7 Data Collection Methods for Qualitative and Quantitative Data - KyLeads (2022)

Data collection is essential for businesses, organizations, and even personal use. In the digital age data is one of the most valuable resources at your disposal.

The right data, used properly, can propel your brand forward by helping you make the right decisions in areas such as choosing a market segment, finding the ideal marketing mix, financial decisions, and more. When used incorrectly, it can seem like the choices being made by you or your team are always falling short.

How can you make sure you have the right information to make important decisions? By adopting sound data collection methods and analysis. In this guide, you’ll learn:

  • The types of data you can collect
  • 7 data collection methods
  • Steps to collect useful data using the methods you learn

Table of Contents

What is data collection

Data collection is the process of gathering and categorizing relevant information that can then be used to make decisions about specific situations. As you can tell from the definition, it’s not a process that’s only for business.

In every aspect of our lives, we go through the process of data collection. For example, if you want to move to a new city, you collect as much data as you can. When assessing a new job offer, you collect data about the company’s growth, salary scale, etc.

In a business setting, the data collection process and methods are more formal and tend to yield better outcomes as a result. That’s in part due to a clear delineation between the types of data that can be collected.

Types of data you can collect

The type of data you collect determines how much you can trust it and the versatility. There are two major types of data that can be further broken down into subcategories.

Primary data collection

Primary data, also known as raw data, is the data you collect yourself and are the first person to interpret. It’s data that’s gotten directly from the source. That could be in-person interviews, surveys sent out to your audience, or even courses. Put another way, you’re the first person or group to interact with and draw conclusions from the data.

Primary data is usually collected with a specific goal in mind but can be more challenging for the researcher to interpret. That’s because the data is unstructured and needs to be arranged in a way that allows you to make meaningful decisions.

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Secondary data collection

Secondary data refers to information you use which has been collected, analyzed, and structured by another person or group. Things like research papers, books, other websites, etc. can be considered primary data that, when used by you, are secondary data.

This type of data is much easier to collect and use but it may not be as applicable to your situation. For example, HubSpot does a survey of marketers every year and publishes its findings in a report called The State of Inbound. The data is high quality but may not be as useful to your specific situation even if you serve marketers.

7 Data Collection Methods for Qualitative and Quantitative Data - KyLeads (2)

Both primary and secondary data can be broken down into subcategories referred to as qualitative and quantitative data.

Qualitative data collection

Qualitative data is information that’s descriptive in nature. It’s used to understand and characterize a problem, sentiment, or an individual/group. It can be recorded and measured but cannot be quantified using numbers.

For example, you can record that someone is unhappy and measure the level of unhappiness using descriptive words but it can’t be quantified. This kind of primary data is gathered using interviews, open-ended survey questions, etc. and can be used to answer the question “why?” Secondary data can be gathered from firsthand accounts such as a journal.

Quantitative data collection

Quantitative data is information gathered in numerical form and, as a result, can be easily ordered and ranked. This data is necessary for calculations and further statistical analysis. Just like with qualitative data, the information derived here can be used to make decisions in a personal or business setting.

Quantitative data is easier to handle and measure because it’s not open to different interpretations. For example, if you ask someone how many times they’ve gone to the gym this week, there’s a simple numerical answer. If you asked someone why they went to the gym, their answer can be interpreted in different ways depending on who’s analyzing it.

Primary quantitative data is gathered using close ended survey questions and rigid one-on-one interviews. Secondary data can be gathered through published research and official statistics. Quantitative data answers the questions “how much” “how often” and “how many.”

7 Data collection methods

There are multiple data collection methods and the one you’ll use will depend on the goals of your research and the tools available for analysis. Let’s look at each one in turn.

1. Close ended question surveys

Close ended survey questions fall under quantitative primary data collection. It’s the process of using structured questions with a predefined series of answers to choose from. Keep in mind that close ended questions can be combined with open-ended questions within the same survey.

That means you’re able to collect quantitative and qualitative data from the same respondent. A good example of this would be an NPS survey. The first question includes a rating scale while the second question is an open-ended question and seeks to understand the reason behind the answer.

Likert scale questions (which is an interval scale) also fall under this category. They’re ideal for measuring the degree of something like frequency or feeling.

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Pros

  • They’re inexpensive and can be sent out to many people
  • People are able to answer anonymously
  • It’s easy to analyze the data received because the survey software will do a lot of the work

Cons

  • The response rate is lower
  • You’re unable to ask clarifying questions in most cases
  • Many respondents won’t complete the entire survey

2. Open-ended surveys

Open-ended survey questions are ideal when you’re trying to understand the motivations, characteristics, or sentiment behind a stance. You’re able to capture data that close ended questions simply can’t give you.

While open-ended survey questions can yield a wealth of insights, it’s important not to overdo it. When you have too many open-ended questions or they’re too complex, fatigue sets in. This increases the likelihood that your respondents will abandon the survey altogether, leaving you with incomplete data.

7 Data Collection Methods for Qualitative and Quantitative Data - KyLeads (4)

Pros

  • They yield more insights
  • You can get voice of customer data to use in marketing campaigns like social media, email marketing, and SEO campaigns.
  • Can be used to probe different angles of a problem even if you don’t have prior experience

Cons

  • Much more difficult to analyze
  • Still can’t ask clarifying questions
  • Answers may be all over the place and hard to group

3. Interviews

Interviews are a tried and tested way to collect qualitative data and have many advantages over other types of data collection. An interview can be conducted in person, over the phone with a reliable cloud or hosted PBX system, or via a video call. The in-person method is ideal because you’re able to read body language and facial expressions and pair it with the responses being given.

There are three main types of interviews. A structured interview which can be considered a questionnaire that’s given verbally. There’s little to no deviation from the questions that were set in the beginning. A semi-structured interview has a general guideline but gives the interviewer the leeway to explore different areas based on the responses received. An unstructured interview has a clear purpose but the interviewer is able to use their discretion about the type of questions to ask, what to explore, and what to ignore. This gives the most flexibility.

Pros

  • Gather deep insights from people interviewed
  • Ability to explore interesting topics on the fly
  • Develop a more nuanced understanding of the problem or situation at hand
  • The data tends to be more accurate because of the clarifying questions that can be posed

Cons

  • Expensive to do them at scale
  • May be difficult to coordinate schedules with the person being interviewed
  • Much more time consuming than other methods

4. Online analytics tools

In the digital age, there are countless analytics tools you can use to track and understand user behavior. If you have a website or app, you’ll be able to gather a wealth of data. For example, using Google Analytics, you can see the most popular pages, how many people are visiting them, the path they take before converting, and so much more.

With those insights, you can optimize different aspects of the sales funnel and improve your results over time.

Pros

  • Understand how people are interacting with your web properties
  • Create tests and hypothesis to improve your results

Cons

  • Unable to interact with visitors in a meaningful way
  • The data is limited and doesn’t tell you why certain things happen

5. Observational data collection

This is one of the most passive data collection methods and may not be the best first choice. The researcher can observe as a neutral third party or as a participant in the activities going on.

Because of this, it’s possible to introduce biases into the research which will affect the quality of the data. As a participant, their attitudes or perception of what’s being observed may be skewed in one direction or another and make it hard to remain objective.

Pros

  • It’s widely accepted
  • Can be applied in many of situations
  • Relatively easy to set up and execute

Cons

  • More difficult to remain objective
  • Some things cannot be observed by a researcher

6. Focus groups

Focus groups are similar to interviews but take advantage of a group. A focus group comprises of 3 – 10 people and an observer/moderator. Fewer than that and you’re better off doing interviews and any more than that may be unmanageable.

It’s ideal when you’re trying to recreate a specific situation or want to test different scenarios and see how people will react. The best results come when the participants fit a specific demographic or psychographic profile.

Pros

  • The information is insightful and reliable
  • It’s more economical than hosting individual interviews
  • You can also collect quantitative data by administering surveys at the beginning of the session

Cons

  • More expensive than other methods
  • Participants can become the victims of groupthink
  • Difficult to coordinate the schedule of multiple participants
  • Need specialized researchers to moderate the group

7. Research or reported data collection

This data collection method is used when you can’t take advantage of primary data. Instead, you’re able to use information that has already been gathered from primary sources and made available to the public. In some cases, the information is free to use and in other cases, you may have to pay to gain access. For example, some research papers require payment.

Pros

  • Faster than in-person interviews
  • You can use multiple data sources together to get a more holistic picture

Cons

  • Reliant on the quality of the third party for your data
  • It may be difficult to find data that’s directly related to the problem you want to solve

Important steps to collect useful data

At this point, you know the data collection methods available, their pros, and their cons. Now, let’s look at the steps required to collect meaningful data.

Determine the goal for the data collection

You can collect data and store it until it becomes useful one day. This doesn’t help you or prove the case for the resources you expend to get the data in the first place. Before you implement any data collection strategy, take a moment to understand where it’ll be applicable.

Who will you collect the data from, where and how will you use it? Will you exclude certain audiences completely?

For example, if you’re sending out a survey, what are you trying to measure and improve? Is a customer satisfaction survey, price sensitivity survey, or countless other types of surveys best? Each one has its own nuances, pros, and cons.

How long you’ll collect the data

In a few cases, you can collect data indefinitely and continually update your assessments. For example, you should be collecting analytics data from your website at all times. In most cases, there should be a hard stop date for your data collection. After that, you can start to analyze it, draw conclusions, and implement changes.

For example, you may want to record analytics data about an A/B test you’re running over the course of a month. It has a definite end date because you can’t analyze the data until the experiment is over.

Choose a data collection method

Set aside time to consider different data collection methods. You should pick a primary channel, and think about secondary options. For example, you might decide to collect data by asking people on your email list to fill in an online survey. A secondary method might be advertising the survey offline in your store. You could use a dynamic QR code generator to make it easy to access the survey.

If you use the wrong data collection method then it can severely impact the quality and usefulness of your data. For example, if you’re exploring a new product category and don’t have deep knowledge about the customers and competitors, a close ended survey will strengthen assumptions that may or may not be correct.

In this case, an open-ended survey where people can give more details would be better. Once you’ve finished that initial data collection exercise, you can confirm or invalidate many assumptions and then send out a close ended survey with more confidence.

Implement your data collection strategy

After you’ve done the initial planning and research, it’s time to implement it. Be flexible here because you may realize that the data collection method you chose isn’t ideal or the timeframe isn’t long enough to give you meaningful data. In those situations, you may want to change course or scrap the exercise and start over.

Analyze and draw conclusions from the data

The last step is the most important. At this point, your raw data isn’t too useful but when you categorize and quantify it, you can tease out insights that can be used in multiple areas.

Even after the initial analysis, it’s a good idea to get a third party to take a look or someone else in your organization. They may draw different conclusions than you which can open the doors for better results in marketing or operations.

Data security and protection

Collecting data is great, but what about safety and security? With the rapid advancement of technology and the value of information, having robust practices to staysafe from data breaches is a must. And the risk is not only about leaking valuable insights but also facing lawsuits from people whose details it is. Managing data is not something to take lightly.

First and foremost, make sure that your data collection methods don’t compromise your customers’ security online. Add to that, you can use a secureonline data roomto handle, process, and analyze confidential customer information. That way, you will be able to benefit from the insights you collect without risking any data leaks or security breaches.

Conclusion

Data is what makes the world go round and there are many data collection methods you can use to gain insights into your market. The one you choose will depend heavily on your goals, your customer base, and the resources available to your organization.

Don’t look at any methods as being better than another. Rather, look at them as being appropriate for specific situations. Start your data collection journey by choosing the collection method that’s the easiest for you to implement right now and work your way up as you start to see results from it.

FAQs

What are the methods of data collection both qualitative and quantitative? ›

Quantitative research methods are measuring and counting. Qualitative research methods are interviewing and observing. Quantitative data is analyzed using statistical analysis. Qualitative data is analyzed by grouping the data into categories and themes.

Which data collection method quantitative or qualitative is best and why? ›

Because quantitative methods are not about gaining an in-depth understanding but rather grasping a general understanding of a particular context with precise results, quantitative data is easier to collect and analyse and there are less chances of bias in the result interpretation.

What is the best data collection method for quantitative research data? ›

Of all the quantitative data collection methods, surveys and questionnaires are among the easiest and most effective. Many graduate students conducting doctoral research use this method because surveys and questionnaires are applicable to both quantitative and qualitative research.

What are the examples of qualitative and quantitative data? ›

Differences between Quantitative and Qualitative Data
Quantitative DataQualitative Data
Collected data can be statistically analyzedCollected data can just be observed and not evaluated
Examples: Height, Weight, Time, Price, Temperature, etc.Examples: Scents, Appearance, Beauty, Colors, Flavors, etc.
2 more rows

Why is it important to collect both qualitative and quantitative data? ›

Using a combination of qualitative and quantitative data can improve an evaluation by ensuring that the limitations of one type of data are balanced by the strengths of another. This will ensure that understanding is improved by integrating different ways of knowing.

What are the method of data collection explain? ›

Data collection methods are broken into two core categories—primary and secondary. Primary data collection methods gather information directly, so it is source data. Secondary data collection methods pull information from existing repositories. It could be third-party source material or the output of the analysis.

What are the 5 methods to analyze qualitative data? ›

5 qualitative data analysis methods explained
  • Content analysis.
  • Thematic analysis.
  • Narrative analysis.
  • Grounded theory analysis.
  • Discourse analysis.
9 Aug 2022

What are the techniques or methods used to analyze qualitative data how about quantitative data? ›

Two main qualitative data analysis techniques used by data analysts are content analysis and discourse analysis. Another popular method is narrative analysis, which focuses on stories and experiences shared by a study's participants.

What is meant by qualitative and quantitative analysis? ›

Generally speaking, quantitative analysis involves looking at the hard data, the actual numbers. Qualitative analysis is less tangible. It concerns subjective characteristics and opinions – things that cannot be expressed as a number. Here's a closer look at aspects of both and how they are used.

What is the best example of quantitative research method? ›

An example of quantitative research is the survey conducted to understand the amount of time a doctor takes to tend to a patient when the patient walks into the hospital.

What are the common data collection methods used in quantitative research? ›

There are several methods by which you can collect quantitative data, which include:
  • Experiments.
  • Controlled observations.
  • Surveys: paper, kiosk, mobile, questionnaires.
  • Longitudinal studies.
  • Polls.
  • Telephone interviews.
  • Face-to-face interviews.

What is the importance of data collection in research? ›

The most critical objective of data collection is ensuring that information-rich and reliable data is collected for statistical analysis so that data-driven decisions can be made for research.

What are the 10 examples of qualitative research? ›

10 Examples of Qualitative Data
  • Observation Notes. Observation is an important method of qualitative data collection. ...
  • Semi-structured interviews. ...
  • Open-ended survey. ...
  • Participant diaries or journals. ...
  • Portfolios of evidence. ...
  • Concept Maps. ...
  • Case Studies. ...
  • Focus Groups.

What is difference between quantitative and qualitative data? ›

Quantitative data is countable or measurable, relating to numbers. Qualitative data is descriptive, relating to language.

What are examples of quantitative data? ›

Quantitative data is data that can be counted or measured in numerical values. The two main types of quantitative data are discrete data and continuous data. Height in feet, age in years, and weight in pounds are examples of quantitative data.

How can you gather more accurate qualitative and quantitative data? ›

There are a few common methods by which you can collect qualitative data:
  1. Interviews.
  2. Case studies.
  3. Secondary research (record keeping)
  4. Expert opinions.
  5. Focus groups.
  6. Online surveys (mobile, kiosk, desktop)
  7. Paper surveys.
  8. Observational studies.

How do you use qualitative and quantitative research together? ›

There are four ways for designing a research study with both quantitative and qualitative methods: Triangulation Design, Embedded Design, Explanatory Design, and Exploratory Design.

How do qualitative and quantitative research work together? ›

Simply put, quantitative data gets you the numbers to prove the broad general points of your research. Qualitative data brings you the details and the depth to understand their full implications. To get the best results from these methods in your surveys, it's important that you understand the differences between them.

What is data collection with example? ›

collection of data from information services providers and other external data sources; tracking social media, discussion forums, reviews sites, blogs and other online channels; surveys, questionnaires and forms, done online, in person or by phone, email or regular mail; focus groups and one-on-one interviews; and.

What is a data collection tool? ›

What is a Data Collection Tool? Data collection tools refer to the devices/instruments used to collect data, such as a paper questionnaire or computer-assisted interviewing system. Case Studies, Checklists, Interviews, Observation sometimes, and Surveys or Questionnaires are all tools used to collect data.

Which methods of collecting data is more effective? ›

Here are some of the most common primary data collection methods:
  • Interviews. Interviews are a direct method of data collection. ...
  • Observations. In this method, researchers observe a situation around them and record the findings. ...
  • Surveys and Questionnaires. ...
  • Focus Groups. ...
  • Oral Histories.
13 Oct 2021

How do you do data collection in research? ›

6. What is involved in collecting data – six steps to success
  1. Step 1: Identify issues and/or opportunities for collecting data. ...
  2. Step 2: Select issue(s) and/or opportunity(ies) and set goals. ...
  3. Step 3: Plan an approach and methods. ...
  4. Step 4: Collect data. ...
  5. Step 5: Analyze and interpret data. ...
  6. Step 6: Act on results.

What are data collection methods PDF? ›

The different methods that have been explained include interview, focus groups, questionnaire and schedule, observation, case study, ethnographies, oral history and projective techniques.

What are the 8 steps of content analysis? ›

  • Step 1: Prepare the Data. ...
  • Step 2: Define the Unit of Analysis. ...
  • Step 3: Develop Categories and a Coding Scheme. ...
  • Step 4: Test Your Coding Scheme on a Sample of Text. ...
  • Step 5: Code All the Text. ...
  • Step 6: Assess Your Coding Consistency. ...
  • Step 7: Draw Conclusions from the Coded Data. ...
  • Step 8: Report Your Methods and Findings.

What is the best method of data analysis for qualitative research? ›

The most commonly used data analysis methods are: Content analysis: This is one of the most common methods to analyze qualitative data. It is used to analyze documented information in the form of texts, media, or even physical items.

How do you measure qualitative data? ›

Qualitative data analysis cannot be counted or measured because it describes the data. It refers to the words or labels used to describe certain characteristics or traits. This type of data answers the "why" or "how" behind the analysis.

What is data analysis in qualitative research example? ›

What is Qualitative Data Analysis? Qualitative data analysis is a process of gathering, structuring and interpreting qualitative data to understand what it represents. Qualitative data is non-numerical and unstructured.

What are 3 examples of quantitative research? ›

There are three types of Quantitative Research Questions used in research: Descriptive Research Questions. Comparative Research Questions. Relationship-based Research Questions.

What are the 4 types of quantitative research methods? ›

There are four main types of Quantitative research: Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research. attempts to establish cause- effect relationships among the variables. These types of design are very similar to true experiments, but with some key differences.

What is the main difference between qualitative and quantitative observations? ›

Qualitative observations are made when you use your senses to observe the results. (Sight, smell, touch, taste and hear.) Quantitative observations are made with instruments such as rulers, balances, graduated cylinders, beakers, and thermometers. These results are measurable.

How can you tell if research is quantitative or qualitative? ›

Quantitative studies rely on numerical or measurable data. In contrast, qualitative studies rely on personal accounts or documents that illustrate in detail how people think or respond within society.

What is the quantitative analysis process give examples of this process? ›

Examples of quantitative analysis

To build a numerical interpretation of a given situation, analysts often collect and assess historical data. Some examples of quantitative analysis include: Closed-ended questionnaires and surveys. Historical financial reports.

Are interviews qualitative or quantitative? ›

An interview is a qualitative research method that relies on asking questions in order to collect data. Interviews involve two or more people, one of whom is the interviewer asking the questions.

What is the example of qualitative? ›

Qualitative Information – Involves a descriptive judgment using concept words instead of numbers. Gender, country name, animal species, and emotional state are examples of qualitative information.

What is the difference between qualitative and quantitative research Brainly? ›

One is the qualitative analysis and different is quantitative research. Quantitative research utilizes statistical and analytical statements to get a conclusion whereas the qualitative search depends on the verbal and written data.

What is the importance of data collection in quantitative research? ›

In quantitative research process, data collection is a very important step. Quality data collection methods improve the accuracy or validity of study outcomes or findings. Nurse researchers have emphasized on the use of valid and reliable instruments to measure a variety of phenomena of interest in nursing.

What is quantitative data collection tools? ›

Quantitative data is measurable numerical data researchers collect by asking close-ended or multiple-choice questions using surveys, polls, questionnaires, and other methods.

What are the advantages of quantitative research in terms of data collection analysis and presentation? ›

A major benefit of using quantitative data is its objectivity. It relies on concrete numbers and fewer variables. This can help to remove biases from the research and make the findings more accurate. Another benefit is that it is often easier to obtain large sample sizes.

Why is data useful? ›

Good data allows organizations to establish baselines, benchmarks, and goals to keep moving forward. Because data allows you to measure, you will be able to establish baselines, find benchmarks and set performance goals. A baseline is what a certain area looks like before a particular solution is implemented.

What are data collection tools in qualitative research? ›

There are a variety of methods of data collection in qualitative research, including observations, textual or visual analysis (eg from books or videos) and interviews (individual or group). However, the most common methods used, particularly in healthcare research, are interviews and focus groups.

What are the methods used for qualitative data collection? ›

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [1, 14, 16, 17].

What are qualitative data collection methods? ›

Qualitative Data Collection Methods
  1. Surveys/questionnaires.
  2. Interviews.
  3. Focus groups.
  4. Observations.
  5. Records/archival review.
4 Jan 2022

What are some quantitative data collection methods? ›

There are several methods by which you can collect quantitative data, which include:
  1. Experiments.
  2. Controlled observations.
  3. Surveys: paper, kiosk, mobile, questionnaires.
  4. Longitudinal studies.
  5. Polls.
  6. Telephone interviews.
  7. Face-to-face interviews.

What are the 10 examples of qualitative research? ›

10 Examples of Qualitative Data
  • Observation Notes. Observation is an important method of qualitative data collection. ...
  • Semi-structured interviews. ...
  • Open-ended survey. ...
  • Participant diaries or journals. ...
  • Portfolios of evidence. ...
  • Concept Maps. ...
  • Case Studies. ...
  • Focus Groups.

What are the qualitative and quantitative research? ›

Quantitative studies rely on numerical or measurable data. In contrast, qualitative studies rely on personal accounts or documents that illustrate in detail how people think or respond within society.

What is an example of quantitative? ›

Quantitative Information – Involves a measurable quantity—numbers are used. Some examples are length, mass, temperature, and time. Quantitative information is often called data, but can also be things other than numbers.

Which data collection method is best for qualitative research? ›

The methods mentioned in the blog – interviews, surveys, group discussions, and observations are the most widely and commonly used qualitative data collection methods. Although there are few other data collection methods, such as longitudinal studies, document revision, etc., they are rarely used.

What is method of data collection PDF? ›

9.1 CONCEPT OF DATA COLLECTION. Data collection is the process of gathering and measuring information on variables of interest, in an. established systematic fashion that enables one to answer stated research questions, test. hypotheses, and evaluate outcomes.

What are the data collection methods briefly explain? ›

In general, questionnaires, surveys, and documents and records are quantitative, while interviews, focus groups, observations, and oral histories are qualitative. There can also be crossover between the two methods.

What are the 4 types of data collection? ›

Data may be grouped into four main types based on methods for collection: observational, experimental, simulation, and derived. The type of research data you collect may affect the way you manage that data.

What is quantitative data collection tools? ›

Quantitative data is measurable numerical data researchers collect by asking close-ended or multiple-choice questions using surveys, polls, questionnaires, and other methods.

What is qualitative data and quantitative data? ›

Quantitative data are data about numeric variables (e.g. how many; how much; or how often). Qualitative data are measures of 'types' and may be represented by a name, symbol, or a number code. Qualitative data are data about categorical variables (e.g. what type).

What is the best example of quantitative research method? ›

An example of quantitative research is the survey conducted to understand the amount of time a doctor takes to tend to a patient when the patient walks into the hospital.

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