9 reasons why analytics in the newsroom fail

Big screens with a fancy dashboard on the wall have become a staple of the modern newsroom. Sure, it looks cool and gives editors the feeling of being informed. But honestly, does anybody actually look at these dashboards? Do they really drive editorial decisions? Do you actually perform actions based on what you see on the screen?

If not, it's probably because it shows the wrong kind of data: from a different world, made for different people. After all, data suitable for businesspeople or data scientists rarely inspires journalists. If you wonder why the traditional analytics approach often fails in the newsroom, we're here to give you 9 reasons. This blog was updated and republished by smartocto with kind permission from Laurens de Knijff.

1. Dusty data language
2. When it comes to data, less is more
3. Numbers without context are just that: numbers
4. Social media channels are not islands
5. Your website is not necessarily your main channel
6. Reporting periods don't show the big picture
7. Totals are a wrong metric to measure story impact
8. The next day... is just one day too late
9. The importance of accuracy is a myth

1. Dusty data language

Technical analytics jargon in dashboards or reports, albeit correct, rarely stimulates a conversation about data. Journalists are not data analysts. They don't really care how many 'unique cookies per specified main directory for tag2’ there are, they just want to know how many 'visits', ‘views’ or ‘catch’ their story generated. So why not just call it that? And if you create a manual for all the metrics and their specific meaning, you'll make sure that everyone knows exactly what they're looking at. Also, not all data is interesting for every role in the newsroom. Maybe it's time to think about custom dashboards, so everyone can create the overview that helps optimise their work.

2. When it comes to data, less is more

It is very tempting to show all the data that is available. The more the better, right? Not exactly. Remember our warning about data shock? Data is only useful if it answers the right questions and gives you actionable insights. The more data is shown for the sake of showing data, the less it will mean to the user. It may all look very fancy, but what are you really going to do with this kind of information? Is it even informative? A good rule of thumb for editorial analytics is: if you can't act on it, it's a bad metric. That's why we're so adamant about actionability and smart notifications, and trying to take it even further with our Triple N project.

3. Numbers without context are just that: numbers

Numbers or graphs without any context are pretty useless. Say your dashboard shows you that your story had 98.345 visitors so far. That may look impressive. But is it actually good or bad, in the big picture of things? You should always have a reference if you want to be able to interpret data correctly. Without one, you'll never know if you should act on the number or not. Traditional reports often give you the previous reporting period as a reference (+0,5%), but that is not the kind of context you need. Truly actionable data gives you clear targets, expectations or baselines. Once you know what you're working towards, determining if you're on the right track becomes much easier - with the help of data.

4. Social media are not islands

Do you use any of those social monitoring tools? They're great if you want to get an idea of your performance on each channel as a whole. But if you want to review and compare the performance of a single story on all of those channels, that's when it becomes complicated. With these tools, there's usually no omnichannel view per story. Every channel has their own tool, insights, metrics and dashboards. Keeping an eye on all of them simultaneously can be daunting. And even if you do, you still won't see the big picture because you're monitoring channels, not stories.

5. Your website doesn't have to be your main channel

A custom Google Analytics dashboard with lots of numbers on a big screen can look impressive. But it only shows data from your website. Something could be happening on Twitter, or is engagement going through the roof on Facebook or Instagram? You wouldn't know from looking at your dashboard. People talk about your content on the channel of their choice, they could be ignoring your website completely. You've got a huge blind spot on your dashboards if you don't somehow integrate your social data with the website data. Especially if you're trying to follow an omnichannel content strategy.

6. Reporting periods don't show the whole picture

Daily or weekly reports of your content's performance don't show the whole picture. Stories have a certain biorhythm - some reach their peak right away (breaking news stories for example) others take time to accumulate page views but can stay relevant for weeks, months or years. And finally, older stories may pop back up again when a related story is on your reader's radar. This pattern is never in sync with standard reporting periods. In a weekly report delivered on Monday, the story posted on Sunday has little chance of reaching the top 10. Even if it was very successful. You'll never grasp the full impact of a story by looking at these weekly or daily reports. Instead, put the story at the center and follow it across channels and periods.

7. For story impact, totals are a wrong metric

Totals are the fuel of the business intelligence department. Managers love totals, which is why traditional reporting is focussed on showing website-totals: total unique visitors yesterday, total pageviews of news articles today, total shares on social. Totals therefore are usually the focus of your analytics solution, but they're not very actionable for the newsroom. You cannot optimise on totals. You can optimise on individual items. What you need is an overview of the story performance, something that shows you the impact of that story on all channels where it was published.

8. The next day… is one day too late

You just published your story. When are you getting its analytics report? Tomorrow? Next month? That's great for your long term strategy, but by then there's not much you can do about that story's impact anymore. You should want those insights of your story's performance now, right after publication, in real time. Why? Because right now gives you the chance to optimise while it still counts: improve it, play around with the headline or teaser, create a follow-up, summarise the comments. The data should inspire action - you own that story and should be in control of the engagement it's generating. After all, you're an editor in the fast and furious digital age!

9. The importance of accuracy is a myth

If you use analytics data to support long term business goals, it has to be 100% accurate. It needs to be verified, double checked, aggregated and stored in a secure place. This kind of accuracy takes time. Time that editors don't have. They need data now, in real time, as we showed above. The newsroom doesn't require that level of accuracy either. They should be more interested in trends: which story is growing, which one is dying? And they need it fast, rather than 100% accurate. Raw, good enough data is more effective in an editorial setting, than the company’s traditional, enterprise analytics systems.

Save the ‘official’ data for accountability, but rely on fast and real-time data for actionability.

Like our content?

Subscribe to our newsletter to receive blogs, news, technical updates and more, right in your inbox!