A client finds you in search, sees a Direct ad, meets your brand in VK and Telegram, and asks an AI assistant about you. Full-cycle promotion unites all channels into one strategy with shared KPIs: traffic, leads, cost per lead. The channels reinforce each other — the result exceeds the sum of parts.
A single plan for all channels: semantics, content, ads and analytics work together.
Technical base, semantics, articles and pages for demand — organic grows month over month.
Yandex.Direct and targeting deliver leads from week one and feed data to SEO.
We prepare the site for AI assistant answers: structure, facts, llms.txt, citability.
We check the site, niche and competitors. We build a channel plan for KPIs and budget.
Metrica, GA4, goals, call tracking, end-to-end analytics into CRM. We trust numbers only.
We launch Direct and targeting: first leads from week two, data straight into analytics.
Technicals, semantics, content plan, markup. Organic starts growing.
Articles, cases, demand-driven pages. Crowd and guest publications.
llms.txt, FAQ markup, AI answer monitoring. Weekly reports and sessions.
SEO brings cheap but slow traffic; ads bring fast but paid traffic. Together they hedge each other and lower the overall CPL: ad data speeds up SEO, organic reduces budget dependence. A single channel is a stoppage risk.
Paid channels deliver leads from week two after launch. First SEO results — in month 2–3, stable organic growth — in month 4–6. Exact timing depends on niche competition.
SEO work, Yandex.Direct management, VK/Telegram targeting, basic GEO work (llms.txt, FAQ markup), analytics, weekly reports and a monthly session. The ad budget is paid separately.
A live dashboard with spend, traffic and leads is available 24/7. Weekly — a summary, monthly — a strategy session with a plan. All numbers come from official systems: Metrica, GA4, CRM.
Yes. We often start with Direct (fast leads) or SEO (a long-term base), adding the rest in 1–2 months. The strategy is written for the full mix from the start so the channels do not conflict.
Yes: we prepare answer structures, implement llms.txt and markup, monitor how the site appears in ChatGPT, Alice and Perplexity answers for target queries. It is included in the full package.