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The AI Marketing Department

We build and operate your AI marketing department on monthly sprints. £3,000 to £8,000 a month, no minimum. Each sprint, the system gets sharper as it learns your business. The work is not a project. We replace the marketing function — content production, paid acquisition, attribution, AI search, model selection — and run it under one operating layer on your infrastructure. Outputs ship every week, executed by agents in production, reviewed by humans, monitored against your real revenue numbers.

Implementation

How we set up the AI marketing department on your stack — accounts, agents, data flows, observability. The first sprint, end-to-end.

Sub-cluster

Infrastructure

The platforms, integrations, and orchestration layer the function runs on. Always your stack — your cloud, your CRM, your Notion. We get access; you keep ownership.

Sub-cluster

Workflows

The actual production pipelines. Agent-led, human-reviewed, shipping weekly. From brief to draft to publish, from ad copy to placement to attribution.

Sub-cluster

Economics

What it costs to run the marketing function on AI versus hiring. Hours-based pricing, multi-model stack, no separate API invoice.

Sub-cluster

Failure modes

The places AI marketing breaks — hallucinations, brand voice drift, attribution gaps, model deprecation. How we catch them, in production, every sprint.

Sub-cluster

Most marketing teams are running stacks designed for a 2018 world — disconnected tools, manual workflows, and humans doing what AI can now do faster and cheaper. The marketing function is a department, not a tool problem. We rebuild it as one.

— Marketing Operations thesis
§ · Flagship posts

Marketing Operations

Why most AI marketing automation projects stall at month 3

Why most AI marketing automation projects stall at month 3

Read post: Why most AI marketing automation projects stall at month 3

Marketing Operations

The AI marketing operations playbook that's built for reality

The AI marketing operations playbook that's built for reality

Read post: The AI marketing operations playbook that's built for reality

Marketing Operations

How we built our own rank tracker with DataForSEO + Claude Code

We built our own rank tracker with DataForSEO + Claude Code — £27/month versus £99+ for Ahrefs. Complete architecture, TypeScript implementation, PostgreSQL schema, cost breakdown, and the five things that broke during development.

Read post: How we built our own rank tracker with DataForSEO + Claude Code
§ · From other pillars

Content Strategy

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Attribution

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Attribution

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AI Models

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§ · Explore other pillars

Content Strategy

AI content production at scale, with quality and brand voice as constraints.

Explore Content Strategy

Attribution

Server-side tracking, multi-touch attribution, and the models that survive iOS and GA4 changes.

Explore Attribution

AI Search

Showing up where buyers ask AI — Google AI Overviews, ChatGPT, Perplexity, Claude — plus the AI-era SEO that still feeds them.

Explore AI Search

AI Models

Comparing Claude, ChatGPT, Gemini and others — and picking the right model for each marketing job we run for clients.

Explore AI Models

Book a discovery call

Sixty minutes. No slide deck. We tell you which sprint tier fits and when output starts shipping.

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