer sentiments, or generating ideas.

Quantitative Data

Purpose: provides numerical data that can be analyzed statistically.
How it's collected: through closed-ended questions, such as multiple-choice or scaled questions (“Rate your satisfaction on a scale of 1 to 10”).
Use cases: used for descriptive or causal research, trend analysis, and benchmarking.

Choosing the Right Approach

Many surveys use a mix of qualitative and quantitative methods, often starting with qualitative insights to guide the development of more structured, quantitative follow-ups. For instance, qualitative questions in exploratory research can help form hypotheses, which are then tested through quantitative causal research.

How to Conduct a Survey?

Creating and executing a successful survey involves careful planning and execution. Below we present a brief overview of how to run a survey, from getting started to analysing the results.

Step 1: Define Your Objective

Determine the purpose of your survey. What do you want to learn? Clear goals help guide the questions and audience selection.

Step 2: Identify Your Target Audience

Specify who will take the survey. When choosing demographics, consider factors such as age, location, profession, or interests to ensure relevance. Since the target audience largely depends on the use case, relying on basic factors may often not suffice. To achieve the best results, refine your focus and narrow down to identify the most relevant demographic.

Step 3: Design the Questionnaire

Keep questions concise and clear.
Use a mix of question types, such as multiple-choice, Likert scales, and open-ended questions.
Avoid leading or biased questions to maintain objectivity.

Step 4: Choose a Delivery Method

Select the most appropriate channel for your audience, such as email campaigns, pop-up on your website, or social media.

Step 5: Test Your Survey

Run a pilot test with a small group, for example within your team, to identify any confusing or ambiguous questions and refine them before launch.

Step 6: Distribute and Collect Data

Share the survey using your chosen method and monitor the responses to ensure a good participation rate.

Step 7: Analyse and Act on the Results

Use analytics tools or manual methods to interpret the data. Translate findings into actionable insights to achieve your objectives. Often survey software offers decent analytics capabilities, but you can also export responses to Excel, Google Sheets and other third-party tools to further format your data.

How to Write Effective Survey Questions?

Learning to write effective survey questions

The first step in creating survey questions is understanding that there are multiple question types.

Closed-Ended Questions
- Yes/No
- Multiple Choice
- Rating Scale (Likert Scale)
- Dropdown
Open-Ended Questions
Dichotomous Questions (Two Options)
Rank Order Questions
Contingency Questions (Follow-up Based on Previous Answer)

To write effective survey questions, define your goal clearly, as it must align with every question you ask. Use simple, clear language, avoiding jargon or complex phrasing. Focus on asking one thing at a time and avoid leading or biased wording. Provide balanced options, such as equal positive and negative responses, and include an "Other" option when needed. Keep questions short, relevant, and avoid absolutes like "always" or "never." Don't forget to incorporate different question types. You can find an example for each question type in the section below.

If you're struggling to craft the right questions or want to avoid unintentional bias, consider using AI for help. In our deep dive into using ChatGPT for question creation, we identified three key steps to make prompts as precise as possible and broke down the components of an effective prompt into three main layers. Read more about crafting effective prompts for good survey questions here.

Good Survey Questions Examples

1. Closed-Ended Questions

Yes/No Questions:
Example: "Do you prefer using web forms over paper forms?"

Multiple Choice:
Example: "Which of the following form builder features do you use the most? (Select one)"

2. Rating Scale (Likert Scale):‍

‍Example: "How satisfied are you with the current features of Our Product? (1 = Very Dissatisfied, 5 = Very Satisfied)"

3. Open-Ended Questions (Descriptive response)

‍‍‍Example: "What features would you like to see in the next update of Our Product?"

4.Dichotomous Questions (Two options)

‍Example: "Would you recommend Our Product to a friend? (Yes/No)"

5. Rank Order Questions

‍Example: "Please rank the following form builder features in order of importance to you, with 1 being the most important."

Working with the Results

Analysing quantitative data results from a survey

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Once your survey is complete, the real work begins—analysing and acting on the data. Here’s how to approach this crucial stage:

Organise the Data

Collate responses in a structured format. Tools like Excel or specialised survey platforms can help streamline data organisation.

Analyse the Results

Quantitative Analysis

Use statistical methods to identify trends, averages, and significant correlations.

Use spreadsheets: tools like Microsoft Excel or Google Sheets are great for organizing data, calculating averages, or creating basic charts.
Leverage statistical tools: use software like SPSS, R, or Python for advanced statistical analysis, such as correlation or regression.
Visualise data: platforms like Tableau or Power BI make it easier to create graphs, heatmaps, and dashboards to identify trends.

Qualitative Analysis

Look for recurring themes, sentiments, and insights from open-ended responses.

Coding responses: categorise open-ended responses into themes using tools like NVivo or manual coding in spreadsheets.
Word cloud generators: tools like WordArt or MonkeyLearn help visualise key themes from text data.
Sentiment analysis: use tools like IBM Watson or Google Cloud Natural Language for identifying tone and sentiment in qualitative responses.

Visualise the Data

Create charts, graphs, and infographics to present findings clearly. Visual representation helps stakeholders understand the insights at a glance.

Draw Conclusions and Take Actions

Link the results back to your objectives. Identify actionable takeaways that address the problem or question you set out to solve.

Implement strategies based on the insights gained. Whether improving a product, targeting a new audience, or refining a process, ensure the results drive meaningful change.

Best Online Survey Tools

Survey Best Practices

Keep it short: respect respondents’ time by limiting the number of questions and keeping them relevant.
Use simple language: avoid jargon or complex terminology, and make questions easy to understand.
Ask one question at a time: prevent confusion by ensuring each question addresses only one topic.
Provide balanced answer options: include a full range of responses, such as both positive and negative choices, and a neutral option if necessary.
Avoid leading or biased questions: keep questions neutral to avoid influencing the answers.
Use skip logic: direct respondents to the most relevant questions based on their answers.
Ensure mobile compatibility: make sure your survey is responsive and is easy to complete on mobile devices.
Randomise answer choices: minimise bias by randomising the order of answer options in multiple-choice questions.
Offer incentives: encourage participation by offering rewards or incentives, when appropriate.
Follow up: if applicable, thank respondents for their time and share how their feedback will be used.

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