In the early 1990s, computer scientists at IBM attempted to create a machine capable of only a single function. It was not in a field with mass-market appeal, or even one that would generate substantial revenue. Rather, the machine was constructed to play chess, or more specifically, constructed to beat the reigning world champion, Garry Kasparov. After several unsuccessful iterations and many failed games against the champion, the computer Deep Blue was invented, and in 1997, IBM achieved their goal.
I mention this story to help draw a picture of how far A.I. development has come in the past few decades. At the turn of the millennium, the cutting edge of A.I. research was only able to yield a machine that, after nearly a decade of programming, was able to beat a human at a board game. In the 20 years since, A.I. pervades every aspect of our lives, underlying our navigation systems, dictating what type of entertainment we watch and what type of news we consume. Today, unseen algorithms guide much of what we do and much of how we think. Advertisers, never being ones to miss an opportunity, have decided to act on this information, and develop new technologies that synthesize marketing and A.I.
That leads us to today’s topic, chatbots. Chatbots are automated computer programs that respond to consumer inquiries through use of A.I. Whilst initially sparsely utilized, modern developments in machine learning have led to their rapid proliferation. They are becoming an increasingly useful marketing tool, and in many ways, are revolutionizing how we do advertising. Here are some of the reasons why.
Only What’s Necessary
There are several different species of chatbots, each employed for different tasks. Perhaps the most prominent kind of chatbots are the ones used for searching and delivering products. In many ways, these chatbots can be seen as the next step in the progression of user convenience. As a higher number of individuals have moved online, newer innovations are constantly developed in order to create as many conversions as possible. Search-chatbots are a unique step in this evolution of user convenience because with it, users no longer have to deal with extraneous results in their search terms. Every question a bot asks is designed to curate information for the customer, so only the most relevant information can be presented. The onus to rifle through search clutter is shifted from the consumer to a program that is far more adept at finding what it is they want.
Perhaps the most impressive part about this whole process is that chatbots actually get better at doing this as time goes on. Through machine learning, chatbots improve both how they interact with customers, as well as how they interface with and interpret search data. So a process that was already more efficient than the consumer becomes better at its job the more it is used. In this way, chatbots are like the most competent customer-service employee you could ever imagine.
Beyond cutting out inconveniences for consumers, chatbots offer greater potential for product retention than other forms of marketing. The software that encompasses chatbots is not isolated to direct textual interaction with the consumer, but is rather more holistic in nature. Behaviours, habits and preferences of customers are constantly being analysed and fed into the analytical software of chatbots, which allows them to tailor responses and product recommendations for individual users. By personalising marketing in this way, audiences feel a more intimate connection to the brand than they would have otherwise with broad-spectrum social media campaigns.
This personalisation develops a kind of marketing positive feedback loop. As chatbots are able to align their recommendations more accurately with user preferences, users become more likely to interact with them. This leads to more data, and thus closer recommendations, and perpetuates a cycle in which profit accrues to marketers and business owners.
Earlier, I alluded to the ability of chatbots to gather user data and examine consumer habits. Whilst this has clear and effective micro-applications (like the personalisation of products to individual tastes) the macro-applications are perhaps even more ground breaking. One such application is the use of consumer data for market research.
In 2018 alone, it was estimated that approximately 5 million users engaged with survey-bots through Facebook messenger. These bots were posted by a variety of businesses, ranging from tech companies to political campaigns. The data that was extracted from these surveys was then used to inform decisions for business reform. Business decisions (particularly for burgeoning companies) no longer have to be made on broad industry trends or analytics from competitors. Thanks to chatbots, industries can get a keen insight on what their users want before they have even developed a product, and because of this, products can be more carefully tailored around these desires.
Embracing The Future
At the risk of sounding like a luddite, I understand why there is a sense of queasiness in the face of this current wave of automation. We are all at the precipice of an explosion in machine intelligence, and chatbots are but one representation of this fact. However skilled any labourer might be, it is abundantly clear that chatbots, A.I and machine learning are doing things that human beings simply can’t. The economic survival of businesses is predicated on whether or not these advancements are embraced. The latest technological revolution is here, and its application to marketing is not only evident, but necessary.
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