In our modern world, data and information are everything. The organizations that are able to properly harness it excel. Those that cannot fall by the wayside.

There are many types of data and the one you will use depends on myriad factors like what the data is for, your resources, and the accessibility of the data source.

In this guide, you’ll learn about what primary data is, the key advantages, how to collect it, and even get relevant examples.

Primary data definition

Primary data, is essentially data that has been collected directly by the researcher from first-hand or primary sources. It’s also referred to as raw data because it has not been interpreted, processed, or sorted.

The way data is collected and the sources used are often designed to meet the needs of specific research initiatives. For example, if it’s a social research experiment, the data sources may be representative of the people in an entire city. If it’s for customer research then an organization will only collect data from existing or potential customers.

This provides many advantages but also disadvantages which we’ll discuss in a later section. Even though it’s beneficial in many ways, you should be prepared to take more time and invest more energy to get a hold of primary data.

Primary data is often used interchangeably with first-party data. They’re very similar but there’s a slight difference. First-party data refers to an organization/business collecting information directly. Primary data refers to a researcher (which can also be a business) collecting data from the source. Put another way, primary data has a wider definition than first-party data.

A note on secondary data

Secondary data is often used as a substitute for primary data because of the inherent challenges associated with primary data. Secondary data is information that has been collected by other researchers, recorded, and interpreted by them to meet the needs of their research.

Secondary data is often free or comes with minimal costs when compared to primary data. With that being said, you cannot be 100% sure of the quality control implemented when gathering the data. Additionally, the conclusions are drawn or the way the data is presented my lead to different conclusions if you had access to the raw data.

Both primary data and secondary data have their place. Let’s look at some of the advantages and disadvantages of primary data.

Primary data advantages and disadvantages

There are two sides to every coin and primary data is no different. Apart from the obvious advantages and disadvantages, it’s important to look at those that aren’t as clear.

Advantages of primary data

  • Understand and can control the quality of the data – There are many ways to go about collecting primary data. Depending on your needs, you can implement strict quality control procedures that prevent unnecessary errors. You can also make changes to the data collection methods during the process to better meet the needs of the research.
  • Can be made more accurate – This builds on the last point about data quality. When using secondary data, you don’t know how accurate the raw data is due to numerous factors. Maybe some of the answers or observations were corrupted. Maybe the people collecting the data were inexperienced. Whatever the case, when you’re collecting the information yourself, you can put in the effort to ensure it’s accurate. 
  • Tailored to solving the research problem – Data isn’t collected for fun. It almost always has a clear purpose and is applied to solve a problem. While you can apply that data in multiple ways, it’s often not ideal for your purposes if you didn’t get it yourself. When collecting primary data, you can design the collection methods to meet the needs of your research.
  • Data remains private and unique – No one has access to your primary data unless you give it to them. It remains off the open market and, as a result, you can achieve a competitive advantage.

Disadvantages of primary data

  • More costly – Personally collecting data means you have to factor in manpower, locations, tools, and more before successfully collecting the data. This can result in a much larger expense than those who simply used free secondary data or even purchased data from a vendor.
  • Takes more time – when interacting with secondary data, all you have to do is get a report or otherwise access it. For primary data, you have to collect it. Most of the time, the collection process isn’t something that cannot be done quickly or in bulk. After that, it needs to be sorted, categorized, and interpreted.
  • Requires experienced researchers – There are many nuances to collecting data. What is important, what will introduce biases or errors, the best way to structure the research, etc. all need to be taken into consideration. These are the things an experienced researcher will be able to manage. Experienced researchers often command a higher fee or salary.

How to collect primary data

There are multiple ways to collect primary data. It’s important to properly identify the needs of your research so you don’t waste time and energy. For example, a focus group isn’t necessary to measure customer satisfaction. A survey isn’t ideal for ideating and developing a new product.


Surveys are one of the most common types of primary data collection methods. It’s cost-effective and can be used in a wide variety of situations. There are surveys such as customer satisfaction, psychographics, demographics, etc.

A survey consists of a series of questions – both open-ended and closed ended – which respondents answer to the best of their ability. Depending on the type of questions asked, you may be able to do automated analysis and pull out a significant amount of data and insights.

Of course, that’s not possible in every instance and you may need to do manual categorization and analysis.

The key with surveys is to carefully craft the questions so that you’re not inadvertently leading respondents to a certain answer. You can reduce this by sharing the survey with a pilot group before using it with a larger audience to try and catch issues. Another thing to keep in mind with surveys are the inherent biases (such as central tendency bias which is more prevalent with surveys like the Likert scale) and survey fatigue.


Another way to get a hold of quality data is to conduct interviews with the individuals that meet the criteria you set for the research. Interviews can be conducted in person, over the phone, or online via video. Broadly speaking, there are two types of surveys:

  • Structured – All the questions have been mapped out and the interviewer just reads them off a list and records the answers of the participant. There’s no room to explore certain topics even if they’ll reveal deeper insights.
  • Unstructured – There may or may not be a list of questions but the interviewer has full control over what they ask and how they react to the respondent’s answers. For example, the respondent may reveal there’s more to the story through body language or their answer. The interviewer has the authority to further explore those points and as a result, they may get better information to work with.

Structured and unstructured interviews are two extremes of a scale. Most researchers will use a semi-structured interview to collect data. The structured interviews can be performed by inexperienced interviewers while the structured interviews need someone that’s better able to lead the conversation.

With modern technology, the cost of administering interviews is reducing but it’s still more expensive than surveys. The major benefit is that the primary data tends to be qualitative data which is often used for deep analysis and psychographic research.


A less common but incredibly powerful way to get unique primary data is through experimentation. These can be the kinds of experiments most people think of like those in a lab carried out by scientists in white lab coats. They can also be done in a business setting – for example, where you do A/B testing and analyze customer behavior.

Experiments are structured processes that seek to understand the cause, effect, and variables that go into an outcome. For example, an experiment that’s looking to increase the conversion rate of an eCommerce store will test many variables to see which ones have the biggest impact.

This is primary data in the truest sense because you’re gathering it yourself, it’s unique to your research problem, and reveals insights that can be interpreted in many ways.

The best experiments start with a hypothesis such as if we do X then Y will happen. The experiment is designed to test that hypothesis. Even if you’re wrong, you’re able to either produce a better hypothesis or move in a different direction that will enhance your understanding of the research problem.

Focus groups

Focus groups are some of the most expensive ways to collect data but they can also be effective when used in the right context. A focus group usually contains 3 to 10 participants that conform to a specific demographic group and or have a clear psychographic profile. An observer or moderator is also used to steer the group in the right direction.

The usefulness of a focus group is when interactions are needed between more than two people. Since it can simulate situations, you can understand how they’ll react to certain products or even how they’ll use them. One thing to be aware of is groupthink. If one participant is more dominant than others, over time, the entire group may start to agree with many of the things they say.

Now that you’re clear on a few methods to collect primary data, let’s look at a few examples of primary data to drive the points home.

Examples of primary data

The following examples are just scratching the surface. Always keep in mind that

Company market research

Before an organization will launch a product or enter new geographic regions, it’s necessary for them to do market research. This can take various forms but it almost always includes primary data collection.

For example, they may poll existing customers about their product preferences then pull a few of the respondents out for more in-depth interviews. They can then steer their product development or marketing strategy in the right direction.

Observing and writing a thesis on contemporary art

I mention this example because it may not be what you consider when thinking about primary data. Here’s how it would work. The researcher, a student in this case, would go to museums, interact with videos, listen to music, etc. themselves. From there, they’d compile the data they got from their observations and write a thesis.

Polls on employee satisfaction

Polls on employee satisfaction are a direct way to gauge the sentiment in your organization and, if there are any issues, find out ways to address them. The benefit is that employees can be more direct when it’s an anonymous poll. You’re collecting the data from employees directly which makes it primary data collection.


Primary data is, in essence, the data that a researcher collected themselves. It has many benefits but can also be more difficult to handle. I would encourage you to start on a smaller scale with things like surveys and straightforward research problems.

After you’ve built up more experience, you can then focus on more complex issues that may arise. In the end, primary data should be the core of your decision-making and research efforts. There is no substitute so start now instead of later. Let me know what you think in the comments and don’t forget to share.