Adobe tests an AI recommendation tool for headlines and images

AnukritiJuly 7, 2020

0 550 1 minute read

Team members at Adobe have built a new way to use artificial intelligence to automatically personalize a blog for different visitors.

This tool was built as part of the Adobe Sneaks program, where employees can create demos to show off new ideas, which are they showcased (virtually, this year) at the Adobe Summit. And while the Sneaks start out as demos, Adobe Experience Cloud Senior Director Steve Hammond told me that 60% of Sneaks make it into a live product.
Hyman Chung, a senior product manager for Adobe Experience Cloud, said that this Sneak was designed for content creators and content marketers who are probably seeing more traffic during the coronavirus pandemic (Adobe says that in April, its own blog saw a 30% month-over-month increase), and who may be looking for ways to increase reader engagement while doing less work.

So in the demo, the Experience Cloud can go beyond simple A/B testing and personalization, leveraging the company’s AI technology Adobe Sensei to suggest different headlines, images (which can come from a publisher’s media library or Adobe Stock) and preview blurbs for different audiences.

For example, Chung showed me a mocked up a blog for a tourism company, where a single post about traveling to Australia could be presented differently to thrillseekers, frugal travelers, partygoers and others. Human writers and editors can still edit the previews for each audience segment, and they can also consult a Snippet Quality Score to see the details behind Sensei’s recommendation.
Hammond said the demo illustrates Adobe’s general approach to AI, which is more about applying automation to specific use cases rather than trying to build a broad platform. He also noted that the AI isn’t changing the content itself — just the way the content is promoted on the main site.
“This is leveraging the creativity you’ve got and matching it with content,” he said. “You can streamline and adapt the content to different audiences without changing the content itself.”
And from a privacy perspective, Hammond noted that these audience personas are usually based on information that visitors have opted to share with a brand or website.