Today’s column is written by Chris Martellotti, co-founder at Wholetone Media.
Today, data is more of a language than a product. What has challenged many businesses is their ability to translate the new mountains of data they’ve collected internally and monetize its value.
In ad tech, a number of point solutions have been built to solve given needs in
the market. Ad servers, media exchanges, measurement tools, data management platforms, fraud vendors, ad networks, viewability vendors and dynamic creative all solve for the need to understand, value, buy and sell inventory. Overall, this has been a good thing for the industry, as there has been healthy competition to choose the top solutions for specific market pain points.
On the sales side, things have also changed a lot. The traditional media sale, whereby somebody sells an audience that is consuming a piece of content, has been ripped apart. For publishers, audiences and content are not always tied together, and thousands of middlemen have captured value, and continue to capture value, from riding the tide of a fluid marketplace. With the rise of technology like header bidding and the evolution of tactics like people-based targeting and native advertising, the most targeted and premium advertising experience can now be transacted through programmatic infrastructure.
So where do we go from here?
If you focus specifically on the sell side, publishers are faced with a big hurdle. Many publishers have header bidding, direct advertising demand from sales teams and third-party demand from networks and exchanges, not to mention a number of different ad units, perhaps across different properties, from a number of different countries, on different devices, representing a number of different cohorts of users.
How does one make sense of all of this data? Publishers must take stock of their data assets, determine if their business is exposed to risk and identify which levers they can pull to fill gaps or maximize revenue.
Asking The Right Questions
Publishers have many tools at their disposal to help find these answers. Any publisher has an ad server, exchanges, server logs and third-party networks, for example, and there also is direct demand, programmatic demand, a CRM, analytics data and perhaps viewability data or registration data, all of which can offer very helpful insights to solve business queries.
To do that, the publisher must first understand the goals of its business and determine the right questions to ask to achieve them. Is it trying to maximize revenue for the entire business? Publishers may want to understand the revenue per user and how it fluctuates. What is the revenue per session? What audiences and ad units are bought at the highest CPM in the open exchange? What audiences have the highest sell-through in the private marketplace, and is this priced properly in comparison to open exchange demand? What impact does viewability have on CPM and sell-through rate? What content sections drive the highest visit frequency? How does session depth affect RPM? And how does referral source from social vs. search affect RPM?
There are thousands of questions publishers can ask, but the bifurcation of users and revenue has left many in a challenging position, as they haven’t learned how to use the data within their business to answer the questions that can help achieve real business goals.
Data Storage
An obstacle in many organizations is that different groups rely on different data sets to accomplish different goals, which may or may not impact the underlying goals of the business.
Publishers should create a process that aggregates, stores and normalizes raw data from all of its various inputs. This is not an easy task, but it is fundamental. There are some software tool sets in the market that can help with this if needed.
An Iterative Process
Once publishers can use their normalized data to answer critical questions to achieve their business goals, they must continue and constantly iterate the process while measuring progress over time. This is the lens through which every publishing organization must look through to grow efficiently.
With the new language of the advertising economy being “data,” it’s important to know how to ask the right business questions, take control of the business’s data inputs and outputs and ensure that the entire staff is making decisions from the same data sets. Many publishers today struggle to understand the value of the data they sit on, and the bigger challenge is that they don’t know the right way to navigate all of the data to staff properly and sell in the most efficient way possible.
The operations behind first-party data within many publishers are starting to mature. There are publishers that have it, and those that are far behind. There are thousands of appropriate questions businesses can use their own data to answer, and the answers can change how publishers package up their direct sales inventory, how they should hire and even how to perform simple tasks, such as making business decisions based on up-to-date revenue figures, which are rarely available in real time.
For some, this reporting and data is one giant mess, and overworked analysts are constantly pulling different reports to understand revenue trends or performance. For other organizations, this reporting and analysis is at the heart of their business, aligning different teams and focusing efforts on measurable business problems.
This is the future of publishing, and this is what Netflix is doing and what Amazon nearly invented: one-to-one data engines that produce content specifically catered to the audience that is digesting it, broken down to a single unit and backed by the appropriate business goals to drive continued growth.
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This post was syndicated from Ad Exchanger.