Analysis and decision-making in business rely on available data. This data is collected to analyze the performance of a business and draw actionable conclusions. The different methods of data collection are, therefore, essential to assess business units and make assumptions while solving particular problems. With a sudden increase in the demand for commercial applications in artificial intelligence (AI) and machine learning in recent years, data collection has gained more importance than ever. Naturally, data scientists have had to come up with newer methods of collecting data, some that didn’t exist before the digital revolution.     

Before we explain the methods of collecting primary data, we have to look at data collection as a whole. Data collection is one of the crucial elements of statistical research. It’s the process of collecting information from all available sources when looking for solutions to a problem. It helps evaluate the outcome and predict future trends and possibilities. The idea is to start by collecting the most basic data related to one’s needs and then progressing with the type and volume of data that has to be collected. This further determines the two methods of data collection—primary and secondary data collection methods.  

Here we’ll explain the methods of collecting primary data, along with the types and sources of primary data collection.

  1. What Is Primary Data Collection? 

  2. Various Methods Of Collecting Primary Data

  3. Quantitative Methods

  4. Qualitative Methods

  5. Advantages Of Primary Data Collection Methods

  6. Disadvantages Of Primary Data Collection Methods

  7. Sources Of Primary Data Collection 


What Is Primary Data Collection?

Primary data collection involves gathering data from first-hand experiences and sources, which haven’t been available in the past. It’s quite simply the first information in its basic form. Primary data is specific to the motive of research and is highly accurate. Primary data sources are tailored or chosen to meet the specific requirements of a given problem or research. It’s important to first identify the aim of the survey or research and the target population to determine what online or offline source will be best suited. 

There are two types of primary data collection methods—quantitative and qualitative methods of primary data collection. Establishing a clear goal and target audience helps efficiently determine which one of the two types of primary data collection methods will be best to achieve the set goals.

Various Methods Of Collecting Primary Data

Organizations use various sources to collect facts, figures, symbols, objects and information on events. This is collectively known as data. What method of data collection they use depends on the problem they’re dealing with and what outcomes they would prefer. Let’s look at the various methods of collecting primary data:

Quantitative Methods

Quantitative methods are often used for market research that usually demand forecasting and use statistical tools. Out of all the different methods of collecting primary data, this method uses historical data to make long-term demand forecasts. Statistical methods minimize the element of subjectivity, making them highly reliable. Let’s look at some quantitative primary data collection methods:


  • Time Series Analysis

‘Time series’ is a sequential order of values at equal time intervals. Patterns are used to identify trends, which help organizations predict the demand for products and services for a given period of time.


  • Smoothing Techniques

Smoothing techniques come in handy where time trends lack significance as they eliminate random variations from historical data. This exposes patterns and estimates future demand. Simple and weighted moving average methods are commonly used for such forecasting techniques.


  • Barometric Method  

In this method, researchers adopt a leading indicators approach to use current developments and utilize them to speculate future trends. Past events are considered leading indicators if they’re capable of predicting future events. 

In the absence of historical data, researchers use qualitative methods to facilitate decision-making.

Qualitative Methods

From its name, we understand that qualitative methods don’t need historical data, numbers or mathematical calculations. It deals with non-quantifiable elements and is based on factors such as judgment, intuition, conjecture, emotion and experience. Let’s explain the methods of collecting primary data qualitatively: 

  • Surveys 

Surveys are one of the most popular ways to collect primary data. A target audience is identified to gather feedback or their insights into choices, opinions and preferences related to a product or service. It could be an offline or online survey. Online surveys can be customized to run analytics and get hidden insights.


  •  Polls

    Polls deal with multiple-choice questions or one primary question to read audience sentiments. It’s easy to generate quick responses from people as they’re short and can be embedded into different platforms when done online. It’s a great way to compare target groups and different individuals in a particular group.


  • Interviews 

    Out of the various methods of collecting primary data, interviews are considered the most intricate and effective, especially if done face-to-face. This method involves a series of questions that the respondents answer either in person or over a communication channel such as email, telephone or video call. It’s a feasible method when participants are less in number.


  • The Delphi Technique

In this data collection method, experts are given an estimate and a set of assumptions laid down by other industry experts. These assumptions and estimates can be revised and reconsidered. The final demand forecast is a result of the consensus of all experts.


  • Questionnaires

    Questionnaires are sets of questions that may or may not be open-ended. Respondents have to answer based on their experiences and knowledge related to the issue at hand. Although questionnaires are considered a part of a survey, the end goal may be different. 


  • Focus Groups

Focus groups are small groups of people, usually eight to ten members who discuss common areas related to a problem. Individuals offer their insights during discussions and moderators are responsible for regulating these discussions. The end goal is to have the group reach a consensus. 

Qualitative methods of primary data collection are used when a business wants to gain insights on products and note intangibles that could make or break a business. 

Advantages Of Primary Data Collection Methods

Have a look at the advantages associated with the different methods of collecting primary data:

  • Whether it’s product features or employee productivity, collecting primary data allows businesses to address specific issues that they want to deal with 
  • Compared to secondary data, primary data is far more accurate because secondary data isn’t regulated and there’s a risk of collecting false information 
  • Primary data is the property of the researcher who may or may not choose to share it. This means that businesses can keep information from being accessed by competitors. They may even decide to sell crucial data to rivals in the future at very high prices 
  • The information from primary sources is updated as data is collected in real-time 
  • Primary data collection methods let researchers control research design and the methods they use 

Having the freedom to choose subjects and methods of execution means there’s no limit to the amount and kind of data that can be generated.


Disadvantages Of Primary Data Collection Methods

Here are some of the disadvantages related to the different methods of collecting primary data:

  1. This is an expensive process of data collection, irrespective of the size of the research. It involves appointing trained professionals and may need sophisticated, expensive methods.  
  2. Data has to be collected from the root, which makes it a time-consuming affair. Researchers have to spend significant time collecting and processing data.
  3. Primary research may require huge volumes of data and the research demand may seem unrealistic. For instance, it’s not feasible to do a census of people in a community to outline the target market.  

Although using secondary data makes more sense in some cases, even with their drawbacks, primary data collection methods are much more reliable in giving a competitive edge to a business.

Sources Of Primary Data Collection

Once the objective and target population is identified, organizations can narrow down the sources from which they need to gather data. Here are some common sources of primary data collection that researchers use:  

  • Market Research

    Gathering data on the target market and consumer needs is an important aspect of business strategy. Organizations have to use various methods of collecting primary data to modify research and learn about purchasing power, usage and feature preferences.


  • Thesis

    Collecting data directly from the primary source is fundamental for academic research and thesis. Subjective study needs primary data.


  • Survivors

    Psychologists need primary data to understand and treat trauma survivors. No matter how similar their experiences may be, each survivor has a different story to tell, which means such studies require primary data.  


Research and statistical studies cannot neglect primary data collection methods, especially in business. It entails using immediate data from the source to draw conclusions and make predictions. Executives must collaborate with trained researchers to deal with sensitive matters that require data collection. They may choose to Learn New Skills On The Job and perform research only when chances of damage are minimal and they have a clear picture of the objective.

Data collection is concerned with finding solutions. There are few things as satisfying as coming up with a solution that hits the nail on the head. Go behind the scenes with Harappa’s Create New Solutions pathway to fully understand the process of problem-solving. Learn to make research foolproof and analyze scenarios error-free. Lay down insightful questions, look for relevant data and use smart analyses to create working solutions. Learn to make well-reasoned and clearly articulated arguments that are backed by logic and evidence.