How Publishers Can Become Masters of Their First-Party Data

Google may have given publishers and advertisers a little breathing space when it comes to finding a new solution for targeted advertising. But, elsewhere, digital giants and regulators have already decided that third-party cookies – for years the mainstay of digital advertising – have had their day.

Without a cookie reprieve — or any single viable replacement on the horizon — digital advertising and media monetization will most likely rely on a number of alternatives going forward, and first-party data, in particular, will be key to any future strategies.

Harnessing first-party data at scale will ensure marketers can keep delivering relevant and engaging ads across the web in a privacy-secure way, while sustaining revenue for publishers and strengthening their position in the online ecosystem. 

Powering this shift, however, will require sell-side players to master their data by adopting strategies that maximize data collation, orchestration, and implementation.

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1. Taking Stock of Data 

Whatever their size, most publishers have vast scope to capitalize on direct audience data. A tendency to underestimate how much data is already available, however, can raise doubts about the opportunities for first-party-centric operations and revenue generation. Simple as it seems, that’s why the first step is to thoroughly check current supplies. 

By taking stock of existing raw assets — including log-in details shared by users, behavioral information, as well as data about on-site clicks, views, searches, and content — publishers can gain a complete picture of what they hold.

By embracing intelligent automation, they can also increase audit efficiency and scale. Harnessing platforms capable of instantly gathering and organizing data from every source allows publishers to streamline multichannel collection and create the right basis to later analyze compliance and usability. 

2. Maximizing Data Value 

Historically, third-party data orchestration has mainly focused on syncing multiple fragments of external information and matching cookies to owned data. To an extent, connecting dots remains a major part of managing first-party data — but the key difference lies with more emphasis on consistently making the most of it, not just fitting puzzle pieces together. 

Firstly, that means sorting data by value right from the cleansing stage. In addition to covering quality control basics — such as consolidation, filtering and harmonization — publishers must establish whether data has practical potential, either as a deterministic signal for addressable ads, or to help inform predictions from artificially intelligent (AI) technologies.

Second up is identification.

Once the pick of the bunch is put into a workable structure, it’s still crucial to assign IDs that enable the ongoing delivery of tailored content and ads – both from a user experience and revenue perspective. Achieving this calls for complex coordination on multiple fronts: immediately linking incoming first-party data with existing or new IDs, and ensuring any new IDs also align to current identifiers. But the payoff is IDs that contain rich insights such as age and gender, alongside non-personal data based on activity.

3. Fueling Efficiency 

Despite providing a solid foundation for smart decision-making and personalization on its own, data about known users is likely to need amplification for publishers to enhance their ad offerings and meet marketing needs. As a result, augmenting data is an integral element of final implementation to make sure first-party data efforts drive higher overall value.

Enrichment gives publishers the capacity to optimize their audience knowledge. Feeding in cleansed data with pre-assigned IDs, they can set AI algorithms to work on assessing the known habits, tastes, and behaviors of consenting individuals, and use the insights they gain to produce accurate predictions about unknown users who have similar traits.

As well as eliminating the need to rely on borrowed third-party data, this means publishers can leverage smart predictive modeling to persistently expand their targeting range, user understanding and relationships, and match rates.

From here, publishers will have a rich blend of probabilistic and deterministic data they can activate in a similar way to third-party data, but with the added advantages of better accuracy and quality. Data plugged into ad servers and exchanges will drive sharper ad tailoring and segmentation rooted in privacy-secure practices that drive better results for everyone – media owners, marketers, and users alike.

Digital advertising is undergoing an unstoppable and necessary shift, but it doesn’t have to mean the end of identity and engaging, profitable ads. By becoming real masters of the data at their fingertips and seizing the opportunities smart tools provide, publishers can use their first-party data to benefit and support the entire digital space.