To get back in control, publishers need to command their trading data, understand their audiences and work together with buyers to strengthen productive relationships
Part 2 of a two part series on data-driven publishing: part one is here.
In part 1 of this essay, we outlined the information access and technology imbalance between ad buyers and publishers in the programmatic ecosystem. Below we’ll share a few actions publishers can take to tip the scales and become more confident in programmatic selling. This will be good for both parties as it will bring more brand quality inventory into programmatic channels — and grow the market.
Lets start by stating the obvious.
Publishers must take the first step. This means accessing their seller trading data*. Without ownership of informative trading data, publishers will be left guessing in every new channel and holding their finger in the air when trying to manage yield across a growing portfolio of programmatic distribution channels. Data serves as the foundation for confident decision making by publishers and ad buyers alike.
Call to action 1: Command your trading data
Simply put, as with insertion orders and all other historical channels, publishers need to hold firm on knowing the identity of their buyers and controlling their seller trading data. That means working with exchange partners that are transparent and will provide you accurate trading data.
It’s not hard to see why trading data matters more than ever now versus a few years ago. Given that publishers were originally built as content “factories” and not programmatic yield management specialists that leverage “big data”, outsourcing yield management to networks used to be understandable. But publishers know that without command of quality trading data and knowledge of where demand might lie, they will either guess, or shift more and more of their margin to others in the supply chain who claim to monetize better.
Call to action 2: Become adept at data-driven selling
Today, outsourcing of yield management competencies to intermediaries no longer makes good business sense. Smart publishers understand this. They have transformed themselves into firms that understand both data and content production. If you want an example of what highly successful data-driven publishing looks like, look at the great work that Vikram Samoya and The Weather company has done with their data and inventory. It’s no wonder. Vikram knows full well the power of becoming data proficient from his time spent at BlueKai, a DMP.
Call to action 3: Use your data to gain the programmatic confidence to bring the “good stuff” to these channels
It’s easy to see why publishers need the same type of information the buy side has. But it’s not only to level the playing field. It’s equally important for helping publishers feel comfortable bringing better quality ad inventory to the programmatic world. As long as market information is asymmetrical, only the remnant party will keep rolling on in RTB.
Brands that spend the real (big) dollars need quality content, with real users (actually seeing their ads). If publishers are not data-driven and healthy, they will bring less of this quality inventory to programmatic, and the market’s expansion will slow dramatically.
Call to action 4: Use your leverage to advance the greater good
It’s clear that working toward bringing more balance to the programmatic world helps everyone in the ecosystem. Premium publishers will bring something the buy side and ad tech firms desperately want — quality, safe inventory. In turn, premium publishers will get the fair prices they deserve from an open and fair marketplace, ensuring that more publishers can thrive in this new programmatic world. But it’s on the publisher to take the first step. Are you ready? We’re here to help.
* Seller Trading Data – the bid-level data a publisher’s auctions generate on the ad exchange. Trading data includes key data about auctions, buyers, advertisers, bidders, segments, format, time of the day, browsers, operating systems, etcetera. When a seller’s trading data is combined with the seller’s first-party data, more insight and value can be extracted from inventory.