NativeAI

Beyond Page Views: 4 Metrics Bloggers & Digital Publishers should care about

By NativeAI / September 5, 2018

Sometimes it feels as if content analytics are stuck in time.

While digital platforms and devices evolve at a breathtaking pace, bloggers and content creators continue to rely heavily on a very old-school metric: pageviews. And though there is nothing inherently wrong with this metric, relying primarily on pageviews is not an effective strategy.

Why? Because it is only the tip of the iceberg. As a newsroom survey conducted by The Reuters Institute and The University of Oxford found, journalists and editors are increasingly finding that Page Views provides a shallow overview rather than actionable insight.

When publishing online, bloggers enjoyed the first-mover advantage, with a superior grasp on social sharing tactics, search optimization etc. However, journalists and digital media publishers have bridged the gap using advanced measurement and custom analytics which uncover insights that regular metrics like PageViews, simply cannot.

Fundamentally, to really understand how your pieces are performing and what needs be done to improve future results it is essential to go much deeper.

Specifically, to truly gauge and optimize content, every publisher should look beyond pageviews and dive into these four types of Analytics metrics:

  • Quality: How Is Your Content Truly Performing?

The core problem with pageviews as a metric is that it only tells you that a certain number of people arrived at a piece of content.

What you don't get is any sense of the value of this traffic and what happened next. Which sources are these views coming from? Are audiences arriving and then immediately leaving? Do people read/watch fully or tend to move on quickly?

If you want a richer understanding or performance, it's important to look past quantity and examine quality. This is where metrics such as traffic sources, time spent reading, and scroll depth come into play. By examining these analytics you gain an understanding of engagement, not just visits.

Consider for example, an Engagement Quality metric. We at NativeAI have defined this metric to be an objective measure of the audience attention that a particular story captured, using the time on page, type of post (video, slideshow, text), scroll depth and the length of the page itself.

Engagement Quality can allow you to objectively compare the attention that different content pieces, campaigns & channels to a highly meaningful objective - holding your readers’ attention.

  • Audience Profiles: Who Is Engaging With Your Content?

Another issue with pageviews is that the metric focuses on the what and not the who. Of course no metric can capture every dimension of an interaction, but even on that front, a pageview lacks the depth in perspective to be useful for any other dimension.

While knowing the quantity of visits to a page is nice, the real value for publishers is in the people behind that metric. Who is engaging with your content? Are they the people you are trying to reach? What are their interests and likely actions?

Fundamentally, what matters beyond overall views are the individuals engaging with your content. That's why analytics such as audience interest graphs and behavioral insights are so essential: they map the numbers to audience profiles, enabling you to truly understand who is interacting with your pieces.

NativeAI can classify articles & stories into news categories and use Engagement Quality as a filter to segment audiences by the topics that interest them. This is an invaluable asset for audience development, promotional campaign management and editorial strategy.

  • Real-Time Performance:  What Is Happening Right Now?

One problem that many publishers struggle with when it comes to pageviews isn't just the metric itself, but also when they are able to process it.

All too often traffic-based analytics such as pageviews are looked at long after content is posted, providing insights only into what happened in the past and what could have been done differently.

What is often more useful are real-time metrics that present what is happening right now. In addition to real-time page views, these can include real-time referral traffic, real-time community engagement, and real-time bounce rates.

goal with these metrics is to be able to continually boost content performance: by having insights into which pieces are succeeding and which are struggling in the moment, you can make on-the-fly decisions about where to focus promotion and additional effort.

  • Future Behavior: What Content Should You Be Creating?

Of course, an effective content strategy isn't just about the past and the now — to succeed you also need to be able to plan for the future.

Again, analytics beyond Page Views can help here. With insights such as knowing which topics your audiences might be interested in you can take unexpected directions and find new pockets of engagement. This enables you to chart a continually-optimized, data-driven editorial strategy that produces the pieces people are most likely to engage with.

Ultimately, by combining engagement quality metrics, audience profiles, real-time reporting, and insights into future behavior you can create the right content for the right people and deliver it at the right time. This can dramatically improve both the efficiency and effectiveness of your efforts.

So, given these advantages, why don't publishers delve deeper into analytics? In large part it is because many believe gaining access to rich metrics is difficult.

The truth is that it is not. With content analytics platforms such as NativeAI, it's possible for publishers of all sizes to access tailored content insights with minimal effort. Through a simple dashboard, you can quickly see real-time performance, understand the the specific interests of your audiences, and view the Engagement Quality (EQ) of every piece of content you post. In other words, moving beyond Page Views is probably much easier than you may think.

Written by NativeAI / September 5, 2018