![]() The data obtained via quantitative data collection methods can be used to conduct market research, test existing ideas or predictions, learn about your customers, measure general trends, and make important decisions.įor instance, you can use it to measure the success of your product and which aspects may need improvement, the level of satisfaction of your customers, to find out whether and why your competitors are outselling you, or any other type of research.Īs quantitative data collection methods are often based on mathematical calculations, the data obtained that way is usually seen as more objective and reliable than qualitative. Quantitative survey questions are in most cases closed-ended and created in accordance with the research goals, thus making the answers easily transformable into numbers, charts, graphs, and tables. Quantitative research is most likely to provide answers to questions such as who? when? where? what? and how many? That being said, quantitative data is usually expressed in numerical form and can represent size, length, duration, amount, price, and so on. This type of data deals with things that are measurable and can be expressed in numbers or figures, or using other values that express quantity. Some examples of secondary data include census data gathered by the US Census Bureau, stock prices data published by Nasdaq, employment and salaries data posted on Glassdoor, all kinds of statistics on Statista, etc.įurther along the line, both primary and secondary data can be broken down into subcategories based on whether the data is qualitative or quantitative. But, on the other hand, it’s often very difficult to find secondary data that’s 100% applicable to your own situation, unlike primary data collection, which is in most cases done with a specific need in mind. ![]() Secondary data collection is much easier and faster than primary. If you are using books, research papers, statistics, survey results that were created by someone else, they are considered to be secondary data. Secondary data represents information that has already been collected, structured, and analyzed by another researcher. Unstructured data needs to be organized and analyzed if it’s going to be used as in-depth fuel for decision-making. In other words, unstructured daza collected as primary data but nothing meaningful has been done with it. In this case, you are the first person to interact with and draw conclusions from such data, which makes it more difficult to interpret it.Īccording to reasearch, about 80% of all collected data by 2025. Primary data (also referred to as raw data) is the data you collect first-hand, directly from the source. Secondary Data Collection Primary data collection It helps resolve issues and improve the quality of your product or service based on the feedback obtainedĪccording to Clario, global top collectors of personal data among social media apps are:Īnd given how successfull they are when it comes to meeting their users’ needs and interests, it is safe to say that streamlined and efficient data collection process is at the core of any serious business in 2023.īefore we dive deeper into different data collection techniques and methods, let’s just briefly differentiate between the two main types of data collection – primary and secondary.It facilitates decision making and improves the quality of decisions made.It lets you segment your audience into different customer groups and direct different marketing strategies at each of the groups based on their individual needs. ![]() ![]() ![]()
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