The way we use and collect data has changed. And we are using data for more complex and detailed use cases.
As we strive for deeper insights and more personalized outcomes from our data-driven projects, our collected data should be new, fresh, and tailored to the business needs.
This is where primary data comes into play. Through primary data collection, researchers and business leaders can obtain personalized data for their complex and unique projects.
In this article, primary data collecting is examined, along with how it varies from secondary data, the various types of primary data collection methods, and the advantages and disadvantages of each.
What is primary data collection?
Primary data collection involves collecting fresh data from a live person or a group of people who have extensive knowledge of the topic or have experienced the event in question.
For instance, if businesses need to learn about the public perception of a product directly from its users, then primary data collection is the way to go. Similarly, primary data collection also works for AI projects that require highly personalized datasets.
Primary vs. secondary data collection
Primary data is new and is collected for an original study or purpose for which no data had previously been collected for.
Secondary or tertiary data, on the other hand, is data that has already been collected for previous studies or is extracted from previously done research.
Secondary data is also available publicly, which makes it cheaper to collect r as compared to primary data, albeit offering less personalization.
What are the types of primary data collection?
The common primary data collection methods are:
- Surveys: A survey can be done offline or online. It consists of a list of questions answered by a group of people to extract data about a specific topic.
- Focus groups: This type of data collection is done by interviewing a small group of participants about a specific topic and recording their responses.
- Interviews: This is simply conducted through setting up online or face-to-face meetings with specialists with knowledge in the area you are researching on.
- Quizzes: These are small tests that can be done online or offline. The questions in the quiz are designed to extract data regarding a certain topic.
What are the advantages and disadvantages of primary data collection?
The following are some positives of primary data collection:
Primary data is reliable since it is collected by you or any other third-party data collection vendor/research company. This level of reliability can not be achieved in pre-existing secondary data.
Primary data collection is tailored to your data-hungry project’s needs. Secondary data can not offer the level of personalization that primary data collection can offer.
Primary data collection does not have any legal restrictions attached to it. You do not need to get copyrights. As long as you follow ethical and legal considerations, you can use the data freely, keep it, or sell it in the future.
Since the data is specific to the requirements and is sourced from professionals from the same field/area, it is arguably more accurate.
Primary data collection can also has some negatives
Primary data collection can be relatively more expensive than secondary data. This is because it requires the recruitment of participants or the hiring of a vendor/research company. Secondary data can even be free sometimes.
The costs vary on the size of the projects; however, the following expenses can make up the total cost of a project:
- Recruitment costs
- Interviewing costs
- Extra interviewing costs of participants with special needs like house-rest patients.
- Software costs for managing the gathered data, such as SPSS
- Recording and other equipment
- Transcription costs if done with a third-party
Collecting primary data can be relatively more time-consuming than secondary. The process requires ethical approvals, recruitment of participants, preparation of surveys/questionnaires, analysis, and cleaning of the data.
For more in-depth knowledge on data collection, feel free to download our whitepaper:
- Quick Guide to Data Collection Quality Assurance
- Top 4 Data Collection Methods
- Crowdsourced AI Data Collection Benefits & Best Practices
If you need help finding a vendor or have any questions, feel free to contact us:
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