In the age when information is power, how we gather that information should be one of our major concerns, right? Also, which of the many data collection methods is the best for your particular needs?
Whatever the answer to the two questions above, one thing is for sure – whether you’re an enterprise, organization, agency, entrepreneur, researcher, student, or just a curious individual, data gathering needs to be one of your top priorities.
Still, raw data doesn’t always have to be particularly useful. Without proper context and structure, it’s just a set of random facts and figures after all. However, if you organize, structure, and analyze data obtained from different sources, you’ve got yourself a powerful “fuel” for your decision-making.
So, why do we collect data?
Why Collect Data
Data collection is defined as the “process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer queries, stated research questions, test hypotheses, and evaluate outcomes.”
It is estimated that, by 2024, the total volume of data created and consumed worldwide will reach 149 zettabytes. That being said, there are numerous reasons for data collection, but here we are going to focus primarily on those relevant to marketers and small business owners:
- It helps you learn more about your target audience by collecting demographic information
- It enables you to discover trends in the way people change their opinions and behavior over time or in different circumstances
- 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
- It facilitates decision making and improves the quality of decisions made
- It helps resolve issues and improve the quality of your product or service based on the feedback obtained
Before 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.
Primary vs. Secondary Data Collection
Primary data collection
Primary data (also referred to as raw data) is the data you collect first-hand directly from the source. 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.
According to CIO, 80-90% of data generated today is unstructured. In other words, it’s been collected as primary data but nothing meaningful has been done with it. Unstructured data needs to be organized and analyzed if it’s going to be used as fuel for decision-making.
Secondary data collection
Secondary data represents information that has already been collected, structured, and analyzed by another researcher. 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 collection is much easier and faster than primary. 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.
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.
Further along the line, both primary and secondary data can be broken down into subcategories based on whether the data is qualitative or quantitative.
Quantitative vs. Qualitative data
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. That being said, quantitative data is usually expressed in numerical form and can represent size, length, duration, amount, price, and so on.
Quantitative research is most likely to provide answers to questions such as who? when? where? what? and how many?
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.
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.
For 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.
As 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. Some of the most common quantitative data collection techniques include surveys and questionnaires (with closed-ended questions).
Compared to qualitative techniques, quantitative methods are usually cheaper and it takes less time to gather data this way. Plus, due to a pretty high level of standardization, it’s much easier to compare and analyze the findings obtained using quantitative data collection methods.
Unlike quantitative data, which deals with numbers and figures, qualitative data is descriptive in nature rather than numerical. Qualitative data is usually not easily measurable as quantitative and can be gained through observation or open-ended survey or interview questions.
Qualitative research is most likely to provide answers to questions such as “why?” and “how?”
As mentioned, qualitative data collection methods are most likely to consist of open-ended questions and descriptive answers and little or no numerical value. Qualitative data is an excellent way to gain insight into your audience’s thoughts and behavior (maybe the ones you identified using quantitative research, but weren’t able to analyze in greater detail).
Data obtained using qualitative data collection methods can be used to find new ideas, opportunities, and problems, test their value and accuracy, formulate predictions, explore a certain field in more detail, and explain the numbers obtained using quantitative data collection techniques.
As quantitative data collection methods usually do not involve numbers and mathematical calculations but are rather concerned with words, sounds, thoughts, feelings, and other non-quantifiable data, qualitative data is often seen as more subjective, but at the same time, it allows a greater depth of understanding.
Some of the most common qualitative data collection techniques include open-ended surveys and questionnaires, interviews, focus groups, observation, case studies, and so on.
Data Collection Methods
Before we dive deeper into different data collection tools and methods – what are the 5 types of data collection? Here they are:
- Surveys, quizzes, and questionnaires
- Focus groups
- Direct observations
- Documents and records (and other types of secondary data, which won’t be our main focus here)
Data collection methods can further be classified into quantitative and qualitative, each of which is based on different tools and means.
Quantitative data collection methods
1. Closed-ended Surveys and Online Quizzes
Closed-ended surveys and online quizzes are based on questions that give respondents predefined answer options to opt for. There are two main types of closed-ended surveys – those based on categorical and those based on interval/ratio questions.
Categorical survey questions can be further classified into dichotomous (‘yes/no’), multiple-choice questions, or checkbox questions and can be answered with a simple “yes” or “no” or a specific piece of predefined information.
Interval/ratio questions, on the other hand, can consist of rating-scale, Likert-scale, or matrix questions and involve a set of predefined values to choose from on a fixed scale. To learn more, we have prepared a guide on different types of closed-ended survey questions.
Once again, these types of data collection methods are a great choice when looking to get simple and easily analyzable counts, such as “85% of respondents said surveys are an effective means of data collection” or “56% of men and 61% of women have taken a survey this year” (disclaimer: made-up stats).
Here’s an example of a closed-ended image survey question created using LeadQuizzes:
If you’d like to create something like this on your own, learn more about how to make the best use of our survey maker.
Tip: Instead of creating an online survey from scratch, you can use one of LeadQuizzes’ professionally designed survey templates. All you need to do is log in to your account, choose one of 34 data collection templates, and easily customize it to fit your needs.
Qualitative data collection methods
2. Open-Ended Surveys and Questionnaires
Opposite to closed-ended are open-ended surveys and questionnaires. The main difference between the two is the fact that closed-ended surveys offer predefined answer options the respondent must choose from, whereas open-ended surveys allow the respondents much more freedom and flexibility when providing their answers.
Here’s an example that best illustrates the difference:
When creating an open-ended survey, keep in mind the length of your survey and the number and complexity of questions. You need to carefully determine the optimal number of questions, as answering open-ended questions can be time-consuming and demanding, and you don’t want to overwhelm your respondents.
Compared to closed-ended surveys, one of the quantitative data collection methods, the findings of open-ended surveys are more difficult to compile and analyze due to the fact that there are no uniform answer options to choose from. In addition, surveys are considered to be among the most cost-effective data collection tools.
3. 1-on-1 Interviews
One-on-one (or face-to-face) interviews are one of the most common types of data collection methods in qualitative research. Here, the interviewer collects data directly from the interviewee. Due to it being a very personal approach, this data collection technique is perfect when you need to gather highly personalized data.
Depending on your specific needs, the interview can be informal, unstructured, conversational, and even spontaneous (as if you were talking to your friend) – in which case it’s more difficult and time-consuming to process the obtained data – or it can be semi-structured and standardized to a certain extent (if you, for example, ask the same series of open-ended questions).
4. Focus groups
The focus group data collection method is essentially an interview method, but instead of being done 1-on-1, here we have a group discussion.
Whenever the resources for 1-on-1 interviews are limited (whether in terms of people, money, or time) or you need to recreate a particular social situation in order to gather data on people’s attitudes and behaviors, focus groups can come in very handy.
Ideally, a focus group should have 3-10 people, plus a moderator. Of course, depending on the research goal and what the data obtained is to be used for, there should be some common denominators for all the members of the focus group.
For example, if you’re doing a study on the rehabilitation of teenage female drug users, all the members of your focus group have to be girls recovering from drug addiction. Other parameters, such as age, education, employment, marital status do not have to be similar.
5. Direct observation
Direct observation is one of the most passive qualitative data collection methods. Here, the data collector takes a participatory stance, observing the setting in which the subjects of their observation are while taking down notes, video/audio recordings, photos, and so on.
Due to its participatory nature, direct observation can lead to bias in research, as the participation may influence the attitudes and opinions of the researcher, making it challenging for them to remain objective. Plus, the fact that the researcher is a participant too can affect the naturalness of the actions and behaviors of subjects who know they’re being observed.
Getting started with online data collection – Create a survey
Above, you’ve been introduced to 5 different data collection methods that can help you gather all the quantitative and qualitative data you need. Even though we’ve classified the techniques according to the type of data you’re most likely to obtain, many of the methods used above can be used to gather both qualitative and quantitative data.
Surveys, as you may have noticed, are particularly effective in collecting both types of data, depending on whether you structure your survey questions as open-ended or closed-ended.
If you’d like to get started with online data collection right now, just click on the button below to get access to start creating surveys for free!