AI Revenue Engine for Media

The Promise of Audience Behavior Data

A central function of an enterprise publishing system is the ability to correlate content with reader behavior.  Simple concept, but difficult to execute.

Questions inevitably arise:

  • How exactly do we envision acting on these new insights into individual reader preferences, purchases and activity on our site? 
  • Before that, how do we intend to manage the data and how do we measure success?

Enterprise publishing is about breaking down silos – leveraging a single platform to execute a web-first content strategy, creating context to engage readers, transforming a site to a complete resource and creating content once for multiple delivery channels and devices.

Now, with Audience Behavior data, publishers can take the next step: correlating content and tying marketing strategy and tactics to known reader behavior and preferences for individuals and groups. 

Think of the opportunities that arise when we can generate reports that drill down to each customer, member, subscriber or registered user on a website:

–       Individuals or groups visiting your site during a given time period

–       Subscribers or members who have NOT visited your site for a specified time

–       Articles viewed

–       Files downloaded

–       Frequency of visits by individuals from a specific state or company

–       Individuals visiting your site (or not visiting) who are nearing a subscription or membership expiration date

–       Individuals viewing specific pages or downloading files from a Buyers Guide

 

Possible uses are great, but how do they contribute to your bottom line?

–       Increase renewal rates by targeting renewal campaigns based on specific content preferences.

–       Increase sales by cross-selling to individuals with overlapping content interests.

–       Increase lead value to advertisers and buyers guide sponsors with detailed lead profiles.

–       Increase retention rates by adjusting content to match reader preferences.

–       Develop new products by building opportunities from the most popular content and products.

–       Reevaluate ad rates: bury impressions data by adding detailed behavior and preferences to your audience profile.

–       Improve site performance: tailor content to individual and group interests.

The result?  Increase Revenue per Reader by increasing renewal rates, targeting cross-sells and releasing new products that target known reader interests.

ABOUT THE AUTHOR
Publishers bridging content management and AI with Model Context Protocol

Publishers bridge gap between content management and AI with Model Context Protocol

Every publisher I talk to has the same story. They’ve invested in a powerful CMS. They’ve built out a content...

ePublishing AI search and engagement engine best practices article

Launch Your Knowledge: AI Search & Engagement Engine Best Practices

AI search isn’t just another search bar. It’s an extension of your editorial trust—a way for your audience to access...

Microsoft Clarity heatmap and session recording analytics dashboard

Microsoft Clarity: The Perfect Complement to Google Analytics

Microsoft Clarity is a free behavioral analytics tool that provides qualitative insights into user behavior through session recordings and heatmaps....

AI-aware editor using artificial intelligence tools in a modern newsroom

The Rise of the “AI-Aware” Editor: Skills Tomorrow’s Editorial Teams Need

Publishing has always been a trade defined by adaptation. From Gutenberg’s press to the first desktop publishing software, every new...