As publishers digitize they must find new ways of reaching out to readers, and focus on building a revenue model based on subscriptions in a media marketplace that has never been more crowded and competitive.
When they attempt to address these concerns, publishers typically encounter technical issues including:
The goal was to create a system that addressed these concerns, equipping publishers for digital success.
In particular, it was necessary to deliver:
- Increased sales efficiency
- Transparency of data and decision-making facilitation based on analysis
- Automated suggestions to readers and campaign running
- Calculation of likelihood to subscribe
- Personalized content consumption patterns
Personalizing publishing CRO at scale with machine learning
- A reader visits the publisher’s site.
- The backend matches that reader with a persistent identity inside the tool and an analysis of their previous onsite behavior.
- Based on this, the system offers that reader content with a higher probability to encourage conversion.
- The system also generates tailored calls to action and personalized proposals emphasizing the content most likely to generate conversions.
- Post-subscription, the process continues, with relevant offers displayed to segmented subscribers to encourage retention and upgrade, and sales involved in upselling and cross-selling where appropriate.
Key features of the system
Lightpoint built the system with:
Google bigquery, Mongo, Postgres
Go (REST WebAPI), Python, NodeJs
GCP, GA, Google Data studio