Uninterpreted data is hard to understand for editors and measures are hardly actionable. We wanted to give active feedback and action recommendations.

Since the common IAB topic classification is indistinct for the local news market in many cases, we implemented a tailor-made topic classifier on all our published content. Each published article’s content profile is stored in a database. Linking first-party userdata and traffic data, the following scores are calculated:

• Conversion: Which articles / topics drive subscriptions?
• Reach: Which articles / topics drive traffic?
• Engagement: Which articles / topics keep readers on the site?
• Anti-Churn: Which articles / topics bring subscribers back to the site?
• Monetary: Which articles / topics create high revenue and CLV?

Based on the data, we are creating the following data tools:

• The Editors Dashboard: We created a responsive dashboard which helps the editors to monitor and improve their article performance. Above all it is supposed to give valuable feedback and actionable optimization recommendations.
• The Topic Analyzer: The Topic Analyzer is the engine room especially made for sophisticated data science purposes. Based on raw data it allows us to generate various insights, reports and data models and gives us a big picture on our topics and helps making the right strategic decisions.