How do we know that media as an industry is doing well? If you look at digital ad growth you would think we’re killing it. Or the market cap for the big platforms. Or the number of new companies and job growth in media tech.
Everything is going up, up, up.
Except the parts that are failing.
Quality news is suffering terribly, and therefore maybe media is not as successful as it appears from the outside.
It may not be Google’s fault or Facebook’s fault. It might be poor decisions at the top creating this existential crisis. Cutting cancers out of bodies saves lives. Perhaps news as we know it doesn’t need to exist and other forms are replacing it. Perhaps it’s a form of natural selection and that’s just the way it is.
You wouldn’t be wrong for sitting in those camps. But you would be short-sighted. We can do better. It starts by looking at media as an ecosystem, connected parts that serve different purposes to make a healthier and happier society as a whole.
The beauty of networks, the idea that has made Facebook and countless Silicon Valley success stories possible, is that the connections become inherently valuable. People thrive on being connected. Businesses do, too.
Unfortunately, news orgs have never connected to anything very well. They’ve maintained their islands, and piece by piece every aspect of the business gets replaced by things that connect instead.
Connecting them should be easy, though. And if we can connect news orgs to the wider media ecosystem then the whole market will win.
One way to connect news orgs into the wider media ecosystem is to use technology to deconstruct the news and identify things that should connect and the value of those connections.
In any article we know the people, places and things the article mentions, and we can deduce what the most important entities are in a given story. By using these concepts as connective tissue we can link networks and network activity with the news.
On Facebook people amplify stories about those concepts and therefore they give them more value (or ignore the ones they don’t value). Data from stock markets or Wikipedia or other sources can weight the importance of those things. Search marketing and targeted impression values tell us what commercial demand looks like for a given entity, too.
Taking this idea a step further we know from Kaleida research, for example, that 100 articles have been written about Meghan Markle in the last month from leading publishers in the US and UK. She is an American TV actress who is now Prince Harry’s girlfriend.
Those articles have been shared on Facebook about 100,000 times or about 33 shares per article per day, on average. She is not a top tier celebrity like Kim Kardashian or Jay Z, so we don’t have to weight the value of her name for this example…not yet, anyhow.
We can get search rankings and bidding prices for her name on Google AdWords or other ad platforms. Let’s say search drives $2/click against 100k searches per month, maybe $2k per day in value.
We know quality publishers value this topic. We know people care about the subject by how much they are sharing those articles. And we understand advertiser demand around the topic from PPCs.
Maybe there’s a formula here:
Value of subject = (Performance ad revenue x Social distribution) — Cost of production
$2,000 per day from search clicks x 33 avg shares per article about Meghan Markle from across a selection of quality media outlets = $6,600 per day media value or about $2M for the month. After an estimated $100,000 in production costs the topic becomes worth $1.9M.
If there are, say, 500 topics a month of equal value then we’re talking about $1B per month in total value across the media ecosystem related to news.
That’s not money generated by publishers. Equally, it’s not value captured by platforms in a vacuum. It’s a recognition of value in the market related to news coverage on a topic by topic basis, using concepts as connections.
There are lots of ways to apply such a model on the publisher side. For example, more coverage of a topic doesn’t make it more valuable either for the publisher or the wider media ecosystem. More coverage means articles have to work harder to break through, so maybe less coverage with higher impact is the way to both increase value and sustain positioning. This model could prove that.
Again, this is merely a concept. It’s meant to demonstrate that connecting the news into a larger context is not only possible but perhaps necessary.
If we want to understand the strength of media and technology as an industry then we need to measure the impact of the news. And if we want to become stronger we need to balance the amazing growth we’re seeing in distribution and advertising with substance that reinforces it or perhaps even accelerates it. Until news is connected success in digital media is just big muscles on small bones.
We’re starting to expose some of this thinking about connecting concepts in the news through data we provide at Kaleida, so keep an eye out for it in our daily email newsletters and the charts and tools on kaleida.com. Also, if you are in the business of measuring value in networks and ecosystems we would love to talk to you.