The following is a guest contributed post from Jeremy Fain, CEO and founder of Cognitiv.
A lot of people have asked me about my thoughts for 2018, and what I think the overarching trends in advertising technology and deep learning will be in the coming year. Far be it from me to disappoint my fans – so here’s my take on next year’s biggest topics:
Marketers will have to start thinking seriously about deep learning.
AI has been a buzzword for the past several years, as clearly evidenced by the vast numbers of products claiming to be AI currently on the market. While most of these applications don’t really live up to the picture of AI that most people have in their heads of a Jetsons-like robot, there have lately been a series of discoveries, most notably in the field of deep learning, that are sure to have a serious impact on the way that most businesses operate.
Deep learning and neural networks are at the heart of some of the most astonishing machine learning developments, from image recognition to the natural language processing that enables gadgets like Amazon’s Alexa and Google Home to operate. But access to the technology and insights of deep learning is no longer limited to the big players, as new tools have arrived to bring the computing power and analytical insight of deep learning to marketers.
In some ways, the current wave of AI products is good, because it means that more people, including marketers, have become aware of what AI has the potential to do as well as its possible limitations. As more advanced forms of AI become market-ready, deep learning will be at the forefront of any of those conversations, and marketers will begin to understand the value of using deep learning to buy media and create audiences to advertise against, becoming better equipped to lead their businesses to success in 2018 and beyond.
Mobile ad networks will be forced to become more transparent.
Before programmatic became a mainstay of digital advertising, ad networks performed an important function as an intermediary between digital advertisers and publishers. They could help publishers find buyers for their inventory, and they could put inventory from multiple publishers together to make it easier for advertisers to buy. Because most inventory came from smaller publishers, it cost less, and was a cost-effective value proposition for most advertisers.
The rise of programmatic, however, created a way for advertisers to directly buy from any publisher with added transparency into pricing and websites. Suddenly, ad networks had to deliver more value than just inventory aggregation. This transition took place in the traditional digital display world years ago but has yet to take place in mobile advertising. 2018 will be the year where mobile ad networks will have to prove their added costs or face the reality that mobile advertisers have begun to use programmatic for user acquisition and retention campaigns.
Header bidding will become a problem on the agency side, so its use will diminish.
This relates in some ways to the general theme of greater transparency in the digital advertising markets. Header bidding code allows a publisher to offer the same impression in multiple exchanges at the same time, ultimately leading to the impression being sold for a higher price than if a single exchange was used. This means advertisers are bidding multiple times on the same inventory and, because of the nature of programmatic, they are likely paying more. Originally, header bidding was meant to allow advertisers to compete programmatically for all of a publisher’s inventory, instead of just the unsold “dregs” that were left over after directly sold insertion orders had been fulfilled. The technology, however, is now being used to offer the same impression through multiple exchanges to the same DSP. This has driven DSP costs up because of the skyrocketing number of “duplicate” bid requests being received from multiple exchanges and has given rise to an entirely new ad tech industry of trying to sift through these duplicate impression requests.
A much more elegant, and likely solution in 2018, will be that advertisers through their agencies will require the use of the ads.txt standard. This file is meant to be made available by every publisher wishing to sell their inventory programmatically. It lists the exchanges their inventory is available in. Ads.txt was created to stop a flagrant type of fraud where websites list themselves inaccurately as more valuable websites, but Ads.txt can also be a great tool to cut down on duplicate impressions. A publisher has the right to sell its inventory any way it chooses, and different exchanges may have different strengths for different types of inventory, so I do not predict (or advise) that advertisers will require pubs use only one exchange. In the end though, I predict that header bidding as it is used today is on its way out. The costs are too high for DSPs and advertisers will realize they are bidding on the same exact impression and ultimately paying a higher price. I’ve never met an advertiser that liked that.
If there’s any overarching theme here, it’s the idea that marketers and advertisers are constantly getting more savvy about the tools they’re using, whether it’s AI, ad networks, or ad exchanges. They will begin asking tough questions and demanding accountability in 2018 in new ways that will, as always, lead to big changes in the advertising ecosystem.
The post Opinion: Marketers Have to Start Thinking Seriously About Deep Learning appeared first on Mobile Marketing Watch.