It doesn’t matter if you’re a business, a student, or a research facility. Data collection is essential and the proper data collection methods will make or break your research.
If you get the correct data, you can make the right decisions in a timely fashion. This extends to finding the right market segments, using the correct mix of marketing, planning finances, and everything in between. If you have the wrong data then, obviously, you’ll make the wrong decisions.
No one sets out to make mistakes.
A straightforward way to avoid costly mistakes is to use the right data collection method then apply sound analysis. This guide dives deep into the type of data that can be collected, multiple data collection methods, and steps that should be followed when collecting data.
What is data collection
In simple terms, data collection is the process used to get and sort information that is used to make choices about relevant situations. It can be used by businesses, individuals, family units, governments, and more.
It’s a means to an end – not a goal in itself.
Think of data collection through the lens of your everyday life. Before you buy something, you may need to check your account balance. That’s an act of data collection that helps you decide whether you should make a purchase. If you want to buy a new house, you collect data about amenities that are close by, the school district, and the crime rate.
The list of times when you need to collect data throughout the day can stretch on forever. The difference between personal data collection and business data collection is that the latter is usually more formal or structured and emphasizes making rational decisions.
Data types that can be collected
The type of data collected has an impact on what it can be used for and how much you can trust it. There are many types and subtypes of data. We’ll focus on four of the major ones here.
Primary data
Primary data is considered the best type of data. It’s often used interchangeably with first-party data and is information that you’ve collected yourself from a source. A source, in this case, can be anything such as customer surveys, observation, interviews, etc.
With primary data, you’re the first person to interact with the information and no one else has access to it – unless you share or sell it. While it’s usually the most accurate, it’s also more difficult to work with because it needs to be analyzed before useful insights are drawn.
Secondary data
Secondary data is, in essence, someone else’s first-party data. It has been collected, analyzed, structured, and presented by a third party. A few examples of secondary data include research papers, reports, books, etc.
Since the major work has already been done, it’s easier to interact with and draw conclusions from. The drawback is that you don’t have much visibility into how the data was collected, cleaned, and collated. The organization or individual preparing the data may not have accounted for important variables and, as a result, the data is skewed. These are things to take into consideration when using secondary data.
An example of secondary data is the Influitive state of customer marketing report. An annual research paper that highlights trends in the industry.
Within the broad categories of primary and secondary data, you can further break information down into qualitative data and qualitative data.
Qualitative data
At its core, qualitative data is information that is descriptive. It can be used to better understand a situation, problem, sentiment, feeling, group, individual, etc. While it can be recorded and measured to an extent, numbers wouldn’t suffice to quantify it.
For example, someone could describe the way they feel about a product or situation, but you would have a hard time accurately measuring that with numbers alone. Qualitative data is gathered through surveys using open-ended questions, can be written down or otherwise recorded based on someone’s observations, and gotten through interviews.
Secondary qualitative data is usually gathered through firsthand accounts of a situation such as a journal entry or research notes. Use this data to understand the why behind decisions and situations.
Quantitative data
This is a type of data that’s collected in the form of numbers which makes it easier to order or rank. It’s used for deeper analysis, calculations, and statistics. Even though it’s in a numerical form, it can still be used to make decisions just like qualitative data.
The benefit is that it’s easier for most researchers to handle because it’s cut and dry. The data is clear to see and understand so it’s less open to interpretation like qualitative data.
Surveys can be used to collect primary quantitative information but instead of open-ended questions, close ended questions are used. Secondary quantitative information is gathered through research and statistics. Use this data when trying to figure out how much of something, how often, or how many.
The 7 most effective data collection methods
Keep in mind that the following list isn’t exhaustive. There are more ways to collect data but the methods outlined here will yield the best qualitative and quantitative data.
1. Close ended question surveys
A close-ended survey question can be used for quantitative data collection. It’s when researchers use questions with a finite number of prearranged answers to gather relevant data. For example, a multiple-choice question is a close ended question.
Surveys can contain both open-ended and close ended questions. Some of the most impactful surveys contain both which allows for a broader range of information to be collected. This is effective in qualifying quantitative data.
For example, if you ask someone to rate customer service on a scale of 1 – 10. After they answer, you follow up and ask why did they give the service that score. You understand the score and the reason for the score.
Likert scale questions are a specific type of close ended question that is used to measure the degree to which something happens or the frequency of the occurrence without
2. Open-ended survey questions
An open-ended survey is less structured and gives the respondent more room to express their feelings, opinions, motivations, characteristics, or stance. It’s a great option when you want to expand on a close ended question or better understand a topic that’s important to your research.
Many researchers want to use open-ended questions almost exclusively but it can yield poor survey results because respondents become fatigued. It’s not easy for them to give you a long and insightful answer every time. If they get tired, they’re more likely to abandon the survey.
3. Interviews
Interviews are one of the most effective ways to collect data from a specific group of people. They can be administered in many different ways and you can react to the nuances of body language to guide the interview and explore certain topics in more detail. A survey doesn’t have this type of flexibility.
There are three main ways to use an interview to collect data from individuals. Structured interviews are rigid questionnaires that are administered verbally. It follows a script and isn’t changed much depending on the situation. Semi-structured interviews work from a script/questionnaire but are adaptable to the situation. This is the most common type. An unstructured interview has a goal but the interviewer is given complete freedom about which questions to ask and when to ask them.
4. Analytics software
Most websites have some form of analytics software set up to track how people interact with products, services, and pages. Even free tools like Google Analytics will tell you a lot about user behavior and allow you to tweak the information gathered. This is primary data and can be qualitative or quantitative depending on the software used.
A good way to use this information is by tweaking your sales funnel or offers to better accommodate the needs of users. The end result is better business outcomes for you and a more enjoyable experience for customers.
5. Observational data collection method
This type of data collection is often overlooked because it’s only ideal in a narrow band of cases. To use this method, a researcher looks on as a third party without interaction with the activity of what’s being observed or as an active participant.
In both cases, it’s possible to introduce biases. The bias may be through observation (seeing what they perceive to be the truth) or through interacting with the subject being observed. Oftentimes, it’s difficult to remain objective so this data collection strategy isn’t used as the first choice in most cases.
6. Focus groups
A focus group is an interview with multiple participants at once – a group. It usually contains 3 to 10 participants that fit a specific demographic required by the researcher. A professional observer is often used to moderate the focus group.
It’s one of the most expensive methods to collect data and is ideal when you want to test different scenarios in a controlled environment. The benefit of a focus group is having participants from specific backgrounds but groupthink can be an issue if one or two participants are more vocal than others.
7. Research data collection
Use this strategy when constraints prevent you from taking advantage of the first-party (primary) data sources mentioned above. You take research that another individual or organization has compiled, sort through it, and then use it for your own purposes.
Sometimes, it’s free and sometimes, you’ll have to pay for the data. It’s a good idea to use multiple data sets to get a holistic overview of the scenario you’re researching.
Things to consider when collecting data
You have the data collection methods that you’ll use so now it’s time to look at what you should consider before, during, and after data collection.
What is your goal
People rarely collect data for no reason but they often collect it without fully articulating their goals. For example, they want to get a better understanding of their audience. It’s a goal but it’s too vague to allow you to perform meaningful data collection.
Like other aspects of your life or business, there should be a SMART goal associated with data collection.
- Who do you want to get data from
- What will you use the data to understand
- Are there certain criteria the data can meet
- Do you need a specific sample size
- Etc.
Answering these simple questions can drastically improve the usefulness of the information that you eventually gather.
How long will the exercise last
Sometimes, you’ll collect data for an indefinite period and use the new information as it comes in (like with analytics). At other times, the information you collect is time-sensitive (like polling customers before the holiday season).
Whatever the case, it’s important to determine the length of time before you get started. That way, you’ll know how much urgency to apply and have a clear timeline for your planning.
Settle on a specific data collection method
Using the right method to collect your information is key. Even though multiple methods can be applied in various situations, not all of them are ideal.
For example, if you’re researching a market segment, you wouldn’t use too many close-ended questions because your experience is lacking and you may accidentally exclude deep insights. Instead, you’d ask open-ended questions, use the information you gain to form hypotheses that confirm or deny your current assumptions, then use close ended questions to test your new hypothesis.
Once you’ve settled on a data collection method, go ahead and implement it. Keep in mind that you may not get it right the first time. You may realize that you’re not getting enough data, it’s not detailed enough, or people are weird. Whatever. Tweak and optimize until you get what you need.
Analyze and make decisions
The whole point of data collection is to make better decisions. After you’ve gathered all the information you can or that you need, start the process of analyzing it. Categorize it into groups and try to figure out the insights that are waiting for you.
Once you’ve worked with the data for a while, don’t be shy about inviting a neutral third party to take a look to see if they come to different conclusions or are able to draw out deeper insights. Once you’re confident in what you’re seeing, go ahead and make decisions.
Conclusion
Data, especially in the modern world, is what makes businesses and individuals tick – whether we realize it or not. The right data collection methods may allow you to uncover competitive advantages while the wrong ones will only serve as a hindrance.
Use the information in this guide to make the right choices the first time around and get more useful data. Keep in mind that no method is right or wrong – only ideal for the situation – so don’t’ fall in love with anyone. Use them like the tools they are and you’ll benefit from it. Let me know what you think in the comments and don’t forget to share.
