User experience design (UX) isn’t a guessing game anymore: AI helps you personalize the customer journey at every step, making it more relevant, more engaging, and more delightful. Register now for this VB Live event to learn why AI should be the foundation of all your UX design, and where to start.
“This is such a great time to be alive if you’re into data,” says David Parmenter, director of engineering and data at Adobe Document Cloud. “The capability of computers just gets better and better. The stuff we get to work on is cooler and cooler.”
At Adobe, a company that’s all about content, content creators, and ensuring that subscribers to their services stay subscribed, that means using AI and machine learning to continuously improve the user experience.
“Things we can do that will help content creators do their jobs are really important to us,” Parmenter explains.
That includes improvements in image recognition, such as allowing a Photoshop artist to perform a delicate operation, such as selecting human hair in an image, easily — previously a hugely effort-intense labor. Or now that the program recognizes human movement and gestures, animators and can apply those directly to a digital puppet, without the hours of painstaking point and clicking.
“The best of breed now is you can do it with the click of a button,” he says. “There’s a lot of UX design there. You have to give the user a gesture that makes sense to them, that they can then execute on, and it has to work the first time or they’ll never use the feature again.”
The biggest benefit of AI for user experience is twofold: it speeds up things that were very tedious, he explains, and it adds brand-new capabilities that couldn’t have been possible even just a few years ago.
He points to the problem of refining creative asset searches. For Adobe Stock, the company’s creative assets database, the company’s focus is on surfacing relevant content based on who you are and based on the kind of searches you’ve done before, as well as eliminating the reliance on inaccurate, incomplete metadata that used to depend on input from individual photographers.
“You’d rely on somebody tagging a photo to say, this is a picture of a woman on a bicycle. As Stock has a lot of user-generated content, the author who submitted the photo would have to fill that in. But now we can find things in the photo that nobody would ever fill in.”
With unsupervised learning, a branch of machine learning, their algorithm learns from mountains of test data that has not been labeled, classified, or categorized. Rather than iterating as the algorithm receives feedback, it continuously works to identify commonalities across the data pool and learns based on their presence or absence in each new piece of data.
“That would be really hard to do without AI,” he says. “It’s just not possible for a human to process all of this data.”
Another example is the Adobe Lightroom, a platform for photographers to store, edit, and organize their images. “I have 100,000 photos in my library,” says Parmenter, “and I’m not much of a photographer. Real photographers have millions.”
Adobe Sensei uses machine learning to not only recognize people, content, and keywords for better search in Lightroom — among millions in your library — but can surface the best-quality photos from your library or a set of photos by training the system on numerous signals that identify a high-quality photo versus a low-quality one. Again, the savings in time for the end user is enormous.
To launch your own AI-powered UX, Parmenter suggests starting more simply, with something tractable that adds value.
“My general feeling is, if you can find a problem that is either really hard for your users, and there’s no better way, or something that would really delight them and make them 10 times more productive, those are the things to look for,” he says. “Start with something that simply integrates into your existing product suite as a delighter, and grow from there.”
The impact to the bottom line in utilizing AI for UX is a little difficult to measure, Parmenter has found — though A/B testing is always useful for determining whether a specific feature has offered any kind of lift, or whether a message has resonated. Yet, the overall value is in rewarding subscribers which, in turn, ensures their loyalty.
“The way that you pay back somebody for subscribing to your business is by delivering ongoing value,” says Parmenter. “There’s no way we’re not going to keep innovating.”
To learn more about how AI is helping brands create powerful UX and transforming how users interact with their apps, real-world case studies and more, don’t miss this VB Live event.
Don’t miss out!
Attend this webinar and learn:
- How AI supercharges the relevancy, elegance, and engagement of modern design.
- The ways well-known brands are creating intuitive apps with powerful UX supported by AI
- The relationship between effective design and a strong ROI
- Real-world successes and failures in AI-driven design
Speakers:
- Steph Hay, VP, Conversational AI Design & Integrated Experiences, Capital One
- David Parmenter, Director of Engineering & Data, Adobe Document Cloud
- Stewart Rogers, Analyst-at-Large, VentureBeat
- Dave Clark, Host, VentureBeat
