Content that ranks in search and gets cited by AI.

A content marketing engagement starts with a strategy sprint — keyword research across your full topic space, a funnel map connecting content types to buyer stages, a competitive content audit showing what is already ranking and why, and an editorial calendar for the first three months. From there, we produce and publish content monthly at the agreed output volume. Deliverables typically include long-form articles (1,500 to 3,000 words) targeting primary keywords, supporting cluster content (800 to 1,200 words) targeting secondary and long-tail terms, case studies written from client interviews, and comparison or alternative pages targeting high-intent buyers who are already evaluating solutions. Every piece is AEO-structured — opening with a concise direct answer to the target query, then expanding into depth — so it is eligible to appear in both featured snippets and AI-generated answers.

Most content agencies produce content at scale without understanding the product. They write about general topics adjacent to your space because generic content is faster and cheaper to produce than technically credible content about your specific product category. The result is articles that read fine but have no authority in search because they are not written by someone with genuine domain knowledge, and they do not earn AI citations because AI models weight author expertise and factual specificity heavily. We write content that could only be written by someone who understands your product, your buyers, and your category. We do not produce ten articles a month that say nothing — we produce four to six articles a month that say something credible, specific, and useful, and that rank as a result.

We track three categories of metric for every content programme. Reach metrics — organic sessions, keyword ranking positions, impressions in Search Console — tell us whether the content is being found. Engagement metrics — time on page, scroll depth, click-through rate to product pages — tell us whether it is resonating. Revenue metrics — trial signups, demo requests, or pipeline attributed to organic content — tell us whether it is contributing to the business. We also track AI citation rate — whether our content is appearing as a source in ChatGPT, Perplexity, or Google AI Overviews on target queries. Monthly reports cover all four categories. If a content type is not producing results after three months, we cut it and shift the output budget to what is working.

We write content in-house. We use AI as a research and drafting tool in the same way a journalist would use a search engine — for background research, fact-checking, and outline generation. The final content is written and edited by a human who understands your product, your audience, and the subject matter. We do not produce AI-generated articles at scale, because that content does not rank reliably in competitive keyword spaces, does not earn AI citations (AI models have low confidence in AI-generated content as a citation source), and does not build the brand authority that makes content compound over time. The output volume per retainer reflects the reality that good content takes time to produce.

Content marketing is a compounding channel, not a fast one. For a domain with existing authority and some organic traffic, articles targeting low-to-medium difficulty keywords can rank on page one within 6 to 10 weeks of publication. For a newer domain or a highly competitive category, the same articles may take 3 to 6 months to reach page-one positions. The compounding effect means the returns increase over time — a piece published in month two is still earning traffic in month twelve. We set this expectation explicitly at the start of every engagement and pair content with channels that produce faster results (paid search, email) during the period when content is building. The combination produces near-term pipeline while the content compound builds for the long term.

Yes. We write for software companies, SaaS products, AI tools, and technical B2B buyers. The writers on our content programmes have backgrounds in technology, and we brief every piece with product documentation, customer interview transcripts, and subject-matter input from your team before writing starts. Technical accuracy is not optional — an AI agent company whose content explains AI agents incorrectly loses credibility with the exact audience it is trying to reach. We send every piece back to a technical reviewer on your team before publication. One round of technical review is built into every article's production cycle.