Between clicks and questions – The art of data collection

Pasquale Schifino

Data is the new oil – a frequently quoted phrase that has long since become reality.

Whether you’re shopping online, visiting the doctor, or scrolling through social media, data is being collected, analyzed, and evaluated everywhere.

But how do companies, government agencies, and scientists actually obtain this data?

The answer lies in data collection – an inconspicuous but crucial step in the data lifecycle.

In this article, we take a look at the different types of data collection, why it is so important, and what role you play in it – perhaps quite unconsciously.

🎯 The most important summarized:

Data collection means much more than simply gathering data: it is a structured process in which information is obtained in a targeted and systematic manner. It is not only the quantity of data that is crucial, but above all its quality, relevance, and purpose.

Primary data is collected directly from the source and is therefore very accurate, but time-consuming and costly. Secondary data comes from existing sources, can be used quickly and cheaply, but is often less accurate.

Modern technologies enable new ways of collecting data—from tracking and cookies to wearables, connected devices, and gamification surveys. These methods provide valuable, often automated insights. At the same time, they increase the requirements for ethical standards and data protection, especially in terms of the GDPR.

Data is more than just collected numbers—behind every data set is a person. That is why conscious and responsible handling is essential: data protection, transparency, and ethical considerations are at least as important as the collection itself.

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Table of contents

1. What exactly is data collection?

2. What types of data collection are there?

3. Creative methods of data collection in the digital age

4. Why is data collection so important—and sensitive at the same time?

5. Conclusion

6. More on the topic of data collection

What exactly is data collection?

Data collection refers to the systematic process of gathering information with the aim of gaining insights from it.

It is not just about large amounts of data, but also about the quality, relevance, and purpose of the data.

Depending on what you want to find out, you choose different methods—and that’s where it gets exciting.

What types of data collection are there?

Primary data collection – data fresh from the source

This involves collecting new, previously unavailable data directly from the source – for example, through:

Surveys (e.g., online surveys, interviews)
Observations (e.g., customer behavior in a store)
Experiments (e.g., A/B testing on websites)
Measurements (e.g., heart rate during exercise)

This type is particularly accurate, but often time-consuming and costly.

It is frequently used when existing data is insufficient or very specific information is required.

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Secondary data collection – Accessing data archives

This involves using existing data, e.g.:

Statistics from government agencies (e.g., Federal Statistical Office)
Research results from other studies
Company data (e.g., from previous projects)
Data from the internet (e.g., reviews, social media)

Secondary data is usually available quickly and cheaply, but may be outdated or not entirely accurate.

Creative methods of data collection in the digital age

Modern technologies have also expanded the possibilities for data collection.

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Examples:

Tracking & cookies: Every click on a website is analyzed – from dwell time to scroll depth.
Wearables: Smartwatches collect health data in real time.
Smart devices: Voice assistants and connected devices continuously provide user data.
Gamification surveys: Playful surveys engage users more and increase data quality.

These innovative methods enable deeper insights – but also raise ethical and data protection issues.

Looking for more methods and tools for data collection?

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Why is data collection so important—and sensitive at the same time?

Without data, there would be no informed decisions, no personalized advertising, no research.

But with large-scale data collection comes great responsibility: data protection, transparency, and ethical boundaries are crucial.

The GDPR in Europe is an example of how sensitively the handling of personal information is regulated—and must be regulated.

Conclusion

Data collection is the foundation of every data-based decision—whether in science, business, or everyday life.

It can be done traditionally or digitally, directly or indirectly.

But despite all the technology and methodology, data is not just numbers.

Behind every data set is a human being. That is why conscious, responsible handling of data is at least as important as its collection.

Because only those who collect wisely can act wisely.