Optimize B2B Website for Large-Language-Model Searches

I run a B2B site that performs reasonably well on traditional search engines, but I now want it to surface accurately when people query large-language-model based tools such as ChatGPT, Bing Copilot, or Perplexity. To get there, I need deep yet practical SEO work—specifically on-page optimisation and quality link building—executed with an eye toward how modern language models crawl, parse, and rank content. Here is what I expect: • A concise technical and content audit that highlights issues affecting crawlability, schema use, topical authority, and internal linking. • Clear, implementable on-page recommendations (headings, semantic markup, meta data, structured data) and the actual hands-on updates where possible. • A safe, industry-relevant link-building plan that raises domain authority without black-hat tactics. • Guidance on aligning page structure and language so LLMs can extract clean, context-rich answers directly from my pages. • A short performance report after changes go live, including Search Console / GA4 data and any early LLM-search visibility signals you can capture. If you live inside tools like Screaming Frog, Ahrefs, SEMrush, and are comfortable with schema.org, JSON-LD, and EEAT considerations, we’ll get along well. I can grant access to the CMS and existing analytics as soon as we agree on milestones.