Executive Strategy Briefing: AI-supported market expansion

The inevitability of AI in B2B expansion - Beyond productivity

The strategic imperative

The current market landscape is characterized by a technological disruption whose scope could exceed that of previous industrial revolutions. Generative artificial intelligence (AI) is no longer an optional tool to increase efficiency, but is becoming the primary lever for strategic growth and overcoming market stagnation. Companies that view AI merely as a tool for increasing productivity are failing to recognize its transformative potential. The true revolution lies in the redefinition of strategic core processes.

The business case - more than just efficiency

The economic value of generative AI is immense. An analysis by McKinsey identifies that around 75% of the potential value that AI use cases can deliver lies in four key business areas: customer operations, marketing and sales, software engineering, and research and development. This briefing focuses on redefining marketing and sales - the disciplines directly responsible for market development and revenue generation.

While many companies are still evaluating the return on investment (ROI) of AI projects, the discussion has already shifted: It is no longer about whether AI has a positive business case, but how quickly it can be implemented to unlock the "next productivity frontier".

The risk of stagnation

The urgency of this transformation is underlined by the risk of stagnation. Economists debate the exact impact on GDP, with some predicting productivity gains of up to 15%, while others are more skeptical. Regardless of the exact macroeconomic effect, the microeconomic reality for companies is clear: those who delay AI adoption risk being left behind. The German market is already showing signs of stagnation in the creation of new AI-related jobs, suggesting that implementation is slow.

Companies that hesitate now are not only missing out on a trend, but are risking their fundamental competitiveness. The ability to analyze markets faster, target customers more precisely and design campaigns more efficiently is becoming a key differentiator.

From AI tools to AI partners

The successful implementation of strategic AI tools such as Google Gemini, Microsoft Copilot or ChatGPT is fundamentally different to the introduction of conventional software. As an analysis by Harbinger Consulting aptly states, this is "not a software project - it's a cultural change".

This change is a prerequisite for realizing the full value of the technology. AI systems don't just change processes; they shift responsibilities, influence decision-making and require a redefinition of collaboration. Companies that embrace AI as a strategic partner will be able to realize its full potential. This briefing provides the roadmap for the first, crucial step: using AI to identify and develop new markets.

The strategic email sequence: a guide to AI-powered market development

The following three-email sequence is designed to convince B2B decision-makers of the benefits of generative AI for business expansion in a pragmatic and value-oriented way. Each email follows the strategic logic: opportunity (new possibilities through AI), risk (cost of inactivity) and solution (concrete, actionable steps).

Email 1: Beyond the edge of the plate: Identifying new industries through AI market analysis

Subject: Strategic expansion: How to discover hidden markets for your portfolio with AI

Dear Sir or Madam,

Growth is increasingly becoming a challenge in saturated core markets. For the first time, generative AI now offers the opportunity to fundamentally accelerate traditional, often manual market analysis. Instead of weeks of research, you can use AI models such as Google Gemini or ChatGPT to systematically compare your entire service portfolio with thousands of potential markets. This technology allows you to identify untapped "strategic markets at the click of a button" and "fragmented industries with consolidation potential" - opportunities that are often overlooked in traditional analyses.

The risk of not using this technology is a form of operational blindness. While you focus on optimization in known markets, your more agile competitors are already using AI to develop new diversification strategies. They identify and occupy highly profitable niches long before they appear on your radar. The result is not only missed growth potential, but a creeping stagnation of your core business.

However, the transition to AI-supported market analysis is a pragmatic process. Start by defining your own service portfolio not just as a list of products, but as a bundle of core competencies.

Here's how: Use the tried-and-tested prompts (instructional texts for AI) frombloola's online course (https://lp.bloola.com/de/schluss-mit-marketing-nach-gefuehl). The "clear step-by-step instructions" ¹ contained there, which are written specifically for entrepreneurs and not developers, show you how to precisely guide Gemini or ChatGPT to match your portfolio with the unmet needs of new industries.

Start discovering your hidden growth potential today.

Yours sincerely,

[Your name/company]

Email 2: From signal to conversion: precisely localize target companies and contacts with AI

Subject: No more cold calling: Find your ideal B2B customers precisely with AI

Dear Sir or Madam,

The biggest inefficiency in B2B sales is imprecise targeting. Generative AI is now revolutionizing lead generation from the ground up. Instead of relying on expensive, often outdated address lists, AI allows you to create dynamic, data-driven Ideal Customer Profiles (ICPs). Thanks to their deep integration, modern tools such as Microsoft Copilot can even analyze your internal CRM and email data to identify your most profitable existing customers. Based on this, specialized AI tools find external companies that exactly match this profile and already signal a "high purchase intent".

Sticking to manual research processes leads to immense efficiency losses. B2B lead research is not only extremely time-consuming; it is also unreliable. B2B contact data becomes outdated at a rate of around 30% per year due to job changes or reorganizations. Your sales team is wasting valuable time on irrelevant contacts and risking your company's reputation with spam filters with generic "one-size-fits-all" approaches.

Begin the transition to precision prospecting by leveraging your most valuable asset: Your own customer data.

Here's how: Use an integrated tool like Microsoft Copilot to analyze your CRM (e.g. with the prompt: "Create an Ideal Customer Profile (S37) based on the common characteristics of our top 10 customers"). Use these precise insights to scan the market with AI tools. In bloola's online course (https://lp.bloola.com/de/schluss-mit-marketing-nach-gefuehl) you will find a wide range of practical examples ¹ on how to use AI for automated lead qualification and identifying the right decision makers.

Make sure your sales force only talks to the right companies.

Yours sincerely,

[Your name/company]

Email 3: Hyper-personalization at scale: The AI-powered go-to-market campaign

Subject: From strategy to campaign in 48h: AI as your new go-to-market accelerator

Dear Sir or Madam,

Successfully targeting a new industry requires deep understanding and highly personalized content. Generative AI now makes possible what was previously impossible or unaffordable to do manually: "hyper-personalized marketing" at the touch of a button. Instead of weeks of planning, you can use AI to create in-depth B2B buyer personas that are often more accurate than manually researched ones. Based on these personas, AI generates all campaign content - from whitepapers to blog articles to email sequences - that answers the exact "Big 5" questions of your target customers: costs, problems, comparisons, disadvantages and competitive alternatives.

Traditional, generic marketing campaigns are ignored by B2B decision-makers and dismissed as a "one-size-fits-all" approach. Manually creating in-depth, industry-specific content is extremely time-consuming and costly. While you are still planning your first campaign, your AI-powered competitor has already A/B tested and optimized three different content approaches.

Use AI as an accelerator for your entire go-to-market (GTM) pipeline.

Here's how: Use AI to create a detailed persona for your new target industry (from email 1) and your ICP (from email 2). Then guide the AI to develop a content plan that solves the specific problems of this persona. bloola's online course (https://lp.bloola.com/de/schluss-mit-marketing-nach-gefuehl) provides you with actionable marketing examples ¹ to start creating your first AI-powered campaign and dramatically accelerate your time to market.

Start conquering your new markets faster and more relevant now.

Yours sincerely,

[Your name/company]

Strategic deepening: Why this approach works - from data analysis to culture development

The tactics presented in the email sequence are not isolated tricks. They are the result of a fundamental shift in strategic analysis enabled by generative AI. Understanding the underlying mechanisms is critical to successful implementation.

Analysis 1: The revolution in market analysis (foundation for email 1)

Traditional market research is reactive, slow and often based on limited data. AI-powered analysis, on the other hand, is proactive and scales analytical capability exponentially.

The process underlying Email 1 works as follows:

1. Portfolio analysis: a company feeds a generative AI (such as Google Gemini, which is optimized for broad searches) with its detailed portfolio of capabilities.
2. Abstraction of capabilities: The AI not only analyzes keywords (e.g. "cloud storage"), but understands the underlying capabilities and value propositions (e.g. "management of highly redundant, secure data streams in real time").
3. Market screening: In parallel, the AI analyzes publicly available market data, economic reports and industry news. It is trained to recognize "fragmented industries" - i.e. markets with many small players, little consolidation and often inefficient processes.
4. AI-supported insight (the "match"): The AI finds a match that a human would hardly have discovered. For example, it recognizes that the core competence ("management of highly redundant data streams") precisely solves the core problem of a fragmented industry (e.g. "inefficient supply chain telematics in regional building materials wholesale").
5. Strategic outcome: The company discovers a valid, strategic target for a buy-and-build strategy or a new area for organic diversification that would have remained hidden through manual analysis.

Analysis 2: The reinvention of B2B sales (foundation for email 2)

The biggest mistake in B2B sales is the "watering can" approach. It is based on the assumption that quantity leads to quality. The data proves otherwise: B2B contact data quality is abysmal (around 30% decay per year), and buying lists carries significant reputational and spam risks.

AI turns this process around. It doesn't start with the list, but with the Ideal Customer Profile (ICP).

1. The problem with ICP creation: Until now, ICPs were often based on the "gut feeling" of the sales team.
2. The Copilot solution: This is where the strategic value of tools like Microsoft Copilot lies. Thanks to its native integration with Microsoft 365, it can analyze internal company data (from CRM, emails, calendars) in a GDPR-compliant manner (with tools such as Microsoft Purview).
3. The analytical process: A manager can instruct Copilot: "Analyze our sales data from the last 24 months. Identify the common characteristics (industry, size, turnover, technologies used, buying cycle) of our 5% most profitable customers."
4. Strategic outcome: Sales receives a precise, data-based ICP based on actual success. Specialized AI lead tools use this ICP to scan the external market and identify only those leads that match this profile and signal a high purchase intent (e.g. through web behavior or job postings). Acquisition efficiency increases dramatically.

Analysis 3: The GTM pipeline (foundation for email 3)

B2B buyers are demanding. They expect hyper-personalization and content that solves their specific problems. Until now, creating such customized campaigns was extremely time-consuming and labor-intensive.

Generative AI automates strategic go-to-market (GTM) planning and content creation.

1. The B2B persona hurdle: Creating accurate B2B personas is traditionally difficult because decision makers are hard to interview and often operate in complex buying centers.
2. The AI persona solution: AI persona generators use vast amounts of public data (e.g. customer reviews, forum posts, LinkedIn discussions) to create in-depth B2B personas that are often more accurate than manually created ones.
3. The persona as a "brain": This AI persona becomes the basis of the entire campaign.
4. The GTM process: A marketer uses ChatGPT or Gemini and guides the AI: "Create a content plan that answers the 'Big 5' buyer questions for the persona [insert persona name]. Focus on (1) ROI/cost, (2) implementation issues, (3) comparison to, (4) use cases in, and (5) downsides of not implementing. Based on this, create an editorial (whitepaper), three blog posts and a 5-part email nurture sequence."
5. Strategic outcome: The company gets a coherent, psychologically sound and hyper-personalized campaign in hours instead of months. The marketing team is freed up from producing content and can focus on strategy and analyzing campaign results.

Implementation framework: from theory to practice

The effectiveness of the strategies described depends directly on the quality of the instructions given to the AI (prompting) and the choice of the right tool for the job.

The foundation: Effective prompt design for strategy development

A prompt is not a simple search query. It is a detailed, context-rich instruction. To get strategically valuable results, prompts need to be clear and specific.

Example prompt for email 1 (industry analysis with Google Gemini):

"You are a B2B market analyst with expertise in diversification strategies and identifying 'Adjacent Markets'. My company is a mid-sized provider of cybersecurity solutions, historically specialized in the German banking sector. Our service portfolio includes: (1) penetration testing for $ISO 27001$ certification, (2) real-time monitoring of transaction data for fraud detection and (3) phishing training for employees.

Analyze this portfolio and identify 5 'fragmented industries' or sectors outside of finance where these specific skills address a high unmet need. Evaluate each proposed industry based on (1) urgency of the problem (e.g. due to new regulation), (2) market size/potential and (3) competitive density."

Example prompt for email 2 (ICP creation with Microsoft Copilot):

"You are acting as a B2B sales analyst. Access CRM data from the last 24 months. Identify our top 10 customers based on total sales and profitability. Create a detailed Ideal Customer Profile (ICP) for our B2B offering based solely on the common characteristics of these top customers. The profile must include the following criteria: (1) demographics (industry, company size, region), (2) technographics (known software stacks or IT infrastructure used), (3) 'jobs-to-be-done' (what core problem do we solve for them?) and (4) the most common objections in the buying process."

Example prompt for email 3 (campaign creation with ChatGPT):

"You're a B2B campaign strategist with a focus on content marketing for products that require explanation. Our goal is the market launch of our [product] in the. The buyer persona is 'Head of IT & Digitalization' who is primarily interested in increasing efficiency and reducing costs, but has security concerns when implementing new platforms.

Create a complete content marketing plan that proactively answers the 'Big 5' buyer questions of this persona. The plan must include content for each stage of the buyer journey: (1) Top-of-funnel: A blog article on 'The 5 Hidden Inefficiencies in Logistics IT', (2) Mid-of-Funnel: A whitepaper on 'ROI calculation: how [product] amortizes in 12 months' (focus on cost/ROI), (3) Bottom-of-funnel: A comparison page 'Our product vs. [main competitor]' (focus on comparisons/disadvantages)."

Table 1: Strategic AI tool comparison for B2B expansion

The choice of AI model is a strategic decision. Executives need to understand which tool is best suited for which task to maximize ROI and manage GDPR risks.

Final recommendation: AI is not a tool, but a cultural change

This briefing has outlined how generative AI is transforming the core strategic functions of market expansion - industry identification, lead generation and campaign creation. However, the ability to automate and improve these processes is only the consequence of a deeper change.

The real challenge, and at the same time the greatest opportunity, lies not in the technology itself, but in the organization. Analyses clearly show that the promised productivity gains will not materialize if AI is only seen as a "tool". Success requires a "customized AI strategy" that is consistently aligned with the overarching corporate goals.

The introduction of AI is a cultural change. It shifts responsibilities and requires a massive investment in employee training. The human resources (HR) department becomes the key point in the transformation of role profiles, as traditional tasks (such as manual research or text creation) are automated and strategic analysis skills (such as prompting and interpreting AI results) come to the fore.

The recommendation to management is therefore: don't see AI implementation as an IT project, but as a central element of your corporate strategy. The next step is not the purchase of licenses, but the strategic decision on how AI should fundamentally change your processes, your decision-making and the roles of your employees.