News personalization has already been on your roadmap for several years. But progress is too slow and results are average. You want to improve faster. Learn from a media giant that is using a self-learning recommendation engine to successfully deliver a better reading experience.
The world is changing. Every moment your reader is on Netflix, Amazon or Instagram, she is not reading your news. In this war for attention, you have to transform the newsroom to relevance-first. It’s why speed is important and you have to take action today. If you’re not relevant today - people will forget about you.
Is your organization in a similar position?
Before implementing self-learning technology, this media giant had a few roadblocks on the roadmap:
Personalization was on the roadmap for years but progress was going slow
Off-the-shelf solution wasn’t enough for Mediahuis' complex business rules
Mediahuis didn’t have the time and money to build a large-scale recommender engine from scratch
The business leads needed help aligning internal key stakeholders on your personalization strategy
They needed to go beyond simple KPIs boosts and steer towards complex goals and replicate the success of one CTR uplift.
In this report, you’ll learn how this media giant is using a self-learning recommendation engine to successfully transform the reader’s experience with personalization:
The number one solution to greet the reader with the right content in real-time
How to utilize the best recommendation technologies available from the top tech players
How to build strategic knowledge through rapid experimentation
How to have full journalistic control - even when AI enters the newsroom
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