Originally published on AdExchanger
This year will be a great one for digital media trading. Digital media trading has jumped the shark and landed safely. Transparency will increase, fraud will decrease and market structures will only get better. Moving forward, the real challenge is to bring what we have learned to drive the growth and expansion of media trading into all other media and create unified platforms.
At this point, TV media is purchased and not traded. But that could change with the creation of better market-forecasting tools, which would improve our understanding of media markets, enhance decisioning and enable faster, effective and efficient technology-driven TV media trading. The inability to model and understand media markets is a leading obstacle holding back the birth of TV media trading.
Sellers of TV cannot reliably predict how trading may impact revenue flows, while traditional channels are reliable with forecastable revenue. If trading is not provably more reliable and revenue-accretive, there is no reason to switch from purchasing to trading. When sellers forecast higher yields via trading, there will be incentive to actively trade.
Unfortunately, display media is the petri dish where the earliest experimentation happens. Once technologies are created in display, companies try to cram those technologies into other media with little success. The trading technology developed in display was designed for machine-based trading, not people.
Discoverable Pricing, Secret Strategies
The challenge to developing appropriate TV market-forecasting technology is two-fold. The transaction space is highly fragmented, and the asymmetry between buyers and sellers makes the collection of granular data only possible on the buy side. Current technology makes market pricing and trading strategies inseparable, so everyone in the markets wants all of their data secret. Markets operate best when pricing is discoverable and strategies are secret.
As demand aggregators, agency buyers have a significant advantage. Buyers see upfronts, scatter, cable, satellite and local supply, while the suppliers only see the demand for their own inventory.
Broadcasters and networks have few tools to help them understand how to use packaging and pricing techniques to address viewership and market-demand fluctuations. Sellers can see the scatter budgets coming their way and what their sellout is, so they see both supply and demand, but only for the tiny part of the market that their inventory represents.
There is little that data sellers can use to understand granular demand across the market. Given this environment, people use their anecdotal experience and intuition to make up for the lack of data, which reduces the use of machines to add value.
No Solution In Sight
What is even more disturbing is that while the asymmetry exists, the lack of an organized market generating this historical transaction data means that no one is even working on this problem. Buyer and seller transaction information is so closely guarded that general trends are the best we can hope for.
No existing technology accounts for campaign goals, budget, available inventory, market prices or historical performance metrics. There is also no technology that offers recommendations for an optimal media plan.
On the other side, media companies lack the sales tools that enable what-if scenario modeling to understand how the demand they expect should be most effectively allocated across the media. In reality, media plans and media packages span multiple media and publications. That is what the deal conversations are all about, not a single impression or a line item for a placement. Buyers and sellers need a better way to forecast what those conversations will be like and decide the best course of action.
In Use Now
TV media buyers and sellers need better tools for making decisions. For real-time display, the tools are more straightforward, as people could never pull the trigger fast enough, so machines bear the brunt of the control.
For forward-media buying, in which TV is the 900-pound gorilla, people bear the brunt of control, and technology plays more of a support role. While there are some systems that help manage yield after the deal is made, today, the selection and decisioning of what to offer a potential client and the price at which to offer it is nearly completely manual.
With everything we have accomplished, we still face obstacles that will challenge this momentum moving forward. First and foremost among those is the revolution of market forecasting. Unified platforms require unified – not homogenized – tools and analytics to support omnimedia trading.
While media mix modeling has been around for decades, buyers’ and sellers’ ability to transact an ever-increasing granularity of content and audience programmatically is driving an increased need for a revolution of market-forecasting technology.
Momentum is moving in the right direction to help buyers determine what they can buy, how they can buy it quickly and easily and whether it turned out as expected. The technology for modeling what TV media to buy and sell has not kept up.