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Are Real-Time Data Analytics Really Valuable to Digital Publishers?

By NativeAI / August 1, 2018

Data has a remarkably short half-life in the realm of online publishing.

Audience interests and behaviors can change overnight. While last week’s content performance analytics revealed your mobile readers prefer humorous opinion pieces, audience preferences and behaviors may have since evolved.

The fast-paced rate of change in audience behavior and interests is among the reasons why the science of viral content is so complex. While data scientists can uncover characteristics shared by the most viral content, these characteristics aren’t always a future indicator of success.

Real-Time Data Analytics for Publishers

Publishers need actionable insights in real-time, and not a moment later. Opportunities for remarkable engagement are found in the fast-trending spikes in content engagement which reveal content that’s just beginning to perform exceptionally well. By capturing this intelligence in real-time and translating it to immediate performance directives, publishers can achieve real-time engagement results.

Many web analytics dashboards and applications offer real-time insight into content performance, but this data isn’t always enough to drive action. While publishers can see that a recent video on pet adoption is trending, web analytics apps don’t reveal why the content is driving engagement, and whether it’s indicative of demand for more pet-themed content, video content, or heartwarming content.

Real-time insights are critical in publishing, but the difference between actionable and non-actionable audience insights is related to the depth of intelligence. Publishers need solutions which use artificial intelligence to find patterns in content, including:

  • Reads / Volume of Reads
  • Quality / Engagement Quality
  • Publishing Volume / Stories Published

Publishers need the ability to understand why content is performing well or poorly, and perform in-depth analysis on areas that impact their immediate and near-term publishing strategy, including audience interests, channels, and stories.

1. Track Interests in Real Time

Most publishers know enough about the field of information science to understand that topic-based analysis is incredibly complex. Tracking audience interests isn’t as simple as well-defined, high-level categories such as lifestyle, travel, or beauty. The actionable insights are often hidden in deeper analysis of how topics connect to subcategories, such as a demand for articles on organic DIY beauty or interest in low-budget travel to destinations off the beaten path.

It’s not fast or simple to manually discover nuances in audience interest or trends. To measure content engagement, nuance is necessary, which is why the leading publishing analytics platforms integrate artificial intelligence to quickly uncover patterns in unstructured data and interest graphs.

With tools that leverage machine learning and algorithms, publishers can understand interests in real-time with sufficient depth to take immediate action:

  • Which interest categories are beginning to trend among our loyal audience members?
  • Which sub-categories of travel content are driving traffic from social media networks?
  • Which topics represent demand among our audience, but are underserved by our current content assets?

The Native.AI platform uses advanced AI and machine learning tools to measure publisher content against over one million recognized groups of interests and sub-interests. Publishers gain real-time access to graphs of audience interest by segment, interest category, individual user, and other modes of measurement.

2. Track Channels in Real Time

Channels are an important, but often-overlooked aspect of real-time publishing analytics. While many publishers delve into look-back web analytics to understand that 30 percent of their traffic over the last month came from social media, few capitalize on these insights in real-time to guide content creation and promotion.

Channel-based analysis can reveal trends in loyal audience behavior, allowing publishers to understand how and where their readers are spending their time. It can also demonstrate important connections between topic and channel, facilitating understanding of how politically-driven content outperforms lifestyle blogs on Facebook.

Real-time measurement of channel performance can enable publishers to create the content their audience members are looking for, and maximize the potential for content promotion on the right channels.

3. Track Top Stories in Real Time

What are your top-performing stories right now, and why?

While most publishers’ analytics tools can answer the first part of that question, they rarely have the depth of analysis to reveal why recent or evergreen content is driving engagement. Topic-based analysis matters, but it’s not the only characteristic of content that impacts performance.

Author, format, tone, length, and other attributes can all shape an audience’s reaction to content.

Publishers need more than the ability to view real-time content performance on a dashboard. They need drill-down analysis to understand trends in topics, audience interests, formats, authors, and the full scope of why a top story is trending. With this big-picture understanding, it’s possible to replicate the formula for the most-engaging content.

Turning Real-Time Insight into Action

Real-time analytics can inform near-term content creation. By understanding the connections between topic, audience, channel, and story performance, publishers can maximize the characteristics of each piece of content published and avoid wasted efforts. However, there’s more value to actionable real-time insights than just content strategy. Other actions that can be informed by real-time analytics include:

  1. Know What to Promote Now: With channel, topic, and audience-based analysis, publishers can increase the value and performance of evergreen content assets and use prior efforts to drive engagement in the present.
  2. Seeing Outliers as they Happen (Baseline vs. Now): With the ability to understand which assets are driving superior engagement and why, publishers can capture opportunities as they arise, not after-the-fact when audience interests have shifted.
  3. Distribution: Topic and channel-based analysis can inform an effective distribution strategy, allowing publishers to achieve effective on-site personalization, paid social targeting, and other marketing activities. With a distribution strategy that’s informed by real-time data, publishers gain the ability to optimize their return on creation and distribution

Real-time publisher analytics doesn’t need to be complex. While many publishers are struggling to translate web analytics insights into strategic action, the leading publishing platforms make it easy for publishers to develop a data-driven culture, engage with data in real-time, and act on AI-driven recommendations for opportunities.

Native.AI is a leading content intelligence platform designed specifically for publishers and native advertisers, and the only solution to offer engagement quality as a feature. How to Extract Actionable Publishing Insights From Deep Audience Data

Written by NativeAI / August 1, 2018