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The 5 Faces of Programmatic Evolution

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Brief Notes on Automated Advertising based on 5 keys Politics, Ethics, Technique, Economics and Technology. Ranging from Use of data to Conflicts of Interest, from the role of Coding to Optimisation Algorithm, From Reach to User Identification and so on.

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The 5 Faces of Programmatic Evolution

  1. 1. The Five Faces of Programmatic Evolution written by paola furlanetto on May 2017 and updated August 2017 Last May the IAB USA renamed Programmatic as ‘Automated Advertising’. This sends a strong message and describes the activity as what it is: an automation system that can not be avoided. We see brands that are still questioning whether programmatic is an opportunity. Is it possible to choose whether to automate or not? I don’t think so. Non-automation is a futile stance against the inevitable march to progress. But we can choose how to do it: Make the market safe • Create legal and financial incentives for players in the market to act responsibly. • The communication industry can grant full freedom, or impose regulations and guidelines on operators. This route is the one chosen by the USA and Italy, who with MRC certification and UPA White Book respectively, are promoting minimum quality standards for the market. Reduce costs, guarantee ease of control • The market has long questioned the poor value of programmatic media, for several reasons. In addition to arbitrage, there is also the non-use of proprietary data, ineffective planning and buying strategies, the ability to target and of course, talent within client and agency businesses. • There is also the issue of the supply chain. Programmatic is a channel with several stages and middle men, and by its nature is potentially inefficient. Shortening the chain not only limits markups, but also allows smoother integration between platforms and third-party verification. • Google’s recent position on fake ad inventory reminds us that control by third-party verification firms is not only useful, but indeed necessary for brands. But the issues around programmatic media aren’t just to do with costs and brand safety. There are several other important aspects, from cross-media currency definition, to the future role of Artificial Intelligence. To summarise these, I’ve used the Star Model © which covers 5 different understanding variables: Politics, Ethics, Economics, Technique and Technology. 1. Politics • According to Cosimo Accoto’s “Il Mondo Dato” (The world of Data)” publication, “code models the future” and “software deeply changes our idea of what is possible”. • Automation, and with it programmatic media, has a fundamentally political role; in automated advertising it’s possible to develop an ideal framework for commercial communication. Programmatic is the perfect environment to link different tools, touchpoints and devices. Automated advertising allows to design the future and lead us to create guidelines for its development.
  2. 2. • Even at organizational chart level, programmatic is still underestimated. Today programmatic management is often limited to operational roles. A bigger strategic planning from companies is needed. Therefore top management should be involved and more attention should be paid to long terms communications and marketing goals. • Talking about strategic vision, There’s a deep cultural divide today. We have a market with three groups; . firstly we have the powerhouses of Google and Facebook (with Amazon and Apple quickly moving into the fray), These companies lead the market with strategic thinking and the ability of make it actionable. . Next we have brands and traditional publishers, who basically react to market forces. . Lastly, we have agencies and trading desks who are left looking for any ways of increasing their share of business (often eroded by farce contracts with fees close to zero). For brands, it’s time to move more decisively on technological-strategic planning of automation. 2. Ethics • Conflicts of interest and use of data are the most important topics when debating the ethics of automated advertising. Conflicts of interest exist in many forms - two of them, technology vendors as media owners, and agency arbitrage- involve automated advertising business directly. • The use of data is not a new topic in the world of commercial communication, but it is particularly important in programmatic. Brands tends to assume extreme positions; not giving data or, the opposite, granting data freely with limited constraints. This two position are equally risky for the companies, the first makes programmatic campaigns less effective, the second leaves the companies with no protection. There’s a third way, the confused contracts. Maybe this is the most risky option because companies feel safe but they aren’t.. EU and USA laws also provide useful suggestions about relationships between brands and citizens, from which we can draw ideas and guidelines: For use of data: ● Awareness: informing the user about the terms of the possible use of the data in a clear and unambiguous way ● Development and terms of the agreement ● Opt-out options with potential restrictions and penalties For conflict of interest: ● Disclosure: if a person/company is liable for conflict of interest shall declare it before starting any trade initiative (to be applied to the whole chain, not only to agencies’ arbitrage, certainly the the most obvious conflict of interest, but not the only one). So the “conscious choice”, a choice that you make in full cognition of reality, is probably the more appropriate behaviour in conflicts of interest and data management cases.
  3. 3. 3. Economics The Economic variable is the most commonly discussed. Most players in the market identify at least two critical areas in automated advertising: • Arbitrage which allows media agencies to make profits and also to cover resource fees that are not included in the contractual remuneration with the user. • Technological platforms’ long chain with their costs and markup In the Ethic paragraph we referred to Arbitrage possible solutions. But regarding the long channel, as with all “native” publisher-driven communication, it’s important to highlight in details all costs in invoices issued to agencies / brands. 4. Technical development According to Enrica Seregni,“Programmatic is an optimizer”. There are 3 areas of interest: 1. Platform interface and performance. 2. Optimisation algorithms 3. Setting of metrics & KPIs Interfaces are a primary concern for technology providers, while the transparency of the trading model is relevant in cases of arbitrage, but metrics require the most attention. Usually, the success of a communication is directly related to how metrics are defined (reach, first and foremost) and also with the number of consumers actually reached, excluding devices and media duplication over the time. Automated advertising offers buyers the opportunity to calculate effective reach across different touchpoints. The opportunities are enormous but it’s necessary to follow several upstream steps. The main are: - standardised definition of the period of time within which reach is evaluated (reach is strictly linked to the time frame, whether based on cookies or audience sample survey. At some point the individual is not followed anymore, and is considered a new subject, so numbers are inflated) - user /individual identification excluding multi-screen and multi-channel duplication. Part of the current debate about technology is focused on these topics, especially on the second. 5. Technological variable and the current challenges, according to Nene Harrison from Eley Consulting. I’ve known and appreciated Nene Harrison for a long time, since we brought digital media measurement to the attention of several corporation operating in Italy. They were pioneering days for Italian digital audit and I’ve always appreciated Nene’s great competence but also passion, pragmatism and intellectual honesty. I’m now doing some consulting for Eley and asked Nene to indicate in her opinion the main challenges for the programmatic today. To paraphrase in 5 points: 1. The vast majority of brands’ data is held within Google & Facebook’s walled gardens. How do brands wrestle control of their own data back?
  4. 4. 2. Publishers looking to maximise yield / revenue face a big challenge in managing multiple revenue sources – current techniques such as header bidding still need to be developed further. 3. There is still no single standard for viewability measurement; every vendor has their own methodology and results can vary dramatically. 4. Mobile & desktop environments are increasingly hostile to cookies; a robust cookie-less method of tracking is needed if brands are ever to get accurate campaign measurement. 5. Incredible lack of knowledge across the industry about how the various platforms work together – causes price inflation and operational inefficiency, e.g. with simultaneous auctions, double-charging etc. Conclusion As Cosimo Accoto says “(programmatic) software deeply transforms our conception of what is possible”. It is therefore necessary to have a broader view of the topic, looking beyond mere problem solving and thinking ahead, well into the future. It is important that top management is involved in this. Leaving strategic thinking in the hands of commercial entities will undoubtedly increase fragmentation and decrease effectiveness. There are three technical considerations that are key for proper measurement of automated advertising; uniformity in reach time-frames, user identification in multi-screen journey, and user identification in multi-channel journey. Even though conflicts of interest and data management are often discussed, these subjects are not properly addressed in all legal contracts between advertisers and agencies. A “conscious choice” should be made by brands when negotiating. Data ownership agreements, opt-out clauses and, of course, penalties can improve the nature of contracts and can lay a more efficient path to the future of automated advertising.