The Value of Knowing Your Audience's Interests on a Granular Level

By NativeAI / April 24, 2018

If understanding audience interests were simple, driving engagement would be far easier for online publishers.

Audience interests are a concept that reflects fast-changing patterns of consumer demand for topics and ideas. Even highly-niche online publications generally serve several areas of audience interests. A travel blog may offer travel content which fits into interest categories of travel reviews, tips, and even inspiration. 

With the ability to understand audience interests in-depth, you have a remarkable advantage when it comes to driving engagement on-demand, and creating a high-performing, data-informed publishing strategies.

The Value of Audience Interests Intelligence


Most publishers engage in some form of interest-based content performance analysis, whether or not they recognize it. When evaluating content performance over the past quarter, publishing managers and analysts may determine a trend towards superior audience engagement with home decorating video DIY videos or humorous, interactive quizzes.

Manual interest-based analysis is rarely successful for several reasons. First, as you know, audience interests can change over time. Last quarter’s demand for DIY videos may have been replaced with an interest in news-based podcasts. 

Second, effective audience interest analysis is highly-nuanced. Understanding that infographics on technology perform well doesn’t inform you of why this content is highly-effective, or whether the engagement is being driven by data graphics, tech statistics, or any other sub-topics.

Artificial intelligence analytics tools, provide access to deep interest intelligence, including nuanced analysis and prescriptive analysis of audience interests. The NativeAI algorithms are trained to evaluate content against more than one million possible interest entities, determining sub-topical patterns with depth and accuracy.

These kinds of tech-assisted interest features enable you to understand that your audience isn’t only interested in food articles, for example, but that they’re specifically interested in articles about vegan recipes and lifestyle.

Taking Action on Interest Intelligence

When viewed within the context of a single piece, interest intelligence offers value. You can use interest graphs to understand that a recent, high-performing video reflects audience demand for dramatic makeup tutorials, for example.

However, interest-based intelligence informs action most effectively when it’s presented in a self-serve format that allows you to drill-down, analyze interests over time, or view interest trends among a particular audience segment. 


This analysis allows you to immediately answer questions such as:

  • Which interest categories are most popular among first-time website visitors?
  • Which sub-topics are driving repeat visits among loyal audience members from Facebook and LinkedIn?
  • What are some under-served interest opportunities that are trending among our audience?

To inform effective action, you need access to deep interest intelligence that can be viewed over time, by segment, channel, or other forms of drill-down analysis. When coupled with AI-driven recommendations for underserved content topics, interest-based analysis can be used to increase audience engagement.

Interest-based insights enable you to effectively allocate you editorial resources. With the ability to create content in response to audience interests, content creation and promotion resources can be used for better returns.

The NativeAI platform was built to provide this kind of deep audience interest analysis, using machine learning and natural language processing to identify and track more than one million distinct interests. Visit Publisher Analytics to learn more.

How to Extract Actionable Publishing Insights From Deep Audience Data

Written by NativeAI / April 24, 2018