Baseline audience reports contextualise current environment, provide self-assessment
Big Data For News Publishers | 01 May 2025
If data informs your editorial decisions, the central question should always be what works and what doesn’t? But there’s an even more fundamental question to answer first: What does success actually mean?
That definition must reflect your media company’s mission.
Perhaps you aim to offer your audience deeper context on the news. Or maybe you want to spark emotion. Or help people make everyday decisions.
Whatever your intention, the only way to measure impact is to look at what readers consume and how they engage with it.

Thanks to a blend of research and Artificial Intelligence, smartocto is now able to analyse vast volumes of content based on exactly this: editorial intent. That opens up something new and important. For the first time, we can pinpoint where a newsroom’s real strengths lie. In our User Needs programme, 20 media brands used this analysis as a foundation for what we like to call growth hacks — small, strategic experiments that can lead to major insights.
That, in a nutshell, is the role of a baseline report. It shows companies where they are before they try to move forward. It gives experiments the best possible start.
From this position of clarity, newsrooms can begin to identify the content types that resonate and those that fail to land. The goal is not to chase performance for its own sake, but to reinforce editorial strength. In that light, it is a powerful form of self-assessment.
A baseline report built on user needs
Increasingly, media organisations now request a baseline report when they want to take user needs seriously. As INMA’s Amalie Nash recently noted in her newsletter, the user needs model is gaining traction around the globe. Whether the newsroom is based in Amsterdam or Kuala Lumpur, the method has become a common language.
These reports are built on a minimum of 1,000 articles, and the results reveal whether editorial goals are being met. If an organisation is not yet tagging stories by user need, Artificial Intelligence can be used to retrospectively categorise historic content. That, too, is a useful reality check.
Take Der Spiegel, for example. A well-known and respected title in Germany, Der Spiegel produced a report offering a revealing picture of its editorial output. More than 80% of its content serves what we call contextual needs. In practice, this means the majority of articles are designed to either offer perspective (with input from analysts and experts) or educate (by breaking down complex issues).

This largely reflects Der Spiegel’s brand promise. Still, the editorial team saw room for improvement.
Audience data revealed something interesting. Readers also valued other user needs; that, too, is part of Der Spiegel’s identity. Its mission, after all, is not just to explain the news but to set the agenda.

So, what does that suggest? In our view, a more balanced mix of user needs. More fact-driven content, particularly before the paywall, could help draw in new audiences. That, in turn, supports subscription growth. And that is no minor point: It sits right at the heart of the strategy.
Simon Schwandner, head of data and research at Der Spiegel, explained it this way: “We do see that the action-driven articles work well for newer audiences. Fact-driven is kind of our main category, but less powerful, especially for these newer audiences.”
Metrics that matter
It is also important to note article reads are not the only metric that matters. A baseline report becomes much more revealing when examining things like attention time and page depth.

Where possible, we also look at output across different sections of a Web site. That is when real patterns start to emerge. We quickly see which user needs are being ignored in which places.

In the example above, a simple and effective action might be to create more action-driven content in the sports section. For example, articles telling readers when and where to watch football matches. Or, pieces encouraging people to connect around shared experiences and passions in sport.
Ultimately, the success of this approach depends on one thing above all: a solid commitment to the entire growth hack process, from start to finish. First, formulate strong growth hacks. Then, commit to experimenting for at least three months. Finally, follow what happens, closely and consistently. Visitor behaviour will show what works.
Successful growth hacks
For inspiration, here are a few examples of growth hacks that have delivered results:
• Distinguish “update me” and “keep me engaged” pieces. This enhances the user experience and satisfaction while driving regular visits for updates and prolonged engagement with richer content.
• Introduce shorter stories. This captures attention quickly with stories that are easily consumable. Ultimately, it increases reader engagement and shareability, and drives more frequent visits and broader reach.
• Improve delivery and format of context-driven stories. This drives higher user satisfaction and retention by making stories more appealing and accessible.