“The Sell Sider” is a column written for the sell side of the digital media community.
Today’s column is written by Chris Martellotti, co-founder at Wholetone Media.
We are sitting in the middle of a giant shift, as advertisers and publishers navigate from the old seller-driven market to the programmatic-buyer driven market. Today, most sellers and buyers sit in the middle of this transition, and most organizations aren’t properly aligned from a data and reporting standpoint to understand the metrics that are moving the business.
For publishers, this creates a substandard technology stack, poor business intelligence, misaligned sales efforts and over- or understaffed organizational structures. Analysts are busy tracking down reporting errors – elementary work for their skill sets – and the solution for driving revenue boils down to “sell harder.”
What we will continue to see from the market platform leaders, Google and Facebook, specifically, is less data and fewer insights being shared with their customers. They report analytics properly (in most cases at least), but if you are living inside of these tool sets, looking to make business decisions, it only makes sense that you will be informed to sell or buy more of their solutions as they are inherently biased toward their own solutions.
Google and Facebook’s tools are built for scale, not product differentiation, and the market is clamoring for data and insights to help create product differentiation so everyone can have a clear sense of the value being exchanged.
For example, what impact does viewability have on different audience segments being bought or sold? How does user session depth affect revenue per thousand impressions from direct-sold inventory vs. third-party demand? When there is growing complexity of user profiling that goes far deeper than what person on what property, it is important for sellers to understand what variables are actually driving their business.
Where many data management platforms have fallen short has been their focus on enabling sellers and buyers to translate first-party audiences against third-party audience data, audience graphs, such as cross-device layering, or data onboarding. This solves for a need, but it is hard for both the buyers and sellers to understand the collateral impacts this has on their businesses.
It also does not typically solve for the data flow of a given business. Even with media-mix modeling and media attribution, it doesn’t necessarily translate if the architecture to understand their value in reaching business goals has not been built. Every millisecond there is data feeding in and out of businesses, but how is that being understood?
At large, the programmatic landscape is a buyer's market, so how can a seller have its audience bought at a higher price through the auction tools in the market? Are they selling users in a private marketplace for half of the value of what they are worth in the open exchange? Can the advertising experience and pricing floor vary by audience group? How does user behavior differ across different cohorts of users, and what revenue impact does that have?
To solve for this challenge, a publisher might pool together all of its advertising partners and any third-party measurement APIs to get detailed insight into revenue per user and revenue capacity and understand the monetary value of all content distribution channels. These questions generally produce fairly unique outcomes for a media seller and will help them package their audience in new ways that differentiate their value in the market, and can be used by direct efforts, private programmatic and open exchange activity.
The consolidations in ad tech have proven out one fact: The technology stack is commoditized. There are best-in-breed partners to use for given situations, but there is little differentiation. The next evolution is understanding how to use this ad tech stack to help inform business intelligence, operational and leadership teams and also define the organizational structure needed to excel against given KPIs.
There is a new wave coming in, but it is still “a few miles from the coast.” I see organizations quickly moving from free analytics tools baked into the ad technology services they are using, to building or leasing proprietary analytics stacks that are customized to their given business.
This move will free up analytics teams to dive deeper into more pressing business questions. Massive adoption of this behavior is the only thing that will challenge the duopoly of Google and Facebook, turning these behemoths into publishers and platforms supporting a company’s business goals, as opposed to them offering up a biased version of its business goals.
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