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Michael Conway, Chief Technology Officer, Bidtellect

Today’s customers expect a lot from brands. Brands need to personalize and make relevant the content they are delivering to their target customers. An Epsilon survey of 1,000 people (aged 18–64) found that 80% are more likely to do business with a brand that offers personalized experiences, and 90% find personalization appealing.

Personalized marketing has never been more important to advertisers. Platforms need to become highly effective at not only identifying target audiences but also optimizing content delivery. More importantly, how do platforms adjust from third-party cookie identifiers to the cookieless world?

Privacy concerns and regulations

Before May of 2018, programmatic platforms used cookies as a way to identify users. It was also how a vast majority of brands performed targeting until the European Union’s General Data Protection Regulation, the United States’ California Consumer Privacy Act and cookie-use limitations within browsers (i.e., Apple’s ITP) took hold. These regulations, along with Google’s move to eliminate third-party cookies within the next year, have placed severe restrictions on many platforms’ abilities to easily track customer behavior and information to deliver relevant ads and content accordingly.

Many advertisers, faced with these restrictive privacy laws and regulations domestically and globally, are returning to contextual targeting to find customers and expand their reach. But aside from these regulatory effects on many platforms’ ability to use cookies, many advertisers have been less than enthused with cookies’ overall performance in determining behavioral intent, viewability and fraud.

This leads the way for contextual targeting, along with its privacy benefits, to return to the forefront of performance advertising.

The return of contextual targeting

Contextual targeting works like this:

  • Content around ad inventory on a webpage, or the entities and themes present within a video, are extracted and passed to an optimization engine.
  • The content is then evaluated on multiple criteria: safety, suitability, relevance and context. 
  • Advanced targeting solutions layer-in additional real-time data related to the viewer’s context when the ad is viewed, such as time of day and location.
  • If it is brand safe and meets sentiment priorities, DSPs continue with the auction (i.e., the media buy). 

By removing the need for cookies, the platform uses other real-time context-based signals to make a bidding decision. Sophisticated platforms analyze text, video and imagery to create contextual targeting segments in real-time, which are then matched to advertiser requirements. As a result, the delivered advertisement appears in the most relevant and appropriate environment. 

For example, an ad for accounting software may appear in the Wall Street Journal’s markets section. In this instance, the environment is relevant to the product. 

This also ensures that the context is not negatively associated with a product and that the ad does not appear if the article was negative or contained financial misinformation. The ad for accounting software would not appear if the adjacent article is about how accounting software can be misused to embezzle funds easily, for example.

Driving efficiencies with contextual optimization

While contextual targeting places ads relative to the page’s content using page category, keyword and semantics, contextual optimization — or context-driven optimization — goes a step further: Machine learning algorithms optimize bidding and delivery of ads based on the contextual relevance and past performance at the placement level. 

Information from a recent Dentsu study —  ‘Understanding Contextual Relevance and Efficiency’ — revealed platforms that have developed intelligence through machine learning and AI have distinct advantages. Contextual optimization enables the programmatic buying of inventory based on the appropriate categories of relevance, and it can significantly outperform traditional audience targeting based on the user.  

For example, that same Wall Street Journal accounting software advertiser might place ads on the publication’s markets page, paying higher cost-per-click or cost-per-thousand impressions. Or, they might utilize contextual optimization to find other high-performing sites and placements across many other websites and pay much lower CPCs or CPMs with the same results. Contextual optimization also ensures relevancy to the target buyer and brand messaging while finding sites and placements that still deliver the expected return on ad spend at lower costs.

As other user targeting methods based on user ID are phased out thanks to growing privacy regulations, contextual targeting and contextual optimization will be the new standard for advertisers seeking performance outcomes, compliance and better brand safety. 

The ability to place relevant content in front of the right audience at the right time is of utmost value to advertisers. It is not just the ability to target contextually but the intelligence of the platform’s contextual optimization solution that will help ease the concerns of the new cookieless world. 

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