Traditional web analytics tools were not built with publishers in mind. There are web analytics and user analytics tools that market themselves to the publishing industry.
Popular Website & Web/Mobile App Analytics Tools:
If a technology was developed for the traditional website or web and mobile applications, it will most likely be lacking the data features you need most. The reason traditional website and usage analytics fall short for publishers is a lack of audience intelligence. Web analytics can pinpoint content that has performed well, but it doesn’t provide the insights into why that content performed, and another did not.
Content in the publishing industry is very diverse, and that diversity is much deeper than topic categories. There are potentially billions of subcategories for every major topic. And, there are many factors that can influence audience engagement, such as story length, format, mood, voice, author, point-of-view, and countless more.
Just measuring visits, visit duration, scroll depth, and bounce rate doesn’t give insights into the complexities you need to consider in order to drive increased engagement. While that kind of data is valuable, and important to track, it’s not actionable. It doesn’t reveal the color and detail of user behavior the way publisher-oriented analytics should.
Raw numbers only tell a part of the story. You need more than just data to make consistent publishing decisions. Publisher analytics provides publishing-critical insights by searching out anomalies, detects and tracks segmented audiences, and identifies areas of potential performance increases, and reveals where resources are being wasted so they can be rerouted.
Audience engagement goes much deeper than tracking visits and bounce rate. Content analytics measures engagement through a variety of methods, depending on the tool being used. As a publisher, you need to be able to effectively measure what content is interesting to their audience, and which content is actually being read, listened to, watched, and shared across reader’s own networks. Being able to put your finger on what content is driving the most engagement is an invaluable benefit of content analytics for publishers.
Tracking engagement involves many different measurements, like scroll depth and time-on-page, which can make meaningful analysis difficult and time-consuming. This is why we created a single aggregation metric to coalesce all the engagement signals into a single, instantly understandable metric, called Engagement Quality.
Being able to identify and track the content that drives the most engagement gives editorial teams the insights they need to make better decisions and strategies. It’s one thing to have great instincts as a publisher. It’s another to have those instincts combined with data-driven insights on your audience, your contributors’ performance, and the topics that are driving the most engagement in real-time.
Understanding what content is driving the most engagement, and which segments of audience that content is engaging is a must-have to plan & optimize content distribution. Being able to track engagement sliced by audience segments means you can compare what content is performing for your Facebook audiences vs. other channels, for example.
Most publisher-oriented content analytics platforms provide real-time dashboards, which allow you to be nimble - monitor, react and drive your content to meet the goals you want, on the fly. Being able to understand what’s engaging your audience right now allows you to make informed decisions on distribution, content promotion, resource allocation, and editorial strategies rapidly. Being able to capitalize on the shifts of audience interests in the moment is critical for every major publisher.
Read more: What is Content Analytics?
Any website metrics tool can track quantities, but getting a clear picture of the quality of all those pageviews is much more important. Engagement is the elusive “holy grail” of publishing, and without a clear, understandable way to measure engagement, you can’t get a clear picture of their audience’s experiences.
At NativeAI, we have developed a single composite metric called Engagement Quality, or EQ. This one metric is an aggregation of a variety of data (time-on-page, scroll depth vs. story length, etc.) to give a clear picture of the engagement of an article, the entire website, audience segments, and more.
This is one of the main differentiators between NativeAI and traditional website analytics. As a publisher, you don’t just need insight into their content; they need insight into their audience. They need to know what their audience likes, what they are interested in the most.
Effective interest analysis requires machine learning, similar to the graph-based semantic search algorithm of Facebook. While it's a complicated feat of engineering to build, you shouldn’t have a hard time using the tool.
The best intelligence features use machine learning and complex algorithms to determine user interests and to allow you to quickly drill-down and answer questions such as:
Real-time insights from content intelligence software should reveal patterns in the nuances, including information on more than just the article's title or author. With artificial intelligence, the best solutions help you understand what qualities of an article matter to the different audience segments, and respond instantly to fine-tune and maximize reach and engagement.
Beyond the purview of most web analytics tools, gaining insights into your audience is a critical aspect of publisher analytics. Understanding what content audiences want to engage with, the formats they prefer, and the point-of-view of which they want to receive the information is key to driving continual improvement in engagement.
This is one area that we at NativeAI have focused a lot of our resources. Through complex algorithms and machine learning, our publisher analytics platform can identify more than 1M+ distinct interests in content. Then, by looking at how users interact with that content, you can create aggregated interest graphs that describe the behavior audience segments. This way, editors can not just see how many
This is one area NativeAI has focused a lot of our resources. Through complex algorithms and machine learning, our publisher analytics platform can identify more than 1M+ distinct interests in content. Then, by looking at how users interact with that content, publishers can create aggregated interest graphs that describe the behavior of each individual user, as well as whole audience segments. This way, editors can not just see how many page views each story logged, but understand why.
Behavioral analytics that can shape an actionable content strategy drill-down to the psychology of sharing and the emotional triggers that increase an audience member's probability of sharing content with their friends and family. More pragmatically, it allows you to understand the formula of their best-performing content by drilling-down behavior by time, new or returning reader, content category, article type, and other key filters.
As a publisher, you need the ability to interact with a breakdown of site visitor behavior, including the capacity to drill-down to the most engaging topics. This can enable, for example, the discovery that, while 1-in-3 audience members are driven to engage with political content around mid-day from desktops, while 25% of the total audience is interested in local city news while transiting to or from work, consuming media on their mobile devices.
Smarter segmentation allows you to present the right content at the right time to audience members, based on their interests and behavior. With the right audience intelligence technology, you can understand segments according to factors such as:
Measuring and tracking the DNA of content is also important for maintaining high levels of audience engagement. The style, format, and flow of all different kinds of content can be as complex as the audience that content is attempting to engage.
Being able to measure engagement based on content variables like story length, and point-of-view is important. Knowing that humorous articles engage your audience more than technical, or vice versa, is valuable as well. Having the ability to measure engagement across a wide range of content characteristic variables, and get that insight without months of data mining is a powerful tool in the hands of a savvy publisher.
With hundreds of stories being produced on a weekly basis, you need to understand your content subject matter both on a holistic and a granular level. This is one of the greatest advantages of an artificial intelligence powered content analytics platform, like
We developed NativeAI to identify audience interests, and with advanced natural language processing and machine learning, to analyze every piece of content and automatically detect entities and interests discussed within the story, and identifies new ones as well. Then, the algorithm can auto-assign tags based on the detected subject matter. Publishers can also add tags manually, which gives the platform another set of managed data to utilize.
NativeAI can classify stories based on topics, interests, and tags. That means you can view analytics reports grouped by these data sets. Being able to track and monitor engagement and performance by topic and tag is a popular feature among top publishers.
When publishers have insights into the interests of their audience, they can identify golden opportunities to increase audience engagement. If you can segment and measure your audience by their interests, and sub-categories within those interests, you can easily identify the topics that are covered exhaustively on your website, as well as topics that are not getting the attention they deserve.
Read More: Audience Intelligence: The Key to High-Performance Publishing Strategies
Breaking down the quality of each website visit, or segments of
The most basic metric for content success is the number of readers who look at each piece of content. Understanding the number of reads or
Measuring the volume of engagement also reveals patterns and trends
Publishers have never been able to rely on one-time readership. All the way back to the early days of the newspaper, subscriptions from loyal readers was essential for long-term success. And, keeping those subscriptions engaged and interested was key. Today, most publishers can’t rely on the subscription model any longer. Yet, they still must keep a growing stable of engaged, loyal readers if they want long-term success.
Publishers investing in high-quality content for their audiences must rely on data-driven publishing decisions to consistently produce content their audience is interested in. Data and metrics that deliver insights on returning readers, why the return and the DNA of the content that brings them back to the site
NativeAI helps you identify trends by benchmarking current performance against historical baselines. If Tuesday is outperforming Monday, is that because of high-performing stories, or does Tuesday always outperform Monday? Vice versa, if Monday outperforms Tuesday, and if that is an anomaly, you can research a little deeper to find out why performance jumped, and identify opportunities to repeat that success.
Tools are not the golden goose, and having one tool over another may not always be the answer. But, at the end of the day, a publisher needs a content analytics tool that can present them with actionable insights. These are the insights that connect the metric with the (usually not very obvious) next step without the hassle of extensive analysis.
When you find a tool, or set of tools, that can give you that kind of insight on a regular basis; engagement isn’t such a mystery. Editors and contributors alike will be able to identify and act on the behaviors, characteristics, and preferences of their audience. Doing so will empower them to increase engagement, and become a must-have resource for a growing audience.
The best Content Analytics tool for your website is ultimately a function of your priorities:
It comes down to a tool that simplifies and delivers on the needs of all stakeholders in your team - Digital Marketing, Audience Development, Editors and Social Media.
At NativeAI, we understand that this is the deal and that is a fundamental facet of how we have built our Publisher Analytics platform. You must be able to easily connect real user data to the editorial decisions you make every day, period.