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3 reasons chatbots didn’t meet industry expectations in 2017

Great expectations surrounded the dawn of the “chatbot revolution” less than a couple of years ago. Marketers and futurists fantasized of intelligent virtual autonomous agents that would understand us better than ourselves, pick up our desires from chunks of conversations, and turn every word and command we could think of into an immediate action. The idea was something like a mix of JARVIS from the Marvel Universe and HAL from 2001: A Space Odyssey (before he went crazy).

I think that at the beginning of 2018 we can sadly yet quite confidently say chatbots have not met these great expectations. Even discounting Microsoft’s Twitter bot becoming a neo-nazi supporter and other crazy stories, the overall advances of the chatbot industry have failed to materialize the huge benefits we were promised. 2016 and 2017 were not “the years of conversational commerce,” chatbots are not “the new apps,” and the AI we normal people can access through platforms such as Messenger or Amazon Echo still seems much more artificial than intelligent. For example, Facebook recently had to shut down its virtual personal assistant “M” allegedly because it relied too much on humans for providing meaningful and useful answers.

It’s time to understand why these expectations and predictions – made mostly by experts with a proven track record – totally missed the mark. I do firmly believe chatbots can represent a revolutionary, exciting, and somehow liberating new way for humans to interact with this marvelous thing called “The Internet.” This is why I believe it is essential for marketers, developers, and entrepreneurs to understand what went wrong, what mistakes we made, and what we all need to fix in order to fulfill the true potential this technology holds.

Of bots and men

The biggest misunderstanding at the core of this semi-fiasco is the idea that bots can seamlessly and entirely replace humans as virtual assistants, customer care operators, or personal shoppers.

Understanding a joke, picking up the nuances of written or spoken languages, and using intuition to choose the right words to say or actions to take are all things an AI agent will not learn for decades. And even when the technology progresses to this point, it’s possible these qualities may never be replicable in a non-human “brain.” When we believe we can interact with a bot the same way we engage with a live person (or in some cases we are not even told that we are chatting with an automated system) the result we usually get is frustration, coupled with a general mistrust of the technology as a whole.

Bots are bots, humans are humans. Computer programs and systems are really good at certain tasks – finding information quickly, doing heavy computations, and storing petabytes of data – but are very bad at others. They are especially bad at generating that minimum level of empathy any operator dealing with people must feel. Mixing the two can be deadly.

Conversation vs. information

The second problem that made chatbots mostly fall flat on their faces in 2017 is the choice of the interface commonly used. Marketers and developers got carried away by this new toy and thought they were finally able to create “conversational” agents with which humans could dialogue like they would with a friend or a human helper. We dreamed of being like Tony Stark and exchanging witty jokes and deep thoughts with an omnipresent and seemingly omniscient cyber assistant. Well, that was a mistake. Conversations are hard to sustain for non-humans, and once a computer loses track of where it is in a two-way interaction, results can quickly become pretty funny and immediately break the “magic” of the whole situation.

Chatbots should have clearly defined paths and funnels through which they lead visitors toward explicit or implicit goals. The process should include a series of questions and answers, and possibly even links and buttons. This doesn’t mean bots shouldn’t implement and offer natural language processing, it means we should clearly define the realm in which a bot can act. We should create boundaries that the bot cannot cross and that support, contain, and actually help the system offer a much more effective, useful, and fulfilling experience.

In addition to this, well-identified goals allow marketers and business owners to track and measure the ROI of these tools more precisely. We were so excited about this technology that we forgot anything we do costs time, money, and energy so we mostly skipped the analytics part. This is another huge problem since, quite simply, we do not have public (and I doubt even private) numbers that tell us how ecommerce transactions or user engagement on chatbots compare against other, more traditional channels. This level of blind experimentation is something only brands with big pockets that are ready to waste money can afford to do.

The ivory tower

And this leads us to my last point. Small and local businesses have not fully embraced chatbots because they are perceived as complex, difficult to implement, and nearly impossible to measure. Throwing around names like artificial intelligence, machine learning, and natural language processing inevitably scares the heck out of a small business owner.

For example, it’s likely a restaurant owner already has a hefty following on their Facebook page and a couple of successful ad campaigns but would simply like to have a way to better serve prospects and customers asking questions via Messenger. If they have to spend big bucks on such a technology marvel yet don’t have a simple way to understand if it’s working or not, they’ll probably think chatbots are out of their league and maybe even a scam.

We need to come up with simpler yet equally effective solutions that bring this technology into our daily lives and help small business owners leverage the power of automated social interactions. Only after we master this can we focus on building Skynet, if we really want to.

Literally billions of people are on Messenger every day. They constantly have it in their pockets and are ready to use it to receive very simple yet immediately actionable and highly personalized information – something this technology already allows us to do. Are we sure we want to waste this opportunity with faulty chatbot execution?

Silvio Porcellana is an entrepreneur, marketer, and coder working on the Interweb since 1999. He created The Maven System to help fellow entrepreneurs build successful online businesses.

This content was originally published here.

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