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What are the biggest mistakes in marketing?

11/02/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

1. Lack of target group analysis: an essential part of marketing is to understand and analyze the target group. If companies skip this step, it can be difficult to choose the right channels, advertising messages and strategies to reach the target audience.

2. Not being up to date: The ever-changing trends in digital marketing make it difficult for businesses to stay up to date. If businesses don't stay up to date, they can lose potential customers.

3. Insufficient resources: Many businesses don't have the necessary resources to launch and run successful marketing campaigns. Without enough staff, time and budget, it can be difficult to find a path to success.

4. Unclear messaging: When companies don't clearly define what they want to communicate to their customers, it can be difficult to send the right message to the right audience. Unclear messages can lead to misunderstandings and poor customer experiences.

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The art of starting a business: From idea to success

11/01/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Starting a business is an exciting adventure that appeals to many people. But the road from initial idea to success is often rocky and full of challenges. In this article, we take a look at the art of starting a business and how to go from a visionary idea to a thriving business.

The Idea: The Starting Point

Everything starts with an idea. It can come from personal experiences, passions or gaps in the market. However, a good idea is not enough. It must also be tested for its feasibility and marketability. Thorough market research is essential to determine if there is demand for the product or service.

The business plan: The blueprint for success

Once the idea is solid, it is time to create a business plan. This not only serves as a guide for the business, but is also an important document for potential investors and partners. The business plan should include a clear vision, goals, market analysis, marketing strategies and financial projections.

Funding: raising capital

One of the biggest hurdles for budding entrepreneurs is raising capital. This can be achieved through personal savings, loans, investors or crowdfunding. The choice of funding source depends on the type of business and individual circumstances. It is important to make realistic financial projections and consider all costs, including current expenses and salaries.

The legal form: choosing the right business model

Choosing the right legal form for the business is crucial. Whether sole proprietorship, limited liability company or public limited company, each has its own advantages and disadvantages in terms of liability, taxes and administration. It is advisable to seek advice from a professional in good time to find the best option.

The implementation: From plan to reality

With a solid business plan and sufficient funding, it is time to turn the idea into reality. This requires careful planning, hiring skilled staff, sourcing resources and developing products or services. The process often requires adjustments and flexibility to meet changing market conditions.

Marketing: Attracting customers

A successful business cannot thrive without an effective marketing strategy. This includes identifying the target audience, developing a strong brand identity and choosing the right marketing channels. Social media, content marketing and traditional advertising are just a few of the ways to build awareness and attract customers.

Scaling up: from start-up to established company

Once the business is successfully launched, the next challenge is scaling. This means expanding the business and entering new markets. This often requires additional capital and a smart business strategy. Preserving the company's culture and values is just as important as growth itself.

Perseverance: The Key to Success

The art of starting a business requires perseverance and determination. There will be setbacks and challenges, but successful entrepreneurs don't give up. They learn from their mistakes, adapt to new developments and stay true to their vision

In the world of starting a business, there are no guarantees of success, but the right planning, perseverance and passion can greatly increase the odds. The art of starting a business is an exciting journey that rewards those who are willing to take on the adventure. Those who want to go from idea to success should be guided by their vision and always look forward, because the world is waiting for the next innovative entrepreneurs who will change it.

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Advertising on LinkedIn: How to advertise successfully

11/01/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

In today's digital era, LinkedIn has become one of the most important platforms for professional networking and business communication. But LinkedIn is not just a place to expand your professional network. It is also a highly effective platform for advertising and marketing. In this article, we take a look at how you can successfully advertise on LinkedIn.

1. Target group definition is key

The first step to a successful LinkedIn advertising campaign is to accurately define your target audience. LinkedIn offers a variety of targeting options, including job title, industry, location, company size and more. The more specific you are in defining your audience, the more effective your advertising will be.

2. Create engaging ads

Your ads need to be engaging and relevant to your target audience. Use professional images and concise copy that clearly communicates your offer. Make sure your ads highlight the benefits of your products or services

3. Take advantage of LinkedIn's ad formats

LinkedIn offers several ad formats, including Sponsored Content, Sponsored InMail, Display Ads and more. Choose the format that best suits your goal and audience. For example, Sponsored Content ads work well to promote your content, while Sponsored InMail can be used for direct messaging to potential customers.

4. Go for storytelling

Stories are a powerful tool in marketing. Use LinkedIn to tell your company story. Explain how your product or service solves your customers' problems. Show success stories of customers or employees. A well-told story can create a deep emotional connection to your brand.

5. Test and optimise

Successful LinkedIn advertising often requires some experimentation. Test different ads, audiences and budgets to see what works best. Use LinkedIn's analytics tools to track the success of your campaigns, and optimise them regularly.

6. Budgeting and bidding strategies

Set a realistic budget for your LinkedIn advertising campaigns. LinkedIn offers several bidding strategies, including CPC (Cost Per Click), CPM (Cost Per Mille) and CPA (Cost Per Acquisition). Choose the strategy that best suits your goals.

7. Run A/B tests

A/B testing is an effective way to find out which ad variations perform best. For example, vary headlines, images or call-to-action buttons and analyse which version gets the best results

8. Continuous improvement

Successful LinkedIn advertising requires patience and continuous optimisation. Monitor your campaigns carefully, analyse the results and adjust your strategy accordingly.

Overall, LinkedIn offers a powerful platform for advertising in the professional environment. By accurately defining your target audience, creating engaging ads and continuously optimising your campaigns, you can successfully advertise on LinkedIn and reach your business goals.

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Ranking Informatik-Studium - At which university can you study in Germany?

11/01/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

In Germany, there are many universities and colleges that offer degree programmes in computer science. The choice of the best institution often depends on individual interests, the degree sought (Bachelor, Master, etc.) and personal preferences. Here are some renowned educational institutions that offer degree programmes in computer science:

Technische Universität München (TUM): TUM offers a Bachelor's programme in Computer Science and has several Master's programmes in Computer Science, including "Data Engineering and Analytics" and "Computational Science and Engineering."

Saarland University: This university offers a Bachelor's programme in Computer Science and Master's programmes in Computer Science, Visual Computing and more.

Rheinisch-Westfälische Technische Hochschule Aachen (RWTH Aachen University): RWTH Aachen offers a Bachelor's programme in Computer Science and various Master's programmes in Computer Science and Software Engineering.

University of Karlsruhe (KIT): KIT offers a Bachelor's programme in Computer Science and Master's programmes in Computer Science, Information Management and more.

Free University of Berlin: This university offers a Bachelor's programme in Computer Science and Master's programmes in Computer Science and Computer Science.

University of Stuttgart: The University of Stuttgart offers a Bachelor's programme in Computer Science and several Master's programmes in Computer Science, including "Autonomous Systems" and "Visual Computing."

Humboldt University of Berlin: This university offers a Bachelor's programme in Computer Science and Master's programmes in Computer Science, Data Science and more.

Technische Universität Berlin: TU Berlin offers a Bachelor's programme in Computer Science and several Master's programmes in Computer Science, including "Internet Technologies" and "Data Engineering."

University of Mannheim: The University of Mannheim offers a Bachelor's programme in Computer Science and a Master's programme in Data Science.

Technische Universität Darmstadt: This university offers a Bachelor's programme in Computer Science and various Master's programmes in Computer and Information Science.

The above-mentioned educational institutions are just a few examples, and there are many more universities and colleges in Germany that offer computer science or similar degree programmes. It is advisable to check the specific programmes, curricula and prerequisites at each institution to make the best choice for your computer science studies. Also consider the possibility of finding out about current rankings and assessments of computer science degree programmes.

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Which data analysis techniques work best for large unstructured data sets?

11/01/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

A variety of data analysis techniques are suitable for large unstructured data sets. Here are some of the best techniques:

Text mining and text analytics: these techniques are used to analyze unstructured text data, such as documents, emails, social media, and extract relevant information. Text mining algorithms can detect patterns, identify topics, perform sentiment analysis, and recognize important entities such as people, places, or organizations.

Machine Learning: Machine learning encompasses a variety of algorithms and techniques that can be used to identify patterns and relationships in large unstructured data sets. Techniques such as clustering, classification, regression, and anomaly detection can be applied to unstructured data to gain insights and make predictions.

Deep Learning: Deep Learning is a subcategory of machine learning that focuses on neural networks. Deep learning can be used to identify complex patterns in unstructured data. For example, Convolutional Neural Networks (CNNs) can be used for image recognition, while Recurrent Neural Networks (RNNs) can be used to process sequential data such as text or speech.

Image and video analysis: If the data set contains images or videos, special image and video analysis techniques can be applied. For example, techniques such as object recognition, face recognition, motion tracking, and content analysis are used.

NLP (Natural Language Processing): NLP refers to natural language processing and enables the analysis and interpretation of unstructured text data. NLP techniques include tasks such as tokenization, lemmatization, named entity recognition, sentiment analysis, translation, and text generation.

Big Data technologies: For large unstructured data sets, Big Data technologies such as Hadoop or Spark can be used. These technologies enable parallel processing and analysis of large data sets by running tasks on distributed systems or clusters.

It is important to note that the selection of appropriate techniques depends on the specific requirements of the data set and the goals of the data analysis. A combination of techniques may be required to gain comprehensive insights from large unstructured datasets.

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