Heresy? Hear me out.
I have a bold thought that’s gotten me into trouble on a few memorable occasions:
I believe this deeply, but don’t get me wrong! I mean no ill will!
I don’t mean companies should prevent their customers from contacting them.
Rather, companies should strive to provide such high-quality service that customers never feel the need to reach out in the first place!
The Sami people, who live in the northern tips of Scandinavia and Russia, use at least 180 words related to snow and ice. And as many as 1,000 words for reindeer.
What does this have to do with NLU? Read on...Use Cases for an NLU Router
Before we dive into these use cases, you might want to bookmark these recent posts that provide additional background info and perspective leading up to the NLU use case discussion:
Ready? Let's dig into the best use cases for an NLU Router:
NLU is a hot topic these days as it it powering many conversational interfaces.
So I asked our speech experts to help explain NLU.
But first to Breaking Headlines:
These headlines show that language is complex, ambiguous, flexible, and subtle.
A contact center agent can understand the headlines but does a machine/computer/IVR/chatbot have any hope of understanding what is said?
One technology that can help is NLU. It can understand the meaning of conversations, dialogs and spoken interactions.
If it's not already, NLU should be in your customer engagement strategy toolbox.
In this NLU Cheat Sheet, we cover definitions and basics for NLU.
Conversational interfaces where called a break-through technology by MIT Technology Review.
Another article went on to say...
"We think the next era will belong to “the conversational layer” — both text- and voice-driven — that will use chat, messaging, or natural language interfaces to interact with people, brands, services, and bots."
This conversation layer is powered by conversational or dialog agents. A dialog agent can -
Mark Clark, on May 30, 2017 8:00:00 AM
Even though AI is poised to “completely reframe how businesses operate and consumers interact” many firms are not ready to invest. The two top reasons for the standstill are:
One reason behind the standstill is the AI landscape is complex. Navigating the AI ecosystem and prioritizing investment is becoming increasingly difficult.
Forrester says, “AI technologies can help customer insights (CI) pros better understand and interact with customers by mimicking human cognitive functions to sense, think, and act. Forrester has identified AI as one of the top 15 emerging technologies that has the potential to change the world in the next five years.” Here's a list:
Mark Clark, on May 25, 2017 10:51:24 AM
“New uses of speech technologies are changing the way people interact with companies, devices, and each other. Speech frees users from keyboards and tiny screens and enables valuable, effective interactions in a variety of contexts.” (SpeechTek)
Technologies and use cases for conversational interfaces are rapidly changing. To better understand these industry trends I attended SpeechTEK 2017. Here are a few notes and observations from the field.
The conference brought in a mix of old school contact center vendors (Convergys, Aspect, etc) and new tech vendors (Google, Amazon, etc) analysts, consultants and enterprises. It was interesting to see the collision and friction between the old and the new.
Mark Clark, on Mar 22, 2017 11:25:06 AM
Are you ready to invest in AI technologies to drive contact center performance?
My guess is that you already have.
You might have deployed speech analytics or an IVR using natural language or a Chatbot or fraud prevention. All these solutions likely use machine learning and artificial intelligence to discover insights and optimize performance.
But the AI landscape is buzzing with emerging tech that could have major implications on customer service. Yes, some technologies will optimize existing processes (like IVR self-service) but others will be disruptive to your current processes (like Chatbots over a messaging app).
You're going to invest (more) in AI technologies for customer service.
The only questions are when, on what solutions, and how much.
To answer these questions, lets take a broad view of how the AI landscape is developing and look for trends and patterns.
You could boil the challenges customer service will face over the next five years down to two questions:
The move to digital touchpoints, micro-moments of attention, conversational interfaces and messaging-based interactions is causing major challenges for many organizations. One reason is that customer services apps (and processes) today are designed for single channel, synchronous and dedicated session interactions.
So orchestration of digital interactions is very difficult... but it's not an option to sit it out because that is where the consumer/customer is.
The shift to algorithms driving interactions might be an even bigger challenge. It is very likely that this trend will significantly improve servicing benchmarks (costs, CX) and become competitive differentiators for your business.
Again, it's not an option to sit it out because that is where competitors are going and what consumers will expect.
How, then, do you begin to re-constitute every app you run in the contact center to take advantage of new algorithms that drive these apps in real-time?
Mark Clark, on Feb 10, 2017 11:02:54 AM
Chatbots and intelligent messaging solutions can help you deliver smarter customer service with a better customer experience at a very attractive cost per contact. To achieve the kind of results that get you promoted, it's important to consider a customer service solution in its entirety. Overlook one key element of the solution stack, and it'll never achieve its natural flow.
We use the technology stack in this post to talk about goal and transaction oriented Chatbots both internally and with our customers. You can use it as a checklist to make sure you're not overlooking a critical part of a Chatbot solution for customer service.