When people think about artificial intelligence (AI), they often picture some ominous, super-intelligent robot straight out of a dystopian sci-fi movie. But today’s reality is much different: for many brands, AI is a key tool that helps their teams get more done—and, in the world of marketing, it’s a way to create smoother, more relevant customer experiences without losing the “human touch” that helps connects brands and their customers.
To explore the challenges and best practices that come with using AI to support brilliant customer experiences, we spoke to thought leaders on the subject from Grubhub, Neura, and Overstock.com at last fall’s LTR conference. Here are their five key insights:
It may seem a little counterintuitive, but artificial intelligence—when used thoughtfully—can lead to customer experiences that are actually more personal and more human. How? By making it possible to use data to better understand their customers—and to take action more effectively based on that understanding.
“We don’t get to be in the room with a customer,” said Ramsey Kail, group product manager (Marketing) at Overstock.com. “We don’t get to see their facial expressions. We don’t get to see where their eyes are [or] their mood, but what we can do is pick up on those digital cues, those digital signals and try and turn that into something…something that educates that experience we have with the customer.”
“We’re not engaging with mobile devices—we’re engaging with people,” reminded Ori Shaashua, cofounder and head of product at Neura. That’s why Shaashua urges brands to think about AI as a tool for taking raw data and transforming it into actionable insights. By making it possible to reach customers with more relevant, more valuable brand experiences, AI can make those interactions feel less mechanical and more welcome to the people having them.
The truth is, many brands are still slow to invest in AI as part of their customer engagement strategy because of misconceptions and straight-up misinformation. Old-fashioned ideas about this technology continue to persist, and that’s leaving a lot of brands behind the times—their marketing, growth, and engagement teams unable to get buy-in for AI and unable to reap its rewards.
“There’s a perception that I find we often have to push back against, which is this picture of AI as this disembodied machine that’s sort of on its own and contemplating whether to destroy us all,” said Boris Revechkis, Braze product manager. Revechkis, a former computational neuroscientist, noted that this perception doesn’t have a basis in current reality—instead, he argued, brands should think of AI as “a specific tool for a specific kind of problem” that a team might face when it comes to gaining insights from mass amounts of data.
Marketing is a more competitive space than ever, with more brands fighting for consumers’ attention across more and more digital platforms and channels. So, with that urgency in mind, when does it make sense for marketing, growth, and engagement teams to start investing in artificial intelligence?
“The short answer is: yesterday,” Shaashua said. “AI can solve the problems that all of you guys have today, and I believe that the time is now” to begin investing in artificial intelligence.
According to Revechkis, AI becomes important when your team finds itself inundated with information related to customer engagement. “As soon as the data you’re talking about is of a quantity that is too large for a human—or even a team of humans—to reasonably be expected to analyze and understand,” he said, “that’s when you need to start to leverage algorithms to extract and recognize those patterns.”
When marketing, growth, and engagement teams dive into the use of AI, it’s natural for them to think first about the technology itself and how it works. But while it’s vital to build algorithms and systems that function the way they’re meant to, it’s just as important to take a human-centric attitude when you’re implementing AI in your customer engagement strategy.
“For us, it takes a village,” said Wai Gen Yee, Grubhub’s head of data science. “It also [requires] the AI engineer—the machine learning engineer—to...be human-centered.” According to Yee, there’s a natural evolution that most engineers go through when working with AI. At first, the engineer is mostly concerned with metrics. Over time, they develop more of a business-driven mentality as they get more experience with the AI systems they’re actually working with. And the final stage of their evolution tends to mean becoming “empathetic with the actual customer.” This final stage is the most crucial one and, according to Yee, the one that teams working with AI most need to focus on.
Once you’ve incorporated AI into your company’s customer engagement efforts, you need to ensure that there’s a structure in place that will allow the implementation to be lasting and effective. “It almost doesn’t matter what algorithms you’re using,” Revechkis said. “If the process—the scientific process underlying them and the data-driven process underlying them—isn’t performed or even attempted correctly, then it almost doesn’t really matter what predictions you generate. Because you’re not going to be evaluating the results and improving them with time.”
“If you can think in terms of not just one-offs, one-off marketing campaigns,” Yee said, “but something [you] can generalize and then do again and again. So...software engineers can actually build something once and use it forever, that’s when you get the really big bang for the buck. You have to have a repeatable system that you can measure the performance of and just make better and better regularly.”
When it comes to getting started with artificial intelligence, the time is probably now. Thankfully, if your brand already takes advantage of the Braze customer engagement platform to humanize their brand experiences, adding in AI capabilities can be as easy as clicking a button. To learn more about the Braze Intelligence Suite, check out our exclusive overview.
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