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.
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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: […]
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Read more: sightcorp.com
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.
Copyright by sightcorp.com
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: […]
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Read more: sightcorp.com
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