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AI in Programmatic Advertising

Everything about AI in Programmatic Advertising

     

What is AI in programmatic advertising?

Programmatic advertising is an auction-based system that allows for the automated buying and selling of advertising space. Both advertisers (those buying ad space) and publishers (those selling ad space) can optimize the results they achieve through programmatic advertising by using AI.

What is the role of AI in Programmatic Advertising?

Unlike non-AI algorithms, machine learning AI algorithms can learn from – and adapt their actions based on – new patterns they encounter, which makes them highly suitable for the real-time environment of programmatic advertising. AI algorithms are also able to process huge datasets quickly. With these factors combined, AI influences various aspects of programmatic advertising:

Personalization:

AI gathers and organizes large quantities of data relating to each user that visits a website. This data can then be used to segment audiences and to serve more relevant, more personalized ad content to each user. In some cases, it is even possible to use AI to adjust the ad creative based on what it knows about the user who will be seeing the ad.

Content matching:

Natural Language Processing (NLP), which is a component of AI, can be used to improve the contextual relevance of ads by comparing the content of an ad to the content of a website and making sure that ads are displayed only on relevant websites. This also helps to protect brand image, by making sure that ads do not appear in an inappropriate context.

Budgeting:

AI can help advertisers to adjust their bidding strategies based on their customer information and to determine the right bidding price for ad space they want to purchase. This helps to reduce ad spend and to increase ROI.

AI can also help to determine which advertisers are more likely to be successful with their bids for the ad space, which benefits the publishers by limiting the auction only to the most suitable bidders.

Predictive analytics:

AI algorithms can deliver predictive insights by taking into account a wide range of factors, such as a customer’s browsing history, a customer’s installed apps, a customer’s past purchases, a customer’s past interactions with ads, and a customer’s resemblance to previously identified high-value customers. These insights can help advertisers to improve their targeting and bidding and to increase their ROI.

Sentiment analysis and programmatic advertising:

In the context of programmatic advertising, sentiment analysis involves identifying the mood of the customer who is about to see an ad, as well as that user’s likelihood of entering into a transaction in response to that ad. AI can be used to conduct sentiment analysis in some of the following ways:

  • In the case of digital out-of-home (DOOH) advertising displays: by identifying a viewer’s mood through facial analysis. In this case, it may be possible to update the ad content in real time based on the viewer’s emotional state.
  • By using NLP to analyze the sentiment of the content on the page that a user is viewing and determining which types of ads perform best alongside that type of content.
  • By analyzing the user’s past browsing behavior and responses to similar ads, and predicting how the user is likely to respond.

 

(Note that the last two options are not offered by Sightcorp.)

Learn More About Sightcorp’s Facial Analysis Solutions

Who benefits from AI in programmatic advertising?

As seen above, both advertisers and publishers benefit from the application of AI in programmatic advertising. However, they are not the only ones. Customers can also benefit, in the sense that they will see more ad content that is relevant and useful to them, and less ad content that is irrelevant and disruptive to them. It should also be noted here that both advertisers and publishers have an obligation to use customer data responsibly and in accordance with the applicable laws and privacy regulations.

Will AI replace human advertisers?

Currently, the answer is ‘no’. AI is taking over the repetitive and mundane tasks, freeing up advertisers to focus on the more strategic and creative elements of their work. In future, as AI becomes more sophisticated, one of the challenges will be to decide exactly which tasks should be delegated to AI and which tasks should be done by humans. In the context of advertising, AI is there to enhance the work done by humans, not to replace it.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.