Quantitative research is a research methodology used by researchers to test theories and hypotheses about the attitudes and behaviors of their customers on the basis of numerical and statistical evidence. Researchers use surveys to question a large number of people or customers to obtain measurable and bias-free data in an indirect manner.

Quantitative research characteristics
In technical terms, quantitative research is mainly concerned with discovering facts about social phenomena while assuming a fixed and measurable reality.

Offering numbers and stats-based insights, this research methodology is a crucial part of primary research and helps understand how well an organizational decision is going to work out.

For example, suppose your qualitative analysis shows that your customers are looking for social media-based customer support. In that case, quantitative analysis will help you see how many of your customers are looking for this support. If 10% of your customers are looking for such a service, you might or might not consider offering this feature. But, if 40% of your regular customers are seeking support via social media, then it is something you just cannot overlook.

Next, we discuss the characteristics of a quantitative research methodology to help you understand it in a better manner.

Characteristics of Quantitative Research
Quantitative research clarifies the fuzziness of research data from qualitative research analysis. With numerical insights, you can formulate a better and more profitable business decision.

Hence, quantitative research is more readily contestable, sharpens intelligent discussion, helps you see the rival hypotheses, and dynamically contributes to the research process.

Let us have a quick look at some of its characteristics.

Measurable Variables
The data collection methods in quantitative research are structured and contain items requiring measurable variables, such as age, number of family members, salary range, highest education, etc.

These structured data collection methods comprise polls, surveys, questionnaires, etc. All of them have measurable approaches.

For example, they would have survey questions like the ones shown in the following image:

Source
As you can see, all the variables are measurable.

Ensuring that all the variables are measurable calls for in-depth and less erroneous data that can offer reliable, actionable insights.

Sample Size
No matter what data analysis methods for quantitative research are being used, the sample size is kept such that it represents the target market. As the main aim of the research methodology is to get numerical insights, the sample size is fairly large. Depending on the survey objective and scope, it might span hundreds of thousands of people.

There are different types of sampling methods in quantitative research that we will discuss in the next sections.

However, it is important to note that the sampling methods are chosen on the basis of research objectives.

Normal Population Distribution
To maintain the data reliability of a quantitative research methodology, we assume that the population distribution curve is normal. This type of population distribution curve is preferred over a non-normal distribution as the sample size is large and the characteristics of the sample vary with its size.

This requires adhering to the random sampling principle to avoid the researcher’s bias in result interpretation. Any bias can ruin the fairness of the entire process and defeats the purpose of research.

Well-Structured Data Representation
The data analysis methods in quantitative research produce highly structured data results and are represented in well-formed data assessment tools. Some common examples include tables, figures, graphs, etc., that integrate and combine large blocks of data.

So, you can discover hidden data trends, relationships, and differences among various measurable variables. This helps the researchers understand the survey data and formulate actionable insights for business decision-making.

Can Produce Predictive Outcomes
Quantitative analysis of data can also be used for estimations and prediction outcomes. You can construct if-then scenarios and analyze the data for identification of any upcoming trends or events.

However, this requires advanced analytics and involves complex mathematical computations. So, it is mostly done via quantitative research tools that come with advanced analytics capabilities.

Now that we have had a detailed overview of the quantitative methodology, let us explore its various types.

Types of Quantitative Research Methods
There can be many ways to collect data via quantitative research methods that are chosen as per the research objective and scope. These methods allow you to build your own observations regarding any hypotheses – unknown, entirely new, or unexplained.

You can hypothesize a proof and build a prediction of outcomes supporting the same. You can also create a detailed stepwise plan for data collection, analysis, and testing.

Below, we explore quantitative research methods and discuss some examples to enhance your understanding of them.

1. Survey Research
Surveys are the easiest, most common, and one of the most sought-after quantitative research techniques. The main aim of a survey is to widely gather and describe the characteristics of a target population or customers. Surveys are the foremost quantitative method preferred by both small and large organizations.

They help them understand their customers, products, and other brand offerings in a proper manner.

Surveys are of two types:

Cross-sectional Survey: This type of survey is conducted specifically on a target population for a given amount of time, such as retail store surveys, health care trade, etc.
Longitudinal Surveys: This type of survey is conducted at different time durations, such as applied sciences and medicine surveys.
Some common survey-based quantitative research examples include:

How frequently do you answer your calls while driving?
How many texts do you send per day on average?
How often do you respond to your texts while you are at work?
2. Descriptive Research
This research methodology aims to explain the current status of an identified and measurable variable.

So, via descriptive research, you can explain and interpret many things, such as:

Current status of customer satisfaction
Settings
Conditions
Events
In this methodology, it is not mandatory for the researcher to have a hypothesis right from the start. However, once the data is collected, they might form a hypothesis as well to give a proper direction to the research.

Here, the data is assorted systematically, and researchers have to choose the units and measurement of every variable in a careful manner.

Some common examples of descriptive research include:

Elementary teachers using math manipulatives
Global warming description for Scientists
Description of physical activities organized in schools, etc.
3. Correlational Research
This research method is used when you have to establish a relation between two close business entities and figure out how one of them impacts the other. You need at least two separate samples or population groups for correlational research.

This type of research helps you discover trends and patterns in data, but it does not observe the different patterns. As no variables are manipulated during the process, this methodology is often considered a type of descriptive research.

Some common examples of Correlational research are:

Relationships between the types of activities done in a particular class and the achievement of students resulting from them
Relationship between diet and anxiety disorders
4. Experimental Research
This is one of the unique types of quantitative research methods as it is based on one or more theories. It is also termed true experimentation and can use the scientific method for establishing the cause-effect relation over a group of research variables.

You can use multiple theories for conducting this research, and its different components are:

A comparison group of randomly selected customers or respondents as experimental and control groups
An independent variable called experimental variable, which can be applied over the experimental groups
A dependent variable, also called the effect or post-test variable that you can measure identically for all the groups
Some common examples of experimental research include:

Testing the long-term and short-term effects of a new drug
Checking who uses social media more for maintaining relationships – men or women
5. Questionnaires
You can use quantitative research questionnaires to collect data for market research as well as for anthropological and social research.

A questionnaire has a list of questions or items that you can use to gather research data from respondents. This data can be about their experiences, attitudes, or opinions.

The questionnaires are of two types:

Self-administered: They are shared online, easy to administer for large and small groups, and cost-efficient. However, they can also lead to irrelevant data collection as you might make a mistake while setting questions or while aiming at a particular customer segment.
Researcher-administered: They are planned and created by proper researchers and ensure better results. They help you ensure that the respondents are representative of your target audience and there are no unclear or ambiguous questions in the list.