Taxonomies have long been a not-so-sexy – but totally important – part of our industry. They help bridge the buy and sell sides of digital advertising through a common standard. As a concept in the digital ad world, they refer to naming conventions or “naming groups” that apply structure to groups of data such as audiences or content. For publishers, correctly mapped taxonomies lead to increased buyer opportunities and an improved user experience for those reading their content. For buyers, they can enjoy better brand safety and brand relevance.

The importance of taxonomies today and in the future

Recent developments have put a renewed importance on the accuracy and robustness of taxonomies, as well as the ease of the data flow from seller to buyer. As has been well documented, we are living in an era where user identifiers are being removed from the digital advertising ecosystem. From cookies to MAIDs, the audience targeting capabilities cherished (and sometimes abused) by the buy-side are slowly – but surely – slipping away.

Some Advertisers and Publishers are looking to newer solutions, such as clean rooms and identity solution partners, to express their targeting. But questions remain about how to securely and accurately communicate those identifiers down the chain. So, others are investing in contextual data as a targeting methodology.

Whatever the targeting method, advertisers and publishers need a way to speak the same language so that advertisers know what they’re buying, and publishers can accurately package and sell their content.

IAB taxonomies

Having standardization in programmatic has always been important. Standards are what helped drive programmatic ad spend to $100billion+ annual industry in the United States. That’s why the taxonomies offered by the IAB have long been a staple of our industry. These can be broadly bundled into three sections: content, audience, and the ad product taxonomies (the product being sold within the ads). The IAB taxonomy with the widest adoption is content categories, boasting strong support among both publishers and demand side partners (DSPs) alike.

As we (at ArcSpan) have experienced first-hand, [publishers are now putting more emphasis on the accuracy and breadth of IAB content taxonomy, as many see contextual targeting as a way to “bridge the gap” until they can accurately – and safely – pass first party audiences through to buyers again.

Having previously worked as a trader on the buy-side, I’ve run campaigns then compared the performance of targeting third party content taxonomies vs the IAB taxonomies. On a CPM basis, the IAB would typically perform better (which makes sense, given the third parties charge a fee). However, third-party vendors often yielded stronger engagement.

This might be chalked up to the fact that publishers sometimes mislabel their content. This is an easy mistake to make, given content is constantly updating and ensuring categorization is accurate can often be an arduous, manual process. However, buttoned up publishers will reap the rewards, especially given the renewed importance of addressability without third party cookies.

Google taxonomies

Another argument for the renewed importance of the IAB content categories is that Google has integrated them in their Topics API functionality. For those that are unaware, Topics is Google’s approach to targeting once cookies are deprecated. Within Topics, a user is assigned three topics for targeting purposes in Google’s Chrome browser, and these topics are then passed downstream to the buyer for targeting. Although some see this as a behaviorally-driven approach, the actual set of topics used will be pulled from both the IAB content taxonomy and Google’s own audience taxonomy.

Seller Defined Audiences

Finally, I’d be remiss to not mention the very buzzy topic of “Seller Defined Audiences.” These audiences not only leverage the IAB taxonomies, they also require a publisher to pass first party addressable identifiers into the bid stream.

Publishers may initially hesitate to adopt this strategy, as they don’t want their valuable first party data being scraped by bad-actor vendors. However, this approach, although not yet widely adopted, will be one to watch, as it’s an important concept for both publishers and advertisers.

Beyond the IAB

Even within the adtech industry, the idea of taxonomies doesn’t stop with IAB content categories. There are numerous types of vendors within AdTech that have their own taxonomies. For example, advertisers and publishers alike might have their own, customized taxonomies. A common use case for a custom taxonomy would be when the IAB or Google taxonomies aren’t granular enough to capture the content an advertiser wants to target, or that the publisher is looking to surface.

If a publisher has nuanced, but seemingly high-value segment of content that they want to offer to buyers, they will need to go beyond the IAB’s categorization and offer their own custom categories to buyers. Take, for example, Trusted Media Brands: they recorded 110% growth in 202,1 due in part to their overhauled taxonomy, to focusing on better insights for buyers. Likewise, advertisers’ needs are constantly evolving, so certain advertisers have their own custom taxonomies.

As a final point on the topic of taxonomies: in this article I’ve spoken mostly about taxonomies as it relates to web-based buying. While this is certainly the most developed area here, other taxonomies do exist. For example, both mobile in-app and CTV employ custom taxonomies but it’s a bit more difficult to understand content in these environments, as standardization is harder to achieve in CTV and in-app environments.

Invest now

Given the dynamic nature of content, ensuring the heath of both publisher and advertiser taxonomies will require some level of investment. Ideally, the process of creation and updating said taxonomies would be automated and scaled, either by investing in an in-house team or outsourcing to industry experts.

We’ve seen some publishers are going even further by combining their correctly mapped taxonomies with behavioral audiences for advanced segmentation, then serving it to buyers via deals or passed via Open RTB in a seller defined audience. Either way, developing deep taxonomies now will benefit publishers now, and in the future, as buyers look to replace the granular targeting methods they once had with cookies.