Using Data Driven Web Analytics to Spearhead a Digital Publishing Strategy

By NativeAI / May 22, 2018

For digital publications, the future looks a little bleak. Ad revenue is declining, and even top publications are missing their targets by wide margins.

With publishers falling short of their goals, many are scrambling to find new opportunities for growth. For many publications, that opportunity is found in deeper, more actionable audience insights.

More insightful audience data is the new frontier for digital journalism, enabling publishers to produce personalized, high-quality content in the frequency and format readers desire. But if these deeper insights are the key to a better publishing strategy, why aren't more publications prioritizing it?

The answer may surprise you. In many cases, it's not that editorial teams don't understand the importance of data. Often, they just don’t have the tools to wrangle the massive amount of data available to create a more engaging digital publishing strategy.

Data-Driven Web Analytics & Audience Engagement

As a publisher, you have long had access to traditional web analytics. But, a significant amount of the data harnessed from platforms like Google Analytics don't give as much value to publishers as they do to, say, e-commerce websites.

It’s important not to neglect or dismiss data that could quickly get your publications back on track to reaching your goals. Deeper, publisher-oriented content and audience data analytics empower more engaging content, inform distribution methods, and equips editors with the all of the tools necessary for them to be successful. With the adoption of a data-driven editorial strategy, you will notice an immediate difference in how readers engage with your content.

Getting Data Buy-In

To start using data effectively, your entire editorial team must ascribe to the data-over-assumption approach. Otherwise, data will continue to be underutilized. As a publisher, you need to stress the importance of data to your team, and ensure they're incorporating data-driven insights into their day-to-day content and distribution strategies.

Getting the Right Tools

Often, all it takes to get data buy-in is a better tool - one that can make data instantly understandable and actionable, rather than a mountain of numbers and metrics that mean nothing. A tool like NativeAI offers unlimited seating, meaning everyone on your team can get access to the data, and browse the informative dashboards.

A tool that only reports on traditional website analytics isn't going to cut it. When you rely on traditional web analytics, you’re only scratching the surface of audience insights. Using technology that reveals the deeper desires and interests of your audience, means not wasting time seeking additional context on what drives engagement.

For example, the NativeAI, uses artificial intelligence and machine learning to catalog and tracks over one million distinct audience interests. Once installed, the platform starts to identify distinct entities in each piece of content to reveal crucial insights into audience engagement.

Making Data Insights a Priority

Historically, article pitches and ideas have been based on the personal preferences or hunches of the editor or contributor. And, it was an effective path to success - hire a talented editor with a “nose for news,” and your publication would see success. That strategy worked because of the limited number of outlets - in many areas, there was only one news option. But, now we have the internet, and with it comes millions of options for content.

It’s just the plain truth: you can’t operate on hunches and compete with outlets like Buzzfeed, who are leveraging massive amounts of data to learn the preferences of their audience. Content is just more effective when the topics and stories are laser-targeted on the interests of the desired audience.

And in the internet publishing age, “when” is often just as important as “what.”

Timing can be everything. A real-time data analytics dashboard provides the insights to react to incident-based and time-bound topics. This data helps prioritize subjects, channels, formats, and segments that certain stories will have the most effect.

Evergreen news is not as time-bound as current news, and requires a significant amount of investigation and research. For editorial teams, this translates to spending a large amount of time, budget, and resources producing a piece of content. Audience insights ensure these high-investment pieces are the best they can possibly be, and are exact matches to the interests of your audience.

Measuring the Audience, Not Just the Content

The key to higher levels of engagement is intimately understanding your target audience. When you invest in studying their behavior and preferences, you will instinctively evolve your content strategies to match. Conversely, if you rely on guesswork to drive engagement, you will inevitably miss opportunities and potentially lose your audience to other publications that hit the mark.

The interests of the audience, and their sub-interests, are golden data sets that publishers without the right tools will be unable to effectively identify and measure. If you’re investing in developing content for your audience, investing in audience insights just makes sense.

The Power of Data-Driven Publishing

Even with a decline in the effectiveness of traditional advertising, it's not too late for publishers to regain momentum. With a fresh perspective and commitment to audience development and engagement, you can quickly pivot and realign editorial decisions to match your audience's’ interests.

Although it may seem challenging to introduce a new data analytics platform to your publishing processes, it's an essential step to take. See how you can get your team up and running with an intuitive platform and a data-driven mindset in our Actionable Insights Mini-Course. This course is specifically designed to get publishing teams up-to-date on the metrics, reports, and insights necessary to increase audience engagement. How to Extract Actionable Publishing Insights From Deep Audience Data

Written by NativeAI / May 22, 2018