You Ask, I Answer: Bots and the Future of Customer Experience?

In today's episode, Bernie asks, Do you see chatbots being effective in building and growing the relationships between the brand and audience in 2020? So chatbots are a tool, right? They're a tactic. The question really is, or the question should be uh how effective is a chatbot at enhancing the overall customer experience. Remember that a chatbot is really nothing more than a piece of software, right?

The piece of software that interacts with customers at a certain point in the customer experience. Most of the time, they are used in two places. They are used in uh upper funnel introductions and uh end of journey customer uh support, customer relationship management. They're a form of automation, and as such, because they are an automation, they are best suited for highly repetitive, highly predictable tasks. So the real question is, what is your customer experience look like?

What is your customer journey look like? What steps in that customer journey are highly repetitive on the part of the customer, not on on our part. Again, with all customer experience technologies, we want to make sure that we are looking at things from the perspective of the customer and improving things from their perspective, not from ours. The perception for good or ill is that chatbots are a money-saving, job cutting technology that uh companies use to avoid spending money on customer service, avoid spending money on customer experience, uh, reduce headcount. There's some truth to that, right?

Uh however, you choose to deploy chatbots or any customer experience uh technology, you want to avoid playing into that perception, right? You want to use the tools for what they're best at and not use them to cut costs. You want to use them to enhance the customer experience, not take away from it. So, what are what are chatbots good for? What's repetitive?

Getting basic information. Right? Well, your hours. That's that's a question that is well suited for a bot. Um basic asking for help.

So uh a bot that can say like, if you're here for help, how can we help? Do you want someone to call you? Do you want someone to email you? Do you want to do a live chat? Whatever the case is, you can use the bot to reach out and ask people how they want to be helped.

Probably not try to you know build a massive bot to help on behalf of the customer, unless you know that there is just this one thing that everybody needs help with, you probably should fix that thing first. Uh third is finding resources. Bots are really good at helping somebody navigate, especially if you've got a large website, you have a large uh support catalog. If uh you know you're you have a let's say you're a consumer products company and there's you know five hundred frequently asked questions and manual pages and stuff on your website. A bot is really good at helping somebody skip the navigation uh as long as the natural language processing is good.

And you can say, like uh, I need help with uh the manual for these new headphones, you know, the the model XM22 head headphones, and the and the bot should, if it's well programmed, be able to find that content for the customer and get it to them. And fourth, of course, is that bots are really good at greeting and proactively introducing known resources. So as part of that introductory phase, when the customer first comes to the website, the bot should be able to say, Hey, welcome. Here's some things that people commonly look for. What can I help you with?

That way people realize this bot is here to help the customer experience, to help them get to their answers faster. That's really what they're good at is get people to an answer faster. What are they bad at? Well, bots are really bad at handling anomalies and exceptions, right? Uh when somebody writes in and says, Hey, I got the new XM22 headphones and they caught on fire.

That is an exception. I hope it's an exception. Um that's something that again should not be something the software should be trying to handle. That's something that ideally, if they're if a bot is well constructed, it has anomaly and exception detection and set and immediately routes to a human to help out. Bots today, even with really good models, are still not great at natural language queries and conversations.

There's still a tremendous amount of training that has to happen now. It's getting much, much better. Two years ago, uh, I would have said they were terrible at natural language processing, period, but they are much, much better than they used to be. They're still not as good as a person. Um and most of all, bots are really bad at handling unhappy customers.

Right? If someone is angry or upset or frustrated, you want to get them to a human as quickly as possible. You do not want to try to get them to avoid talking to a human because that's not why that person's there. One of the things that companies need to think about is that sometimes, in some cases, depending on how frustrating your product is, your human support almost has to have some like basic therapist training to help to help a person get out of an unhappy emotional state first before solving their problem. That is not something a bot can do.

Period. Now, looking forward in 2020, what do we expect to happen? The last two years have been absolutely exceptional in what has happened to natural language processing and our ability for machines to understand language. You've heard big news this year about Google's BERT models and open AI's GPT2 technology and many, many, many other uh pre-trained models. Those are continuing to grow in complexity, those are continuing to process data and language really well, and I expect that to be the case in 2020 as well.

Making use of those pre-trained models is getting better. The ability for people to simply download a massive pre-trained model, tune it up a little bit for their use case, and then deploy it, has gotten substantially easier in the last year or so. Uh, and again, I expect that to continue. And that that the impact of that is that you will be able to hit the ground running with a chat bot or any um AI task that uses language much faster. Download the model, spend maybe a couple of days tuning it, and immediately roll it out uh in in production.

And chatbot software uh continues to improve as well. It continues to get easier for people to deploy. Two years ago, you were rolling up your sleeves in coding. Right? That was just how you got a chatbot running, and it's one of the reasons why initial people who tried it out were like, yeah, this is not for us because it's a lot of work to support.

Many services are getting much easier to use. Drag and drop uh or very, very simple code. I was uh uh uh sitting down with uh one of my kids over this past weekend, and we built a first uh our first bot in Discord, and it was very straightforward in you know, some basic Python to to get it connected and stuff, super super easy. Um download uh template and just modify it. So bots are getting much easier for brands to deploy as well.

So those are what we have to look forward to for uh the future of customer experience, the future of chatbots in 2020. There are any number of things that could change that we can't see right now. We may have a a revolution in compute power, for example. If that happens, it could be a massive game changer. So some things to look forward to no matter what.

Great question. Leave your follow-up questions below. Uh and of course subscribe to the YouTube channel and the newsletter. We'll talk to you soon. Take care.

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