This means that publishers are under an ever-increasing pressure to capture their audience’s attention. And the competition just keeps getting tougher. How are publishers expected to keep up with the groundswell of noise and amateur-published content?
The secret lies in engagement. Publishers must learn what most engages their audience right now, and produce that content in real-time. The secrets to high audience engagement are hidden inside of hard, scientific data.
How To Develop Audience Engagement Strategies Based on Science and Data
When improving content performance, teams need to make productive adjustments and optimizations in real-time. Without actionable, in-the-moment data at their fingertips, publishers must rely on assumptions or knee-jerk reactions to make publishing decisions. And, given the nature of the competition for readers’ attention, publishers can’t gamble on hunches.
Content strategies need to begin with real data. And, that data must be both relevant and recent. Relevant publishing data means the information is valuable for publishing decisions. And recent means, right now. Publishers need relevancy to understand what is driving engagement in their readers down to the smallest audience segments. And, they need recency to allow them to react to the trends in engagement to maximize the effectiveness of their content.
The use of a real-time, publisher-relevant analytics dashboard empowers publishers with fresh data. They can immediately see what stories and topics are driving the most engagement, which helps them decide on content promotion, new topics to exploit, and more. Waiting for a report tomorrow could mean missing out on a huge wave of new readers who possibly may no longer be interested in the story that was hot yesterday.
Discover and Exploit Under-served Content Opportunities
It’s easy for publishers to create too much content for some topics, and not enough for others; especially, if they don’t have a deep insight into their current audience. With the right data tools, publishers can uncover unusual reader behavior they can take advantage of, such as users in a particular channel that are suddenly more interested in a particular topic or author. Then, they can publish more or less content based on that insight.
Publishers that use the NativeAI platform, for example, get the advantage of the artificial intelligent engine that analyzes, detects, and tracks over one million distinct audience interests. This machine-learning ability shows publishers topics that are getting over-saturated, as well as uncovers topics that are of high interest, but getting little coverage.
It’s also valuable to assess which subject matter performs the best, or generating the most reader loyalty. Publishers can also find opportunities by breaking down traffic channels. For example, users from Facebook or Twitter could have more interest in a particular topic or author. Your team can quickly pivot, publishing more or less of that content in the appropriate areas.
Watch Audience Interest Trends
When developing content, audience interests should guide your strategy. And, those interests flex and change dramatically over time. Publishers can’t expect high engagement if they are targeting topics of stale, out-of-date assumptions of what their audience is interested in.
Having a tool that can identify and track the tides of audience interests is extremely valuable. If the political segment of your audience suddenly shifts their interests from stories about individual politicians like Donald Trump or Hillary Clinton, to policy issues like gun control or climate change, publishers should be able to identify that shift and adjust their publishing strategies to match.
Identify and Improve Underperforming Stories and Contributors
One of the hardest things to do is identify the characteristics of underperforming contributors or stories. But, gaining that insight is the first step in fixing the issues and driving higher audience engagement.
Publishing analytics platforms should provide the publisher with data and context to make adjustments quickly, and make educated decisions in the moment. With this data and functionality, brands can fix significant issues and optimize posts that aren't delivering results.
Editorial teams can zero in on what's specifically not working, and use those insights to allocate the right strategies and resources to fix the issues.
Discover What Creates Loyalty and Scale It
Group your visitors by new, returning and loyal readers. Depending on the nature of content you produce and frequency of articles you publish, the threshold where you define a returning user as 'loyal' could change, but it is safe to say that a user who reads over 10 articles or posts a week on your publication is loyal.
Identify the channels, audience interest affinities, devices and geographic location of these users and try to find trends on segments that tend to become loyal. This will help you scale it up by suggesting relevant content at the end of these articles or adding newsletter subscription prompts to ensure you can connect with these users in the future.
Everything is data, and data is nothing without the right tools to extract valuable insights and actionable strategies. The best publisher analytics tools continue to unlock patterns in loyal visitor behavior and their interests, giving publishers the insights necessary to maintain the attention of their most-engaged readers and capture the attention of new audiences.
The right tool takes the guesswork out of increasing engagement. Using data, publishers don't need to assume or guess any aspect of their content marketing strategy. Instead, a content analytics tool such NativeAI can help provide, organize, and break down the insights you need to increase their audience engagement. Learn more about NativeAI.