Monday, March 20, 2017

How quality content can win in the long run

Digital advertising is broken for many publications.
Back in the days when my job was persuading advertisers to spend money with our business publication, I would talk about the importance of a client's ad appearing next to credible, high-quality content. Editorial environment matters, was the argument.

Google, Facebook, and Yahoo pretty much destroyed that business model. They promised advertisers to deliver their ads to specific demographic groups with little waste -- for example, female executives in Baltimore who have searched for information about luxury automobiles in the past year. And their prices were much lower. 

But the importance of high-quality, credible content has just resurfaced in a big way. Some major advertisers in England pulled their ads from Google and YouTube because their ads were placed next to content of extremist organizations promoting hate speech.

Among those pulling ads were French advertising giant Havas, the BBC, the UK government, and The Guardian newspaper. The Times of London first broke the story (paywall). 

What this means is that digital publications can compete with Google, Facebook, YouTube and the rest by relying on a relationship of trust and confidence rather than scale -- totals of eyeballs. 

Frederic Filloux's model for measuring a publication's quality and credibility.
The new tools of competition

Digital Davids can defeat Tech Goliaths by using a number of tools:
  • Web metrics of loyalty, rather than volume of traffic
  • Creating a community of trust rather than a mass of eyeballs
  • Alternative revenue sources for digital media
  • Native advertising, which links editorial content with sponsored content
  • New tools of trust, such as quality scores (see below)
Digital journalism guru Frederic Filloux has some excellent ideas about new tools of trust. In an essay in Monday Note, he pointed out that Facebook and Google themselves are developing some tools to ensure that content is not misleading or "fake". 

The problem is that refining algorithms to detect fake news in individual articles doesn't work reliably, at least not yet.

Filloux, a Knight Fellow at Stanford University, is working on developing algorithms that instead give a quality score to the publisher and the author of a piece of content so that the user can make a judgment of whether to trust an item.

The quality criteria for publishers would be:
  • Journalism awards (reliable sources would be more likely to have won some)
  • Size of the newsroom (click-bait and fake-news factories are often tiny operations)
  • Years of operation (most fake-news specialists are recent)
The quality criteria for authors would be:
  • Journalism awards
  • Social media footprint (who connects to the author)
  • Quantity of work noted in Lexis/Nexis
  • LinkedIn resume
About 40 factors in all would figure into this quality score, and Filloux, with the scientifc approach he favors, is well aware of potential weaknesses -- the criteria themselves could be gamed and falsified, for example. 

Nonetheless, it is exciting to see a journalist taking on this huge problem in an innovative and systematic way. I, for one, will be watching closely.


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