Why Advertising Has Only Been Scratching The Surface Of AI

5
at
5
minutes
Technical Level
December 2, 2021
5
minutes
Technical Level
December 2, 2021
Rob Fan
Chief Technology Officer
In this day and age, capturing the attention of your audience is not an easy task. Our devices are constantly buzzing with updates on our social media profiles or favorite news feeds. In fact, our reliance on smart devices and technology has shortened our attention span down to 8 seconds on average, shorter than that of a goldfish. Amidst all these distractions, how can advertisers deliver relevant and custom ad experiences in this day and age?

Advertising & Artificial Intelligence: Where We Are Now

Contextual targeting is gaining popularity for the cookie-less era, and it's getting some help from AI. Contextual targeting involves displaying ads based on a website's content. For example, placing an ad for dining chairs on an interior design website, or an ad for running shoes on a running forum. With AI, the process becomes even more powerful, enabling the analysis of languages, images, videos, and overall sentiment of the web page. AI is capable of turning all of this information, down to the colors and thematics of a series of images, into insightful data. With AI, targeting won’t involve tracking on a personal level, but rather automatically configuring the ad creative to complement the context of the page.

The Future: Using AI to Build Custom Experiences

The real value of AI will come when the advertising industry utilizes AI to help with the creative. Hundreds of apps across varying industries are already applying deep learning language models such as GPT-3, to power “search, conversation, text completion” and more. For example, DALL·E is a transformer language model derived from GPT-3 to be able to take in text and produce images in its place. Another notable example is Amazon Rekognition, a service analyzing images and videos to detect and identify content at scale through deep learning technology. While this might seem like sci-fi, NLP (natural language processing) has come a long way to improving language tasks and it can now generate compelling and interesting ad copy (headlines, descriptions, etc). This capability can also be extended to tasks like choosing the best performing thumbnail images.  

Increasing the Possibilities With Component Parts

At Sharethrough, we helped usher in the new wave of modern omnichannel ad exchanges that operate with component parts, which will have an advantage as AI capabilities advance. What are component parts? Component parts are the metadata like brand, headline, thumbnail image, etc that can be used to construct an ad on the fly.


With component parts, AI can be used to modify and add to the metadata or generate variations of the metadata which could be multivariate tested for optimal performance. Basically, component parts enable AI to gather data and find the best combinations to deliver the optimal custom ad experiences tailored to said user.

One Campaign, One Thousand Creatives

This increases the possibilities to build fluid designs (fonts, colors, layouts), calls to action, and bespoke thumbnail images/focus areas on images combined with the tried and true contextual and behavioral targeting will result in new world of advertising where no one ad looks the same for any site, user, time of day, browsing mode.

Imagine using AI to generate different versions of an ad and then feeding it into an AI optimised engine to find the best performing creative and publisher combination. If all ads in the future are customized to each single person, there could be slight differences between creatives. Therefore, the same campaign could generate different ads for different demographics, simultaneously.

One of the strengths of AI is that it can become familiar with the creation of “derivatives” of an original creative concept; then move on to make automatic alterations and spin offs of that concept on its own. This would thereby alleviate the manual work creative teams would otherwise have to do and could in fact produce even better results.

AI & The Cookieless Era

You can’t create better user experiences online solely by improving the creative. Efficient targeting is the key to successful campaigns for advertisers. The inevitable removal of third-party cookies stands to make advertising less effective - partly due to the fact that audience targeting will be less precise. In fact, people are more annoyed when they see an ad for a product they wouldn’t purchase vs. seeing a terrible commercial.

As mentioned earlier, contextual targeting is the best alternative to third-party cookies. It has the ability to target users based on the content they visit on the web, rather than the actual cookie trail of individual visits.

AI can also eventually determine the best ad format based on predictions of that person’s consumption behaviors. For instance, in a recent study by Sharethrough, when consumers were asked if they kept their phones on mute even while a video was playing, 85% of 25-34 year olds said they did, compared to 64% of 35-44 year olds. With this logic, campaigns powered by AI would be able to determine which format works best for the person who preferred muting their devices (a captioned video) vs. those who rather keep them on loud (a traditional video ad).

Instead of context only being limited to a video or audio's channel, AI can be used to interpret and identify the context of the actual content of the video or audio file. With the increase of personalization and new data from the proliferation of IoTs, AI can combine these data points to provide new contextual signals not just of the content but potentially of a user's surroundings and situations.

So What’s Next?

From what we know about AI & machine learning, the more data we have, the better it is trained to predict the outcome. In effect, advertising costs may decrease in the future to run more campaigns to find what is most optimal.

AI will need to come into play to justify ROI for advertisers. It will need to figure out if ads are generating new leads, and if new customers are walking into stores.

The future of AI and Advertising will take advertising to the next level, enabling advertisers to spend more time on creative original thought while leaving AI to determine the best niche combo that performs.

In this day and age, capturing the attention of your audience is not an easy task. Our devices are constantly buzzing with updates on our social media profiles or favorite news feeds. In fact, our reliance on smart devices and technology has shortened our attention span down to 8 seconds on average, shorter than that of a goldfish. Amidst all these distractions, how can advertisers deliver relevant and custom ad experiences in this day and age?

Advertising & Artificial Intelligence: Where We Are Now

Contextual targeting is gaining popularity for the cookie-less era, and it's getting some help from AI. Contextual targeting involves displaying ads based on a website's content. For example, placing an ad for dining chairs on an interior design website, or an ad for running shoes on a running forum. With AI, the process becomes even more powerful, enabling the analysis of languages, images, videos, and overall sentiment of the web page. AI is capable of turning all of this information, down to the colors and thematics of a series of images, into insightful data. With AI, targeting won’t involve tracking on a personal level, but rather automatically configuring the ad creative to complement the context of the page.

The Future: Using AI to Build Custom Experiences

The real value of AI will come when the advertising industry utilizes AI to help with the creative. Hundreds of apps across varying industries are already applying deep learning language models such as GPT-3, to power “search, conversation, text completion” and more. For example, DALL·E is a transformer language model derived from GPT-3 to be able to take in text and produce images in its place. Another notable example is Amazon Rekognition, a service analyzing images and videos to detect and identify content at scale through deep learning technology. While this might seem like sci-fi, NLP (natural language processing) has come a long way to improving language tasks and it can now generate compelling and interesting ad copy (headlines, descriptions, etc). This capability can also be extended to tasks like choosing the best performing thumbnail images.  

Increasing the Possibilities With Component Parts

At Sharethrough, we helped usher in the new wave of modern omnichannel ad exchanges that operate with component parts, which will have an advantage as AI capabilities advance. What are component parts? Component parts are the metadata like brand, headline, thumbnail image, etc that can be used to construct an ad on the fly.


With component parts, AI can be used to modify and add to the metadata or generate variations of the metadata which could be multivariate tested for optimal performance. Basically, component parts enable AI to gather data and find the best combinations to deliver the optimal custom ad experiences tailored to said user.

One Campaign, One Thousand Creatives

This increases the possibilities to build fluid designs (fonts, colors, layouts), calls to action, and bespoke thumbnail images/focus areas on images combined with the tried and true contextual and behavioral targeting will result in new world of advertising where no one ad looks the same for any site, user, time of day, browsing mode.

Imagine using AI to generate different versions of an ad and then feeding it into an AI optimised engine to find the best performing creative and publisher combination. If all ads in the future are customized to each single person, there could be slight differences between creatives. Therefore, the same campaign could generate different ads for different demographics, simultaneously.

One of the strengths of AI is that it can become familiar with the creation of “derivatives” of an original creative concept; then move on to make automatic alterations and spin offs of that concept on its own. This would thereby alleviate the manual work creative teams would otherwise have to do and could in fact produce even better results.

AI & The Cookieless Era

You can’t create better user experiences online solely by improving the creative. Efficient targeting is the key to successful campaigns for advertisers. The inevitable removal of third-party cookies stands to make advertising less effective - partly due to the fact that audience targeting will be less precise. In fact, people are more annoyed when they see an ad for a product they wouldn’t purchase vs. seeing a terrible commercial.

As mentioned earlier, contextual targeting is the best alternative to third-party cookies. It has the ability to target users based on the content they visit on the web, rather than the actual cookie trail of individual visits.

AI can also eventually determine the best ad format based on predictions of that person’s consumption behaviors. For instance, in a recent study by Sharethrough, when consumers were asked if they kept their phones on mute even while a video was playing, 85% of 25-34 year olds said they did, compared to 64% of 35-44 year olds. With this logic, campaigns powered by AI would be able to determine which format works best for the person who preferred muting their devices (a captioned video) vs. those who rather keep them on loud (a traditional video ad).

Instead of context only being limited to a video or audio's channel, AI can be used to interpret and identify the context of the actual content of the video or audio file. With the increase of personalization and new data from the proliferation of IoTs, AI can combine these data points to provide new contextual signals not just of the content but potentially of a user's surroundings and situations.

So What’s Next?

From what we know about AI & machine learning, the more data we have, the better it is trained to predict the outcome. In effect, advertising costs may decrease in the future to run more campaigns to find what is most optimal.

AI will need to come into play to justify ROI for advertisers. It will need to figure out if ads are generating new leads, and if new customers are walking into stores.

The future of AI and Advertising will take advertising to the next level, enabling advertisers to spend more time on creative original thought while leaving AI to determine the best niche combo that performs.

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About Behind Headlines: 180 Seconds in Ad Tech—

Behind Headlines: 180 Seconds in Ad Tech is a short 3-minute podcast exploring the news in the digital advertising industry. Ad tech is a fast-growing industry with many updates happening daily. As it can be hard for most to keep up with the latest news, the Sharethrough team wanted to create an audio series compiling notable mentions each week.

In this day and age, capturing the attention of your audience is not an easy task. Our devices are constantly buzzing with updates on our social media profiles or favorite news feeds. In fact, our reliance on smart devices and technology has shortened our attention span down to 8 seconds on average, shorter than that of a goldfish. Amidst all these distractions, how can advertisers deliver relevant and custom ad experiences in this day and age?

Advertising & Artificial Intelligence: Where We Are Now

Contextual targeting is gaining popularity for the cookie-less era, and it's getting some help from AI. Contextual targeting involves displaying ads based on a website's content. For example, placing an ad for dining chairs on an interior design website, or an ad for running shoes on a running forum. With AI, the process becomes even more powerful, enabling the analysis of languages, images, videos, and overall sentiment of the web page. AI is capable of turning all of this information, down to the colors and thematics of a series of images, into insightful data. With AI, targeting won’t involve tracking on a personal level, but rather automatically configuring the ad creative to complement the context of the page.

The Future: Using AI to Build Custom Experiences

The real value of AI will come when the advertising industry utilizes AI to help with the creative. Hundreds of apps across varying industries are already applying deep learning language models such as GPT-3, to power “search, conversation, text completion” and more. For example, DALL·E is a transformer language model derived from GPT-3 to be able to take in text and produce images in its place. Another notable example is Amazon Rekognition, a service analyzing images and videos to detect and identify content at scale through deep learning technology. While this might seem like sci-fi, NLP (natural language processing) has come a long way to improving language tasks and it can now generate compelling and interesting ad copy (headlines, descriptions, etc). This capability can also be extended to tasks like choosing the best performing thumbnail images.  

Increasing the Possibilities With Component Parts

At Sharethrough, we helped usher in the new wave of modern omnichannel ad exchanges that operate with component parts, which will have an advantage as AI capabilities advance. What are component parts? Component parts are the metadata like brand, headline, thumbnail image, etc that can be used to construct an ad on the fly.


With component parts, AI can be used to modify and add to the metadata or generate variations of the metadata which could be multivariate tested for optimal performance. Basically, component parts enable AI to gather data and find the best combinations to deliver the optimal custom ad experiences tailored to said user.

One Campaign, One Thousand Creatives

This increases the possibilities to build fluid designs (fonts, colors, layouts), calls to action, and bespoke thumbnail images/focus areas on images combined with the tried and true contextual and behavioral targeting will result in new world of advertising where no one ad looks the same for any site, user, time of day, browsing mode.

Imagine using AI to generate different versions of an ad and then feeding it into an AI optimised engine to find the best performing creative and publisher combination. If all ads in the future are customized to each single person, there could be slight differences between creatives. Therefore, the same campaign could generate different ads for different demographics, simultaneously.

One of the strengths of AI is that it can become familiar with the creation of “derivatives” of an original creative concept; then move on to make automatic alterations and spin offs of that concept on its own. This would thereby alleviate the manual work creative teams would otherwise have to do and could in fact produce even better results.

AI & The Cookieless Era

You can’t create better user experiences online solely by improving the creative. Efficient targeting is the key to successful campaigns for advertisers. The inevitable removal of third-party cookies stands to make advertising less effective - partly due to the fact that audience targeting will be less precise. In fact, people are more annoyed when they see an ad for a product they wouldn’t purchase vs. seeing a terrible commercial.

As mentioned earlier, contextual targeting is the best alternative to third-party cookies. It has the ability to target users based on the content they visit on the web, rather than the actual cookie trail of individual visits.

AI can also eventually determine the best ad format based on predictions of that person’s consumption behaviors. For instance, in a recent study by Sharethrough, when consumers were asked if they kept their phones on mute even while a video was playing, 85% of 25-34 year olds said they did, compared to 64% of 35-44 year olds. With this logic, campaigns powered by AI would be able to determine which format works best for the person who preferred muting their devices (a captioned video) vs. those who rather keep them on loud (a traditional video ad).

Instead of context only being limited to a video or audio's channel, AI can be used to interpret and identify the context of the actual content of the video or audio file. With the increase of personalization and new data from the proliferation of IoTs, AI can combine these data points to provide new contextual signals not just of the content but potentially of a user's surroundings and situations.

So What’s Next?

From what we know about AI & machine learning, the more data we have, the better it is trained to predict the outcome. In effect, advertising costs may decrease in the future to run more campaigns to find what is most optimal.

AI will need to come into play to justify ROI for advertisers. It will need to figure out if ads are generating new leads, and if new customers are walking into stores.

The future of AI and Advertising will take advertising to the next level, enabling advertisers to spend more time on creative original thought while leaving AI to determine the best niche combo that performs.

About Calibrate—

Founded in 2015, Calibrate is a yearly conference for new engineering managers hosted by seasoned engineering managers. The experience level of the speakers ranges from newcomers all the way through senior engineering leaders with over twenty years of experience in the field. Each speaker is greatly concerned about the craft of engineering management. Organized and hosted by Sharethrough, it was conducted yearly in September, from 2015-2019 in San Francisco, California.

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Rob Fan
Chief Technology Officer

About the Author

Rob has been a technology leader and entrepreneurial thinker for over 15 years. As the technical co-founder of Sharethrough, Rob, in addition to holding nearly every technical position at some point, has guided the formation of an industry leading product and engineering organization.

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