Website Visitor Identification Software for a Marketing and Sales Automation Corporation
Based on a persistent user identity that survives cache clearance and cookie deletion, the website visitor identification software system matches users with content by analyzing their behavior and predicting their response, suggesting content with a high percentage likelihood to encourage subscription or upgrade.


The Client
Business challenge
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:
Tech stack:
Database:
Google bigquery, Mongo, Postgres
Back-end:
Go (REST WebAPI), Python, NodeJs
UI:
TypeScript
Other:
GCP, GA, Google Data studio