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The Best Sales Strategies for B2B Providers & SaaS Companies in 2025

15d ago | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

In 2025, B2B providers and SaaS companies face new challenges in sales: increasing competition, more complex buying decisions, and evolving customer needs. At the same time, digital tools, data analytics, and automation offer enormous opportunities. But which sales strategies are particularly effective today for generating leads, winning customers, and building long-term relationships?

1. Account-Based Selling (ABS) and Targeted Focus
Account-Based Selling is the standard strategy for complex B2B sales in 2025. Instead of sending broad, generalized offers, companies focus on selected key accounts. Through precise analysis of target customers and personalized outreach, conversion rates can be significantly increased.

2. Combining Inside Sales and Field Sales
Digital tools make it possible to manage the entire sales process more efficiently. Inside sales teams qualify leads and conduct initial meetings online, while field sales staff are deployed for in-person meetings or complex negotiations. This combination improves efficiency and reduces wasted effort.

3. Sales Automation and CRM Systems
Modern CRM systems and automation tools support lead management, follow-ups, and pipeline tracking. AI-powered lead scoring models help identify high-potential deals early and prioritize resources effectively. This ensures the sales team focuses on the most promising opportunities.

4. Value-Based Selling and Customer Success
The focus is on delivering value to the customer. SaaS companies increasingly rely on value-based selling, where the pitch emphasizes the tangible benefits of the software rather than price alone. At the same time, strong customer success teams ensure long-term retention and create upselling opportunities.

5. Multichannel Sales Strategy
By 2025, a single-channel approach is no longer sufficient. Successful companies use a mix of email, social selling, webinars, trade shows, and events. Digital tools like LinkedIn Sales Navigator, targeted content campaigns, and retargeting complement this strategy, increasing visibility with the right decision-makers.

6. Data-Driven Sales Optimization
Analyzing sales metrics is critical for strategy adjustment. Conversion rates, sales cycle duration, customer feedback, and market trends provide valuable insights. Companies that operate data-driven can continuously optimize their processes and increase their success rates.

Conclusion:
The best sales strategies for B2B providers and SaaS companies in 2025 combine personalization, digital tools, and data-driven decision-making. Account-Based Selling, sales automation, value-based selling, and multichannel approaches are key to success. Companies that implement these strategies consistently not only acquire new customers but also build sustainable relationships and secure long-term growth.

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What is Data Scraping?

22d ago | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Whether it's product prices, job listings, real estate offers, or stock market data: the internet is full of publicly available information. But when that data is collected in large volumes and automatically processed, it’s called data scraping. A term that’s increasingly relevant in the age of AI, big data, and digital business models — but also legally and ethically controversial.

Definition: What is data scraping?

Data scraping refers to the automated process of extracting data from websites or online platforms. Special software tools or scripts — known as scrapers — scan websites, identify structured information (like tables, text, or metadata), and save it into databases or spreadsheets for further use.

Common use cases for data scraping include:

  • Price monitoring in e-commerce (e.g. comparing Amazon and eBay listings)
  • Tracking job postings across multiple career sites
  • Analyzing customer reviews or forum comments
  • Extracting contact data from online directories

The data collected is often used for market research, competitive analysis, lead generation, or training artificial intelligence systems.

Technically simple, but not always legal

Technically speaking, data scraping is relatively easy. Even a basic Python script using libraries like BeautifulSoup, Scrapy, or Selenium can extract web content automatically. Browser plugins and low-code tools have made it even more accessible to non-programmers.

But legally, data scraping is a gray area. In the EU and Germany, website content is protected under copyright laws, even if it's publicly accessible. Mass copying and reuse of data may violate copyright law, website terms of service, or the General Data Protection Regulation (GDPR) — especially when personal data is involved.

Major platforms like LinkedIn, Facebook, and Amazon actively fight unauthorized scraping. At the same time, many companies use scraping techniques themselves for competitive intelligence or market analysis.

Data scraping vs. APIs: A legal alternative?

Many websites now offer APIs (Application Programming Interfaces) — official access points for retrieving structured data legally and efficiently. APIs are stable, documented, and often permitted under clear usage terms. However, they are sometimes limited, expensive, or don't provide all the data a company wants.

As a result, scraping is often the “unofficial” workaround, especially when no API is available or when the API limits usage too tightly.

Use cases: From SEO to AI training

Data scraping plays a key role in various digital business models. Common fields of application include:

  • SEO: Tracking search engine rankings, analyzing competitors’ content
  • E-commerce: Dynamic pricing, catalog monitoring, offer comparisons
  • Finance: Real-time news, market signals, or portfolio tracking
  • Artificial Intelligence: Gathering training data for chatbots, language models, or image recognition

Journalists also use scraping, especially in investigative and data-driven reporting — for example, to analyze large data leaks or identify hidden patterns in public records.

Risks and ethical concerns

Despite its usefulness, data scraping raises serious legal and ethical issues. In addition to copyright and privacy concerns, it also raises questions of fair use and server load — scraping can overwhelm websites with automated requests. Some platforms block scrapers or deploy bot detection tools to prevent abuse.

There is also risk of misuse: scraping can be used for spam, misinformation, or even identity theft — for example, by harvesting email addresses or profile pictures from public sites.

Conclusion: Powerful, but with limits

Data scraping is a powerful tool in the data-driven economy. It provides access to information that would otherwise be difficult to obtain — enabling insights, automation, and innovation. However, the line between smart data strategy and legal violation is thin.

Anyone who wants to use scraping professionally must not only understand the technical side, but also comply with legal frameworks, follow ethical guidelines, and ensure responsible data handling.

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Content Marketing – Mass Job Losses Among Copywriters and Content Creators Due to AI

10/09/2025 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Digitalization has transformed many professions over the past decades, but rarely has a shift been as rapid and disruptive as the one currently unfolding in content marketing. With the rise of artificial intelligence (AI) — particularly generative language models like GPT-4 and Google's Gemini — an entire profession is under threat: content writers, copywriters, and freelance authors are facing a wave of displacement. What was once considered essential creative work is now increasingly automated. A structural shake-up is underway — with far-reaching consequences for companies, agencies, and workers alike.

AI writes — faster, cheaper, and more scalable

The business case for AI in content marketing is hard to ignore: Artificial intelligence can generate SEO-optimized blog posts, product descriptions, newsletters, or social media captions within seconds — 24/7, without vacation, sick days, or minimum wage.

Take this example: where a human copywriter used to spend several hours on a well-researched blog article, an AI model like GPT-4o can generate multiple versions of the same topic in minutes. Tools like Jasper, Neuroflash, and Writesonic already offer “Content-as-a-Service” — often at a fraction of traditional costs.

According to a recent study by the Institute for Employment Research (IAB), up to 40% of freelance content writers in Germany feel their livelihoods are threatened by AI. In the US and UK, the trend is even more pronounced, with major media companies having already laid off or significantly downsized their writing teams.

Layoffs, pay cuts, outsourcing

“I’ve worked as a freelance copywriter for over ten years for agencies and startups, but since early 2024, I’ve barely received any new assignments,” says Sandra K., a freelance writer from Hamburg. “Many clients now generate their texts with AI and only book an editor — if at all.”

Similar stories are emerging across the industry: permanent positions are being cut, freelancer rates slashed, or contracts canceled altogether. Entry-level and junior writers are particularly affected, as their typical tasks — simple product texts or social media captions — can now be almost entirely automated.

Major agencies like Jung von Matt and Serviceplan are already experimenting with AI systems for automated content creation. Meanwhile, companies are bringing content production in-house, as AI-driven tools have become easy enough for non-experts to use.

"Human creativity is irreplaceable" — or is it?

Supporters of human-written content argue that real creativity, empathy, and cultural nuance remain unique to humans. But technological advances in recent years are challenging that assumption.

AI-generated texts can now mimic tone, style, humor, emotion, and target group appeal with surprising accuracy. The line between human and machine-generated writing is becoming increasingly blurred — not just for readers, but also for editors and marketing professionals.

“We now let AI write about 70% of our blog content,” says Lisa Meier, head of content at an e-commerce company. “The quality is more than sufficient — and with a bit of editing, nobody can tell the difference.”

New roles, new opportunities — or just hot air?

While traditional writing jobs are declining, new roles are emerging around the use of AI in marketing: prompt designers, AI editors, content curators. But these new jobs require different skillsets — technical knowledge, data literacy, and strategic thinking. For many copywriters, the transition is difficult.

“The shift toward AI-supported work isn't inherently bad,” says labor market expert Dr. Jens Langenbach. “But we’re witnessing a massive restructuring: those who don’t retrain or specialize will be left behind.”

Educational institutions and industry associations are also under pressure: training programs for copywriters or online editors often feel outdated. AI proficiency, data analysis, and tool literacy should already be core curriculum — but the pace of institutional adaptation lags behind the technology itself.

Ethics, quality, and trust — where is content heading?

Beyond economic concerns, ethical and qualitative issues are also surfacing: Can we still trust AI-generated content? Who is responsible for misinformation, plagiarism, or biased language produced by machines?

Experts also warn of a looming “content inflation”: as every company begins using AI to produce vast amounts of content, attention for individual posts drops — and public trust in the credibility of online sources erodes.

“Content marketing risks becoming a soulless blend of sameness,” warns media ethicist Prof. Dr. Katharina Scholz. “That’s why we still need human curators who work with integrity, originality, and responsibility.”

Conclusion: An industry in transition — the end or a new beginning?

The mass job losses in content marketing are real — and accelerating. Artificial intelligence is transforming how we create, consume, and evaluate content. For many writers, this means reskilling, specializing, or saying goodbye to a once-creative and independent profession.

Yet the upheaval also creates opportunity. Those who understand AI tools, think strategically, and are willing to redefine their roles can still thrive in the new content ecosystem — perhaps even with more influence than before.

The question remains: In the future, will we still know — or even want to know — whether a piece of content was written by a human?

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Scaling as a B2B SaaS Company – Strategy and Tactics Including Marketing and Sales

10/06/2025 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Scaling a B2B SaaS company is one of the biggest challenges in today’s software industry. Growth means not only acquiring more customers but also expanding processes, technology, marketing, and sales efficiently and sustainably. Successful scaling requires a clear strategy and concrete tactics across all areas of the business.

1. Strategic Foundations of Scaling

Before scaling, a solid foundation is essential:

  • Product-Market Fit: The SaaS product must precisely meet the needs of the target audience and deliver real value.
  • Customer Understanding: Deep knowledge of buyer personas, industries, pain points, and decision-making processes is indispensable.
  • Scalable Business Model: Pricing, sales channels, and support structures must be designed for growth.
  • Technical Scalability: The software’s infrastructure and architecture must handle increasing user numbers and demands smoothly.

2. Marketing Strategy for Scaling

Marketing plays a central role in increasing reach, generating qualified leads, and positioning the brand as a trusted partner.

  • Inbound Marketing: Content marketing, SEO, webinars, whitepapers, and thought leadership help gain organic visibility and attract potential customers.
  • Account-Based Marketing (ABM): Targeted campaigns that address key accounts with personalized messages.
  • Marketing Automation: Automated workflows and lead nurturing systematically qualify prospects and prepare them for sales.
  • Branding and Positioning: Clear messaging and a strong brand presence build trust and differentiation in a competitive market.

3. Sales Strategy and Tactics

Sales in B2B SaaS requires a blend of digital and personal approaches:

  • Sales Development Representatives (SDRs): They qualify leads and pave the way for Account Executives.
  • Account Executives (AEs): Responsible for consulting, negotiations, and closing large deals.
  • Customer Success Management: Essential for customer retention and upselling after closing deals.
  • Self-Service and Freemium Models: Enable scalable entry points that sales teams can complement later.

4. Key Metrics (KPIs) for Scaling

Scaling must be continuously monitored and adjusted:

  • Customer Acquisition Cost (CAC): How much does it cost to acquire a new customer?
  • Customer Lifetime Value (CLV): How much revenue does a customer generate over the entire relationship?
  • Churn Rate: How many customers are lost over a specific period?
  • Monthly Recurring Revenue (MRR): Steadily increasing recurring revenue forms the growth foundation.
  • Conversion Rates: From visitor to lead, lead to customer — every stage must be optimized.

5. Organizational and Technological Scaling

Growth also requires internal adjustments beyond marketing and sales:

  • Team Structure: Clear roles, responsibilities, and efficient collaboration between marketing, sales, and customer success.
  • CRM and Sales Tools: Automation, data analysis, and pipeline management support handling large volumes.
  • Scalable IT Infrastructure: Cloud services and microservices architectures enable fast growth and flexible development.

6. Challenges and Success Factors

Common pitfalls include:

  • Poor lead quality
  • Unclear target audience messaging
  • Lack of alignment between marketing and sales
  • Customer churn
  • Technical bottlenecks and performance issues

Success factors include:

  • Clear strategic direction
  • Data-driven decision-making
  • Agile processes and fast feedback loops
  • Investment in customer retention and support
  • Continuous learning and adaptation

Conclusion

Scaling a B2B SaaS company is a holistic process that combines strategic thinking and operational execution. Only when marketing, sales, product, and organization work harmoniously can sustainable and profitable growth be achieved. With the right strategy, clear KPIs, and continuous optimization, successful expansion is within reach.

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Succeeding Online in 2025 – What Really Matters for B2B Companies

10/02/2025 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

The digital B2B market is more dynamic than ever: buyers expect speed, transparency, and personalized offers. Technologies like AI, automation, and data-driven marketing are reshaping the rules of the game. So what really determines online success for B2B companies in 2025?

Digital Visibility Remains Key

Even in 2025, the rule stands: if you’re not visible online, you hardly exist for potential customers. SEO, paid media, and above all relevant content remain essential. Personalization continues to grow in importance – content must not only be informative, but also tailored to industries and buyer personas.

“In B2B, having a website is no longer enough – you must be visible, helpful, and trustworthy throughout the customer journey.”

Customer-Centricity as a Competitive Advantage

Successful B2B companies focus not on their product, but on solving customer problems. This means:

  • Clear buyer personas backed by data insights.
  • Content across the entire funnel – from awareness to conversion.
  • Digital-first service: quick response times, self-service portals, chatbots.
Tip: Customer-centricity is not just a marketing tactic – it’s a cultural commitment. Without internal adoption, initiatives remain superficial.

Technology & Automation

AI-driven tools, marketing automation, and CRM systems are already standard. In 2025, the focus is on integration: data from sales, marketing, and service must flow seamlessly to enable consistent customer journeys and tailored offers.

Equally important: data literacy within teams. Technology is only as effective as the people who know how to use it.

Trust and Thought Leadership

B2B buyers invest in solutions built for the long term. Trust is built through content, references, and digital presence. Formats such as whitepapers, expert blogs, webinars, and industry podcasts strengthen positioning as a thought leader.

The Human Touch in a Digital World

Despite automation, the human factor remains decisive. Digital channels initiate contact – but deals are often closed in personal conversations. Successful B2B companies combine digital efficiency with human relationships.

The Five Success Factors for 2025 at a Glance

  1. Visibility through relevant, personalized content.
  2. Customer-centricity across all touchpoints.
  3. Integration of technology, data, and automation.
  4. Building trust and thought leadership.
  5. Balancing digital efficiency with human interaction.

Conclusion

Succeeding online in 2025 is no coincidence – it’s the result of strategic planning and cultural adaptation. Companies that keep customers at the center, integrate technologies effectively, and build trust will lead the market in the long term.

The internet is no longer just a sales channel – it’s the central marketplace.

Note: This article summarizes key trends. Each B2B company should conduct its own analysis and benchmarking to develop a tailored digital strategy.

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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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