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Contextual advertising explained


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Contextual advertising or contextual targeting takes place in an environment where the need to protect the personal data of Internet users is a concern. The subject of programmatic advertising is a hotly debated topic, so much so that web players have put in place solutions to limit abusive tracking and the scope of targeting on online user behavior.

It should be said that the appearance of the GDPR has had an impact on the coverage of ad spaces and the sale of their inventories. The notion of consent to cookies has changed the game for companies, to the benefit of Internet users who are always looking for more security and transparency. 

The challenge is therefore to find more GDPR compliant alternatives in an environment that is transparent to the public, advertisers and legislators.

However, adaptation comes at a cost that cannot be ignored. That’s why implementing a new programmatic advertising medium includes understanding the players involved and managing the costs associated with ad delivery. The goal is to reduce or eliminate the financial losses associated with the transition to a new business model for companies.

To support this initiative, advertisers need to be convinced that a new ad format not based on user behavior will be profitable. Indeed, it is well known that the removal of tracking and third-party cookies greatly reduces publishers’ revenues.

But then, what solution would be able to act in the direction of Internet users’ wishes, without invading their privacy and preserving publishers’ profitability?

Definition of contextual advertising

Contextual advertising is an advertising technique in which contextually selected ads are inserted on a communication medium such as the web or TV to target a specific audience. 

To illustrate our point, let’s take the example of insurance companies that prefer to publish their advertising content on health websites. 

Thanks to contextual advertising, you have the possibility of using several ad formats including:

·         Native. Native advertising can have contextual targeting, as it can be aligned with the visual design of a website. This has the merit of making it more appealing and reliable to Internet users.

·         Video. An ad in a Youtube video has the advantage of targeting the interest of those who view this format. Therefore, when a person clicks on a makeover video, he or she may receive an advertisement for clothing sites, for example.

·   Behavioral. This involves mixing the context of the page viewed with the user’s behavior. This can be his geographical location or a page visited.

How to do contextual advertising?

Contextual data retrieval makes it possible to categorize a page from the moment an Internet user consults a source in which he has an interest.

Behavioral analysis is performed on the page instead of the domain name or URL. This gives publishers the ability to target the most relevant content on their website in relation to their customer databases.

As a result, they make their advertising campaigns more profitable and target areas or sub-areas of interest. It is therefore very easy to target a niche sector or a large audience.

The key to the success of contextualization lies in the personalization of the user experience. Indeed, Internet users prefer ads that address their needs. Thus, they are more receptive to content for which they have a proven affinity.

The objective is to create an interaction between your targets and your ads.

Another concept to consider in contextual advertising is brand safety. It is about identifying irrelevant or unfavorable contexts in which you don’t want to show ads.

Therefore, when contextual targeting is combined with artificial intelligence, it helps to improve the targeting of content that is more tailored to a specific audience.

However, there is a downside. How to measure advertising campaigns without using cookies? It is difficult to measure Internet users after consulting a content and therefore, the success of campaigns. For this reason, a question is asked before and after the launch of an advertising campaign for more efficiency in the measurement of key indicators for publishers. 

Artificial intelligence and ad targeting

Programmatic advertising automates the buying/selling of ads based on targets that advertisers prefer to buy by impression.

The Real-Time Bidding technique is the flagship format of programmatic based on an automatic bidding system to deliver ads to Internet users.

As we have already discussed, it is the behavior of the online user that predominates at any given moment. Programmatic advertising has made it possible to gain in relevance in the identification of targets and the sending of messages.

Better yet, in order to optimize the user experience, advertising platforms are continuously optimizing their algorithms and limiting the need for targeting in campaign design.

In fact, campaign returns would be better without using targeting. It is important to understand that narrowing a segment leads to over-solicitation on the same product or service category and increases the cost per acquisition. Being restrictive can also reduce opportunities to address a better audience.

The trend is therefore towards no-targeting, i.e. opting for the largest audience and entrusting the advertising targeting to artificial intelligence. However, nothing prevents you from indicating your targets to be excluded and giving useful information to the algorithm about your best customers. This will allow you to create similar audiences.

Thus, artificial intelligence contributes to the personalization of ads for Internet users who wish to protect the privacy of their personal data and brings out the contextual advertising that will allow you to get the best audiences at the best price.

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