Sorry, we could not find the combination you entered »
Please enter your email and we will send you an email where you can pick a new password.
Reset password:


Plus Report - By Thomas Baekdal - September 2017

How Editorial Analytics can Help you Define your Editorial Strategy

Shared by Plus subscriber
Avinash Kaushik
This is Baekdal Plus content. It is shared with you for free by a member. Please reshare it.

Let's talk about analytics, but not the type everyone else is talking about. Instead, let's talk about a type of analytics that can directly aid your newsroom to define a much better editorial strategy, as well as help create focus for your journalists.

In short, let's talk about Editorial Analytics.

Editorial analytics are a number of metrics that are directly linked to your editorial planning, goals, and purpose. And instead of being based on measuring page views or even read rates, they take a step back and measure impact and focus.

But before we go into the details of what this is, let's very briefly talk about why we need this.

Two fundamental problems facing every publisher

There are two major problems facing the media industry.

The first problem is that we now live in a shared media world, where all the boundaries of the past have been torn down.

Local newspapers show a good example of this.

In the past, local newspapers received almost 100% of the attention, while having almost no competition. As such, every local newspaper is defined around being this generalized package of a little bit of everything (which was a good thing in the old markets).

Today, of course, all of that has changed. Local newspapers now have to share that attention with many other channels, all of which are now competing with them.

The result is that your package with 'a little bit everything' has become a negative. If the only thing you have to offer is a little bit of everything, and someone else comes along with something more specific, more targeted, and more useful... you lose.

A little bit of everything is the worst thing to offer in a market faced by strong competition, because it prevents you from standing out.

The other problem is about when we consume media.

Media as a whole has always been something people consumed when they didn't have anything else to do. In other words, it was a low-intent form of consumption.

Newspapers in particular are really bad at this, because every single news story is basically a quick snack that you can glance at while you are on your way to work.

This is what news stories have always been. They are low-intent micro-moments.

The problem is the same as before. The digital world has proven to be a far more effective channel for this.

Both of these problems result in the same outcome, which is that we lack real distinction. When traditional publishers ask their readers to subscribe, people reply with: "Why? What are you doing that is worth paying for compared to all the other things we already have?"

And most traditional publishers, editors, and journalists simply don't have an answer to this.

This simple but exceptionally important change is completely destroying the traditional model of publishing. And the only way to fix this is to change the model.

In the future, the winning strategy for any publisher is to create distinction. Do something that will tell your audience why you are worth following (and paying for). What do you do that is special? What makes you unique? What service do you provide?

So what does this trend have to do with editorial analytics?

Well, the problem we have today is that normal analytics doesn't help you stand out. Instead, it only helps you optimize for the same thing everyone else is optimizing for.

For instance, when you look at basic analytics, like pageviews and bounce rates, you will automatically start to shift your focus towards the type of content that has more views.

But, since the most viewed content is also often the low-focused, low-intent, micro-moment type of articles, optimizing for pageviews also means that you become less distinct. It is directly making you do more of the same thing that everyone else is trying to do. And when you combine this with the social world, you end up just being another random link in this endless news feed of random content.

That's not a business model, because you will always be secondary to the platform itself (which is often Facebook).

Basic analytics can give you a lot of useful insights about what people are doing right now, but it doesn't help you refine your editorial focus.

The same is true for business metrics. Business metrics such as subscription rates, churn rates, renewal rates, revenue, profit, and so forth, are incredibly important metrics to have. But none of these metrics help a journalist define how to write an article.

Business metrics are almost always the result of long-term momentum. For instance, the reason people decide to renew a subscription is rarely because of any single article.

And when you show your business metrics to your newsroom, your journalists have no idea what to do about them. It's too abstract and too disconnected from their daily work.

So what we need is a different type of metric that is specifically linked to measuring the impact of the actual journalism, from an editorial perspective.

In other words, what we need is editorial analytics.

Introduction to editorial analytics

In order to really understand editorial analytics, we need to start, not by looking at any data, but instead looking at what we want the data to tell us.

A very good example of this is something my good friend Avinash Kaushik talks about all the time. For instance, in a recent post on LinkedIn, he wrote: "No Data, Just Questions Please."

This sounds counter-intuitive until you realize how powerful this is.

The problem we have today is that we often just look at the data without knowing what to look for.

We will create analytics reports, set up dashboards, create fancy visual real-time traffic screens for our journalists to see, etc. But, none of that really means anything. We are just 'puking up data' as Avinash calls it.

But if you define your analytics around questions, we can completely reframe our focus. As Avinash writes:

Questions provide context, questions lead to relationships, questions expand your horizon, questions lead you business savvy, and in doing all that, and more, questions provide that magical missing ingredient: Purpose.

For instance, some of the questions he suggests in his post are:

You immediately see how powerful this is compared to just looking at a standard analytics dashboard. The question about cost, for instance, forces you to focus your analysis on just the metrics that would answer that single question.

The question about lifetime value, which is something publishers should really care more about, also requires an entirely different approach to measuring and analysing analytics than your standard reports can provide.

Obviously, Avinash is not talking about publishing here. His questions are very ecommerce-centric, but the concept is the same for us.

So, let me give you a number of publisher-centric questions defined around the concept of editorial analytics.

And we will start with how we cover news.

Editorial metric: How do people feel about crime?

Last week, I wrote about five problems in the media that are unintentionally causing harm to our society. In it, I talked about how the role of journalism isn't to just report stories, but to make sure that we end up making our readers smarter.

A good example is with how we cover crime, compared to the public perception of crime levels.

One of the things we see again and again, is how the public is increasingly misinformed about the levels and dangers of crime.

In a recent study from my country, 80% of the public thought that crime was going in the opposite direction to what is really happening, and we often see the same trend in other countries.

For instance, in the US, we noticed a complete reversal of the trends in crime perception after the 9/11 terrorist attack.

So, is crime going up or down? Well, it's complicated. There was a weird uptick in violent crime in 2016, but, historically, the world is getting safer. In the 1990s, both the crime levels and the perception of crime were all going in the same direction. But then after 9/11, people's perception of crime started to go back up, even though the level of crime kept falling.

This is a massive problem, because it indicates that the public is misinformed. And this deception of reality is then being used by some politicians to stoke fear and drive votes for issues that aren't actually a problem, which causes further issues for our democracies.

So, here we have an obvious editorial metric for us to define, which is:

What is the perception gap for crime, between reality and the imagined?

What you do is this.

First, you go out and look at the real data to see what is actually happening in the world. For things like crime, this data is usually very easy to find.

You then do a study among your own readers where you ask them: "What do you think is happening?"

Next, you compare the two, and you will probably find something like this.

You then look at the gap between these two points, and you give that a number... which is now your baseline.

Now we have an editorial metric.

You then show this metric to your journalists and you tell them that it's now their job to make sure that this gap is reduced to as close to zero as possible. Because the role of a journalist is not just to report a story, but to make sure the reader is correctly informed.

And then, sometime later (six months, a year), you do exactly the same study. Once again, you look at the real data, you ask your own readers what they think, and you compare the two.

And now what you should hopefully see is this:

Not only will this have a very positive impact on our society as a whole, but think about the challenge I mentioned, about publishers not being able to create distinction.

This would!

By defining your editorial strategy around an editorial metric like this one, you can directly use it to drive value up for your readers, which in turn would drive subscriptions.

You would be able to say: "This is how misinformed people were before they started reading our newspapers, and this is how informed they are now!"

Think about how powerful a selling point this is. You are demonstrating real value, by offering your readers the chance to get smarter and better informed through real metrics.

You can prove that you are worth paying for.

This is exactly what newspapers need.

For instance, when the New York Times ran its 'Truth' campaign, its main selling point was to say "Truth is more important than ever".


This was a good slogan, and NYT is definitely growing, but imagine how much more powerful it would be if they could also prove it.

With editorial analytics they can, because they would be able to directly show people how their articles get people closer to that truth.

Also, think about the problem with fake news. Again, the main issue is that people often can't tell the difference, but if you were to use editorial analytics, you could directly show people you can be trusted.

And, on top of this, it also helps refine your newsroom, because it centers the focus of all your journalists around these metrics. It helps the journalists see and know the focus of the story even before they write it.

If you give your journalists a picture of what the real world is actually like, they won't just report random stories without thinking about it. They would start to ask smarter questions when doing interviews; they would be able to refine what and who to trust; but more importantly, they would start to write each article with the facts in mind... as opposed to just fact-checking what somebody said in a follow-up article.

They can do all that, because they know that their job is to do this:

And, of course, this doesn't just relate to crime, but for every topic you cover. Obviously, some are harder to define than others, but the concept is still the same.

Defining a set of editorial metrics around the question of perception versus reality is so incredibly powerful because it turns your unfocused, random news coverage into something of real, measurable value.

What is the perception gap between reality and the imagined... for each major issue that we cover?

But let's talk about something that isn't news.

Editorial metric: Are people getting healthier?

Another very obvious thing to define an editorial metric around are all those activities we do to improve ourselves. Like health care.

Today most health publishers just put out random stories about exercise, foods, etc., but almost no publisher actually measures it.

Just think about that for a moment.

Isn't it weird that a health publisher has no metrics that indicate the actual health, or health improvements, of their audience?

You've got pageviews, bounce rates, referral percentages, and Facebook views... but no metric actually related to any of your editorial focus areas.

It's crazy!

It's also unique to the media industry, because other health-based companies do use health data as their key performance metrics.

A good example of this is what we see all the tech companies do.

Take a look at Apple.

When they launched their updated Apple Watch Series 3 earlier this month, they spent a lot of time talking about Apple HealthKit, and how it's defined around helping you be more active and become healthier.

These are their 'editorial metrics'.

For instance, when you watch their intro video, you will see how they have defined their purpose around 4 key areas.


Everything is connected. When you move more, you tend to feel less stressed. If you sleep better, you tend to eat better.

But notice how each one of these things is also a metric. It's something that you can directly quantify.

Every single time Apple comes out with a new update or a new feature, it will be laser focused on improving these metrics so that you end up with better and better results.

And from a user perspective, each app is designed around motivating you to improve your own personal health metrics as well.

In other words, Apple has defined its HealthKit around what is basically a set of editorial metrics, which then defines their purpose, focuses their engineering and design teams, and motivates their audiences.

Everyone from start to finish has a clear understanding of what they need to work towards, because these editorial metrics always point them in the right direction.

For instance, their activity app is laser focused on the metric of movement. And the success criteria for the app is whether or not it is successful at changing the level of movement you do before you started compared to what you do today... and tomorrow.


Think about how empowered this simple metric makes you feel.

Now compare this to what you see, for instance, in many fitness magazines. I have seen fitness magazines discuss their 'social strategies' and 'how to get more views on Facebook', and the tactic they come up with is to create more of the type of content that you can just watch without moving at all.

When you design your content around quick-content-snacks that you can just watch when you are not really in the mood to do anything, you are directly encouraging people not to move.

Think about how insane that is for a fitness magazine.

But also think about it in business terms. If your fitness magazine doesn't encourage me to move, why would I want to subscribe to it?

The only reason why anyone would ever pay for your fitness articles is if you are successful in helping people do more fitness, and through that feel better in their lives. If you are not delivering that, you have nothing of value... you just have a lot of completely meaningless views on Facebook.

So, the editorial metric for a fitness magazine should be "How much movement do we create?"

And don't just talk about it. Measure it. Build tools around it. Drive actual physical engagement with it.

Take something like this article from Women's Health

With traditional analytics, you would measure this in terms of pageviews, and, if you are slightly more advanced, you might even measure read-rates to know whether people actually read it or not.

But none of those metrics really mean anything.

What you should actually be measuring is 'participation rate', as in:

In other words, you could define your editorial metric as:

How can we improve the rate of participation for our fitness articles?

Again, think about how much focus this question brings to your editorial strategy and planning.

Maybe you could change the format to motivate people to participate, and to act more like an active guide rather than just a passive article.

Maybe, you need to build this more like a service that people can use for training. Maybe you could add tools that help people track and refine their progress (and also to help you track this better).

This is what companies like Apple do all the time. Right now they are working on the next version of HealthKit, and they are doing this while being 100% focused on improving their core metrics.

They are asking these exact questions, and measuring their success based on the outcome.

How can we get people to participate more with HealthKit?

Editorial metric: Are our readers getting smarter?

Another form of editorial metric is related to any form of publishing designed to improve people's skills. Sites about photography, art, DIY, teaching, etc.

The concept is the same as before. If you are trying to teach people something, why would you measure that with pageviews or Facebook likes? Those metrics don't imply learning.

Take a site like ArtStation, which I have mentioned in some of my previous articles because it has a brilliant model.

They have essentially defined their editorial metric as:

What is the quality of user-submissions?


How can we improve the quality of the art that people share?

These two questions define every single aspect of their site. From the format, to the editorial strategy, and also to their technical implementation of how the site works.

For instance, in order to use ArtStation, they require that you go through an account verification process. And they make the reason for this quite clear:

ArtStation is a professional community. The quality of our users is high and our signal to noise ratio is highest in the industry.

To maintain a high quality community, we only want serious users on ArtStation and that is why we have implemented this verification step.

They are doing this to reduce the problem with low-end accounts, as well as being able to eliminate trolls, bots, and other types of fake accounts.

We went from having to ban hundreds of fake accounts and trolls every month, spending thousands of dollars in lost time and effort, down to banning literally only a couple of accounts every month. This really does work and the quality of the community has improved dramatically.

And when you complain, ArtStation has a very simple message:

If you feel this verification is lame, don't use ArtStation. Simple. It really doesn't bother us because we know the system works and it has not affected our growth at all. We continue to grow leaps and bounds with high quality artists. This system is actually keeping out the lame users.

We can all have a long debate about the tone-of-voice here and whether you should call some users "lame", but the point is that ArtStation has a very sharp editorial focus.

And, while I don't know if they have actually quantified quality as a direct metric, it's pretty clear that the quality of what appears on their site defines their success, and their editorial focus.

You see this very clearly everywhere you look. From the services they provide to their users and subscribers, to the quality and expertise of people that they interview, to the level of skill they encourage through their challenges.

The result of this is a site that doesn't really work that well for low-intent social boredom (aka Facebook), but which works brilliantly as a place for professionals to gather and get inspired.

So, quality of your work is a very powerful editorial metric if you want to stand out and convince people to pay.

I can also show you what happens if you don't do this.

Take a look at Popular Photography.

Popular Photography was launched in 1937 but, after 80 years, in March 2017 it sadly had to close down.

I could write a long article about why this happened, but there were essentially two key reasons why it failed.

The first reason was simply because the market changed. Exactly the same thing that killed Kodak also killed Popular Photography. When digital photography moved into our phones, the entire market started to split apart and polarize in two very different directions.

One direction was towards more professionally focused photography, which Popular Photography wasn't very good at with its 'consumer focus'.

The other direction was towards phones, Instagram, Snapchat... which is all about everyday low-intent photography, which nobody would ever subscribe to a magazine to read about.

As a result, Popular Photography found itself lost in the middle, offering people a magazine that nobody needed anymore.

The second problem was that, in order to fix their decline, they started optimizing for the vanity metrics (like we see with so many other publishers).

As a result, their articles became ever more pointless, as you clearly see when you look at the type of articles they posted just before they closed.

Here you see a news story about a new feature on Instagram, which merely tells us that this feature now exists. There is kind of a weird story about how someone is better than you. And then there is some typical viral crap that publishers have started posting, which is basically some journalist finding a video on YouTube and then posting that as an article.

The combination of this, the split in the market and the loss of focus, meant that Popular Photography lost its reason to exist... and, sadly, had to close.

They were looking at all the wrong metrics, and they didn't have any editorial metrics to act as a focus point for their value.

We see the difference every time we look at the digital natives. All digital natives focus on being special and amazing. Take a person like Peter McKinnon, who in only a year has been able to create a YouTube channel about photography with over a million subscribers.

He is essentially doing what Popular Photography should have done, because every single one of his videos is designed around the editorial metric of:

Are my viewers getting smarter?

He is not just posting random viral videos he happened to find somewhere. For instance, while Popular Photography merely posted a news story about some new feature on Instagram, Peter McKinnon takes you out to a famous instagrammer to give you tips about how to shoot food.


Or what if you quickly want to know how they shot the videos for that video? Sure, here you go:


The difference is shocking!

And this, again, is what it means to have an editorial metric. In Peter's case, I don't think he has a spreadsheet where he is actually measuring 'smartness' as a number, but I can assure you that it's constantly in the back of his mind.

Every single thing he does is constantly evaluated against this metric of "what can I do to improve this so that people end up smarter?"

It's so important.

Not everything is easy to define editorially

Many of the examples above involved some type of user interaction, either directly or indirectly. And with the case of news, the focus on informing the public is also an obvious one.

The hardest editorial metrics to define, however, are when the audience don't have to think or do anything.

A good example of that is entertainment.

Entertainment content works without any involvement from the audience at all. They don't have to engage. They don't have try it out themselves. They don't have to learn anything, or end up smarter than when they started.

It's just something fun.

For instance, after I have finished a long day of writing and analysing, I often just sit down with my iPad and find something relaxing and enjoyable to watch. But at that moment, I'm not looking to learn anything, or be challenged with yet another skill. I'm just tired and want to do nothing for a few hours.

In that moment, for a publisher to have an editorial metric doesn't really make much sense, because I'm not looking for something to focus me.

Instead, you need to look at other metrics to define whether you are delivering what people need. For instance, YouTube defines its success metrics around watched time. And this is also what they are aiming to improve.

So, when YouTube has meetings about how to make YouTube better, they are not really talking about how to get more views. They are talking about how to get you to spend more time, and to make that time more enjoyable.

This is not really an editorial metric, because there is no real focus, but it is still a metric defined by a question.

And this brings us back to where we started.

If you are trying to have an impact on your audience, defining your editorial strategy around an editorial metric is absolutely critical. But no matter what you aim to do, know the questions before you look for answers in the data.

The main reason publishers often wander around not knowing what to do, is because you never looked for the question.


The Baekdal Plus Newsletter is the best way to be notified about the latest media reports, but it also comes with extra insights.

Get the newsletter

Thomas Baekdal

Founder, media analyst, author, and publisher. Follow on Twitter

"Thomas Baekdal is one of Scandinavia's most sought-after experts in the digitization of media companies. He has made ​​himself known for his analysis of how digitization has changed the way we consume media."
Swedish business magazine, Resumé


—   analytics   —


How my focus on analytics has changed as an independent publisher


How can publishers measure trust and other editorial metrics?


A guide to analytics for independent journalists


Why producing less news leads to a boost in subscriptions


GDPR: How publishers can track things without tracking people


Machine Learning is like black-magic for publishers