Contextual advertising has been on the agenda of online marketers lately. Undoubtedly, the biggest reason for this is the regulations that both brands and governments have brought one after another in the field of user data privacy. It seems that contextual advertising will be a hot topic in the new media buying world to emerge after these regulations.
What is Contextual Advertising?
It’s pretty simple. Contextual advertising is ads that are displayed based on the context the target audience is in. It’s like seeing a cooker ad on a recipe website.
Contextual advertising focuses on the context of the user rather than who the user is. In this way, the need for demographic and psychological data of the user to show the right ad is eliminated.
Is Contextual Advertising Something New?
No. If you’ve been in internet advertising for more than a decade, you know that the answer to that question is no.
Contextual advertising has been used for years in all media, not just online ads. However, thanks to the recent development of user tracking techniques, advertisers have moved away from contextual ads.
Why Advertisers Moved Away from Contextual Ads
Advertisers have moved away from contextual advertising because cookie-based behavioral ad models outperform contextual ad models. However, it is not possible to say that contextual advertising has wholly disappeared.
Brands that specifically own a particular niche continued to be customers of contextual advertising. For example, most of the ads for sports betting brands are still published on sports-related websites.
What are the Advantages of Contextual Advertising?
Contextual advertising has many advantages, including the following.
Less dependency on User Data
Contextual advertising can be a solution to the cookie problem, which is the biggest problem faced by advertisers in the current period. Since the targeting in contextual advertising is based on the context, not the behavioral data of the user, the dependency on cookies that create data privacy problems is reduced.
Behavioral targeting can often cause us to see unrelated ads. It’s weird to see an ad for diapers on a website we visit to read news about the latest model cars.
Contextual targeting doesn’t have such problems. Since the ad impressions are made according to the media they are in, the ads are relevant to the content.
Less Ad Fatigue
One of the biggest disadvantages of behavioral advertising is that it shows the same ad to the same user over and over. In behavioral targeting, although the same ad is shown to the user repeatedly, ad fatigue is reduced because these ads are related to the content that the user is consuming.
If Contextual Advertising Didn’t Work in the Past, Why Should It Work Today?
This is a question that is probably on the agenda of anyone who sees contextual advertising as an alternative to behavioral targeting these days.
We mentioned that contextual advertising had performance issues in the past. The biggest reason for this was that the technology of the period made it necessary to place the ads manually. This was a huge problem for publishers with large inventories of ad space. Therefore, the performance optimization of the ad spaces could not be fully performed.
Today, with the development of AI technologies, it is possible to overcome this problem. Thanks to an AI that can better detect the content, and therefore the context, more accurate ad impressions have become possible.
Google Might Be a Problem
Contextual advertising has a major obstacle to re-popularity: Google.
Since February 2020, Google has removed the ability for advertisers to target by content category. It is possible to say that Google wants the behavioral targeting models dominated by it to continue.
Although Google dominates the world in behavioral targeting, the same does not go for contextual advertising. Many alternative DSPs are developing strong products in this area where Google is weak.
We’re sure to talk more about contextual targeting models in the coming months. It is helpful to closely follow the developments in AI technologies working in the field of content analysis and the position that Google will take.