There has long been an abyss between the technological ability to extract an almost infinite amount of information, and end users’ ability to translate that information into meaningful actions.

Editorial analytics: from reports to something more … human

One of the fears surrounding AI is that it may render reporting jobs obsolete.

Perhaps it will. But that’s not where the opportunity lies.

The opportunity right now is identifying what editorial analytics’ purpose has been — and then thinking about what its purpose could be.

In those heady, early days of digitalisation, it was revelatory to get any numbers at all. For the first time, newsrooms could actually peek over readers’ shoulders. We knew more than how many print copies shifted. We could move beyond working on information based on what people said they read to what they actually read.

When numbers could be customised into personalised reports, that nuance became even more useful — but those insights relied on in-newsroom translation and required someone able to do something with those insights.

In many newsrooms, it has almost become a running joke that colleagues are not particularly good with numbers. Every team needs at least one newsroom nerd to point out that the first draft probably meant percentage points rather than percentages.

So, while AI can help (or “help,” depending on your viewpoint) with the production of news content, perhaps it’s better viewed as an opportunity to shift the paradigm.

Instead of robot-journalists, how about we think about the fact that AI can now act as a digital assistant? What if it could serve as a virtual personal assistant that didn’t threaten the creative impulses and strengths of the newsroom but presented (daily, in the inbox) a report showing the status quo and, critically, what you could do with the information identified in those reports?

In this scenario, AI-driven tools don’t offload an infinite amount of information to an already swamped group of editors. They curate the information you need to maximise your resources and optimise your newsroom’s output.

Meet your AI-powered assistant

So, what we’re getting closer to now is effectively self-reporting data storytelling: a system set up to reveal trends, behaviours, and interests of readers. To identify where the peaks and troughs of attention are.

This is the beating heart of how editorial analytics solutions should now aim to develop their AI-led solutions.

Imagine having an assistant in your newsroom whose job, at the end of your eight-hour shift, is to compile a written report on the most important events and changes — all of which have been revealed by tracking and analysing your data.

Imagine they place that report on your desk — well-organised into smaller chapters, with an introduction, conclusion, and recommendations.

Imagine that this assistant attends your editorial meetings, understands your editorial policy, and works with you to formulate the most important questions you seek to answer through your data.

In other words, your assistant’s job is to monitor all changes in your data and visualisations on your dashboards, conduct statistical data analyses, distinguish the important from the irrelevant, record the most significant trends and changes, and deliver all of that to you in a timely manner — without getting too technical.

Data storytelling leads to better decision making

Smartocto’s Chief AI Officer Goran Milovanovic put it this way: “Interpreting reports and dashboards takes a lot of time. Ultimately, people always think in language, and organise thoughts in stories. Accordingly, what we’re developing is an in-house data storyteller.

“Its job is to reveal the answers to key questions, consistently: What is important? What isn’t? Each new shift of editors can potentially go through these questions and answers and see where their attention is needed.”

The beauty of automating this approach is in its consistency. Because it can be set up however it’s needed, every newsroom shift could conceivably start by reading such a report. And, every time that happens, the editors in question can see exactly where their team’s attention is best spent.

No one is giving up their autonomy, their creativity, or their editorial gut instinct. Everyone gets the information they need to make their work matter.

“The future of editorial analytics is about how tech companies can use data as the foundation to make good decisions — from an editorial and business point of view,” said Erik van Heeswijk, smartocto CEO. “These should be the notifications that move from insight to action and help you proactively: Create more of this type of story on the sports desk, time certain articles to specific parts of the day, or assign author X primarily to topic Y.

“It can become your newsroom’s secret weapon and your cue to use proven results from the past to fuel future productions and optimise distribution.”

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