Digital Engagement Blog

The pace of change, and particularly AI adoption, is skyrocketing - moving at a magnitude that enterprises are challenged to meet. Today’s most active digital consumers and largest segment of the workforce, Millennials and iGen, are challenging that rate of change based on their technology adoption, behaviors and preferences. The Blockbuster Video bankruptcy remains a key example of why enterprises must adapt to consumer expectations, and it’s more evident and validated 5 years after their closure. Three critical expectations that impacted the Blockbuster Video failure also influence today’s adoption of artificial intelligence (AI). In this intelligence economy, meeting consumer and employee expectations can mean the success or failure of the business.

On an otherwise normal Friday, one thing happened that shifted the world as we know it.

Though we all knew this day was special, it passed more or less without fanfare. But, looking back, it was the catalyst for how today’s leaders engage with their customers. It changed us all.

It has shaped every day since, and its significance will be felt for decades to come.

On June 29, 2007, the Spice Girls announced their reunion tour.

More importantly? The first iPhone went on sale.

On June 29, 2007, technology started our digital transformation. In time, it made us all feel smarter…act faster…and become FAR less patient than at any time in history.

It opened up a world where continually increasing customer expectations would forever challenge companies to keep up:

• Where technology would expand at a pace few could fathom.
• Where old approaches struggled to address new challenges.
• And where new leaders would rise, replacing the stalwarts who couldn’t…or wouldn’t…adapt.

Which brings us to today.

Conversational Interfaces

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 -

• listen to what you say
• understand what you want and your intent, and
• take action
• respond to you

Download a copy of Forrester's "The Top Emerging Technologies In Artificial Intelligence" here.

The Top Emerging AI Technologies

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:

• We are unclear what AI can be used for in our business
• There is no defined business case for AI investment

One reason behind the standstill is the AI landscape is complex. Navigating the AI ecosystem and prioritizing investment is becoming increasingly difficult.

15 Top Emerging Technologies

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:

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.

Good job.

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:

• How do we engage customers as they interact across digital touchpoints?
• How do we embed intelligence into servicing applications to take advantage of the ability of algorithms to optimize far beyond what we've achieved to date?

Orchestrating Digital Touchpoints

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.

Algorithms Driving Apps

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?

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.  

In this guest blog, Amy Stapleton from Opus Research outlines three ways Intelligent Assistance technologies can work for Marketing.  The post is based on Amy's white paper, Six Perspectives on Intelligent Assistance, which is available at the end of this blog.

Intelligent Assistance Benefits Go Beyond Customer Care

Customer care professionals have been leveraging the benefits of intelligent assistants and similar self-service technologies for many years. On the flip side, most marketing professionals didn’t spend much time thinking about smart self-service solutions in the past. Self-service and marketing wandered down two separate paths. But with the 2016 “Facebook Messenger bot platform announcement” generating excitement around chatbots on messaging platforms, marketing executives are getting into the intelligent assistance game too.