Data collection is the process of gathering and analyzing accurate data from various sources to determine possible outcomes, trends and probabilities, etc. To learn more, keep scrolling.
Knowledge is power, information is information, and data is information digitized, at least as defined in IT. Therefore, data is power. To leverage that data into a successful business strategy, you must first gather it. That’s the first step you need to take.
As a first step, we will focus on data collection to help you get started. How does it work? There’s more to it than just searching Google! In addition, what are the different types of data collection? In addition, what are the types of tools and techniques available for data collection?
You’ve come to the right place if you want to learn about how data collection works.
Related: Digital Analytics for Dummies
Table of Contents
What is Data Collection: A Definition?
To define data collection, it is essential to ask the question, “What is data? ” In a nutshell, data is information that has been formatted in a particular way. Thus, data collection is the process of gathering, measuring, and analyzing accurate data from a variety of sources to answer research questions, evaluate outcomes, and forecast trends.
The importance of collecting data can be attributed to the fact that our society relies heavily on data. To make informed business decisions, ensure quality assurance, and maintain research integrity, accurate data collection is essential.
Researchers need to identify the types of data, the sources, and the methods they will be used during data collection. There are many different ways to collect data, as we will soon discover. The collection of data is heavily relied upon in the fields of research, commerce, and government.
Three questions must be answered before an analyst begins collecting data:
- What is the purpose of this research?
- In what ways do they plan to collect data?
- What methods and procedures will collect, store, and process the data?
In addition, we can divide data into qualitative and quantitative categories. The qualitative data includes descriptions such as colour, size, quality, and appearance. The quantitative data is, unsurprisingly, based on numbers, such as statistics, polls, and percentages.
Why Do We Need Data Collection?
To create a plan of attack or make a ruling in a court case, judges and generals need as much relevant information as possible. The best courses of action come from informed decisions, and data and information are synonymous.
As we’ll see later, data collection isn’t a new concept, but the world has changed. Today, there is more data available than ever before, and it exists in forms that were unimaginable a century ago. As technology has advanced, data collection has had to keep up with the times.
No matter if you’re working in academia or the commercial sector, collecting data can help you make better decisions.
Now that you know what data collection is and why we need it, let’s examine how we can collect data. Although “data collection” may sound high-tech and digital, it doesn’t necessarily involve computers, big data, and the internet. It could be a telephone survey, a mail-in comment card, or a guy with a clipboard asking passersby some questions. But let’s try to organize the different data collection methods into a semblance of order.
What Are the Different Methods of Data Collection?
In business analytics, there are seven primary methods of collecting data:
- Surveys
- Transactional Tracking
- Interviews and Focus Groups
- Observation
- Online Tracking
- Forms
- Social Media Monitoring
Data Collection Process Example
1. How many plants do I have?
This is a simple question that should be answered before beginning any data collection. You want to know how much space you have to work with. If you don’t know how many plants you have, then you need to count them. Counting plants is not difficult if you have a good idea of what they look like.
2. What type of lights am I using?
You should know what kind of lights you are using before starting any data collection. Different types of lights produce different amounts of light at different times of the day. Knowing what kind of lights, you use will help you determine how much time you spend indoors and how much time you spend outside.
3. Where did my seeds come from?
If you are collecting data about your plants, you should know where your seeds came from. Seeds are often sold online or at local dispensaries. If you bought your seeds from a dispensary, you should ask them where they got their seeds from.
4. Do I have enough room?
The amount of space you have to grow your plants is important. You may have to move your plants around if you don’t have enough space. If you don’t have enough room, you might consider moving your plants to a bigger container.
5. Is my grow area clean?
Cleanliness is important. Your grow area should be free of debris and dirt. Dirt and debris can cause problems for your plants. Cleaning your grow area regularly will keep your plants happy and healthy.
6. Are my plants watered correctly?
Watering your plants correctly is important. Watering your plants too little or too much can lead to poor growth and even death. Make sure you water your plants properly.
7. Have I been keeping track of my data?
Keeping track of your data is important. You should write down everything you think is relevant to your experiment. Keeping track of your data will allow you to compare results over time.
Implementing Data Collection Tools
In previous sections, we’ve learned about the many different types of data that can be collected, from the different websites people visit and the ads they see along the way. Just like there are many different data points, there are various ways to collect data, each with its features and purposes.
Although much of the information these tools collect and organize for you can be found on the web server logs for your site, that’s not always easy or practical. In this section, we’ll take a look at three tools that will help you collect data.
Data Collection Tool #1: Facebook Pixel
Pixels also referred to as tags, are used for tracking, measurement and advertising. As mentioned in the introduction section above, it’s not always easy or practical to look at data from your web server logs or even cookies. Luckily you can work with companies to help you track user behaviour or advertise products.
A pixel is a small piece of code that you can add to your website that instructs it to send some information to an identified third party, in other words, these companies looking to help you utilize your data. The Facebook pixel is one example.
Data Collection Tool #2: SDKs
An SDK, or software development kit, is a library of pieces of code that you can integrate into your app to add certain functions. Where on a website you can use a pixel or tag, you would use an SDK for your app.
The SDK sends the information about people’s interaction with the app to, for example, Google Analytics where both website and app information can be aggregated. A great example of an SDK that you might see every day is an app that asks you to sign in with your Google or Facebook account.
For your website, you might use an SDK to create a smooth checkout experience for customers, as well as, of course, track various data points of your browsers’ activity. If users have signed into your app using their Facebook account, for instance, you can also see whether an ad they saw on Facebook inspired them to download your app and make in-app purchases.
Data Collection Tool #3: APIs
An API, or an application programming interface, is a tool that establishes a connection between two pieces of software. Remember the example of sharing a news article on Twitter from the previous lesson? In the same way, APIs make it possible to share your article, they make it possible to share data directly with certain marketing or advertising platforms.
This is useful because you can then use these connections to learn more about the results of your marketing activities. For example, you can send purchase data to Facebook, which can then help you figure out whether the ads you placed on their platform lead to the purchases.
Implementing the tools – How to do it?
Using these tools is often as easy as integrating them into your website’s already existing code. Most of these tools, for example, the Facebook pixel and the Google Ads Remarketing, have the code readily available in the help documentation or other information for web developers. This allows you or your content developers to install the code easily so you can start tracking.
Why they’re useful?
Implementing tools such as these can allow you to encourage browsers of your website and app to purchase, subscribe and more. The Facebook pixel, for example, can also create custom target audiences consisting of people who have engaged with the website and who you would like to target with more specific advertising messages.
These tools also allow you to integrate your website experience with that of your app. For example, you can use an SDK to instruct your app to send certain information over to the platform that created the SDK, and that data can then be connected to other actions marketers take using the platform, like advertising.
How to Collect the Right Data for Your Business?
When collecting data from customers for marketing purposes, you must understand how to collect information ethically. This includes asking permission before taking customer data, keeping records safely, and using only the data you need.
Ask Questions About Their Needs.
It’s important to understand what your customers want when collecting data from them. You might ask questions about their needs if you’re selling products or services. For example, you might ask “What do you think about our product?” or “How would you rate our service?”
Ask Them About Their Preferences.
Another way to collect data from customers is by asking them about their preferences. This helps you learn more about how they use your business. For example, you could ask “Do you prefer to shop online or in stores?” or ” Do you prefer to buy one item at a time or multiple items at once?”
Find Out More About Their Preference.
If you’re looking to improve customer service, then you need to understand what your customers want. Ask them questions about their preferences so you can provide better service.
Understand Their Preference.
It’s important to understand your customers’ preferences before you start collecting data. This will help you make sure you’re providing the right products and services.
Know Their Preference.
If you’re looking to collect customer data, there are two main ways to do so: through surveys and interviews. Surveys allow you to gather data quickly and easily. However, they only provide limited insight into what people think. Interviews give you a deeper understanding of how people feel and why they behave as they do.
The Importance of Ensuring Accurate and Appropriate Data Collection
Regardless of the study’s subject matter or preferred method for defining data (quantitative, qualitative), accurate data collection is crucial to preserving research integrity. Data-gathering errors are less likely to occur when the right tools are used (whether they are brand-new, updated versions, or already available).
Among the effects of incorrect data collection are:
- Resource-wasting conclusions based on erroneous assumptions
- Public policy decisions that compromise public safety
- Inability to respond correctly to research inquiries
- Affecting human or animal participants in a harmful manner
- By deceiving other researchers into pursuing futile research avenues
- Inability to replicate and validate the study
Research findings can lead to disproportionate harm when used to support public policy recommendations, even if the degree of influence from flawed data collection varies by discipline.
Issues Related to Maintaining the Integrity of Data Collection
Whether errors were deliberately committed (deliberate falsifications) or not, maintaining data integrity is the main justification for assisting the error detection process (systematic or random errors).
Study results are scientifically valid if quality assurance and quality control are used to protect data integrity.
Each strategy is used at various stages of the research timeline:
- Data quality control – tasks performed both after and during data collection
- The quality assurance process occurs before data collection begins
What are some common challenges in collecting data?
- Data Quality Issues
- Inconsistent Data
- Data Downtime
- Ambiguous Data
- Duplicate Data
- Too Much Data
- Hidden Data
- Inaccurate Data
What are the Key Steps in the Data Collection Process?
In the Data Collection Process, there are 5 key steps. They are explained briefly below –
- Decide What Data You Want to Gather
- Establish a Deadline for Data Collection
- Select a Data Collection Approach
- Gather Information
- Examine the Information and Apply Your Findings
Data Collection Considerations and Best Practices
To gather data in the field, we must carefully plan before spending time and money. In addition to saving time and resources, effective data collection strategies can help us collect richer, more accurate, and richer data.
The following are some best practices we can follow to achieve the best results:
- Each additional point of data should be considered in light of the price
- Identify each piece of data and plan how to collect it
- Using mobile devices for data collection can be a challenge. Considering your options is a good idea
- Identify the data you need to gather and consider it carefully
- Don’t forget to consider identifiers
- Using mobile devices to collect data is the best method
Also Read: A/B Testing: The 5 Steps to Starting an A/B Test Campaign