Researching means exploring new ideas, answering questions and solving problems in a systematic manner. It is the fundamental way in which new discoveries are made and progress is achieved, whether it’s science, technology, medicine, society, law or any other field.
There are several different types of research, which can seem to be complex and difficult to understand. On top of that the categories may overlap depending on the basis of categorization. You can do a quantitative experiment that uses primary data sources to find a practical solution to a problem. Or you might do long-form observational field research.
This guide aims to simplify this complex classification of research types. Whether you're a student, scholar or curious learner, this breakdown will help you understand how research is categorised and how to choose the right type for your needs.
Here’s a quick reference chart for the broad categories of research based on the key factors:
Purpose
Methadology
Nature of Study
Time Frame
Reasoning Logic
Environment
Data Type
Data Source
Let’s dive in to take a detailed look at the research types to understand each of them better.
‘Purpose’ is the reason for conducting the research. It may be to further basic understanding of a subject or to solve a specific real-world problem.
Fundamental research (also known as basic research or pure research) is often the first thing that comes to mind when you think about academic research. This type of research aims to deepen the understanding of a topic and broaden the theoretical foundation.
E.g., Discovering the gravitational interaction between two subatomic particles furthers the understanding of physics and the world we live in. This is a basic research study that explores theoretical knowledge.
Applied research aims to solve a real-world problem. Here, the researcher uses existing knowledge to make a practical contribution to the field of study.
E.g., Inventing a new lightweight material that can withstand high stress without breaking for use in designing spacecraft. This is an applied research experiment focused on finding a practical solution.
‘Methodology’ refers to how the research is being conducted. It includes the approach used to collect, analyse and interpret the data.
Qualitative research is based on non-numerical data, gathered from people's experiences, understanding, opinions and observations. Interviews, focus groups, surveys with open ended questions are generally used to gather data in this type of research. It’s focused on the ‘how?’ and ‘why?’.
E.g., A company wants to find out about what image their brand is most associated with amongst their customers. They might conduct a group discussion with a panel of 5-6 regular customers sampled from their known customer pool.
Quantitative research is focused more on the ‘How many?’ and ‘How much?’. It is based on numerical data gathered from a larger sample of the population and statistical analysis of the same. Here you can mostly use surveys with close ended questions, reviews with rating systems, analysis of existing data sets and so on.
E.g., To determine if there is any correlation between family income level and malnutrition amongst children, you might want to do a quantitative study with data sets taken from public census figures and governmental healthcare data sets, and then use regression analysis or other statistical models.
Based on what the research aims to do the nature of study can vary. It can be describing, exploring, analyzing, or testing a relationship.
Descriptive research aims to describe a phenomenon - explaining ‘What’ is happening rather than ‘Why’ or ‘How’. It is often used to capture a snapshot of a population and understand what are the key characteristics of the research. It can be a preliminary step that enables further research.
E.g., Conducting a survey of a wildlife park over time to determine how the population of the wildlife has changed annually. Here focus is on the ‘how many’ and not on the ‘how’ or ‘why’ it increased or decreased.
Analytical research aims to understand the data and analyse it to conclude about the relationship between the variables in the study. Often the focus lies on the cause and effect of a phenomenon. This refers to the ‘Why’ and ‘How’.
E.g., To determine the effect of carbon emissions on the melting of ice caps in a mountain range, the researcher might try to find the relation between carbon emissions in the atmosphere and the ice cap height, analysing the underlying relationship and answering why it happened.
Exploratory research aims to explore a topic that has little previous knowledge and generate new ideas or insights. Often a qualitative method is used to get a fundamental understanding based on which further research can be done.
E.g., To explore the idea on how two AI systems interact with each other you might want to perform an exploratory research that gives a basic understanding of what the AI systems are doing while interacting with each other.
As the name suggests this includes experimentation by manipulating input variables and measuring outputs. It’s a scientific method used to determine cause-and-effect relationships.
E.g., Testing the effects of corrosive materials and regular wear & tear of a material to be used for building underwater ocean infrastructure. The material might be tested in a lab environment being exposed to conditions it will face in the real world and the results are then compared.
This type of research aims to explore the correlation between two or more variables, without changing the variables (in their natural state). It’s often statistical, observational and non-experimental.
E.g., Studying the effects of screen time on sleep quality amongst teenagers by taking a survey of a sample population.
Timeframe refers to when and for how long the research is conducted and the data was collected. It can be a snapshot in a moment of time, over a few days, months or even decades.
In cross sectional research data is collected at a single point of time, in the state the sample population is. This is aimed to understand the current status of a phenomenon.
E.g., A survey conducted in June 2025 to understand people’s attitude towards mobile banking and use of online means of transactions.
In a longitudinal research study the data is collected from the same subjects over a period of time to understand the trends and changes. It tracks patterns and is useful for developmental and behavioural studies.
E.g., Long term tracking of the career progression of a batch of students after graduating from MBA programmes of several universities. It could span over 10 years to form a pattern and gain understanding about what they have achieved post graduation.
The logic of reasoning is the path of thought or logic used to go from information to conclusion. It can either start from a theory or from an observation.
Deductive research starts from a theory or hypothesis which is tested through data collection and analysis via scientific method. It is often referred to as the ‘top-down’ approach. The process looks like this: Theory → Hypothesis → Observation → Confirmation.
E.g., Based on an existing theory that regular exercise improves memory, a researcher may test the hypothesis by comparing memory test results of people who exercise vs. those who don’t.
Inductive research starts with a specific observation based on which further theories and hypotheses are developed. It is often referred to as the ‘bottom-up' approach. The process looks like this: Observation → Pattern → Hypothesis → Theory.
E.g., Observing that students who sleep more tend to perform better in exams, then forming a general theory about sleep and academic performance based on the observation.
This refers to the setting or context in which the research is conducted. It can be in the field, in a lab or a simulation.
Field research is done in the real world, where external factors can affect the outcome of the study. It is much more practical and reflects what would happen in actuality. It often uses qualitative methodology.
E.g., Observation of the cultural practices and social dynamics of a tribe of people living in the Tibetan highlands.
In a laboratory the parameters are controlled precisely and the research is done following a systematic approach. It can be used for many different applications, is often quantitative and experimental in nature.
E.g., Testing the aerodynamics of a new wing design in an air tunnel to determine its effectiveness and other features.
Simulation uses models to replicate real-life scenarios in a lab, a controlled setting or a virtual space. It is very useful when real-life testing may prove to be dangerous, expensive or impractical.
E.g, Simulation testing the traffic congestion after building of a new intersection at the heart of the city.
Based on the kind of information research can be of two types, empirical (real-world data) and conceptual (abstract data).
Empirical research focuses on observable and measurable data. Here data can be collected through experiments, observations, surveys and so on.
E.g., Studying the customer satisfaction from the review system on the app based on reviews collected from thousands of users.
Conceptual research focuses on theoretical concepts, frameworks and models rather than direct observation data. It is abstract, though-driven and used to provide a new perspective while exploring existing data.
E.g., Developing a new theory on leadership styles by analyzing existing models and philosophical texts.
Data sources can be of two types, primary or secondary.
Here the research uses data collection methods such as surveys, experiments, interviews, field observations, etc.
E.g., Survey of a group of students in a university to find out which university services they use most in their day to day life uses primary data collected from the students.
Here the data is taken from another source such as government reports, academic journals, online databases, newspaper articles, etc.
E.g., The literature review of a book written by a physicist and discussing how his theories hold up based on modern data and understanding uses secondary data.
Research can be of different types based on the factors discussed above. There is no one-size-fits-all. The one that you choose will depend on what your objectives are, what resources you have and how you want to approach it.
In this guide we have explored the different types of research. Understanding these categories not only helps in academic or professional settings, but also makes your research more focused, credible and impactful.