Case study: Market entry in Germany — building AI-visible credibility from zero

A Polish industrial manufacturer with 20 years of operational history and a strong domestic client base decided to enter the German market. Their product quality was proven. Their references were solid. Their pricing was competitive.

There was one problem: in Germany, they did not exist.

Not in Google. Not in trade press. Not in any industry database a German procurement manager would consult. And — as we discovered in the first week of our engagement — not in a single AI-generated answer to any relevant sector query.

This is the story of how we changed that in 90 days.

The client

A mid-size manufacturer of industrial components operating primarily in Poland and Central Europe. The company — referred to here as the Client — had revenues above €30 million, an established engineering team, and certifications meeting EU standards. Their products were in active use across Polish, Czech, and Hungarian industrial facilities.

They had never needed to think about their digital presence. In their home market, relationships and referrals carried the business. In Germany, that advantage did not transfer.

The challenge: invisible by default

When the Client's leadership team began exploratory conversations with German procurement contacts, they encountered a consistent pattern. Decision-makers would ask for the company name, conduct a brief online search, find very little, and move to the next conversation. The due diligence threshold in German industrial procurement is high — and digital credibility is a baseline expectation, not a bonus.

We were brought in after one of these conversations produced a direct question from a German potential partner: "We cannot find any independent information about your company online. Can you help us understand why?"

Our initial audit confirmed the scale of the problem. The Client's German-language digital footprint was essentially zero. There was no German Wikipedia entry. No mentions in German trade publications. No German-language press releases. No schema markup identifying the company as an EU-certified manufacturer. And when we ran systematic prompts across ChatGPT, Perplexity, and Google AI Overviews asking about industrial component suppliers serving the German market — the Client did not appear in a single response.

Their Share of Model was 0%.

The diagnostic: what German B2B buyers actually check

Before beginning any work, we mapped the actual research behaviour of German industrial procurement teams. The pattern was consistent across company sizes:

First, a name search on Google — primarily to confirm existence and find a German-language presence. Second, a check of industry databases and certification registries. Third, an increasingly common step: a query to an AI assistant asking for an overview of the supplier category or a direct question about the specific company.

German procurement culture places particular weight on verifiable third-party confirmation. A company's own website carries limited weight without corroborating references from independent sources — press coverage, industry association membership, certification body listings, and increasingly, AI-generated summaries that confirm the company's existence and positioning.

The Client had none of these signals in the German market. Fixing this required building them systematically, in the right sequence.

The programme: 90 days, four workstreams

Workstream 1 — Structured data and German-language web presence (Weeks 1–2)

We began with what AI systems and search engines read first: structured technical signals. This included adding German-language schema.org markup to the Client's website identifying the company, its product categories, certifications, and operating markets. We created a German-language company description page with unambiguous, factually precise language — not marketing copy, but the kind of neutral, declarative text that AI systems extract and cite.

We also submitted the company to relevant German industry directories and certification registries, ensuring that the basic factual record existed in the databases that procurement tools query.

Workstream 2 — Wikipedia (Weeks 2–4)

A neutral, well-referenced Wikipedia entry is the single most high-impact action available in a GEO programme. We drafted an entry covering the company's founding, product range, certifications, and EU market presence — strictly in encyclopaedic tone, relying on verifiable references including the company's published certification documents, trade association membership records, and existing Polish press coverage.

The entry was submitted, reviewed, and published within three weeks. It immediately became the most-cited source about the company across AI platforms.

Workstream 3 — Authority content in German trade press (Weeks 3–10)

We identified four German industrial trade publications with active digital archives indexed by major AI systems. Working with the Client's engineering team, we developed two bylined technical articles — one on component specification tolerances in German industrial standards, one on supply chain resilience for Central European manufacturers — and placed them under the Client's name.

We also secured two editorial mentions: a company announcement in a sector newsletter and a brief profile in a DACH manufacturing industry roundup. None of these required advertising spend. They required expert content and editorial relationships.

Workstream 4 — Share of Model tracking (Ongoing from Week 1)

From the first day of the engagement, we ran weekly prompt testing across ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot. We tracked a set of 12 target queries — questions a German procurement manager might plausibly ask — and recorded how often the Client appeared, in what context, and with what accuracy.

This tracking served two purposes: it measured progress, and it surfaced inaccuracies quickly so we could correct them before they became embedded in AI responses.

The results: 90 days

By the end of the engagement:

The Client appeared in 7 of 12 target AI queries — a Share of Model shift from 0% to 58% against a defined query set. In two of those queries, they appeared in the top three mentioned companies.

German-language search for the company name returned the Wikipedia entry, the company website with German content, and two trade press mentions — all on the first page.

Three German procurement contacts who had previously disengaged re-opened conversations following the Client's improved digital presence. One referenced finding them through a ChatGPT query directly.

The Client's CEO noted that for the first time, introductory calls with German prospects began with the conversation rather than a credibility check.

What this case illustrates

Market entry in Germany — and increasingly across the EU — now has a digital credibility component that cannot be bypassed. The question procurement teams are asking is no longer just "can I find this company online?" It is "what does AI say about this company when I ask?"

For manufacturers and industrial suppliers entering Germany from Central or Eastern Europe, the structural disadvantage is real: strong domestic reputations do not transfer automatically across borders or across language barriers. Building AI-visible credibility is a deliberate, sequenced programme — not a one-time task.

The good news is that it is buildable. In 90 days, a company with zero German-language digital presence can establish the foundational signals that procurement teams and AI systems use to assess credibility. The work is not glamorous — Wikipedia entries, schema markup, trade press placements — but the commercial impact is measurable.

Planning a market entry in Germany or elsewhere in Europe?

We start with a narrative audit — finding out exactly where you stand in AI-generated answers before we touch anything else.

📧 info@ahosdigital.com
📞 +48 451 082 722

Follow our work on AI visibility, SERM, and digital architecture for European enterprise:
🔗 LinkedIn: https://www.linkedin.com/company/ahosdigitalcom/
📖 Medium: https://ahosdigital.medium.com/