Every Friday, The Big Smoke looks at industry news curated by MediaScope. This week, we look at the age of accountability, the AI awakening and ponder if it’s time to break up Google.
Seven questions marketers should ask when weighing the quality of their data (Julie Fleischer – AdWeek)
The media landscape has realigned itself with lightning speed to the power of data. After a century of being limited by “brute force media,” marketers quickly glommed onto the vast potential of digital and addressable audiences.
The data “exhaust” from the digital experience has been a game changer for marketers, powered first by sites, then by ad networks and finally by programmatic. Money shifted from reach-based to “people-based” planning, augmented by powerful new data companies, monetising the categories and groupings of people brands want to reach in ever finer granular detail.
But somewhere along the way, the proposition fractured. We discovered that data itself is not the key to addressable marketing and better business outcomes – quality data is.
Are we entering adtech’s era of accountability? (Ronan Shields – The Drum)
The contagion of this distrust has not been contained within brand-side marketers (or their representative trade bodies), with agencies beating their chests when it comes to demands for Facebook and Google to provide more transparent advertising.
Even demand-side platforms (DSPs which have historically been seen as the black-box operators of the adtech sector) are beginning to apply pressure to supply-side platforms (SSPs) to ensure the quality of inventory they offer is of a required standard.
John Gentry, OpenX, president, says much more publishers are now asking questions around control of their inventory, and transparency around fees.
He adds that the trend towards publishers embracing header bidding technology is indicative of this trend (whereas previously they would have used programmatic technologies to trade remnant inventory).
“What we’re seeing more of an emphasis on quality.”
Is it time to break up Google? (Jonathan Taplin – New York Times)
In just 10 years, the world’s five largest companies by market capitalisation have all changed, save for one: Microsoft. Exxon Mobil, General Electric, Citigroup and Shell Oil are out and Apple, Alphabet (the parent company of Google), Amazon and Facebook have taken their place.
They’re all tech companies, and each dominates its corner of the industry: Google has an 88% market share in search advertising, Facebook (and its subsidiaries Instagram, WhatsApp and Messenger) owns 77% of mobile social traffic and Amazon has a 74% share in the e-book market. In classic economic terms, all three are monopolies.
We have been transported back to the early 20th century, when arguments about “the curse of bigness” were advanced by President Woodrow Wilson’s counsellor, Louis Brandeis, before Wilson appointed him to the Supreme Court. Brandeis wanted to eliminate monopolies, because (in the words of his biographer Melvin Urofsky) “in a democratic society the existence of large centers of private power is dangerous to the continuing vitality of a free people.” We need look no further than the conduct of the largest banks in the 2008 financial crisis or the role that Facebook and Google play in the “fake news” business to know that Brandeis was right.
The great AI awakening (Gideon Lewis-Kraus – New York Times)
Google’s decision to reorganise itself around AI was the first major manifestation of what has become an industrywide machine-learning delirium. Over the past four years, six companies in particular – Google, Facebook, Apple, Amazon, Microsoft and the Chinese firm Baidu – have touched off an arms race for AI talent, particularly within universities. The phrase “artificial intelligence” is invoked as if its meaning were self-evident, but it has always been a source of confusion and controversy. Imagine if you went back to the 1970s, stopped someone on the street, pulled out a smartphone and showed her Google Maps. What is at stake is not just one more piecemeal innovation but control over what very well could represent an entirely new computational platform.