Discover the real prompts Swiss B2B buyers use when researching suppliers via AI — and how to ensure your company appears in the answers.
A decade ago, a Swiss procurement manager researching new suppliers would type "ERP software Switzerland" into Google. Five years ago, they might have refined it to "best ERP software Swiss manufacturing SMB." Today, they open ChatGPT or Perplexity and type something entirely different:
"We are a Swiss manufacturing company with 180 employees, currently using SAP Business One but finding it too complex for our needs. What alternatives should we evaluate that integrate with our existing Swiss banking setup and support German and French interfaces?"
That is not a keyword search. That is a conversation. And the shift from keywords to conversations is transforming which companies get discovered — and which get ignored.
This article shares real examples of the prompts Swiss B2B buyers use across multiple industries and languages, analyses the patterns that emerge, and provides a concrete framework for adapting your content strategy to match how buyers actually interact with AI tools.
Based on testing across AI platforms and analysing real-world usage patterns, here are the kinds of prompts Swiss B2B buyers actually use — grouped by industry. These are not theoretical; they represent how modern buyers phrase their research queries.
Analysing hundreds of real buyer prompts reveals clear patterns that should shape your content strategy:
Traditional search queries stripped away context. "ERP Switzerland" tells you nothing about the buyer. AI prompts are rich with context: company size, industry, current tools, specific requirements, compliance needs, language preferences, and budget constraints.
This means your content needs to address specific scenarios, not generic categories. A page optimised for "ERP software Switzerland" will lose to a page that addresses "ERP alternatives to SAP Business One for Swiss manufacturing SMBs with 100-300 employees."
The most common prompt pattern is not "What is X?" but "Who should we talk to?" or "Who do you recommend?" Buyers are skipping the research phase and going straight to the shortlist. If your company is not in the AI's recommendation set, you are not on the shortlist — period.
Nearly every Swiss B2B buyer prompt includes Swiss-specific elements: FINMA compliance, multilingual requirements, Swiss data residency, integration with Swiss accounting systems (Abacus, Bexio), or explicit geographic preferences. If your content does not address these Swiss specifics, AI models have less reason to recommend you for Swiss queries.
This is a critical insight for Swiss B2B companies. Buyers in German-speaking Switzerland frequently switch between German and English when querying AI tools. They might ask the same question in both languages to compare answers. They might use English for technical queries and German for business queries.
Some real German-language prompts from Swiss buyers:
Your AI visibility needs to work in both languages. If you only optimise for English queries, you miss the German-language prompts — and vice versa.
Understanding these structural differences helps you create content that matches how AI processes buyer queries:
| Dimension | Google Search Query | AI Prompt |
|---|---|---|
| Length | 2-5 words | 20-80 words |
| Format | Keywords | Natural language sentences |
| Context | Minimal | Detailed (company size, industry, requirements) |
| Intent | Find information | Get a recommendation or decision |
| Expected output | List of links to explore | Direct answer with named companies |
Knowing how buyers actually prompt AI tools changes what you should publish:
Instead of optimising a page for "managed IT Zurich," create content that answers the full conversational query: "What to look for in a managed IT provider for a Swiss financial services company." Address the context, the requirements, the compliance needs, and the decision criteria. When an AI encounters a buyer prompt that includes all these elements, your content is a direct match.
Create content for the specific scenarios your buyers describe. If your clients are typically manufacturing companies with 50-200 employees migrating from legacy systems, write an article that addresses exactly that scenario. AI models match prompts to content based on specificity — the more your content matches the prompt's context, the more likely it is to be cited.
Do not treat German content as a translation of English content. Swiss buyers ask different questions in each language, use different terminology, and expect different cultural nuances. Your German content should be native German, written for a Swiss German-speaking audience, addressing the specific concerns they raise in their German-language prompts.
Buyer prompts reveal what information matters to them: pricing models, compliance certifications, integration capabilities, team size, client references, geographic coverage. If this information is absent from your website, AI models cannot include it in their recommendations — even if your company is the perfect fit.
The most effective GEO strategy starts with understanding exactly how your buyers query AI tools. Here is a step-by-step process for building a prompt library specific to your company:
Your sales team is a goldmine of prompt intelligence. Ask them to document the questions prospects ask in initial calls and emails. Common patterns include:
Each of these questions has an AI prompt equivalent. Buyers are increasingly asking these same questions to ChatGPT and Perplexity before — or instead of — contacting your sales team directly.
For each question pattern, create five to ten variations that reflect different buyer contexts:
Run each prompt variation across all seven major AI platforms: ChatGPT, Claude, Google AI Mode, Google AI Overview, Copilot, Perplexity, and Brave. Document:
The prompts where your company does not appear reveal content gaps. For each missing prompt, ask: "Does our website contain specific, factual content that directly addresses this question?" Usually the answer is no — and creating that content is your highest-priority GEO action.
Once you have your prompt library, use this framework to create content that directly matches buyer queries:
| Prompt Pattern | Content Type Needed | Example Content Piece |
|---|---|---|
| "Who are the best [category] in Switzerland?" | Category overview page | "Cloud ERP Solutions for Swiss Manufacturers: Complete Guide" |
| "Compare [product A] vs [product B]" | Comparison article | "SAP Business One vs Abacus: Which Is Right for Swiss SMBs?" |
| "What does [your category] cost?" | Pricing transparency page | "Managed IT Pricing for Swiss Companies: What to Expect in 2026" |
| "We need [specific requirement]" | Use case page | "ISO 13485-Compliant CNC Manufacturing for Swiss Medtech" |
| "What should we look for when choosing..." | Buyer's guide | "How to Choose a Swiss IT Security Partner: 8 Criteria" |
The most effective way to improve your AI visibility is to test it against the actual prompts your buyers use. per4mx does this systematically — simulating real buyer conversations across ChatGPT, Claude, Perplexity, and Google AI to see whether your company appears, how it is described, and what competitors are mentioned alongside you.
But you can start manually. Take the example prompts from your industry above, adapt them to your specific category, and run them across all major AI platforms. The results will tell you exactly where you stand — and where to focus your efforts.
B2B buyers rarely ask a single AI question. They have multi-turn conversations that progressively narrow their search. Understanding the typical follow-up sequence helps you create content that captures attention at every stage:
Your content needs to serve every stage of this conversation. If you appear in the initial query but the AI has nothing to say about your pricing or customer reviews in the follow-up, you may lose the prospect at stage four or five. Comprehensive, fact-rich content across your entire website — not just your homepage — ensures you remain visible throughout the buyer's AI conversation.
The shift from keyword search to conversational AI is not coming — it has already arrived. Swiss B2B buyers are asking AI tools detailed, context-rich questions about their specific needs. The companies that understand these prompts and build their content to match will be the ones AI recommends.
The companies that keep optimising for two-word keywords will wonder why their pipeline is drying up while their competitors — the ones the AI keeps recommending — grow steadily. The data is clear: listen to how your buyers actually ask, and build your presence to answer. To understand the technical mechanics behind this shift, read how AI search actually works. And for the tools to monitor and improve your visibility against real buyer prompts, see our guide to AI visibility tools for B2B.
Three practical approaches: (1) Ask your sales team to document the questions prospects ask in initial conversations — these mirror AI prompts closely. (2) Review your website's search analytics (if you have site search) for the questions visitors type. (3) Use per4mx's prompt simulation feature, which generates realistic buyer prompts based on your industry, company size, and competitive landscape, then tests your visibility against each one. The combination of sales intelligence and automated prompt testing gives you a comprehensive view of how buyers are likely to query AI about your category.
No. AI models process standard German (Hochdeutsch) much better than Swiss German dialect. While Swiss buyers may occasionally type queries in dialect, AI models translate and process them as standard German. Your content should be in standard German — clear, professional, and free of strong dialectal expressions. This ensures both AI models and human readers across the entire DACH region can understand your content. If you want to signal Swiss identity, do so through content topics (Swiss regulations, Swiss market data, Swiss-specific use cases) rather than through dialect.
For a baseline assessment, ten to fifteen prompts across seven AI platforms (70-105 total queries) gives you a statistically meaningful picture. Include a mix of: (1) three to four broad category queries ("best [category] in Switzerland"), (2) three to four specific requirement queries ("who offers [specific feature] for [industry]?"), (3) two to three comparison queries ("compare [competitor] and [your company]"), and (4) two to three German-language equivalents of the above. Run this set weekly for four weeks to establish a trend. per4mx automates this process, running dozens of prompts across all platforms on a configurable schedule.
Yes, there is natural variance in AI responses. The same prompt asked twice may produce slightly different recommendations, different ordering of companies, or different levels of detail. This is due to the probabilistic nature of language model generation. However, the variance is bounded — if your company has strong AI visibility, it will appear in the majority of responses to relevant prompts, even if the exact wording and positioning vary between queries. This is why monitoring over time (weekly) with consistent prompt sets is important: it smooths out the natural variance and reveals true trends in your visibility.
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