NEWS / MARKETING

At the origin of programmatic purchases, the promise was to rely on an algorithm to buy the right ad at the right time for the right user. How? By analyzing in real time more than 40 advertising variables in a few milliseconds. If today’s purchase orders and auctions are driven by an algorithm, what is the purpose of the media trader if not to press a button to launch a campaign?

At the origin of programmatic purchases, the promise was to rely on an algorithm to buy the right ad at the right time for the right user. How? By analyzing in real time more than 40 advertising variables in a few milliseconds. If today’s purchase orders and auctions are driven by an algorithm, what is the purpose of the media trader if not to press a button to launch a campaign?

Since the emergence of the programmatic in France in 2010, technologies have been constantly emerging: to improve the quality of broadcasting, audience targeting via data, but above all in analysis to improve advertisers’ customer knowledge and streamline their media mix.

As an example: here is a selection of technologies that media traders have had to learn to integrate into their strategies to get the most out of their programmatic purchases.

Media trading technologies evolution from 2010 until today

In order to understand all these technologies as quickly as they appear, the media trader will need to demonstrate other skills than pushing a button to launch a programmatic campaign.

The trader acts as an expert advisor on the programmatic technologies that brands must integrate

Every day, new tools are created to make advertising ever more relevant and impactful. This technological ecosystem has become incomprehensible to advertisers: they need a referent who masters and supports them on this subject. The trader thus becomes both a technology expert and a client manager to support brands in building an ecosystem adapted to their needs. When this ecosystem is established, the trader manages the tools, connects them together, and gives back to the client a harmonised campaign balance sheet with understandable lessons from multiple sources.

The internalization of media buying by some advertisers also requires tool consulting and training capabilities on the part of agency media traders. As the transfer of programming skills is always progressive and often partial, advertisers prefer to keep the support of an agency trader who will help them make the right decisions.

The media trader is not alone anymore, accompanied by profiles that have become essential

Some technology providers (Google, Adobe, Adform…) are trying to offer “full-stack” solutions that have the advantage of making all the technological components communicate with each other in a native way. When this is not the case, media traders must rely on teams of traffic developers to help create gateways between each tool.

We are also witnessing a growing role within agencies of profiles of Big Data experts. These stakeholders are essential to ensure that the quantities of data that can be used in programming are properly understood and made accessible to traders and advertisers.

Traders always analyze and decide on optimizations and adjustments themselves, but Big Data analysis allow them to see much more things, much faster, not to miss optimization opportunities, especially if these analysis can be directly activated. A Trading Desk today can only function on its knowledge of the programmatic ecosystem and its expertise as a buyer. More than ever, the profession has become a composite expertise.

Finally, the complexity of ecosystems and the overlapping of many tools requires that agencies be able to improve existing market tools to make them more relevant, easier to use and better connected to each other. Within the agency, the trader is in fact a real trend detector, but needs other support skills. At Artefact, for example, a product team is dedicated to automating certain time-consuming tasks with low added value managed by the internal Trading Desk (trafficking, dashboarding, optimizations, data segmentation, creation of media targets, etc…)

Automation thus enables human traders to intervene strategically on fund projects (measurement of incrementality, testing of new technologies, advertising effectiveness or data driven attribution studies) and advertisers to gain in efficiency.

Humans must intervene to overcome the limits of machines

Auction algorithms are programmed to achieve performance objectives based essentially on volume of actions (impressions, clicks or conversions), and it works quite well. On the other hand, it is essential for humans to intervene to ensure that this high volume of actions is carried out in environments that are favourable to the brand. This is where we work, in particular, with visibility measurement, brand protection and anti-fraud solutions, and where we develop internal solutions for detecting poor advertising practices among publishers.

Focusing on volume, the algorithms also do not take into account the editorial quality of the media on which the advertising campaigns are broadcasted. They will tend to maximize the distribution of campaigns on GAFA sites to the detriment of content sites of editorial groups such as (Prisma Media, Altice Media, Amaury Media, Lagardère…). GAFAs, which do not produce content but allow massive monetization of advertising at huge audience hubs, guarantee a high volume of advertising actions at an unbeatable cost.

Trading desks must have coherent strategies for distributing investments between so-called “Long-tail” sites and content sites known as “Premiums”, with only the relevance of media buying at stake. The machines are unable to demonstrate the difference in impact on memorization, brand image and purchasing decision between advertising delivered in a premium setting and advertising integrated into a less prestigious universe. Therefore we cannot be satisfied with the analysis provided by the machines to develop our strategies.

In the end machines increase the capacity and productivity of media traders for the benefit of advertisers

Pure programmatic ad buying tasks can now be automated to a large extent, allowing trading desks to focus their efforts on increasing the value of media actions: working with advanced allocation models, measuring the impact of online campaigns in stores, or understanding the complementarity of campaigns between different channels.

Thanks to the technology and progress of AI, the role of the Media Trader does not become obsolete, but takes on a more strategic dimension. On the other hand, it is the wording “media trader” that stands out from the reality of the position, which has already been replaced by less restrictive classifications such as Programmatic Consultant, or other Audience Planners.

This article was first published on French Media CB News 

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