This isn’t Hal 9000—machine learning is improving consumer experiences
Today marks 50 years since the debut of Stanley Kubrick’s iconic film 2001: A Space Odyssey, which depicts supercomputer HAL 9000 communicating using words humans use, but to a negative end. Half a century later, the film is notable for its prediction of today’s “potentially dystopian impact of artificial intelligence (AI) technologies.”
Indeed, HAL embodies what those who love to hate AI cite as its great vulnerability: machines that become responsible for things people usually do can malfunction and all goes awry. But the reality is that acceptance and adoption of AI and machine learning is growing and further infiltrating our lives. With its ability to interpret and optimize volumes of data so it’s better understood, more useful and positively serves our needs, AI actually humanizes that information.
Evidence of the positive impact of machine learning is all around us, so seamlessly woven into our everyday lives that we often don’t realize it’s there. Technology-infused generations like millennials are nearly twice as likely to agree—45 percent versus 23 percent who disagree—that AI and other technologies minimize their frustrations as parents, according to a recent survey from IEEE.
It’s not a surprise that 66 percent of Amazon Alexa and Google Home owners use these AI voice devices to entertain friends and family, and 30 percent say it’s even replacing TV time. Experts predict that AI will power smart devices in the home that support physical, emotional, social and mental health, from monitoring and assistive devices like intelligent walkers to robot-assisted dressing. What’s more, about two-thirds of millennial parents would prefer to have AI help them live independently in their golden years while just 37 percent would rely on their own children, according to the IEEE survey.
And yet for marketers, particularly when it comes to automating functions handled for eons by humans, issues of trust, fear of change, implementation and training challenges give them pause. Ninety-two percent of global senior business decision-makers responsible for data and analytics direction are worried about the reputational damage that inappropriate use of analytics could cause for their organization. Businesses want the benefits that digital and automation can deliver, but they don’t always trust the underlying analytics that power those machines.
Experts predict that AI will power smart devices in the home that support physical, emotional, social and mental health.
But the tide is turning. Recent studies show that more than 70 percent of business leaders believe that AI will be the business advantage of the future, and marketers that want to best serve their customers are wise to better understand the significant advantages machine learning can bring to their business.
Look no further than the proven value machine learning has brought to Netflix and its customers by serving content based on learning those customers’ interests. More than 80 percent of the TV shows people watch on Netflix are discovered through the platform’s recommendation system. Netflix uses machine learning and algorithms to help break viewers’ preconceived notions and find shows that they might not have initially chosen. To do this, it looks at nuanced threads within the content, rather than relying on broad genres to make its predictions.
Diving a bit deeper, an overwhelming majority of email marketers (97 percent) are confident that artificial intelligence and machine learning can personalize email content to an individual’s specific interests and improve the customer experience, according to a new market research study from The Relevancy Group in collaboration with OneSpot.
Among the study’s findings is that on a weekly basis, most marketing teams spend over 36 hours—or the equivalent of that entire work week—on manual email segmentation processes, such as content selection and proofing, in an attempt to personalize content. (Retail and consumer products sector marketers are spending a weekly average of 46 hours and 40 hours, respectively.) But 70 percent of marketers say that if they used machine learning and eliminated manual processes, the time saved would be reallocated to program planning, expansion and strategy.
More than half of marketers (51 percent) would instead allocate the time saved to data analysis while subject line optimization (44 percent), segment refinement and list cleansing (35 percent) are other activities to which marketers would shift their time reserve.
Advances in AI and machine learning enable marketers to identify and prioritize each person’s particular interests and deliver what we, as individuals want. That’s how, as humans, we ideally build relationships. If we know one friend likes sports, we don’t assume they all do. We likely tailor our conversations and social gatherings toward those interests and nurture the relationship if we want it to last.
Machine learning technologies are giving us very similar capabilities. They are automating many arduous processes, increasingly transforming how marketers staff teams and manage their tech stacks, but to be effective and humanize data, they are guided by humans. Just like us—and HAL 9000—these technologies are not perfect, but today they’re enabling results that embody a kinder, softer HAL.
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