By Alex White, COO, Peer39
Modern advertising is a data-driven practice. So as new regulations and browser policies take hold, many fear a coming data crunch. In some ways, those fears are accurate – the loss of third-party cookies on Google’s Chrome browser will dramatically shrink the amount of data linked to identifiers. Yet advertisers are beginning to realize that identifier-linked data is just the tip of the iceberg of all that’s available for delivering targeted advertising.
While the ad world will hold on to identity for as long as it can, doing so will come with a loss of distribution and scale. Advertisers don’t simply need an audience or alternative data; they need data options that will scale.
Contextual data represents a clear path forward, especially when combined with audience insights. That is, as long as advertisers can evolve their understanding to grasp the nuances that contextual data sources provide, and then support making it easier for this data to enter the programmatic ecosystem.
In the ad industry, context is often used synonymously with “content,” but these are not interchangeable terms. Context can be applied to content, but it doesn’t have to be. There is circumstance-based contextual data. Location-based and event-based are also contextual signals. In fact, context can mean anything from a sporting event to a financial event to a weather event. Context is as much about the physical environment as it is about the technical environment and the content a user is consuming.
Take a user reading a sports article on the train on their way to work on their mobile device. Not only is the user consuming content about sports, but the fact that they are mobile, commuting, and experiencing the conditions of their surroundings is important. All of this is context. And context affects what we do, and how we react to things.
High-efficiency trading is just signals, and the more signals that can be produced, the more value it is to the trader. Within programmatic, gaining insight into the content, the attributes of the page, the technical environment where the content is being consumed, and the physical context provide a lot of signals to play with.
Whereas audience data relies on identifying a user (something that is increasingly hard to do), contextual data is available on 100% of inventory going through programmatic exchanges, so needless to say, it scales. Even better, there is a thriving world of contextual data companies out there, which should meet the demands of advertisers looking to augment their existing audience strategies.
The challenge is that many of these companies with contextual data are not ad tech companies. They’ve built models for data creation and collection, in support of their customers, but many are not plugged into the ad-buying ecosystem. So how can advertisers learn about, understand, and make use of this data, or these models?
Somehow these providers need to get their data into the buying platforms. But remember, this is context and not the audience. This data is not based on cookie matching or mapping. As most people reading this will know, DSPs are not positioned to bring new data sets of this type into their platforms. In order to prioritize data onboarding on a roadmap, there needs to be customer demand. Small data companies, or those outside of ad tech, often don’t have that demand.
That doesn’t mean that their data set is not valuable. If given the opportunity, these data sets could be more powerful than anyone might expect. The natural integration point would be at the DSP, but DSPs have no shortage of roadmap items either requested or required by their advertisers. Further, there is a lot of tech that a data provider needs to build in order to integrate the data from their models at the scale of RTB.
This new breed of contextual represents a wealth of opportunity for a wide variety of data choices. But there isn’t a mechanism that can easily bring the contextual data of the world into the ad tech ecosystem. This is the major hurdle preventing ad buyers from accessing the rich world of data outside of the audience, and beyond standard contextual.
Ultimately, making new data sources available at scale will come down to intermediaries that already have ties to the ad tech ecosystem. This could include DMPs, holding companies, or other data providers that have integrations with the DSPs.
Cookies going away is a catalyst for getting these new data sets online, and most DSPs recognize that they can’t put all of their eggs in the basket of solving the identity challenge. Even when identity solutions emerge, there’s still a tremendous amount of data available for use in delivering targeted advertising.
After swinging too far in the direction of cookies and identifiers, things are swinging back towards context — or, at least, a balance between context and audience. But for advertisers to fully embrace context and all of the opportunity it offers, they need to think about context more broadly, and the industry needs to lower the barrier of entry for new data partners to inject a variety of interesting and untapped options.
