This article originally appeared on Chief Marketer.
As AI begins to shape our daily lives, brands must consider how they shift their behaviors and interactions to meet customers’ evolving expectations.
Consider how many marketers suddenly thought they absolutely needed a mobile app. Sure, that was a misconception—but it ushered in the importance of simplicity and utility in brand experience. The app mentality forced complicated brands to take a hard look at their products and services and shape them to be fast, nimble and mobile-focused.
We’re already seeing similar misconceptions about how and when brands should experiment with AI, but what else will the AI trend usher in? What will future brand experiences look like when we as consumers become used to (and expect) incredible simplicity, fewer interfaces to interact with and an incredible amount of personalization? Brands will need to think beyond creating experiences they want people to adhere to and start thinking about creating behaviors they want people to adopt.
It’s tempting to go into a new technology whole hog, but incremental steps might be a better tactic when it comes to AI. In recent conversations with Siegel+Gale’s experience team, we considered how AI will be a game changer in 2018.
“Try to unearth small improvements that will have an impact on customers. Don’t force it and don’t try to be too clever,” says Will Shaw, producer. “For example, I am a fan of how Alexa can request an Uber or how Netflix provides recommends by learning what I like to watch. But, I am regularly irritated when a Facebook algorithm servers me ads for an entire industry because I accidentally clicked on the page. These incongruent experiences make me pine for the human factor.”
In some cases, empathy has been lost as brands experiment more and more with AI, agrees Courtney Canale, Director, Experience.
“The balance is ensuring brands retain moments of empathy and connection when it matters most,” she says. “The smartest experiences are the sum of all user inputs and nothing more. Take a Nest Learning Thermostat, I don’t need an empathetic human connection because the Nest is replicating my own preferences over time, and translating my habits into a seamless, useful experience. The more I simply go about my life, the better my experience becomes.”
AI has provided for smoother and more human-like communication interactions, thereby creating stronger relationships between people, machines, and the brands behind them, notes Alex Stark, UX strategist. With branding at the crux of how these relationships are built, what is being communicated matters more than ever, and it is crucial that these machines have “heart.”
“For example, Mattel’s Aristotle audio assistant engages children, answering their questions through a conversational speech format specially built to understand young voices,” says Stark. “Google has trained neural networks to recognize doodle drawing in real time, providing a call back to ancient hieroglyphics in this hyper-technological age. These brands break down the barrier between human and machine to form a seamless relationship across mediums, all while prioritizing their audience’s needs.”
The Opportunity to Experiment
The move towards commoditization of machine learning services is exciting, says James Barnes, Associate Director, Experience Design. IBM’s Watson, Amazon’s AWS, and Microsoft’s Azure, to name a few, offer suites of services for developers. This availability offers the potential for brands—and individuals—to experiment with machine learning applications and projects with minimal expense.
“Cloud-based AI services enable developers to build products that a few years ago would have seemed like magic,” says Barnes. “Because these services provide much of the processing and computational power, the job of product teams switches from designing algorithms to furnishing usable data with a desired output in mind.”
To put it another way, cloud services allow teams developing applications that rely on machine learning to shift some of their resourcing focus from machine learning-specialists to product designers. “Teams no longer need, say, a natural language processing expert to create a proof of concept that can extract meaning from unstructured data,” he says. “Instead, they need generalist programmers who can write the calls to the correct API. And, of course, team members who understand how their product might benefit from such services, and design around them.”
The increasing commodification of goods and services means brands must improve their customer experience to differentiate themselves, says Brian Crooks, creative director.
“This experiential shift has been dramatically affected by the introduction and widespread use of AI and voice UI (VUI). New technologies have shifted how and where consumers interact with brands. Your living room is now a stage and your mobile device a microphone,” Crooks says. “The tone of voice, timing, and interaction have a renewed prominence in this new VUI space versus logos, fonts, and colors. Brands must look to non-traditional areas of expertise such as UX and stage directors for input on how to best communicate their message through non-visual forms.”