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Trading Of US Linear TV Advertising Shifting To Programmatic Trading

Oct. 08 2018 — Both buyers and sellers of traditional linear TV advertising, not including connected TV or over-the-top video, are moving toward the adoption of programmatic trading. In 2017, Kagan estimates that $690 million or 0.9% of total linear TV spend was traded programmatically. Within the next five years, that figure is expected to climb to $9.76 billion or nearly 12% of total linear TV advertising revenue. MVPDs are forecast to trade the greatest percentage of their ad inventory programmatically in 2022 with 30% of ad revenue from programmatic trading.

Kagan defines programmatic trading as being automated and data-enhanced, not just one or the other. Trading may be through a private or open marketplace and does not have to be through an auction, which is more common in digital video advertising.

There are several issues holding participants back from programmatic trading. Unlike digital programmatic marketplaces, where there is a seemingly unending supply of ad inventory, linear TV has a finite supply. Demand for TV inventory exceeds the supply, so there is still an attitude of "If it isn't broken, don't fix it." TV ads are also bought well in advance, not immediately.

While many agencies have experimented with the programmatic trading of linear TV, not all are on board. Many of the advertisers and agencies are interacting directly with the supplier platform rather than going through a demand-side platform, or DSP, today. In their experiments, the agency needs to use separate platforms to aggregate inventory and tie it together, which is a lot of work.

The lack of inventory is one factor holding back programmatic trading. The only way it takes off is to make linear TV inventory available in some type of buyer platform that can combine the various supply platforms. It is even more complicated when the buyer wants to bring in connected TV (OTT).

Agencies do like the automation capabilities of programmatic, particularly where the process takes a lot of time. An algorithm may do better in areas such as weighting estimation, the first pass at scheduling and the negotiation process as well as postings and billings. The process of buying inventory is not difficult, but computing where a buyer will be able to find its preferred audience is. Therefore, interest in automating the planning and analysis to find an optimal audience is high.

We forecast a gradual uptake for programmatic trading with continued testing in 2018. Broadcast stations and networks, cable programmers, and MVPDs need to add more inventory to programmatic platforms before agencies begin using it in earnest. It will take time for all parties to feel comfortable transacting in a new way.

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