Goal has shared details about how you can use the artificial intelligence (AI) to improve the performance of your ad system. in this is ‘AI Sandbox’ of Meta that will test the generative capabilities of AI for advertisers. The company has also announced new features in its suite. ‘Meta Advantage’ of ad automation tools, along with details about their AI infrastructure and the modeling investments that underpin it all.
What is ‘AI Sandbox’?
‘AI Sandbox’ are new tools and features included in the AI and machine learning-based generative ad tools. “Our goal is to learn what works for advertisers and make it easy to use these features in our ad tools”commented John Hegeman, Vice President of Monetization at Meta. To begin with, he added Hegemann, “We’re building tools like text variation, background generation, and image enhancement to do things like make ad text more engaging or creative”. Specifically, these functions will allow:
- text variation: Generates multiple versions of the text to highlight important points in the advertiser’s text, giving you the option to test different messages for certain audiences.
- Fund generator: Create background images from text inputs, allowing advertisers to test multiple backgrounds quickly and diversify their creative assets.
- Image Enhancement: Adjust creative assets to fit different dimensions on different surfaces, such as Stories or Reels, allowing advertisers to spend less time and resources reusing creative assets.
These features are currently in trial with select advertisers and will begin gradually expanding access in July to add more tools.
On the other hand, these are not the only products that use AI and machine learning for campaigns and ad personalization. Meta has a product portfolio called ‘Meta Advantage’ and also introduced new features, among which are: switching from manual campaigns to Advantage+ purchases in one clicklaunch of performance comparisons, as well as the use of video creatives in catalog ads.
Meta Investments in AI
Goal will continue to invest in AI and machine learning. The company will now use more complex models in your ad system to improve measurement when you don’t have access to the same granular level of data.
Previously, on Instagram, for example, Meta required one model to optimize for clicks on Story ads and another to optimize for conversion or sales of Reels ads.
Now, Meta can transfer learnings across multiple objectives simultaneouslyimproving advertiser conversions and the quality of ads for the audience on the platform. Goal plans to reveal more generative AI implementations and tools across all of its apps in the future.