Oct 29, 2022·edited Oct 29, 2022Liked by Ryan Khurana
Some great points. Thanks for this article. I’ve been in creative automation for brands for a number of years.
I will say that - aside from the types of “wow isn’t this AI stuff neat!?” type of campaigns you mention - the capabilities are already FAR ahead of where a lot of brands have been willing to test.
The idea of contextually adapting creative to align with content has been around in the form of Dynamic Creative Optimization for a number of years - dynamically inserting contextually relevant copy, images or CTA via macros into an ad based on pre-defined rules - but brands have been slow to adopt it and reluctant to hand over real decisioning to the algos even when we have had that capability for years.
I remember presenting an ambitious DCO campaign that would leave limited decisioning to the machine to a well known US automotive manufacturer a few years back. The CMO immediately shot it down and opted for a narrowly defined rule set because “What if the machine creates something that isn’t ‘brand safe’? We can’t take that risk.” Mind you this was just remixing existing creative elements in a database that the brand had already approved!
As you point out a lot of the early adoption will be among SMBs and performance marketers who don’t have limitless creative budgets. It’s going to be a fun industry!
This is the best post I've read on the topic – very forward thinking!
I'm coming at generative advertising from the opposite angle: generative AI services that want to monetize through ads have a problem: when you don't know what your users will generate, neither do advertisers. This breaks targeting and threatens a brand safety nightmare.
You actually need something much more like search ads on generative AI sites – but Google doesn't have a 3rd party search-display ad product.
Not every AI product can use SaaS pricing to cover their GPU costs. A bunch of generative companies are about to realize advertising is broken for them.
And I'm not sure if that's the case for established products. You have a history of a user's generations similar to a history of tweets that would let you understand what they're likely to make. I think getting from a stream of generations to predicting what you will like to see next is increasingly becoming a trivial task.
Good point - the data to model preferences is definitely there. I wonder how many publishers will choose to do their own modeling vs hand it off to the ad-tech stack. Sending user prefs to advertisers in a form they can use is still hard. Usually involves partnering with a data management platform to match cookies and send the user data to the ad auction.
Then there's targeting real-time intent on the current prompt. I think the coolest generative search ads may be collaborations between search platforms’ AI and brands’ AIs. Here’s how I imagine AI search integrating an REI ad: https://www.stratos.blue/images/gear-ad-embed.png
Some great points. Thanks for this article. I’ve been in creative automation for brands for a number of years.
I will say that - aside from the types of “wow isn’t this AI stuff neat!?” type of campaigns you mention - the capabilities are already FAR ahead of where a lot of brands have been willing to test.
The idea of contextually adapting creative to align with content has been around in the form of Dynamic Creative Optimization for a number of years - dynamically inserting contextually relevant copy, images or CTA via macros into an ad based on pre-defined rules - but brands have been slow to adopt it and reluctant to hand over real decisioning to the algos even when we have had that capability for years.
I remember presenting an ambitious DCO campaign that would leave limited decisioning to the machine to a well known US automotive manufacturer a few years back. The CMO immediately shot it down and opted for a narrowly defined rule set because “What if the machine creates something that isn’t ‘brand safe’? We can’t take that risk.” Mind you this was just remixing existing creative elements in a database that the brand had already approved!
As you point out a lot of the early adoption will be among SMBs and performance marketers who don’t have limitless creative budgets. It’s going to be a fun industry!
This is the best post I've read on the topic – very forward thinking!
I'm coming at generative advertising from the opposite angle: generative AI services that want to monetize through ads have a problem: when you don't know what your users will generate, neither do advertisers. This breaks targeting and threatens a brand safety nightmare.
You actually need something much more like search ads on generative AI sites – but Google doesn't have a 3rd party search-display ad product.
Not every AI product can use SaaS pricing to cover their GPU costs. A bunch of generative companies are about to realize advertising is broken for them.
Thanks!
And I'm not sure if that's the case for established products. You have a history of a user's generations similar to a history of tweets that would let you understand what they're likely to make. I think getting from a stream of generations to predicting what you will like to see next is increasingly becoming a trivial task.
Good point - the data to model preferences is definitely there. I wonder how many publishers will choose to do their own modeling vs hand it off to the ad-tech stack. Sending user prefs to advertisers in a form they can use is still hard. Usually involves partnering with a data management platform to match cookies and send the user data to the ad auction.
Then there's targeting real-time intent on the current prompt. I think the coolest generative search ads may be collaborations between search platforms’ AI and brands’ AIs. Here’s how I imagine AI search integrating an REI ad: https://www.stratos.blue/images/gear-ad-embed.png