B2B nutraceutical leaders stand at a critical crossroads. The market is dynamic and increasingly complex. Global economic growth remains uneven, competition is intensifying, and B2B buyers are behaving like end consumers. They demand value-driven purchasing experiences and are increasingly willing to switch suppliers in search of better content and offerings. In such a competitive and evolving landscape, how can nutraceutical B2B companies maintain their market position and break through barriers to growth?

Buzzwords like agility, adaptability, and transformation are widely embraced, yet many companies struggle to implement actionable strategies that keep pace with changing market demands.

McKinsey’s latest B2B Pulse Survey highlights that only 20% of companies report consistently implementing AI-powered strategies. (1) Hence, companies investing in digital solutions and AI outperform their competitors in growth and efficiency. Ai-driven technologies particularly enable the following aspects:

• AI-driven Micro-Segmentation & Lead Prioritization - to segment customers more precisely, identify new opportunities, prioritize high-value customer groups, and implement effective churn management strategies.
• AI-Enhanced Sales Performance - helping sales teams better prioritize leads, automate customer touchpoints, and enhance go-to-market strategies. Chatbots and AI-assisted sales tools enable real-time, data-driven decision-making.
• AI-Enabled Dynamic Pricing & Deal Optimization - using real-time data to adjust prices dynamically. AI can tailor deal structures to customer needs while improving overall price discipline and competitiveness.
• AI-Powered Workforce Development – reshaping workforce capabilities and equip sales teams with real-time problem-solving skills, AI-driven analytics expertise, and technical know-how.
• Personalized Marketing & AI-Driven Customer Engagement – is needed, because the era of one-size-fits-all marketing is over. AI enables hyper-personalization, tailoring product positioning, messaging, and customer engagement based on specific market needs. This is the focus of this paper.
• AI-Powered Content Generation & Visual Design - to automate the creation of market-specific texts based on authentic consumer language, generate culturally tailored visuals for each target market, and scale marketing materials across multiple regions while maintaining scientific accuracy.

By 2030, 1.2 billion women worldwide will be experiencing menopause, representing a significant market opportunity for nutraceutical manufacturers focusing on metabolic health solutions. Menopause is a significant hormonal transition that brings various physiological changes, including an increased risk of unbalanced glucose metabolism and Type 2 diabetes. The decline in estrogen levels plays a critical role in insulin sensitivity, fat distribution, and metabolic regulation, making postmenopausal women more vulnerable to metabolic disorders. This demographic shift coincides with increasing awareness of the specific metabolic challenges women face during this transition. Studies indicate that up to 60% of postmenopausal women suffer from metabolic dysregulation (2) due to declining estrogen levels, which directly impacts insulin sensitivity, fat distribution, and glucose metabolism. Unbalanced glucose metabolism in menopausal women is not just a short-term concern but a long-term health challenge, increasing the likelihood of developing Type 2 diabetes, cardiovascular disease, and metabolic syndrome. For nutraceutical ingredient suppliers, specializing in glucose tolerance and metabolic regulation, this growing demographic presents both a significant opportunity for innovation and a complex marketing challenge that requires cultural sensitivity. The traditional approach to international market research for metabolic health ingredients would involve months of focus groups interviews, and surveys. By leveraging a strategic combination of AI tools, companies can dramatically accelerate this process while enhancing the depth and quality of insights. In this case study, AI-tools were used to obtain market research, consumer insights, to carry out data analyses as well as to scale marketing content and adapt messages for different European markets.

The methodical approach used different AI tools working in concert. In this case study, first Perplexity (using Claude Sonnet 3.5), was applied using the “Pro Search” or “Deep Research” setting to analyze forum posts across five European markets, identifying authentic consumer language about metabolic symptoms. A simple effective prompt might be: “Analyze the product reviews for X. List the top 5 likes and top 5 dislikes and find 3 typical verbatim quotes. Pay special attention to emotional experience reports.” Prompting is about testing and starting over. If you can communicate, you can prompt. Gen AI is human-like, and we need to apply human-like communication when creating prompts. Think about the work instructions you would give to a new team member—detailed, without assuming prior knowledge. The same patience and iterative approach are needed when communicating with AI. Best results come from using different AI tools in parallel to reframe prompts and technologies. For more detailed guidance on creating structured prompts for metabolic health content, see Figure 1, Learning Box 1. Systematic analysis of “pains” and “gains” were done, authentic quotes were collected, physical and psychological symptoms were reviewed as well as social impact, long-term challenges and nutraceuticals being used queried. The systematic AI analysis of consumer voices provides not only insights into complaints and needs. It also enables targeted communication in different markets using appropriate customer language. This makes it an indispensable tool for international product development and marketing in the nutraceutical industry.

Figure 1. Learning Box 1

In a second step ChatGPT (o1) was employed to organize unstructured data into actionable marketing frameworks like SWOT (Strengths, Weaknesses, Opportunities, Threats) and STP (Segmentation, Targeting, Positioning), establishing clear go-to-market strategies for metabolic health products in each country. While collecting market research data is crucial, the real challenge lies in transforming it into actionable insights. This is where AI tools excel - turning complex data sets into clear strategic frameworks and marketing concepts. The real power of AI emerges when applying established marketing frameworks to the structured data.

In the final step, Midjourney (6.0) was applied to develop culturally appropriate visual concepts that resonate with women experiencing metabolic challenges in each market, creating cohesive visual identities that align with local perceptions of metabolic health.

For more detailed guidance on AI tools, see Figure 2, Learning Box 2.

Figure 2. Learning Box 2

This AI-enabled methodology allowed for simultaneous analysis of multiple markets in hours rather than weeks, capturing nuanced cultural differences in how metabolic challenges are discussed. Please see an overview of the profess flow in figure 3.

Figure 3. AI-Powered Market Analysis Process

The value of AI in metabolic health product marketing goes far beyond simply accelerating research. Through AI analysis, we discovered profound differences in how metabolic challenges during menopause are conceptualized across markets, which is reflected in authentic user forum discussions. The following table 1 shows the cultural perceptions of metabolic health found in this case study.

Table 1: Cultural Perceptions of Metabolic Health: Beyond Data Acceleration

Particularly, the authentic voice from user forums gives valuable insights into difference of consumer perspective. As one French forum participant noted: "La ménopause, ce n'est pas une maladie, c'est une transition," indicating that glucose fluctuations may be a short-term adjustment. Meanwhile, an Italian counterpart shared: "La menopausa non è una malattia, è un viaggio" (“Menopause is not an illness, it's a journey”), implying a more extended metabolic adaptation. These perspectives directly influence how women approach metabolic solutions in each market. The subtle distinctions in how metabolic changes are contextualized, automatically identified and categorized by AI, provide crucial guidance for developing resonant messaging about glucose tolerance products that aligns with cultural expectations rather than imposing standardized global approaches. Localization ensures accurate translation of metabolic health messaging across markets, while AI-powered tried to add cultural adaptation depth by precisely aligning content with each market's specific understanding of glucose metabolism and related health concepts. For example, when addressing metabolic symptoms, terms like "glucose spikes" or "energy crashes" aren't simply translated verbatim but are recontextualized within the appropriate cultural framework.

In table 2 we summarize the country-specific metabolic health messaging in action. Localization ensures accurate translation of metabolic health messaging across markets, while AI-powered cultural adaptation adds depth by precisely aligning content with each market's specific understanding of glucose metabolism and related health concepts. Each message utilized the authentic language identified in the initial research phase, focusing exclusively on 'Improving Glucose Tolerance in Women during Menopause'

Table 2 Country-Specific Metabolic Health Messaging in Action

The integration of AI tools into metabolic health, B2B marketing, offers transformative benefits.

First to capture the metabolic market intelligence and to gain the market insight that a rapid, simultaneous analysis of how glucose tolerance is discussed across multiple markets provides competitive intelligence that would be prohibitively expensive through traditional methods.

Second, an authentic metabolic health language, as AI-powered analysis reveals authentic consumer language about blood sugar and energy fluctuations within cultural frames that traditional research might miss. Furthermore, it supports an accelerated Metabolic Product Launch, as the development cycle from metabolic product concept to market-ready content is compressed from months to days. Finally, it enables a culturally Precise Glucose Messaging. Communication about glucose tolerance avoids cultural pitfalls while leveraging market-specific opportunities.
For nutraceutical B2B companies seeking to capitalize on the growing market for glucose tolerance solutions for menopausal women, this approach offers a template for success that balances efficiency with the cultural sensitivity required for effective international marketing of metabolic regulation products. Please see a summary of the key takeaways in Figure 4 as well as figure 5, learning box 3, showing a Side-by-side comparison of Traditional B2B Marketing vs. AI-Enhanced B2B Marketing including estimated time needed for each activity. AI is a powerful enhancement to B2B marketing that works best when combined with human expertise. All AI-generated results must be carefully reviewed and validated by professionals. Actual time savings vary depending on task complexity, quality of available data, and the degree of integration of AI solutions into existing processes.

Figure 4. Key Takeaways and Next Steps

Figure 5. Learning box 3 – AI tools

Technologies used yesterday will be replaced by new AI tools today. Will results differ when applying deep seek or Agents? This is content for the next publication. If you like to discuss results of this case study or if you would like to learn more about prompt generation and applying AI, please feel free to contact the authors.

Important Note on AI-Generated Content
The AI-generated texts and strategy suggestions shown in this article are based on our experiences with current AI tools. From our experience, these outputs typically achieve an accuracy of approximately 80% and may contain inaccuracies, cultural misunderstandings, or outdated information.

They do not replace critical review by subject matter experts with cultural and professional expertise. All AI-generated content should be considered a starting point for ideation and thoroughly validated, revised, and reviewed by native speakers and domain experts before use in marketing campaigns. Actual market success depends on adequate human post-processing and adaptation.