How We Got eviacharge.pl to Rank in AI Search Answers — A Real GEO Case Study

How We Got eviacharge.pl to Rank in AI Search Answers — A Real GEO Case Study

Last updated: 17 March 2026 | Author: Konrad Kluz | Category: Case Studies

Generative Engine Optimization (GEO) is the practice of making your website content structured, credible, and conversational enough that AI models — ChatGPT, Perplexity, Claude, Gemini — actively cite it when answering user questions. This case study documents exactly what Geovise did for eviacharge.pl, a Polish EV charging infrastructure provider, to move it from AI-invisible to AI-cited in 90 days.

The numbers in this article include placeholders where client-approved data is pending release. Every technical action described is real and verifiable: you can open Perplexity right now, type "najlepsza ładowarka EV Polska", and see the result.

What Is eviacharge.pl and Why It Was the Right GEO Candidate

eviacharge.pl sells and installs EV charging hardware for residential, commercial, and fleet clients across Poland. The business operates in a high-intent vertical: someone searching for "home EV charger Poland" or "stacja ładowania do domu" is ready to buy, not browse.

That made it a near-perfect GEO candidate for three reasons:

• High commercial intent queries — AI models are increasingly used for product research, not just informational lookups. A buyer asking Perplexity "which EV charger brand is best in Poland" is looking for a recommendation, and AI will cite whoever has the most structured, authoritative answer.
• Underserved AI search landscape — In early 2025, no Polish EV charging brand had meaningful AI visibility. The field was open.
• Existing SEO foundation — eviacharge.pl had decent organic rankings, a functional site, and real product pages. GEO is not a replacement for SEO; it layers on top of it. The baseline was solid.

Geovise took eviacharge.pl as a founding case study to prove the GEO methodology works outside English-language markets. Non-English GEO is where most agencies have no data — and where the opportunity is largest.

The Problem: Invisible in AI Search Despite Solid SEO

Before our engagement, eviacharge.pl ranked on page one for several mid-tail Polish keywords. Google visibility was reasonable. But when we ran our initial GEO audit in Q4 2024, the results were stark:

• 0 citations across ChatGPT, Perplexity, Claude, and Gemini for any EV charging query in Polish
• 0 citations for English-language EV charging queries where a Polish provider would be a logical recommendation
• No structured data beyond basic product schema
• No llms.txt file — AI crawlers had no declared instructions
• robots.txt actively blocking GPTBot and PerplexityBot
• Brand name inconsistency across pages ("eviacharge", "Evia Charge", "EVIACHARGE" all appearing)
• No author attribution or Person schema on any page
• FAQ content existed but was written for Google Featured Snippets, not conversational AI queries

The site was not hostile to AI — it was simply invisible to it. That is the most common state for SMB websites in 2025: not penalised, just unconfigured.

Our GEO Audit: 5 Gaps We Found in 48 Hours

Geovise runs a structured GEO audit that maps a site against the five pillars AI models use when deciding what to cite: authority signals, entity clarity, structured data, crawlability, and answer-ready content.

For eviacharge.pl, the audit surfaced five concrete gaps within two working days:

Gap 1 — Crawler access blocked. robots.txt was using a legacy deny-all policy inherited from a previous developer. GPTBot, ClaudeBot, PerplexityBot, and GoogleExtendedBot were all blocked. AI models cannot cite content they cannot read.

Gap 2 — No entity consistency. The brand appeared in at least four different written forms across the site and in third-party mentions. AI models build a knowledge graph of entities; inconsistency creates ambiguity and reduces citation confidence.

Gap 3 — No structured data for FAQs. The site had a dedicated FAQ page, but it was unstructured plain HTML. FAQPage schema was absent across all pages. This is one of the highest-value GEO signals — 76% of content cited by AI models contains structured list or Q&A content.

Gap 4 — No author or organisation schema. AI models weight content higher when they can resolve the author as a known entity with verifiable credentials. There was no Person schema, no Organisation schema with a verified domain, and no author bio on product or article pages.

Gap 5 — FAQ questions written for Google, not AI. The existing FAQ used short, keyword-rich questions: "EV charger price Poland". AI models process natural language queries: "How much does it cost to install a home EV charger in Poland?". The content needed rewriting for conversational intent.

The GEO Implementation — Exactly What We Changed

Implementation ran over six weeks across three sprints. Here is the complete technical list of changes, in the order we made them:

Sprint 1 — Access and Crawlability (Week 1–2)

• robots.txt update: Removed blanket deny rules. Added explicit allow directives for GPTBot, ClaudeBot, PerplexityBot, GoogleExtendedBot, and anthropic-ai. Retained blocks only for archiving bots not relevant to AI search.
• llms.txt creation: Wrote and deployed a root-level llms.txt file following the emerging standard. The file declares the site's purpose, primary entity (eviacharge.pl), key product categories, and the preferred language for AI summarisation. This gives AI crawlers explicit context before they index a single page.
• Sitemap verification: Confirmed the sitemap was accessible and submitted to all major search consoles, including Bing (which feeds Copilot).

Sprint 2 — Entity and Schema (Week 3–4)

• Entity consistency audit: Standardised the brand name to "eviacharge.pl" across all on-site text, meta tags, alt text, and Open Graph fields. Updated 34 individual instances across 12 pages.
• FAQPage schema implementation: Added FAQPage structured data with 8 conversational questions to the homepage, the main product category page, and the dedicated FAQ page. Questions were rewritten to match natural language query patterns ("What is the range of a Type 2 charger for home use in Poland?").
• Organization schema: Deployed schema.org/Organization markup site-wide, including legalName, url, sameAs (linking to the verified Google Business Profile and LinkedIn company page), and foundingDate.
• Person schema for founder: Added schema.org/Person markup for the company founder on the About page, including name, jobTitle, url, and sameAs references to LinkedIn.
• Author bio structured data: Added visible author attribution with structured markup to all blog posts and guide pages — name, role, and a one-sentence credential statement.

Sprint 3 — Content and Internal Linking (Week 5–6)

• Conversational FAQ rewrite: Rewrote 24 FAQ items across 6 pages. Each answer now opens with a direct, citation-ready summary sentence, followed by supporting detail. This is the structure AI models extract when building responses.
• Internal linking for topic authority: Built a topic cluster around "home EV charging Poland" with the main product page as hub, supported by 4 spoke pages (installation guide, comparison of charger types, grid connection requirements, government subsidies). Internal links used consistent anchor text matching the primary entity.
• Hreflang implementation: Added correct hreflang tags for pl-PL and en-GB versions of key product pages, signalling to multilingual AI models which version to cite for which audience.

Results: Which AI Models Cite eviacharge.pl and for Which Queries

First AI citation appeared after 8 weeks from the start of implementation.

By the 90-day mark, eviacharge.pl was being cited by:

| AI Platform | Query Type | Example Query |

|---|---|---|

| Perplexity | Commercial / Polish | "najlepsza ładowarka EV do domu Polska" |

| ChatGPT | Commercial / Polish | "jaka ładowarka EV do garażu" |

| Perplexity | Commercial / English | "best home EV charger installer Poland" |

| Google AI Overviews | Local / Commercial | "znajdź firmy montujące wallboxy w Warszawie" |

Organic traffic growth: tracked via Google Search Console (data available after 30-day monitoring period)

Branded search growth: tracked via Google Search Console (GSC connected March 2026)

The query "najlepsza ładowarka EV Polska" now returns eviacharge.pl as a cited source in Perplexity's answer panel. This is verifiable: open Perplexity, type the query, and check the citations column on the right.

What the Data Shows

Three patterns emerged that Geovise now treats as validated GEO principles:

1. Crawler access is table stakes. Every blocked bot is a citation you will never receive. Fixing robots.txt alone produced the first indirect AI visibility signals within 10 days — before any schema or content work was complete.
2. FAQPage schema is the highest-leverage single change. Of all the structured data we implemented, FAQPage correlated most directly with AI citations. It gives AI models a pre-formatted, extractable answer — they do not have to infer structure from prose.
3. Non-English GEO works. Polish-language queries are underserved by most AI optimisation practitioners. eviacharge.pl now has citations that no English-language competitor can replicate, because the queries are in Polish and the content is authoritative in that language.

What This Means for Your Business — Key Takeaways

If you are an SMB owner or marketing manager reading this, here is the practical summary:

• GEO is not a replacement for SEO. eviacharge.pl had organic rankings before we started. GEO amplifies an existing foundation; it does not substitute for it.
• The technical barriers are low. Five of the eight changes we made required no new content — only configuration (robots.txt, llms.txt, schema markup, entity standardisation). A competent developer can implement them in under a week.
• Non-English markets are wide open. If you operate in Polish, German, Czech, Hungarian, or any other European language, you have a first-mover window that will close as GEO becomes mainstream.
• Speed matters more than perfection. We deployed an imperfect llms.txt on day three rather than wait for a perfect one on day twenty. The first version was three lines. It still worked.
• Results take weeks, not months. First citations appeared within 8 weeks. This is faster than traditional SEO, because AI models index and update their knowledge more frequently than Google's ranking algorithms re-evaluate a domain.

Geovise runs GEO audits starting at €400. If you want to know your current AI visibility score before committing to a full engagement, that is the right starting point.

Frequently Asked Questions About GEO Case Studies

What does a successful GEO case study look like?

A successful GEO case study shows measurable AI citations for specific queries within 60–90 days of implementation, with verifiable evidence — a specific query a reader can type into Perplexity or ChatGPT and confirm. Traffic growth and branded search growth are secondary indicators, but AI citation itself is the primary proof of concept.

How long does it take to see results from GEO optimization?

First AI citations typically appear within 4–8 weeks of completing core technical changes (crawler access, FAQPage schema, entity consistency). Full citation coverage across multiple platforms and query types takes 60–90 days. This is faster than organic SEO ranking movements, which typically require 3–6 months for new content.

Can GEO optimization work for non-English websites?

Yes — and non-English markets are currently underserved, which makes them higher-opportunity. The eviacharge.pl case study demonstrates measurable AI citations for Polish-language queries. The same technical principles apply in any language: structured data, conversational FAQ content, entity consistency, and open crawler access all work regardless of the language the content is written in.

What is the difference between ranking in Google and appearing in AI search answers?

Google ranking means your page appears in a list of blue links when someone searches a keyword. Appearing in AI search answers means an AI model includes your brand, product, or information as part of a synthesised response to a conversational question — often without the user seeing a traditional results page at all. GEO targets the second behaviour. Both matter; they require different optimisation strategies.

How do you measure GEO success if there are no traditional keyword rankings?

Geovise measures GEO success through three metrics: (1) direct AI citation tracking — manually querying AI platforms with target queries and recording citations; (2) branded search growth in Google Search Console, which correlates with AI-driven brand awareness; and (3) referral traffic from AI platforms such as Perplexity, which now shows in analytics as a distinct traffic source. There are no industry-standard GEO ranking tools yet, so manual citation auditing remains the most reliable method.