Back in the 1950s, when computers could barely fit inside the rooms that housed them and having a digital marketing strategy wasn’t remotely an idea, advertisers worked to revolutionize the way in which promotional messages were disseminated across all the new media and gadgets of post-WWII USA. Radio stars plugged products during their programs, newspapers began to run increasingly diverse advertisements, and the first television ads were barely a decade old. It was in this climate of new technology, new markets, and new audiences that the first systematized approach to telemarketing was developed.
Consumers watched these media companies grow up, learn new tricks, and improve their quality in a number of ways—except, it seems, for telemarketing. While television and print advertisers continually pour millions of dollars into the latest tech and talent for their elaborate productions, telemarketing continued to ruin time at work and home, interrupting people with the same lame sales pitches and unmotivated callers. Seemingly the only technological improvement to grace the field in 20 years has been the rise of automated or “bot” callers which, in practice, seem so far from real people that it’s almost laughable. This isn’t science fiction, robots can’t impersonate people yet.
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Except that sometimes, they do—and you may not have even noticed.
To keep up with the demands of constant customer service requests, some digitally present brands have started using chatbots to handle simpler customer interactions. While far from a perfect technology, chatbots pervade the web pages of more companies than you might think, including such brands as Ikea and Disney, and most major airlines. Is this marketing technology the future of customer services? And if so, how does this sort of tech fit into the content marketing strategies of brands trying to leave a personal mark on the digital space?
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Chatbots are one just one piece of a massive move toward automation that’s defining the industry today. Some of this tech is already familiar, like email or sales automation platforms, which operate on a comparatively more solid log: if user A takes action B, deliver message C. But how much time and money could be saved if our personal devices could interact with us seamlessly, and address less concrete queries that normally require input from a person?
It’s a clearly appealing prospect and quite brilliant in theory, but if current user feedback is to be believed, it may be an idea that’s a bit ahead of its actual implementation. But regardless, The Grid presents a great picture of what people like Elon Musk hope our future with computers looks like—a conversation from human to machine, with all the technical bits worked out by machines that optimize themselves.
In spaces where there’s hard data to be had, such learning algorithms present a lot of opportunity. As long as a program can be developed to analyze, interpret, test, and iterate on data, then it may be able to help optimize any number of facets for your digital marketing strategy. But what happens when feedback doesn’t come in the form of heat maps on a site or metrics in an analytics page?
Teaching the Machine to Speak
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While we may not be able to teach a computer to understand human emotion yet, some very intelligent people over at companies such as Imperson have been able to analyze patterns of speech and use them to create “bots” that can simulate interaction with a customer care representative. While limited in capability, Imperson has specifically tried to tackle the more inhuman elements of most chatbots and create methods for convincing human responses (even when the human user doesn’t stick to quite the expected scripts). Their customized bots have been able to help with a wide variety of challenges, from customer service for large companies to wowing audiences for Disney.
But there are two key elements of Imperson’s approach to these projects that are imperative for marketers to understand. The first is the custom-built nature of their bots. At least for now, there is no self-learning “one size fits all” bot solution for any company, no matter how simple the application. If your brand wants to consider using bots as a way of lessening the load in some places within your brand’s narrative, every effort should be made to customize, minimize, and camouflage it. But secondly, it’s important to be specific about the goal your bot exists to fulfill. The more functions your bot is supposed to tackle, the more spaces there are for a user to ask questions or provide input in a way that derails the conversation and results in them leaving. Bots tailored to specific needs or goals—particularly for top-of-the-funnel interactions—can help do the grunt work of separating your audience into segments early on, enabling your human team do the work of creating the perfect experience for each user individually.
Do brands need to be pulling in chatbots and other machine learning tools right now? Probably not. But should your digital marketing strategy take into account means of moving toward this marketing technology into the future? Absolutely.