Case Study

Advancing Viewer Engagement with Intelligent Data Integration

Summary

A leading digital content innovator needed a way to both detect and understand data anomalies amongst their subscriber base.

Our Role

  • Data Strategy
  • Analytics
  • Data Visualization
  • Data Engineering

Summary

A leading digital content innovator needed a way to both detect and understand data anomalies amongst their subscriber base.

Our Role

  • Data Strategy
  • Analytics
  • Data Visualization
  • Data Engineering

Background and Challenge

A key player in the digital content innovation industry, was investing heavily in digital media to attract new subscribers. Despite this significant investment, they lacked a crucial component in their strategy: advanced data analysis, particularly in anomaly detection. This gap hindered their ability to link spikes or dips in viewership with external events, causing a reliance on manual research to piece together their performance data with content-related and environmental factors. Additionally, they missed insights on viewer preferences, especially in cases where geographic limitations restricted content access, leaving a blind spot in understanding viewer behavior.

Solution and Outcome

To transform this challenge into an opportunity, we proposed integrating external event data into the client’s data warehouse. This integration was aimed at automating the process of correlating viewer engagement with concurrent events, thereby reducing manual effort and enhancing accuracy. Furthermore, we suggested capturing data on viewers’ content access limitations based on geographic restrictions.

These proposals were integrated into our annual strategic roadmap for the client and we began to execute. This strategy not only streamlined the process of the client understanding and reacting to viewer preferences but also opened new avenues for targeted content development and marketing, ensuring the client’s sustained growth in a rapidly evolving market.

Top