Survey Research: Definition, Types & Methods | SurveyMonkey (2024)

What is survey research?

Types of survey research

Applications of survey research

What forms can research surveys take?

Why conduct research surveys?

Research survey design

• Usage: surveys are used to gather information about human behavior
• Systematic: survey research follows proven procedures to collect evidence
• Replicable: applying the same methods more than once should achieve similar results
• Types: surveys can be exploratory, descriptive, or casual used in both online and offline forms
• Data: survey research can generate both quantitative and qualitative data
• Impartial: sampling is randomized to avoid bias

• Contains probing questions: used to understand more about a topic qualitatively
• Uncovers new details: answers can uncover unknown issues or new solutions as you learn more about your topic
• Doesn’t generate measurable data: as noted with qualitative surveys, the data is not quantifiable
• Answers the “why”: unlike quantitative research methods seeks to answer why something happened or the motivation behind a behavior

Descriptive research is the most common and conclusive form of survey research due to its quantitative nature. Unlike exploratory research methods, descriptive research utilizes pre-planned, structured surveys with closed-ended questions. It’s also deductive, meaning that the survey structure and questions are determined beforehand based on existing theories or areas of inquiry. The data gathered is then used to test hypotheses or assumptions.

The goal of descriptive research is to quantify and categorize opinions, attitudes, or beliefs held by a particular population regarding a given subject. For example, a descriptive survey may use multiple choice questions with predefined response options. While not providing the depth of qualitative insights, these standardized questions yield data that can be statistically analyzed and inferred upon.

• Focuses on the “what” not “why”: unlike exploratory research, descriptive research seeks to define a target audience’s attitudes, opinions, and behaviors.
• Quantitative: resulting data is numerical and can be statistically analyzed to identify patterns, averages, and correlations for quantitative insights.
• Conclusive: utilizes quantitative, closed-ended questions that generate numerical data to draw statistically significant conclusions.
• Significant: measures the significance of results to determine patterns and trends.

Causal research is also quantitative, pre-planned, and structured like descriptive research. For this reason, it is also considered conclusive. However, causal research goes beyond observation to determine the cause and effect relationship between variables.

While descriptive research observes and quantifies phenomena, causal research actively manipulates variables through experimentation to test hypotheses about causal effects. For example, a causal survey might compare control and test groups to evaluate the impact of different interventions.
The objectives of causal research are two-fold:

1. To establish connection between variables through quantitative data analysis.
2. To determine whether a causal relationship exists by intentionally modifying variables and measuring results.

• Conclusive: research is structured in design, preplanning, and quantitative in nature, allowing researchers to make definitive statements about causal relationships.
• Scientific:the goal of identifying cause and effect relationships make causal research more scientific than exploratory or descriptive research.
• Controlled: control for confounding factors by holding all other variables constant to isolate the effects of the variable being tested.
• Ordered: to establish causation, the cause must be proven to precede the proposed effect.

• Exploratory research applications include case studies, field observations, focus groups, and interviews.
• Descriptive research applications include descriptive surveys, descriptive-normative surveys, descriptive analysis surveys, and correlative surveys.
• Causal research applications include product testing, advertising improvements, customer retention efforts, and community needs.

• Accurate results: Online surveys have a very low margin of error because they are extremely convenient for most people to complete.
• Human error is minimized:: When you’re ready to analyze the data, a survey platform can perform complex calculations for you.
• Respondents are anonymous : Online surveys are generally anonymous, meaning they are more comfortable to say exactly what they want without penalty.
• Large audiences are accessible: Online surveys allow you to reach a global audience. For example, with SurveyMonkey Audience, you can reach your target market with up to 5,000 complete responses.
• Flexibility: Online survey technology allows researchers to use skip logic based on a participant’s answer to a question. With this feature, the survey is tailored to each person as they proceed through the questions.
• Quickstart templates: SurveyMonkey offers many free, customizable survey templates to help you get your survey ready quickly—add branding such as logos, images, fonts, etc.

Face-to-face interviews can yield rich, detailed insights through direct conversation and observation, but they tend to be prohibitively expensive for large samples. Survey interviewers must be fully trained to obtain high-quality data that takes advantage of this format. For example, they must recognize and note body language cues, ask relevant follow-up questions, and probe for more information when necessary.

In addition, there is also the risk of multiple types of survey bias with in-person interviews—read more about them here.

Research surveys are valuable for gaining insights that inform decisions and strategy. For example, a restaurant owner may survey customers to improve service. A political campaign could poll constituents to sharpen messaging. Or a software company might seek feedback from users to guide product development.

Regardless of the end goals, there are four main reasons for conducting research surveys.

1. Surveys provide hard numbers: When you administer a survey that yields quantitative data, you can gain hard numbers to back up your decisions. Hard numbers are also useful when bringing research to stakeholders for decision-making—if you can prove that customers prefer one product feature over another through quantifiable data, it’s more powerful.
   
2. Surveys provide ongoing benchmarks: Data patterns that point to trends are incredibly powerful when identified in your research, as opposed to data about what your customers want. Consider the Net Promoter Score® (NPS), which gives you an idea of where your company loyalty stands. If you repeat the NPS quarterly and notice that the scores are declining, you can then take action to investigate and fix the problem.
   
3. Surveys can reach large audiences: Larger audiences are necessary for research validity and generalizations for a particular population in some cases. Online surveys created and administered with platforms like SurveyMonkey are much more convenient for large groups, as they are mobile responsive.
   
4. Survey anonymity promotes candid feedback: Online surveys allow participants to remain anonymous, encouraging open and honest opinions. Anonymity removes barriers, allowing people to provide more truthful, candid responses without fear of judgment.

• Develop research questions that relate to your goals. Remove any unnecessary or redundant questions that don't provide useful insights.
• Organize the survey logically, starting with easy and non-sensitive questions before moving to more complex or personal ones.
• Keep language simple, avoiding technical jargon or complicated phrasing that may confuse participants.
• Limit survey length and fatigue where possible to maintain participant engagement.
• Entice participation with incentives like discounts, points, or gift cards as a thank-you for responding.
• Test the survey before launch to refine questions and overall flow based on feedback.