As an interactive marketing professional, I find that listening, due to technology changes, has made some truly significant changes within the last few years.
Back when I was younger, listening was limited to humming along to Twisted Sister’s “We’re Not Gonna Take It,” responding to a friend or parent for information and of course, watching a TV show or two. In those previous experiences, I found that in the exchange of listening to each other that trust occurred.
When you take a step back and look at trust, it pertains to reliability within your own life. Today, trust permeates just about every facet you can think of, and in the world of business, it can mean everything. A marketer’s trust is his word. It represents his honor to those he influences.
Now, listening has changed significantly. More and more “bots” are taking an active part in this communications process. Here, the trust issue now factors in these listening communication processes.
So, would you ever buy something from a robot? Are you sure you haven’t already?
The idea of an automated response algorithm (or “bot” as we’ll refer to it from now on) is still a controversial one, despite the fact they’ve been on the rise in use for the better part of a decade. It’s the idea of filtering, designing, and learning key language and phrases that major cable providers have put to good use when you call their hotline because your Wi-Fi went out. But even those bots are old news, as “conversational commerce” started to cusp the horizon.
The rough idea is this: because of our developments in translating conversational language skills into normally-indecipherable “computerese” that only hard drives can understand, developers went at the problem backwards and have taught PCs to turn coded solutions and ideas into actual words that the average person can understand. Through this method, just about anyone with a third grade vocabulary can now talk to bots about Christmas gift ideas for mom, discuss military history with an encyclopedia, or just trade Sheakespeare sonnets with a twitter bot haunted by the Bard’s ghost. Sounds next generation, right? Only when we get it right.
Perhaps the most famous recent example of this concept going wrong would be Microsoft’s Tay bot that survived twitter for only 16 hours before being pulled offline. The reason? Tay learned new words and ideas from tweets sent to it by other human twitter users; so naturally, it learned racist profanity and proclaimed that Hitler was an intelligent man before too long. A lot of companies were reminded of an important lesson that day—if you leave intelligence to the masses, we will twist and deform it faster than it could ever be used for something constructive.
But if human nature can’t interact with these bots on a free level for even five minutes without manipulating them to say or do something crude, what’s the point of bots anyway? Well for one they’ve been one of the single greatest evolutions for customer service for major retailers. Almost every single cable provider and major retailer employs speech-recognition bots as the first line of defense for concerned customers. And yes, in the years since implementation, bots have shown significantly more accuracy in solution identification than the average customer care provider.
It seems to me that when regulated and given the proper infrastructure on interaction, these bots can and will respond with people just fine via the phone and in social media channels like Twitter and Facebook. Much like Skynet from the Terminator movie franchise, when we give the system free will it will go haywire in some rather harmful ways. But if we collaborate with them and set the right parameters, bots will soon book your flights and fix your Google fiber problems faster than a tech ever could. They’ll respond to both negative and positive customer interaction on social media channels. However, to reach a consistent response, marketing, operations and customer support people must agree on the basic responses that these bots can generate.
We bot this city to Rock and Roll.
Edited by
Ken Briodagh
