Chatbots go back more than half a century, first gaining mainstream attention from computer scientist Alan Turing’s article “Computing Machinery and Intelligence,” and later from Joseph Weizenbaum’s program, ELIZA, in the mid-1960s. Bots have come a long way since those early ideas and programs, and are now used for purposes like messaging apps on social platforms, digital customer service reps, purchasing platforms, and sales tools. Consumers have largely embraced chatbots, citing these three features as the top benefits: 24-hour service, direct responses, and answers to simple questions.
More from PostFunnel on Chatbots:
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It’s About Time to Build Yourself A Chatbot
Forbes shared two interesting stats that gave perspective on how people and companies have become more connected with this type of technology: by 2020, 85% of consumer engagement with businesses will be handled without interacting with another human. And 80% of businesses say they currently use or are planning to use chatbots by 2020. Facebook hit 300,000 chatbots on its platform last year, up from 100,000 the previous year.
But like every other technological advancement, chatbots have competition — namely, advancements in other types of AI and predictive analytics. Forrester forecasts a 15% compound annual growth rate for the predictive analytics marketing through 2021. Anytime something new hits, it’s easy to wonder if it will overtake what’s already there.
These other digital tools have worked their way into the customer experience in recent years, but does that mean there won’t be space for chatbots going forward?
Fuel for predictive analytics
To answer that question, it’s imperative to first consider the nuts and bolts of the analytic advancements chatbots are up against. At its most basic level, predictive analytics uses historical data to predict quantitative future events and trends. This data-driven capability relies on machine learning tools to provide the desired results – and it’s only as dependable as the information being fed into its database.
As Peter Sondergaard of Gartner Research said, “Information is the oil of the 21st century, and analytics is the combustion engine.” One source of that information is the chatbot, which extracts valuable data from customers. This data is vital to predicting their future behaviors, needs, pain points, and expectations. As one example, Zendesk created Satisfaction Prediction to anticipate customer satisfaction ratings before they happen. Part of the formula involves using the ticket text the customer has submitted — which is similar to the text you would receive via chatbots. This is one piece of the puzzle. While there are, of course, other data sources that cumulate to form predictive analytics, information collected via chatbots provides valuable insights into one-on-one conversations with customers.
Will there be an audience?
The consumer groups using chatbots and the question of if that use will be sustained are two important parts of the possible longevity of this technology. Demographic research is key here. The viewership most interested in chatbots are men ages 25 to 34 — the marketing sweetspot, considering millennials are projected to spend $1.4 trillion shopping each year by 2020. For comparison, the highest interest for women with chatbots comes at ages 34 to 49 — with the 65+ age range showing the least interest for both men and women.
Another component is whether the audience would rather communicate with this type of AI for eCommerce and customer support. that only 57% of people would rather get help from a real person than an AI program, and 40% said they didn’t care whether they were talking to a human or a machine as long as they received the help they needed. HubSpot also found that 48% of consumers would rather use live chat than any other means of contact. According to research, 69% said they would consider talking to a chatbot before a human to get their questions answered quickly. While we’re not trying to make the argument for AI over human interactions, it’s worth noting that consumer awareness is the first step to audience adoption and continued use.
Money drives decisions
As long as businesses are profiting with chatbots, they will continue to have a place in the market. Drift found that 27% of consumers would buy a basic item through a chatbot. Does this mean they may also make that same purchase through another, more advanced type of AI? Maybe. But just like many grocery chains now offer free in-store pickup as well as delivery, you want to make sure your brand provides different purchasing options to meet customers where they’re at.
Chatbots are continuing to evolve and advance, just like other types of AI and predictive analytics. As long as this technology adds value to companies and their analytics — and consumers use them — chatbots will remain a part of marketing and customer service strategies. It takes time for one type of technology to completely phase out, because consumers have to learn to trust the new advancement as they’ve trusted the old ones — even if new types of AI would serve them better.
Really, the question shouldn’t be whether or not predictive analytics and other types of AI will replace chatbots (at least not for the foreseeable future). Instead, you should be asking how new – and newer – innovations can work together to bring your brand better results.
