HuffPo and BuzzFeed co-founder Jonah Peretti recently said in a long and fascinating interview by Felix Salmon published at Matter:
I love metrics and I love thinking about optimization, but I think that the optimal state is being slightly suboptimal because as soon as you try to actually optimize, particularly for a single metric, you end up finding that the best way to optimize for that metric ends up perverting the metric and making the metric mean the opposite of what it used to mean.
This reminded me of an idea I’ve been kicking around for a while about how best to approach digital editorial strategy: it requires an ability to wield metrics, vision and instinct in just the right proportions.
It’s something I’ve been a part of for my own tiny blog here, an arts and culture website I co-founded, and even a business journal’s web presence. I’ve learned a few important things from my experience with editorial strategy, and while none of them are particularly surprising or mysterious, I think writing them out will be helpful to myself and perhaps to others.
Contribute to the conversation
Metrics are a great place to begin a conversation about editorial strategy but a terrible way to end it. I’ve seen metrics substituted for thinking critically about editorial direction all over the web, and what’s worse is I’ve been in the room when some of those poor decisions were made and I failed to object. It’s not a mistake I’m proud of, nor one I would make again.
But it’s easy to criticize after the fact. True leadership demands urgency. Whenever metrics are the deciding factor in an editorial decision, someone is making a mistake and it’s your responsibility to tell them.
Be respectful when their name is closer to the top of the org-chart than yours, but be direct and back up your assertions with evidence. Even if you’re outranked by everyone else in the room, at worst, you’ll be ignored, and at best you’ll show initiative and concern for the publication’s success.
I’m not saying there is no place for metrics in editorial strategy. They should absolutely be involved in the decision-making process, but they should never be the sole ingredient. In other words, these days metrics are usually necessary1 but never sufficient to make an informed editorial judgement.
Reactive vs. critical thinking
Pure reactivity is the wrong way to use metrics, and looks something like this:
“Everyone clicks this type of story, so let’s do more of this type of story!"
Don’t use metrics to narrowly define editorial strategy. After all, an algorithm could do that with little or no human intervention (and, as I’ll discuss below, they often do). Popular topics don’t need much additional promotion. They surface organically and allow you to focus on promoting lesser-known work of equal quality. This is a powerful concept if you’re wiling to use it in your strategy sessions.
Use metrics as one factor in your strategy. After all, the numbers are way to read between your own lines and to learn what drives popular content beyond mere keywords. That looks something like this:
“Everyone clicks on this type of story. What about it, beyond the mere subject matter, makes it so appealing?"
One problem, many possible solutions
There are many reasons some content does more pageviews, higher time-on-page or lower bounce rates than other content. Here are some illustrations of the problem of a narrow band of popular topics getting the majority of attention, and some ways I have thought up and in some cases successfully implemented to solve the problem.
The “Top Post” Filter Bubble
Eli Pariser popularized the idea of the filter bubble, an explanation for how tailored web content reinforces viewpoints with which we already agree, and insulates us from alternative perspectives. Metrics are often used to do this on websites.
The most-read stories of the previous day might be featured prominently in the sidebar. This additional exposure gets them even more clicks, and even if the software causes articles older than one day to “age out” of the featured-posts box, it still severely limits the potential for featuring other articles.
This may be the problem at some sites: your digital publication doesn’t know how to surface its best content. Consider adding to popular posts some links to less popular but equally valuable content. This will combat the filter bubble and help expose readers to good stuff they may otherwise miss.
The Slideshow Site
Slideshows are a dangerous game. They are almost guaranteed to turn your steady daily traffic into a big spike. If even half your daily visitors go through even half a 20-slide show, you’re doing five times your usual traffic that day. If you’re not careful, you risk becoming known as the slideshow site, instead of the news site.
If you insist on building slideshows, use myriad internal links to point your slideshow viewers to your substantive content. Better yet, work with in-house or outside developers to automate internal links to archive pages. For example, if you run a site about New York, the first time the name “Michael Bloomberg” appears in an article, your content management system could auto-generate a link to a page listing all articles mentioning his name.
10 Things About Headlines You Have to Read to Believe
Sorry to mislead you, but I’m only to going to talk about one. Slideshows often have numbers in the headline by definition. That is one explanation for why they’re so popular. People like headlines with numbers, as a quick search for “numbers in headlines” will illustrate.
I don’t advocate making every article a list. In fact, that’s a terrible idea, at least for news sites. But it’s worth incorporating numbers into headlines where it doesn’t look forced. For example, instead of “CEOs cite multiple syngeries as key to upcoming merger,” try “3 reasons Hospital 1 and Hospital 2 are merging, straight from the CEOs.”
On-point but out of sight
Maybe topics clearly within your site’s wheelhouse don’t perform well, no matter how many headlines, reporters or A/B tested tweets you use to produce and market them. This may simply mean the audience for those topics is substantially smaller than your broader audience. Don’t wait for the audience to find you.
I had great success finding an audience for some very niche stories because I sought it out on Reddit, in web forums, in Google+ Communities, with Twitter hashtags and more. The idea is that there are groups of people who self-select for interest in topics otherwise lacking broad appeal. Those audiences are smaller, but they are also more engaged, so the time spent finding them is worth it.
These are just examples, and the problems differ from site to site. But I think they explain the value and the limits of metrics in evaluating and improving editorial strategy at digital publications.