Digital Media Company: Content ROI visibility increased, ad spend optimized by 28%.

Background

The situation before we started

This digital media company published content across their website, YouTube, three podcast platforms, Instagram, TikTok, and a newsletter with 80,000 subscribers. Each platform had its own analytics, and the team had no way to answer fundamental questions: Which content topics drive the most revenue? Which platform delivers the best ROI per hour of production? How does content performance on one platform predict performance on others?

The Challenge

Our Approach

How we solved it

We built a cross-platform analytics system that ingested data from all eight content platforms, standardised metrics (impressions, engagement, conversions, revenue), and created a unified attribution model. The ingestion layer used a combination of official APIs and custom scrapers, normalising data into a consistent schema. We implemented multi-touch attribution modelling to understand how content on one platform influenced conversions on another. The dashboard gave the editorial team a single view of content performance with the ability to slice by topic, format, platform, and time period. We also built a content scoring model that predicted likely performance based on topic, format, and historical patterns.

Technology Stack

The Result

Services used in this engagement