Marketing Agency

AI Content & Reporting Pipeline

Delivered in 8 weeks
AI Business Automation
Content output increase
Same team, significantly more deliverables per client
$4.2k
Monthly retainer secured
New contract won on the back of increased capacity
8 wks
Time to deliver
From brief to fully operational pipeline

The situation

The situation

A digital marketing agency was managing SEO content production for 20+ clients — each with their own tone, keyword focus, and monthly reporting requirements. Every article was written by a human writer, briefed manually, edited, and uploaded. Monthly reports were assembled by pulling data from Google Search Console, formatting it into a template, and writing a narrative summary. With 20 clients, this was consuming the majority of two people's time every month.

The complication

The complication

The agency's clients had explicitly asked for more content — they wanted 6–8 articles a month rather than 2–3. The agency couldn't quote for that volume without hiring more writers, and the economics didn't work at the rates clients were paying. They needed to produce more without proportionally increasing headcount.

What we built

The system, component by component

A keyword brief generator that pulls ranking data from Google Search Console via API, identifies content gaps, and produces structured briefs for each client automatically

A long-form article drafting pipeline using GPT-4o, with a per-client "voice profile" stored in Airtable that conditions the model on each client's tone, preferred structure, and banned phrases

An editorial review step where each draft is flagged for human review only if it falls below a quality threshold — most articles pass without changes

A monthly report generator that pulls GSC data, compares it to the previous period, writes a plain-English narrative summary, and formats it into the agency's report template as a ready-to-send PDF

An Airtable dashboard that tracks content status, publication dates, and report delivery for all 20 clients

Under the hood

Technical note

The voice profiles were built by having GPT-4o analyse each client's existing content and extract stylistic patterns — sentence length, formality level, topic framing. These are stored as structured prompts in Airtable and prepended to every generation request for that client. The result is that articles for a B2B SaaS client read noticeably differently from articles for a consumer lifestyle client — without manual intervention.

Stack used

OpenAI GPT-4oNext.jsAirtableGoogle Search Console APIVercel

What changed

What changed

The agency now produces 6–8 articles per client per month instead of 2–3, at the same cost base. The reporting that used to take two days of manual work each month now takes a few hours of review. A new client contract worth $4.2k/month was won specifically because the agency could credibly promise volume they previously couldn't deliver.

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Cvorix - Enterprise Software Solutions | Custom Development & AI