[Report] How to Drive Audience Engagement with AI-powered Content Recommendations
For publishers across the digital media industry, the ability to personalize content recommendations based on precise data and AI is becoming essential for engaging and expanding their online readership.
By now it’s no secret that audiences clearly favor brands that personalize their offers and more than two-thirds of customers expect publishers to offer content that addresses their needs. And with myriad channels audiences engage with, publishers need more dynamic ways to empower their content offerings and keep visitors returning to their sites.
Luckily, modern tech solutions are increasingly sophisticated at providing data-driven content recommendations. Armed with advanced analytics, marketers are taking advantage of powerful algorithms that serve personalized content based on specific user metrics and behaviors. These capabilities enable them to not only grab user attention and engage them at every stage of the customer journey, but to transform the entire reader experience.
This new report from Piano and Digiday explores the insights and tactics publishers are employing to tailor content recommendations that drive quantifiable reader, viewer and listener engagement. In this guide, you will learn how to:
- Leverage privacy-compliant first-party data to create algorithms that truly connect with readers’ interests
- Test ways to increase readership and improve customer experiences with optimal content placement and customized templates
- Deploy analytics and tagging to evaluate and streamline content recommendations as part of a seamless reader experience
- Find expert-led content recommendation resources that provide dynamic formats and delivery systems
Learn how successful publishers are capturing audiences with personalized content recommendations that drive engagement and revenue: