What are the content interests of your audiences?
Many publishers can't answer this question in detail. All too often, there's a vague sense of what people like, but the specific topic areas that resonate with visitors remain unknown.
This is a huge missed opportunity. Properly understanding audience interests has a wide-range of benefits, including driving more visits and engagement; enabling better related content targeting and strategic planning; and boosting subscription conversions and retention.
Fundamentally, if you truly understand your audience's interests then you can consistently deliver the pieces that are most likely to be clicked on and consumed in-depth.
So, how do you do it? How can you gain an accurate understanding of your audience interests?
Here is a simple four-step process that publishers of all sizes can utilize:
Step 1. Start With Individual Pieces
The best way to think about determining audience interests is to visualize a set of concentric circles: you start in the center with the smallest content units and then expand out.
So, the first step is to look at how individual pieces are performing.
This, of course, is something that most publishers do already. However, where they sometimes go astray is in looking primarily at traffic metrics.
When it comes to determining interests, much more important than visits or clicks is engagement: you want to know which pieces people are diving into deeply, not just what they ending up on. This will give you an initial sense of which areas are truly resonating with audiences.
Step 2. Identify Key Topics of Interest
The next step is to go a level up and see which topics engagement coalesces around.
Traditionally this has been done by looking at which content tags perform well. That has some value — it's better than not looking at all — but it's also fundamentally flawed: tags are often incorrect/incomplete because they are manually inputted by creators and they're not usually grouped into hierarchies. This combination makes getting useful tag-based analytic insights difficult.
A better approach is to determine topic interests by using an AI-based tool that can classify content intelligently and at scale. Our NativeAI platform approaches the task by using natural language processing and machine learning to associate pieces with more than 1 million audience interests, then organizes the data into a topic hierarchy.
What you get from this is a clear view of the topics your audiences are interested in, as well as the full chain of nested topics (i.e., Sports -> Football -> NFL -> Cleveland Browns).
Step 3. Segment Audiences by Topic Interests
A big missed step when it comes to effectively utilizing audience interests as part of a content strategy is organization.
It's not enough to know that some part of your audience is interested in some topics: you need to understand the level of affinity for each topic area and how your visitors group around shared interests.
In other words, you need to segment your audiences by topic interest. Doing this does two things: First, it enables you to see how deep interest is in some topics and sub-topics versus others (i.e., does your audience gravitate more to sports vs. music, the NFL vs. college football, the Cleveland Browns vs. New England Patriots). Second, segmenting your audience by topic allows you to take action based on interests: you can target pieces, newsletters, ads, etc., to specific audiences based on their affinities.
Step 4: Find Opportunities to Engage With Other Topic Interests
Finally, you can find opportunities to more deeply engage segmented audiences by delivering content around other topics they might be interested in.
After all, most audiences are not just curious about one topic, usually there are a host of other areas which they find compelling. Sometimes these connections are relatively simple to make — audiences interested in the Cleveland Browns may likely be interested in the Cleveland Indians — but often the links are unexpected. For example, the audience segment interested in the Cleveland Browns may also over-index in interest in jazz or cryptocurrencies.
To suss these difficult, non-obvious connections out it again helps to turn to a powerful machine-learning and AI powered platform (such as NativeAI Analytics) that can process large amounts of content.
Ultimately, after going-step by step, you'll end up with a powerful set of new tools to better engage visitors and build loyalty: you'll know exactly which topics connect with audiences and how these fit into your content hierarchy; understand the size of these different segments and how they connect; and be able to deliver the most relevant related content to your readers.