Data, data, data - it’s all we seem to hear about these days. If you want to improve your marketing campaigns, you need data. If you want to wash your car effectively, you need data. If you want to cook a great risotto, you need data.
If you take a step back from your business, you’ll probably see data flowing through every department, system, and platform. Readily available, it informs marketing campaigns, product development, personalization, and more. But today we want to get our heads out of endless charts, graphs, and tables. Instead, what is data collection? What are the different types of data? What are some effective sources of data?
In 2021, speak to most marketers and they will tell you that the best strategy is to drown in data - you can never have too much. In our opinion, it’s better to learn the information in this guide because you’ll start to use data more efficiently rather than always looking for more!
What’s Data Collection?
In simple terms, data collection describes the process of gathering information. Normally, businesses want to obtain this information because it helps them to learn from the past and improve the future. In marketing, we’re always looking to improve personalization, recommendations, ad campaigns, product development, and everything else that we do from 9 to 5 each day.
Traditionally, data would refer to surveys, interviews, focus groups and other information gleaned from field research. Before the digital age, marketers had to arrange focus groups and ask people questions (that’s right, actually talking to people). Now, we’re in a very different world and we can collect data without even talking to anybody thanks to digital tools.
As well as collecting more data, we can also collect more accurate data. Yet, this doesn’t mean that all online data is free from contaminants. You might collect data from the wrong source, or human error could lead to bias and other problems.
Types of Data Collection
While all data refers to some form of information, not all data is gathered in the same way. For example, third-party data refers to information that is collected elsewhere and then shared with others. As an advertiser yourself, you might use data from surveys that were completed by other businesses.
On the other hand, data that you collect yourself is called first-party data. As an example, you could launch an online survey and ask recipients to answer questions. You created the survey, you contacted the customers, and the customers provided their answers to you. Since you generated this information yourself, it’s first-party data and belongs to the business.
So, what’s second-party data? If you imagine first- and third-party data at two ends of a spectrum, second-party data would sit somewhere in the middle. Generally speaking, the phrase covers data that you didn’t collect yourself but to which you still have some affiliation. While third-party data is shared with anybody willing to access it (or pay for it), second-party data is shared privately between parties.
In the modern market, companies often work together and share insights because the benefits are mutually beneficial. As you can imagine, there’s often confusion between second-party data and third-party data - so much so that experts argue about differences between the two. However, the important thing is that you recognize how data you collect yourself is different from data collected elsewhere (whether by an affiliated company or a random source).
Also, data doesn’t just differ based on the source because quality is also important. While the data you collect is accurate and reliable, this changes as you stray further from your own involvement. Third-party has less reliability and accuracy because you don’t know the conditions under which the data was collected, the bias of the people taking the data, and other factors.
Qualitative vs Quantitative Data
When learning more about data, you’ll also see mentions of qualitative and quantitative data. But what do these long, confusing words mean? Don’t worry, it’s simple enough.
In short, quantitative data measures numbers and statistics while qualitative data goes deeper into motivations and emotions.
Quantitative Data
Focusing on numbers, the following are considered examples of quantitative data:
These days, we can almost store endless amounts of this sort of data. What’s more, we can make quick judgments on the data. For example, a high bounce rate suggests that we need to improve the landing page. Meanwhile, lots of clicks on an ad means that it’s resonating with the audience. Yet, quantitative data also comes with various challenges. For one thing, it tells you what is happening without delving into why it’s happening.
It’s great to know that conversion rates on a campaign are increasing, but it’s impossible to infer anything else from the data because you don’t know the cause of the strong performance. Why did a prospective lead click on an ad? Knowing the conversion rate won’t get you close to an answer to this question.
Additionally, the fact that we can store endless amounts of this data brings security and privacy concerns. If you get carried away with data collection, your business will fall foul of the compliance regulations and hackers will get excited by the prospect of tapping into your system. All of a sudden, you’re having to explain to customers why you were holding so much data.
If you’re to gather quantitative data, it’s wise to introduce a data tracking plan. With this, you know exactly what data you collect, how, and why. Furthermore, you can also segment your audience so that you don’t have redundant data for certain segments.
Qualitative Data
If you want to learn the motivations and emotions of your audience, you need qualitative data. Although there are exceptions, the general rule is that quantitative data consists of numbers while qualitative data consists of words. As an example, you might send customers a survey to gauge their opinions about your new products.
With a 100-word answer from each customer, you get much better insights into their decision-making process, emotions, motivations, and more. Of course, you may have already thought of some issues. How are you supposed to read 1,000 surveys when they all contain long answers? Also, it’s generally more expensive to collect qualitative data (and it requires more time too!).
Cheaper alternatives are entering the market, such as virtual focus groups, but these aren’t as effective as physically spending time around people. Thankfully, you’ll find technology today that can process qualitative data and pick up on trends, patterns, frequently used phrases, and other important points.
When collecting data, the best solution is often a balance between qualitative and quantitative data. Also, think about the outcome you’re trying to achieve before deciding whether it requires one or the other.
Common Data Collection Methods
With the addition of digital platforms and automation, the number of available data collection methods has increased dramatically over the years. Yet, this doesn’t mean that traditional methods are outdated. You can glean important insights from the following:
Focus Groups and Interviews
Firstly, there’s a reason why marketers still use interviews and focus groups…it works. Whether virtual or physical, you interact with people in real-time and can go off-script to generate more effective insights. As well as recording responses, you can also learn from body language. How do participants react? What is their overall feeling about the topic of discussion?
Naturally, organizing interviews and focus groups will require investment. Also, it’s difficult to scale unless you spend even more money.
Polls and Surveys
In truth, this is a simpler form of the first suggestion. Rather than interacting with people through interviews, you ask for their opinions using polls and surveys. As well as multiple-choice questions, you can also include leading questions to learn more.
Unfortunately, it’s difficult to get honest opinions sometimes because the questions naturally lean one way or the other. When done in a group, people also feel swayed by the opinions of others. If nine people say X, only the strongest-willed individuals will give Y as their answer.
Social Media
Moving into the digital world even further, tools like Trapica, Bilbi, and Hootsuite provide insights into the behavior of your audience on social media. What are people saying about your brand? What do they think of the industry? Furthermore, you can monitor trends and patterns in the market.
These days, social media monitoring is easier with the addition of machine learning and artificial intelligence. Within moments, you receive insights and suggested actions for your marketing strategy.
Transactional and Behavioral Data
Finally, other good sources of data come from behavioral and transactional sources. While the former analyses the behavior of people on your website or app, the latter collects data while leads become customers during the purchase process. You’ll learn about their favorite payment methods and other preferences as they purchase products from the brand.
With a customer data platform, it’s possible to keep data from all the sources above in the same place to prevent confusion and frustration!
