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The Unwritten Rules of the PR Industry

09/29/2025 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

The unwritten rules of Public Relations (PR) aren't found in textbooks, yet they strongly influence how successful you are in the field. They’re based on experience, ethics, trust, and intuition. Ignoring them doesn’t just jeopardize your campaigns — it can damage your reputation or that of your clients.

1. Credibility is everything

PR can do a lot — but it can’t save lies. If you’re not honest in your messaging, you’ll get exposed sooner or later. Credibility is the currency of PR — once lost, it’s nearly impossible to regain.

2. Know your audience better than yourself

Successful PR starts with a deep understanding of the target audience. Only those who know how their audience thinks, feels, and behaves can craft messages that truly resonate.

3. Editors have the final say

No matter how well you prepare your story — whether or not it gets published is ultimately up to the editor. PR pros respect this and focus on building long-term, trust-based relationships with the media.

4. Timing is everything

The best story is worthless if it lands at the wrong time. Great PR requires a feel for current events, news cycles, and social sentiment.

5. “Off the record” means confidential — for real

Trust is the backbone of good media relations. If you leak confidential information or misuse “off the record” comments, you’ll damage your reputation and relationships — sometimes permanently.

6. PR is not advertising

Press work is not marketing. Promotional language has no place in press releases or interviews. Journalists are looking for news value — not sales talk.

7. True skill shows in a crisis

Crisis communication demands speed, transparency, and honesty. Denial, cover-ups, or silence usually make things worse. Taking responsibility early can be a reputational win.

8. Storytelling beats data overload

Facts, figures, and statistics matter — but stories stick. Good PR turns information into compelling, human, relatable narratives that people remember.

9. Consistency beats noise

PR is not about one big moment — it’s about long-term relationship building. If you only show up when you want attention, people stop listening. Consistent, strategic communication wins.

10. Everything is communication

It’s not just what you say that matters — it’s what you do, how you act, and even what you don’t say. Emails, meetings, social media, body language — it’s all part of the public perception. Everything communicates. Everything can be PR — or anti-PR.

Conclusion

The unwritten rules of PR can't be measured in KPIs — but they determine trust, influence, and long-term success. Those who understand and respect them build the foundation for meaningful, effective communication.

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How Data-Driven PR Works

08/20/2025 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

In today’s increasingly digital communication landscape, data-driven public relations (PR) is becoming ever more important. Companies and organizations use data to make informed decisions, deliver targeted content, and measure the effectiveness of their communication strategies.

Definition: What Does Data-Driven PR Mean?

Data-driven PR refers to the use of qualitative and quantitative data to improve the planning, execution, and evaluation of communication strategies. Instead of relying solely on intuition or experience, this approach is based on measurable insights.

Key Data Sources

Successful data-driven PR relies on various sources:

  • Media analysis: Evaluation of traditional and digital media coverage.
  • Social media monitoring: Tracking mentions, hashtags, and trends across social platforms.
  • Web and SEO data: Analysis of website traffic, search behavior, and user journeys.
  • Surveys and market research: Gathering qualitative and quantitative insights about brand perception.

The Data-Driven PR Process

The process can be divided into four key steps:

  1. Collecting data: Gathering relevant information through tools and analytics.
  2. Analyzing data: Using statistics, AI, and models to identify patterns and insights.
  3. Developing strategy: Defining communication goals, target groups, and messages based on findings.
  4. Measuring success: Tracking KPIs such as reach, engagement, or reputation to evaluate effectiveness.

Benefits of Data-Driven PR

Leveraging data provides several advantages:

  • Greater accuracy in reaching target audiences.
  • Increased efficiency through smarter resource allocation.
  • Transparency and accountability of results.
  • Early trend detection for faster response to market changes.

Challenges and Limitations

Despite its benefits, data-driven PR also presents challenges. Data protection and quality are critical factors. There is also the risk of focusing too heavily on numbers while neglecting creativity. Successful PR requires a balance between analytical precision and creative storytelling.

Conclusion

Data-driven PR is not a passing trend but a fundamental evolution of corporate communications. It enables more precise targeting, better performance tracking, and stronger strategic alignment. Organizations that combine smart data usage with human creativity will gain a decisive advantage in the battle for attention and trust.

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Failure Rates in University Studies – Causes, Challenges, and Possible Solutions

12/12/2024 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Failure Rates in University Studies – Causes, Challenges, and Possible Solutions

Introduction: A Growing Concern in Higher Education

High failure rates in exams and degree programs have been a significant challenge in the education system for years. Fields such as engineering, mathematics, and natural sciences are particularly affected. But what are the main reasons behind this issue, what consequences does it have, and how can universities and students address it together?

The Facts: Data and Statistics

According to recent studies, failure rates in disciplines like mechanical engineering, electrical engineering, and mathematics often exceed 40%. Similarly, fields such as law or economics show comparable rates in certain exams.

These figures not only impact students but also raise questions about the structure and support systems of higher education. First-year students, in particular, seem to struggle, highlighting the difficulties of transitioning from school to university.

Causes of High Failure Rates

The reasons for high failure rates are diverse and often interconnected:

  • Academic Overload: Many students find it challenging to keep up with the fast pace and complexity of course content.
  • Lack of Preparation: Secondary education does not always adequately prepare students for university demands.
  • Low Motivation: Students often choose programs without a genuine interest or understanding of the field.
  • Unfavorable Study Conditions: Overcrowded lectures, limited support services, and inefficient exam formats contribute to failure rates.
  • Personal Challenges: Financial difficulties, mental health issues, and poor time management further hinder academic success.

Consequences: Impact on Students and Universities

For students, repeated exam failures can lead to frustration, increased pressure, and, in the worst cases, dropping out. High failure rates also pose challenges for universities, as they affect graduation rates and the perceived quality of academic programs.

Furthermore, high failure rates raise concerns about the fairness and quality of education. Are exams designed appropriately, or is there a deeper structural issue in the education system?

Solutions: How to Reduce Failure Rates

Addressing high failure rates requires action at multiple levels:

  • Improved Preparation: Bridge courses or orientation semesters can help close knowledge gaps.
  • Enhanced Support: Small group work, tutorials, and regular feedback sessions can better support students.
  • Revised Exam Formats: Modern approaches such as project work or oral exams could alleviate pressure.
  • Mental Health Support: Counseling services and stress management workshops help students overcome personal hurdles.
  • Stronger School-University Collaboration: Early guidance and partnerships can ease the transition.

Conclusion: A Joint Path to Better Outcomes

High failure rates in university studies are a complex issue affecting both students and universities. Solving this problem requires joint efforts: universities need to adapt their programs and support systems, while students must take responsibility and demonstrate discipline.

With targeted measures and improved communication between all stakeholders, higher education can once again become a path to success – for individual students and for the education system as a whole.

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The Gini Coefficient: A Measure of Social Inequality

09/12/2024 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Introduction

The Gini coefficient is a statistical measure used to assess the income or wealth distribution within a specific population or country. It serves as a crucial tool for analyzing social inequality and is utilized by economists, sociologists, and policymakers worldwide. In this article, we will delve deeper into the Gini coefficient, its calculation methods, and its significance for society.

History of the Gini Coefficient

The Gini coefficient was developed in the early 20th century by the Italian statistician Corrado Gini. It was introduced in 1912 and has since become one of the most widely used indicators of social inequality. Initially designed for analyzing income distributions, the Gini coefficient is now also used for measuring the distribution of wealth, education, and other resources.

Calculation of the Gini Coefficient

The Gini coefficient is expressed on a scale from 0 to 1 or from 0 to 100, where 0 represents complete equality and 1 or 100 represents complete inequality. A Gini coefficient of 0 would indicate that all individuals have the same income or wealth, while a value of 1 or 100 suggests that one person possesses all the wealth.

The calculation of the Gini coefficient involves plotting the Lorenz curve, a cumulative distribution function of income or wealth against the cumulative population. The further the Lorenz curve is from the diagonal line, the more unequal the income or wealth distribution.

Mathematically, the Gini coefficient can be calculated as follows:

G = A / (A + B)

where:

  • G is the Gini coefficient,
  • A is the area between the Lorenz curve and the diagonal line,
  • B is the area under the diagonal line.

Significance of the Gini Coefficient

The Gini coefficient serves as an important indicator of social justice and wealth distribution within a society. Countries with a high Gini coefficient exhibit greater income or wealth inequality, while those with a low Gini coefficient are seen as more egalitarian.

High inequality can lead to social tensions, political instability, and hindered economic growth. Therefore, monitoring the Gini coefficient and implementing policies to reduce inequality are crucial for governments and organizations.

Criticism and Limitations of the Gini Coefficient

While the Gini coefficient is a useful tool for measuring social inequality, it also has its limitations. It does not take into account other important factors such as access to education, healthcare, or social services, which can also contribute to inequality.

Furthermore, the Gini coefficient may be difficult to compare between different countries due to varying cultural, economic, and social conditions.

Conclusion

The Gini coefficient is a valuable instrument for measuring income and wealth distribution and analyzing social inequality within a society. Despite its limitations, it remains a vital indicator for policymakers and researchers to monitor and improve resource distribution and equity. It is essential to consider the Gini coefficient in conjunction with other socio-economic indicators to gain a comprehensive understanding of a society's social conditions and challenges.

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What Services Does Statistical Consulting Include?

08/19/2024 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Statistics is an essential tool in many areas, from research and development to business decision-making. Statistical consulting firms offer professional support in data analysis, interpretation, and application of statistical methods. In this article, you will learn about the different services that statistical consulting includes.


Data Analysis

Data analysis is a central component of statistics. Statistical consulting firms assist businesses and researchers in collecting, preparing, and analyzing data.

  • Data Cleaning: Identifying and correcting erroneous or incomplete data.
  • Descriptive Statistics: Describing and summarizing data through statistical measures.
  • Inferential Statistics: Applying statistical tests and models to draw conclusions from data.

Statistical Consulting for Research

Statistics is an indispensable tool in scientific research. Statistical consulting firms support researchers in planning, conducting, and analyzing studies.

  • Study Design: Consulting on the selection of appropriate statistical methods and sample sizes.
  • Statistical Modeling: Developing and applying statistical models to investigate hypotheses.
  • Interpretation of Results: Assisting in the interpretation and communication of statistical findings.

Statistical Consulting for Businesses

Statistics also plays a significant role in the business world, such as market research, quality assurance, and decision-making. Statistical consulting firms offer services to support businesses.

  • Market Research: Analyzing market data to identify trends and customer preferences.
  • Quality Control: Monitoring and improving production processes through statistical quality control methods.
  • Decision Analysis: Assisting in the use of statistical methods to optimize business decisions.

Statistical Software and Training

The use of specialized statistical software is often required to conduct complex analyses. Statistical consulting firms offer training and support in selecting and applying statistical software.

  • Software Selection: Recommending and assisting in the selection of appropriate statistical software.
  • Training: Training employees in the use of statistical software and methods.
  • Technical Support: Providing technical support for statistical software and analyses.

Conclusion

Statistical consulting offers a broad range of services aimed at assisting businesses, researchers, and organizations in effectively utilizing data and statistical methods. Through professional data analysis, statistical modeling, and consulting, statistical consulting firms help their clients make informed decisions and achieve business success.

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The Media & PR-Database 2025

Media & PR Database 2025

The media and PR database with 2025 with information on more than 20,000 newspaper, magazine and radio editorial offices and much more.

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