Lies, damned lies and (readership) statistics: Newsroom Transition Note #3

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Will readership numbers really spark anxiety in the newsroom? Let me count the ways.

This is the third-part of a series of notes from my time at TODAY, a small newsroom in Singapore where I had spent 34 months trying to figure out what’s needed for a print-to-digital transition. Here are the first and second parts.

Many journalists like to joke that they ended up in the profession because they hate numbers. Unfortunately, there’s more than a grain of truth to this.

At TODAY, I was taken aback by how the daily parsing of readership statistics struck a raw nerve among some senior editors. The antipathy wasn’t merely triggered by the lack of knowledge about what to do with the torrent of readership data.

Rather, it was an emotional and at times irrational response to the open (and often brutal) judgement of their editorial decisions by the public, one that raises tough questions about the newsroom’s mission, values and self-image.

Context matters in this case. For decades, the only way a print newsroom could get detailed answers on what people were reading was via a time-consuming and expensive survey. The high cost is one reason why many print newsrooms don’t do readership surveys often, if at all.

The result: Editors and journalists go with a mix of professional judgement and gut feel in deciding what they think readers want or need.

In the digital environment, however, readers tell you every minute what they are reading (or not), for how long, and on what platforms — in effect passing judgement 24/7 on a newsroom’s decisions.

Predictably, stories that do well online involve tragic accidents, online controversies and quirky people/events. The serious stories on politics and policies that take far longer to write and report — these often sink without a trace.

A story’s online popularity can often be inversely (some say perversely) proportional to the effort required, and demoralisingly so.

Helping a legacy newsroom come to grips with analytics is a tricky task as the issue at hand is not merely about data-literacy, but also one that gets to the heart of work-place morale, values and priorities.

Yes, the questions about clickbait have to be addressed. But beyond that, what are the numbers that really matter to the newsroom? Page views? Unique visitors? Or likes and shares on social media?

How do you chart the newsroom’s growth in an honest fashion without cherrypicking the numbers to paint an overly-optimistic picture? These questions require an honest conversation about the compromises needed to strike a balance between editorial values and growth.

Beyond improving data-literacy, the other major goal is to nudge the newsroom towards a data-led decision making process — something which is not as instinctive among journalists as you might think.

Editors may think of themselves as a hard nosed bunch who make tough decisions based on cold hard numbers and facts. But in truth, they are just as emotionally attached to failing products as managers in other industries.

Does it make sense, for instance, to maintain an email newsletter service when readership numbers have stagnated at a very low level for over a year? Can these readers be migrated to another platform that’s experiencing higher growth?

The answers are often obvious once you start digging into the readership numbers. But the newsroom won’t act if the managers instinctively distrust the numbers, or don’t even bother digging out the data in the first place.

“Readership data” and “analytics” are bandied about so much in the news industry these days that it is tempting to assume that the issue has been put beyond doubt.

It is not. In legacy newsrooms, it would be a mistake to assume that numbers “speak for themselves”.

LESSONS IN DIGITAL TRANSITION: Notes From A Small Newsroom

Note#1: Coalition of the willing

Note#2: Post-print Traumatic Stress Disorder

Note#4: What to think when thinking about digital transformation in a newsroom

Note #5: Change fatigue

Note #6: Final thoughts

Data Science | Media | Politics

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