7 Data Collection Methods and Examples (Plus Data Types)

By Indeed Editorial Team

Published 16 October 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Data collection is an important strategy that a company can use to learn about its performance within the market. Since there are several types of data and various collection methods, it's important to select the one that can best meet a company's goals. Learning more about data collection methods can help you develop the skills to select the proper data strategy for success. In this article, we describe the data collection types and offer seven key methods of data collection and examples to help you prepare a successful data strategy.

7 methods of data collection

Here are seven methods of data collection that can help you collect relevant and timely data:

1. Observation

Observational data collection methods involve examining and watching specific processes to learn more about them. In many cases, a data collector may observe people or animals in their natural habitats to learn more about how they behave on a daily basis. They may also create artificial scenarios, like those of laboratory studies, to manipulate the circumstances that they'd like to view. No matter if the observation is natural or manufactured, it's often best for the observer to stay out of sight so that they can gather accurate, uninterrupted data.

Example: A children's store named Bubbly Baby wants to develop a new children's toy to sell exclusively in their store. The production team at Bubbly Baby plans to conduct observational research with babies, whose parents have provided consent to examine what toys interest them the most. During the observation sessions, the production team stands in another room to view the toy selections each baby makes. This recorded information may then guide their development process and help them develop a new toy with components that each of the babies enjoyed.

2. Survey

Surveys can be a great way to gather quick responses from customers, employees or any other group that you'd like to study. Data collectors can create surveys that ask open-ended or multiple-choice questions. They may also ask respondents to include demographic information like their age or gender to inform data analysis. Surveys are often easy to distribute online, which can help researchers gather data quickly without interacting with, and potentially influencing, the respondents.

Example: A small car rental company called Rachel's Car Rentals is interested in learning more about customers' perceptions about renting a car with them. To expand their reach and maintain cost efficiency, they choose to create and send out a survey to all of their customers over the past six months. The survey includes multiple choice and short-answer questions and spaces for customers to provide additional comments if they have more insight to share.

Related: 10 Most Essential Data Analysis Skills

3. Focus group

A focus group is a curated group of users that a company may recruit to offer their opinions. Companies often create focus groups comprised of customers to learn more about the users' feelings about the company's products or offerings. Focus groups can also help a company predict the success of a future product. Within a focus group setting, respondents often share feelings, opinions or emotions rather than statistics.

Example: Green Wicker University is considering a brand refresh. The university designers put together some mockup brand logos and materials to share with focus group participants to gauge their perceptions. During this session, someone from the marketing team may run the session as a moderator and stay with participants to present them with each potential refresh idea. Before moving on to the next one, they may stop and ask participants what they think or feel about what they're seeing.

Related: What Is Market Research? Definition, Types and Examples

4. Interview

Interview methods can be more personal and involve face-to-face discussions about a topic between the researcher and the participant. Researchers might share the questions with participants before interview sessions to allow them to decide if they feel comfortable taking part. This method may include gathering consent forms for video or audio recordings. If you choose to collect data with this method, recording sessions with video or audio might provide benefits if you plan to reference them when creating future business plans.

Example: Knit-a-little-bit, an instructional series focused on teaching people how to knit at different levels, worries that they aren't gaining customers at their projected rate. To understand the reasoning behind this, the company arranges interviews with potential customers to listen to their perspectives. During each interview, the researcher asks participants questions and records their answers. Once the interviewers record and analyse the data collected from all interviews, the company may use it to help boost its position in the market or make updates to its brand strategy.

Related: 4 Interview Methods in Research and When to Use Them

5. Design thinking

Design thinking methods may focus on brainstorming with participants to generate unique ideas or solutions. Companies might use this method if they're interested in solving challenges consumers face as product users. These sessions can happen face-to-face or virtually depending on where researchers and participants are located. If you choose to collect data with this method, whether you're face-to-face or virtual, using physical or technological sticky notes might help you organise and record participants' ideas.

Example: Meditative Monkey, a meditation company, is interested in developing a new product specifically for individuals who struggle to fall asleep at night. They tried to brainstorm as a company, but want to gather more innovative ideas and decide to run a design thinking session with participants. They write a protocol as a guide to ensure that the session stays focused to gather as many ideas from participants as possible. Their protocol contains a script and guided steps for the thinking process.

6. User testing

Companies usually use user testing during or after the development of products or services. If they choose to use it during development, it might be to determine where users find the product challenging to navigate. They might also use it after they've already released a product or service if they're interested in making updates. If you choose to collect data with this method, it may help to allow participants to go through products or services on their own to avoid having your own biases or knowledge influence the user testing results.

Example: Baller Bingo, a bingo game for smartphones, is interested in making updates to its application. First, they want to understand where users specifically want improvements and choose to use user testing methods. During their sessions, they ask participants to engage with all aspects of the application and then ask them what navigation or features they might like to see improved. Baller Bingo can then take this information to implement updates to their game.

Related: What Is Research Methodology and Why Is It Important?

7. Existing data

As a data collection method, existing data involves gathering secondary information to help guide research and knowledge. Since existing data can be easier to gather than other data methods, you can quickly use this method to inform data strategy. You can also use existing data in combination with other methods to give a comprehensive understanding of a particular topic. For example, existing data could inform the questions you ask in an interview or determine the topic in a focus group. You can gather existing data through previous company research, relevant academic studies or books, articles or podcasts about the subject.

Example: A tech provider, Franklin Technical Solutions, wants to run a comprehensive study about customer experience throughout the history of the company. While researchers may complete some surveys and interviews to learn more from current customers, they also choose to use existing research to learn about previous customer experience initiatives and their success rates. They gather more existing data from third-party sources about customer experience initiatives from other organisations to help them inform their recommendations.

Data collection types

Here are some important data collection types to help you improve your data skills:


Quantitative data involves collecting numerical information for potential use in a mathematical calculation. For example, quantitative data could include group ages, sales performance numbers or years that an employee has been with a company. It could also include self-performance ratings or numeric rankings. You can often collect quantitative data through surveys or research into company records or databases.

Related: Examples of Quantitative Skills and How to Highlight Them


In contrast to quantitative data, qualitative data collection includes the gathering of non-numeric information. Some examples of this data type include the emotions or feelings of survey respondents or open-ended accounts of employee satisfaction. While you can easily gather qualitative data through an open-ended survey, you could also use a focus group or other methods to speak directly with stakeholders about their experiences and opinions.


Primary data collection involves gathering raw data from its original source. It can include both quantitative and qualitative information. For example, the direct survey responses that you gather from customers are primary data. Sales numbers that you gather from company records or responses collected from focus groups are primary data, too.


Secondary data collection involves gathering information that originally came from another source. This can include ideas and statistics from published books, research papers or third-party online databases. Since secondary data often doesn't require you to create, run and fund a study or other collection strategy, it can be quicker and easier. The downside is that it may not give you as much freedom to control data collection methods.

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