What is Applied Research? Definition, Types, Examples

Appinio Research · 10.01.2024 · 36min read

What is Applied Research Definition Types Examples

Ever wondered how groundbreaking solutions to real-world challenges are developed, or how innovations come to life? Applied research holds the key. In this guide, we will delve deep into the world of applied research, uncovering its principles, methodologies, and real-world impact. 

From harnessing cutting-edge technology to address healthcare crises to revolutionizing industries through data-driven insights, we'll explore the diverse domains where applied research thrives.


What is Applied Research?

Applied research is a systematic and organized inquiry aimed at solving specific real-world problems or improving existing practices, products, or services. Unlike basic research, which focuses on expanding general knowledge, applied research is all about using existing knowledge to address practical issues.


The primary purpose of applied research is to generate actionable insights and solutions that have a direct impact on practical situations. It seeks to bridge the gap between theory and practice by taking existing knowledge and applying it in real-world contexts. Applied research is driven by the need to address specific challenges, make informed decisions, and drive innovation in various domains.

Importance of Applied Research

Applied research holds immense significance across various fields and industries. Here's a list of reasons why applied research is crucial:

  • Problem Solving: Applied research provides effective solutions to real-world problems, improving processes, products, and services.
  • Innovation: It drives innovation by identifying opportunities for enhancement and developing practical solutions.
  • Evidence-Based Decision-Making: Policymakers and decision-makers rely on applied research findings to make informed choices and shape effective policies.
  • Competitive Advantage: In business, applied research can lead to improved products, increased efficiency, and a competitive edge in the market.
  • Social Impact: Applied research contributes to solving societal issues, from healthcare improvements to environmental sustainability.
  • Technological Advancement: In technology and engineering, it fuels advancements by applying scientific knowledge to practical applications.

Applied Research vs. Basic Research

Applied research differs from basic research in several key ways:

  • Objectives: Applied research aims to address specific practical problems or improve existing processes, while basic research seeks to expand general knowledge.
  • Focus: Applied research focuses on solving real-world challenges, whereas basic research explores fundamental principles and concepts.
  • Applicability: Applied research findings are directly applicable to practical situations, while basic research often lacks immediate practical applications.
  • Immediate Impact: Applied research has a more immediate impact on solving problems and improving practices, whereas basic research may have longer-term or indirect effects on knowledge and innovation.
  • Research Questions: Applied research formulates research questions related to practical issues, while basic research poses questions to explore theoretical or fundamental concepts.

Understanding these distinctions is essential for researchers, policymakers, and stakeholders in various fields, as it guides the choice of research approach and the expected outcomes of a research endeavor.

Types of Applied Research

Applied research encompasses various types, each tailored to specific objectives and domains. Understanding these types is essential for choosing the right approach to address real-world problems effectively. Here are some common types of applied research, each with its distinct focus and methodologies.

Evaluation Research

Purpose: Evaluation research assesses the effectiveness, efficiency, and impact of programs, interventions, or policies. It aims to determine whether these initiatives meet their intended goals and objectives.


Methodology: Researchers employ a range of quantitative and qualitative methods, including surveys, interviews, observations, and data analysis, to evaluate the outcomes and outcomes of programs or interventions.


Example: Evaluating the impact of a public health campaign aimed at reducing smoking rates by analyzing pre- and post-campaign survey data on smoking habits and attitudes.

Action Research

Purpose: Action research focuses on solving practical problems within a specific organizational or community context. It involves collaboration between researchers and practitioners to implement and assess solutions.


Methodology: Action research is iterative and participatory, with researchers and stakeholders working together to identify problems, develop interventions, and assess their effectiveness. It often involves cycles of planning, action, reflection, and adjustment.


Example: Teachers collaborating with researchers to improve classroom teaching methods and student outcomes by implementing and refining innovative teaching strategies.

Case Study Research

Purpose: Case study research investigates a particular individual, organization, or situation in-depth to gain a comprehensive understanding of a specific phenomenon or issue.


Methodology: Researchers collect and analyze a wealth of data, which may include interviews, documents, observations, and archival records. The goal is to provide a detailed and context-rich description of the case.


Example: A detailed examination of a successful startup company's growth strategies and challenges, offering insights into factors contributing to its success.

Applied Experimental Research

Purpose: Applied experimental research seeks to establish causal relationships between variables by manipulating one or more factors and observing their impact on outcomes. It helps determine cause-and-effect relationships in real-world settings.


Methodology: Researchers conduct controlled experiments, similar to those in basic research, but within practical contexts. They manipulate variables and use statistical analysis to assess their effects on specific outcomes.


Example: Testing the impact of different website designs on user engagement and conversion rates by randomly assigning visitors to various design versions and measuring their interactions.

Survey Research

Purpose: Survey research involves collecting data from a sample of individuals or organizations to understand their opinions, attitudes, behaviors, or characteristics. It is commonly used to gather quantitative data on specific topics.


Methodology: Researchers design surveys with carefully crafted questions and administer them to a representative sample of the target population. Statistical analysis is used to draw conclusions based on survey responses.


Example: Conducting a national survey to assess public sentiment and preferences on environmental conservation initiatives and policies.


These types of applied research provide a framework for approaching real-world challenges systematically. Researchers can choose the most appropriate type based on their research goals, objectives, and the nature of the problem or phenomenon they seek to address. By selecting the right approach, applied researchers can generate valuable insights and practical solutions in various fields and disciplines.

How to Prepare for Applied Research?

In the preparatory phase of your applied research journey, you'll lay the groundwork for a successful study. This phase involves a series of crucial steps that will shape the direction and ethics of your research project.

Identifying Research Questions

One of the key starting points for any applied research endeavor is identifying the right research questions. Your research questions should be clear, specific, and directly related to the problem or issue you aim to address.

  • Engage with Stakeholders: Reach out to individuals or groups who are affected by or have an interest in the issue you're researching. Their perspectives can help you formulate relevant questions.
  • Consider Feasibility: Ensure that your research questions are feasible within your available resources, including time, budget, and access to data or participants.
  • Prioritize Impact: Focus on questions that have the potential to create meaningful change or provide valuable insights in your chosen field.

Formulating Hypotheses

Hypotheses serve as the guiding stars of your research, providing a clear direction for your investigation. Formulating hypotheses is a critical step that sets the stage for testing and validating your ideas.

  • Testable Predictions: Your hypotheses should be testable and capable of being proven or disproven through empirical research.
  • Informed by Literature: Base your hypotheses on existing knowledge and insights gained from the literature review. They should build upon what is already known and aim to expand that knowledge.
  • Clarity and Precision: Write your hypotheses in a clear and precise manner, specifying the expected relationship or outcome you intend to explore.

Literature Review

Conducting a thorough literature review is like embarking on a treasure hunt through existing knowledge in your field. It's a comprehensive exploration of what other researchers have already discovered and what gaps in knowledge still exist.

  • Search Strategies: Utilize academic databases, journals, books, and credible online sources to search for relevant literature.
  • Analyze Existing Research: Examine the findings, methodologies, and conclusions of previous studies related to your research topic.
  • Identify Research Gaps: Look for areas where current knowledge is insufficient or contradictory. These gaps will be the foundation for your own research.

Data Collection Methods

Selecting the proper data collection methods is crucial to gather the information needed to address your research questions. The choice of methods will depend on the nature of your research and the type of data you require.

  • Quantitative vs. Qualitative: Decide whether you will collect numerical data (quantitative) or focus on descriptive insights and narratives (qualitative).
  • Survey Design: If surveys are part of your data collection plan, carefully design questions that are clear, unbiased, and aligned with your research goals.
  • Sampling Strategies: Determine how you will select participants or data points to ensure representativeness and reliability.

Ethical Considerations

Ethical considerations are at the heart of responsible research. Ensuring that your study is conducted ethically and with integrity is paramount.

  • Informed Consent: Obtain informed consent from participants, ensuring they understand the purpose of the research, potential risks, and their right to withdraw at any time.
  • Confidentiality: Safeguard participants' personal information and ensure their anonymity when reporting findings.
  • Minimizing Harm: Take measures to mitigate any physical or emotional harm that participants may experience during the research process.
  • Ethical Reporting: Accurately represent your research findings, avoiding manipulation or selective reporting that may mislead readers or stakeholders.

By diligently addressing these aspects of research preparation, you are building a solid foundation for your applied research project, setting the stage for effective data collection and meaningful analysis in the subsequent phases of your study.

How to Design Your Research Study?

When it comes to applied research, the design of your study is paramount. It shapes the entire research process, from data collection to analysis and interpretation. In this section, we will explore the various elements that make up the foundation of your research design.

Research Design Types

Your choice of research design is like selecting the blueprint for your research project. Different research design types offer unique advantages and are suited for different research questions. Here are some common research design types:

  • Experimental Design: In this design, researchers manipulate one or more variables to observe their impact on outcomes. It allows for causal inference but may not always be feasible in applied research due to ethical or practical constraints.
  • Descriptive Design: This design aims to describe a phenomenon or population without manipulating variables. It is often used when researchers want to provide a snapshot of a situation or gain insights into a specific context.
  • Correlational Design: In this design, researchers examine relationships between variables without manipulating them. It helps identify associations but does not establish causation.
  • Longitudinal Design: Longitudinal studies involve collecting data from the same subjects over an extended period. They are valuable for tracking changes or developments over time.
  • Cross-Sectional Design: This design involves data collection from a diverse group of subjects at a single point in time. It's helpful in studying differences or variations among groups.

Sampling Methods

Sampling methods determine who or what will be included in your study. The choice of sampling method has a significant impact on the generalizability of your findings. Here are some standard sampling methods:

  • Random Sampling: This method involves selecting participants or data points entirely at random from the population. It ensures every element has an equal chance of being included, which enhances representativeness.
  • Stratified Sampling: In stratified sampling, the population is divided into subgroups or strata, and then random samples are drawn from each stratum. This method ensures that each subgroup is adequately represented.
  • Convenience Sampling: Researchers choose subjects or data points that are readily available and accessible. While convenient, this method may lead to sampling bias as it may not accurately represent the entire population.
  • Purposive Sampling: In purposive sampling, researchers deliberately select specific individuals or groups based on their expertise, experience, or relevance to the research topic. It is often used when seeking specialized knowledge.

Data Collection Tools

Selecting the right data collection tools is essential to gather accurate and relevant information. Your choice of tools will depend on the research design and objectives. Standard data collection tools include:

  • Questionnaires and Surveys: These structured instruments use standardized questions to gather data from participants. They are suitable for collecting large amounts of quantitative data.
  • Interviews: Interviews can be structured, semi-structured, or unstructured. They provide an opportunity to gather in-depth, qualitative insights from participants.
  • Observation: Direct observation involves systematically watching and recording behaviors or events. It's valuable for studying behaviors or phenomena in their natural context.
  • Secondary Data: Researchers can also utilize existing data sources, such as government reports, databases, or historical records, for their research.

Variables and Measurement

Defining variables and choosing appropriate measurement methods is crucial for ensuring the reliability and validity of your research. Variables are characteristics, phenomena, or factors that can change or vary in your study. They can be categorized into:

  • Independent Variables: These are the variables you manipulate or control in your study to observe their effects on other variables.
  • Dependent Variables: These are the variables you measure to assess the impact of the independent variables.

Choosing the right measurement techniques, scales, or instruments is essential to accurately quantify variables and collect valid data. It's crucial to establish clear operational definitions for each variable to ensure consistency in measurement.

Data Analysis Techniques

Once you have collected your data, the next step is to analyze it effectively. Data analysis involves:

  • Data Cleaning: Removing any errors, inconsistencies, or outliers from your dataset to ensure data quality.
  • Statistical Analysis: Depending on your research design and data type, you may use various statistical techniques such as regression analysis, t-tests, ANOVA, or chi-square tests.
  • Qualitative Analysis: For qualitative data, techniques like thematic analysis, content analysis, or discourse analysis help uncover patterns and themes.
  • Data Visualization: Using graphs, charts, and visual representations to present your data effectively.

Chi-Square Calculator:

t-Test Calculator:

Selecting the appropriate analysis techniques depends on your research questions, data type, and objectives. Proper data analysis is crucial for drawing meaningful conclusions and insights from your research.


With a solid understanding of research design, sampling methods, data collection tools, variables, and measurement, you are well-equipped to embark on your applied research journey. These elements lay the groundwork for collecting valuable data and conducting meaningful analyses in the subsequent phases of your study.

How to Conduct Applied Research?

Now that you've prepared and designed your research study, it's time to delve into the practical aspects of conducting applied research. This phase involves the execution of your research plan, from collecting data to drawing meaningful conclusions. Let's explore the critical components in this stage.

Data Collection Phase

The data collection phase is where your research plan comes to life. It's a crucial step that requires precision and attention to detail to ensure the quality and reliability of your data.

  1. Implement Data Collection Methods: Execute the data collection methods you've chosen, whether they involve surveys, interviews, observations, or the analysis of existing datasets.
  2. Maintain Consistency: Ensure that data collection is carried out consistently according to your research design and protocols. Minimize any variations or deviations that may introduce bias.
  3. Document the Process: Keep thorough records of the data collection process. Note any challenges, unexpected occurrences, or deviations from your original plan. Documentation is essential for transparency and replication.
  4. Quality Assurance: Continuously monitor the quality of the data you collect. Check for errors, missing information, or outliers. Implement data validation and cleaning procedures to address any issues promptly.
  5. Participant Engagement: If your research involves human participants, maintain open and respectful communication with them. Address any questions or concerns and ensure participants' comfort and willingness to participate.

Data Analysis Phase

Once you've collected your data, it's time to make sense of the information you've gathered. The data analysis phase involves transforming raw data into meaningful insights and patterns.

  1. Data Preparation: Start by organizing and cleaning your data. This includes dealing with missing values, outliers, and ensuring data consistency.
  2. Selecting Analysis Methods: Depending on your research design and data type, choose the appropriate statistical or qualitative analysis methods. Common techniques include regression analysis, content analysis, or thematic coding.
  3. Conducting Analysis: Perform the chosen analysis systematically and according to established protocols. Ensure that your analysis is reproducible by documenting every step.
  4. Interpreting Results: Interpretation involves making sense of your findings in the context of your research questions and hypotheses. Consider the statistical significance of the results and any practical implications they may have.
  5. Visualization: Create visual representations of your data, such as graphs, charts, or tables, to convey your findings effectively. Visualizations make complex data more accessible to a broader audience.

Interpretation of Results

Interpreting research results is a critical step that bridges the gap between data analysis and drawing conclusions. This process involves making sense of the patterns and insights that emerge from your analysis.

  1. Relate to Hypotheses: Determine whether your results support or refute your hypotheses. Be prepared to explain any unexpected findings.
  2. Contextualize Findings: Consider the broader context in which your research takes place. How do your results fit into the larger body of knowledge in your field?
  3. Identify Patterns: Highlight significant trends, correlations, or relationships you've uncovered. Discuss their practical implications and relevance.
  4. Acknowledge Limitations: Be transparent about any limitations in your study that may affect the interpretation of results. This includes sample size, data quality, and potential biases.

Drawing Conclusions

Drawing conclusions is the ultimate goal of your research. It involves synthesizing your findings and answering the research questions you initially posed.

  1. Answer Research Questions: Explicitly address the research questions you formulated at the beginning of your study. State whether your findings confirm or challenge your initial hypotheses.
  2. Highlight Insights: Emphasize the key insights and contributions of your research. Discuss the practical implications of your findings and their relevance to the field.
  3. Recommend Actions: Based on your conclusions, suggest practical steps, recommendations, or future research directions. How can your research contribute to addressing the problem or challenge you investigated?
  4. Consider Implications: Reflect on the broader implications of your research for stakeholders, policymakers, or practitioners in your field.

Common Pitfalls to Avoid

During the data collection, analysis, interpretation, and conclusion-drawing phases, it's essential to be aware of common pitfalls that can affect the quality and integrity of your research.

  1. Sampling Bias: Ensure that your sample is representative of the population you intend to study. Address any bias that may have been introduced during data collection.
  2. Data Manipulation: Avoid manipulating or selectively reporting data to fit preconceived notions. Maintain transparency in your analysis and reporting.
  3. Overinterpretation: Be cautious of drawing overly broad conclusions based on limited data. Acknowledge the limitations of your study.
  4. Ignoring Ethical Considerations: Continuously uphold ethical standards in your research, from data collection to reporting. Protect participants' rights and privacy.
  5. Lack of Validation: Ensure that the methods and tools you use for data collection and analysis are valid and reliable. Validation helps establish the credibility of your findings.

By navigating the data collection, analysis, interpretation, and conclusion-drawing phases with care and attention to detail, you'll be well-prepared to confidently share your research findings and contribute to advancing knowledge in your field.

How to Report Applied Research Results?

Now that you've conducted your applied research and drawn meaningful conclusions, it's time to share your insights with the world. Effective reporting and communication are crucial to ensure that your research has a real impact and contributes to the broader knowledge base.

Writing Research Reports

Writing a comprehensive research report is the cornerstone of communicating your findings. It provides a detailed account of your research process, results, and conclusions. Here's what you need to consider:

Structure of a Research Report

  1. Title: Create a concise, informative title that reflects the essence of your research.
  2. Abstract: Summarize your research in a clear and concise manner, highlighting key objectives, methods, results, and conclusions.
  3. Introduction: Provide an overview of your research topic, objectives, significance, and research questions.
  4. Literature Review: Summarize relevant literature and identify gaps in existing knowledge that your research addresses.
  5. Methodology: Describe your research design, sampling methods, data collection tools, and data analysis techniques.
  6. Results: Present your findings using tables, charts, and narratives. Be transparent and objective in reporting your results.
  7. Discussion: Interpret your results, discuss their implications, and relate them to your research questions and hypotheses.
  8. Conclusion: Summarize your main findings, their significance, and the implications for future research or practical applications.
  9. References: Cite all sources and studies you referenced in your report using a consistent citation style (e.g., APA, MLA).

Writing Tips

  • Use clear and concise language, avoiding jargon or overly technical terms.
  • Organize your report logically, with headings and subheadings for easy navigation.
  • Provide evidence and data to support your claims and conclusions.
  • Consider your target audience and tailor the report to their level of expertise and interest.

Creating Visualizations

Visualizations are powerful tools for conveying complex data and making your research findings more accessible. Here are some types of visualizations commonly used in research reports:

Charts and Graphs

  • Bar Charts: Ideal for comparing categories or groups.
  • Line Charts: Effective for showing trends or changes over time.
  • Pie Charts: Useful for displaying proportions or percentages.


  • Data Tables: Present numerical data in an organized format.
  • Cross-tabulations: Show relationships between variables.

Diagrams and Maps

  • Flowcharts: Visualize processes or workflows.
  • Concept Maps: Illustrate connections between concepts.
  • Geographic Maps: Display spatial data and patterns.


When creating visualizations:

  • Choose the correct type of visualization for your data and research questions.
  • Ensure that visualizations are labeled, clear, and easy to understand.
  • Provide context and explanations to help readers interpret the visuals.

Presenting Your Research

Presenting your research to an audience is an opportunity to engage, educate, and inspire. Whether it's through a conference presentation, seminar, or webinar, effective communication is vital.

  • Know Your Audience: Tailor your presentation to the interests and expertise of your audience.
  • Practice: Rehearse your presentation to ensure a smooth delivery and confident demeanor.
  • Use Visual Aids: Enhance your presentation with visual aids such as slides, images, or videos.
  • Engage with Questions: Encourage questions and discussions to foster interaction and clarify points.
  • Stay within Time Limits: Respect time constraints and stay on schedule.

Peer Review Process

Before your research is published, it typically undergoes a peer review process. This involves experts in your field evaluating the quality, validity, and significance of your work. The peer review process aims to ensure the integrity and credibility of your research.

  1. Submission: Submit your research manuscript to a journal or conference for review.
  2. Editorial Review: The editorial team assesses your submission's fit with the journal's scope and may conduct an initial review for quality and compliance.
  3. Peer Review: Your manuscript is sent to peer reviewers who evaluate it for methodology, validity, significance, and adherence to ethical standards.
  4. Feedback and Revision: Based on reviewers' feedback, you may be asked to revise and improve your research.
  5. Acceptance or Rejection: After revisions, the manuscript is reevaluated, and a decision is made regarding publication.

Publishing Your Research

Publishing your research is the final step in sharing your findings with the broader scientific community. It allows others to access and build upon your work. Consider the following when choosing where to publish:

  • Journal Selection: Choose a reputable journal that aligns with your research field and target audience.
  • Review Process: Understand the journal's peer review process and requirements for submission.
  • Open Access: Consider whether you want your research to be open access, freely accessible to all.

Once published, actively promote your research through academic networks, conferences, and social media to maximize its reach and impact.


By effectively reporting and communicating your research findings, you contribute to the advancement of knowledge, inspire others, and ensure that your hard work has a meaningful impact on your field and beyond.

Applied Research Examples

To provide a deeper understanding of applied research's impact and relevance, let's delve into specific real-world examples that demonstrate how this type of research has addressed pressing challenges and improved our lives in tangible ways.

Applied Medical Research: mRNA Vaccines

Example: mRNA (messenger RNA) vaccine technology, exemplified by the COVID-19 vaccines developed by Pfizer-BioNTech and Moderna, is a remarkable achievement in the field of applied medical research.


Applied researchers in this domain utilized mRNA technology to create vaccines that provide immunity against the SARS-CoV-2 virus. Unlike traditional vaccines, which use weakened or inactivated viruses, mRNA vaccines instruct cells to produce a harmless spike protein found on the virus's surface. The immune system then recognizes this protein and mounts a defense, preparing the body to combat the actual virus.


Impact: The rapid development and deployment of mRNA vaccines during the COVID-19 pandemic have been groundbreaking. They've played a crucial role in controlling the spread of the virus and saving countless lives worldwide. This example underscores how applied research can revolutionize healthcare and respond swiftly to global health crises.

Environmental Science and Applied Research: Ocean Cleanup

Example: The Ocean Cleanup Project, founded by Boyan Slat, is an ambitious endeavor rooted in applied research to combat plastic pollution in the world's oceans.


This project employs innovative technology, such as large-scale floating barriers and autonomous systems, to collect and remove plastic debris from the ocean. Applied researchers have played a pivotal role in designing, testing, and optimizing these systems to make them efficient and environmentally friendly.


Impact: The Ocean Cleanup Project is a testament to the power of applied research in addressing pressing environmental challenges. By removing plastic waste from the oceans, it mitigates harm to marine ecosystems and raises awareness about the urgent need for sustainable waste management.

Business and Applied Research: E-commerce Personalization

Example: E-commerce giants like Amazon and Netflix use applied research to develop sophisticated personalization algorithms that tailor product recommendations and content to individual users.


Applied researchers in data science and machine learning analyze user behavior, preferences, and historical data to create recommendation systems. These algorithms utilize predictive analytics to suggest products, movies, or shows that align with a user's interests.


Impact: The application of research-driven personalization has transformed the e-commerce and streaming industries. It enhances user experiences, increases customer engagement, and drives sales by presenting customers with products or content they are more likely to enjoy.

Education and Applied Research: Flipped Classroom Model

Example: The Flipped Classroom Model is an applied research-based teaching approach that has gained popularity in education.


In this model, instructors leverage technology to deliver instructional content (such as video lectures) outside of class, allowing in-class time for active learning, discussions, and problem-solving. Applied research has informed the design and implementation of this pedagogical approach.


Impact: The Flipped Classroom Model has shown promise in enhancing student engagement and learning outcomes. It capitalizes on research findings about how students learn best, emphasizing active participation and collaborative learning.

Agriculture and Applied Research: Precision Agriculture

Example: Precision agriculture employs data-driven technology and applied research to optimize farming practices.


Farmers utilize satellite imagery, sensors, and data analytics to monitor crop conditions, soil health, and weather patterns. Applied research guides the development of precision farming techniques, enabling more efficient resource allocation and reducing environmental impact.


Impact: Precision agriculture increases crop yields, conserves resources (such as water and fertilizer), and minimizes the ecological footprint of farming. This approach contributes to sustainable and economically viable agriculture.


These real-world examples underscore the versatility and impact of applied research across diverse domains. From healthcare and environmental conservation to business, education, and agriculture, applied research continually drives innovation, addresses critical challenges, and enhances the quality of life for individuals and communities worldwide.

Conclusion for Applied Research

Applied research is a powerful force for solving real-world problems and driving progress. By applying existing knowledge and innovative thinking, we can address healthcare challenges, protect our environment, improve businesses, enhance education, and revolutionize agriculture. Through this guide, you've gained valuable insights into the what, why, and how of applied research, unlocking the potential to make a positive impact in your field. So, go forth, conduct meaningful research, and be part of the solution to the world's most pressing issues.

Remember, applied research is not just a concept; it's a practical approach that empowers individuals and teams to create solutions that matter. As you embark on your own applied research endeavors, keep the spirit of inquiry alive, remain open to new ideas, and never underestimate the transformative power of knowledge put into action.

How to Conduct Applied Research in Minutes?

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  • Lightning-Speed Insights: From posing questions to gaining insights, it takes mere minutes. When you need answers fast, Appinio delivers.
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