Marketing Intelligence Pipeline for Adology.AI

James Donner at Adology.AI needed one place to see what his marketing was actually doing — not another spreadsheet. I built the full pipeline: ingest, enrich, report, and ship it to production.

The Challenge

When James Donner brought me in at Adology.AI, the product was solid but the ops side was painful. Campaign data lived in Meta, Google Ads, LinkedIn, and a handful of landing-page tools. Every week someone exported CSVs, pasted them into Google Sheets, and tried to answer basic questions: Which channel drove qualified leads? What did we spend last month by campaign? Where did conversion drop off?

It took 10–15 hours a week of manual work, and the numbers were always a few days stale. That is fine at seed stage. It is not fine when you are trying to scale ad spend and prove ROI to partners.

James did not need a slide deck or a prototype. He needed something his team could run every day without calling a developer.

The Solution

We started with a one-week discovery: map every data source, define the metrics that actually mattered for Adology, and lock scope before writing code.

I built a production pipeline — not a dashboard mockup:

• Ingestion workers pulling ad platform and form data on a schedule
• A central PostgreSQL store so nothing lived in spreadsheets anymore
• Enrichment steps to normalize campaigns, UTM tags, and lead records
• A React reporting layer his team could filter without touching SQL
• Automated summary reports pushed to Slack so Monday mornings were not export day

I owned backend, frontend, and deployment. James got Loom walkthroughs as each piece went live, plus written docs so his team was not dependent on me for day-to-day use.

The Results

The manual reporting loop disappeared. Instead of weekly exports, the team had current numbers in one place.

James Donner, Owner at Adology.AI:
"Zohaib built our end-to-end marketing intelligence pipeline — from data ingestion and enrichment to automated reporting. He delivered production-ready full-stack work with clear communication throughout. Highly recommended."

The pipeline is still running in production. That is the bar I hold every project to: shipped, documented, and usable without me standing over someone's shoulder.