Murat Ulusoy

The architecture of search has shifted. Google integrates generative answers directly into the results page; ChatGPT, Perplexity and Copilot reach hundreds of millions of users daily, citing a tightly curated set of sources per answer. Classical SEO optimizes for ranking positions — what is now also required is optimization for inference: passage-level citability, entity signals, semantic co-occurrence. Agencies whose workflow ends at keyword lists and backlink counts do not structurally cover this layer.

Through a three-stage system: (1) entity building — your brand is recognized by LLMs as a clearly defined entity (Wikidata, Knowledge Graph, structured data). (2) passage-level optimization — content is constructed so that AI models cite it as an authoritative passage. (3) authority signals — digital PR, brand mentions in LLM training sources, and semantic co-occurrence with relevant entities. The outcome: a measurably higher mention rate in generative answers.

It depends on starting position, competition and content maturity. Documented engagements: Soft & Cloud +176% qualified leads at −60% ad spend, Burgia Sauerland +133% revenue and +260% new customers, UE Germany +43.8% organic traffic. These are individual cases, not averages — and they emerged from 12 to 36 months of consistent work. Measurement happens inside client systems (GA4, GSC, CRM); attribution runs to pipeline and revenue level, not ranking positions.

With reputation engineering — a proactive system of sentiment monitoring, search suggest control, authority content seeding and algorithmic suppression. We control which signals Google, Bing and LLMs process on brand queries: from review distribution and Wikipedia footprint to E-E-A-T signals in highly authoritative sources. Your brand becomes a trusted signal for human and machine — robust against crises, competitor attacks and AI hallucinations.

Off-the-shelf tools like Ahrefs or Semrush model the classical SERP — that remains important. The gap: how the brand itself is treated inside generative systems. A cross-model audit therefore runs in parallel — typically 500 to 2,000 curated prompts, queried repeatedly across GPT, Claude, Gemini and Perplexity, with analysis of mention rate, position, sentiment and source citation. Combined with classical KPIs it produces a more complete picture than the sum of the individual tools.

I work exclusively with companies for whom visibility is a strategic revenue lever — typically from an annual investment in the mid six-figure range upward. ROI only computes when the market potential carries the investment. In the strategy call we analyze together whether your setup meets the conditions for scalable growth — honestly and without sales pressure.

We scale SEO and AI-visibility strategies across 15+ language markets — from DACH through Western Europe, Türkiye, MENA and into North America. Clients such as Turkish Airlines, Volkswagen, Johnson & Johnson and ThyssenKrupp are supported multilingually and multi-regionally. This includes hreflang architectures, regional entity signals, LLM optimization in languages beyond English and country-specific reputation strategies.