Premium Content Engine
US daily newspaper and website publisher

A US daily newspaper and website publisher sought out a robust data-driven and reliable way to select paid subscriber-only content.

Traditionally, newsrooms hand-picked content for premium status through “gut feel”. Mather’s Premium Content Engine helps alleviate stress from the newsroom by reducing decision fatigue. PCE is a complementary component to editorial decision-making by organizing content intelligently, selecting articles for premium status through NLP, and maximizing subscriber LTV modeling.

Having an effective Premium Content Strategy can:

  • increase the number of sales attempts to drive acquisition growth
  • convert readers who may not convert under traditional metered paywalls
  • reinforce the value of the publisher’s content to paying subscribers
  • The publisher sends a Slack alert to Mather indicating that an article is ready for scoring.
  • Mather scrapes the publisher’s CMS for article metadata (e.g., section, author, etc.).
  • Mather applies a scoring algorithm to determine if the article is a fit for premium.
  • Mather pushes a recommendation to the publisher via a Slack alert.
  • The publisher interprets the request and makes the final editorial decision.

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