Communications in Context - Roland Selmer

The Communications Trends Defining Next-Gen Customer Engagement

Published June 26, 2017 by Glen Kunene
I recently had the opportunity to speak with Head of Platform Marketing Francisco Kattan and Head of Voice Products Roland Selmer for the debut episode of our video series Communications in Context. The conversation centered on emerging trends that are defining how savvy businesses need to engage their customers. It was a rich topic that led to insightful discussions about concepts such as contextual communications, omnichannel customer experiences, and human plus conversations. Watch the full video here or to read the full transcript, scroll below the video.

 

The Communications Trends Defining Next-Generation Customer Engagement (Full Transcript)

Glen Kunene, Editor-in-Chief at Nexmo: Hi, I’m Glen Kunene. I’m the Editor-in-Chief at Nexmo, the Vonage API platform. And the topic of our virtual discussion today is the future of customer engagement. We’ll be discussing three key communications trends that are having a major impact on how businesses interact with their customers. To provide insight into these trends, I’m joined by two experts with deep knowledge of communications. First, the author of a Nexmo blog post that inspired this discussion, Head of Platform Marketing Francisco Kattan. How are you, Francisco?

Francisco Kattan, Head of Platform Marketing at Nexmo: I’m doing well, Glen. Thank you. Happy to join.

GK: Great. Thanks for being with us. And also Director of Voice Products at Nexmo, Roland Selmer. Hi, Roland.

Roland Selmer, Head of Voice Products at Nexmo: Hey, Glen. How’s it going?

GK: It’s going well. Thanks for joining. Alright, so I think just to set the table, we should start with you, Francisco. You wrote the blog post with this same title. Can you talk about the three trends that you see shaping the future of customer engagement?

FK: Yeah. So, as I wrote in the article, we see three important trends in customer engagement. One is contextual communications. And this means that the contact between customers and companies is driven by the context in which the interaction was initiated, such as why you may be contacting the company or maybe what device you’re on.

The next trend we see is omnichannel conversations. And here the idea is that the interactions between the customer and a company become a continuous conversation, regardless of which channel is used for each interaction. So, for example, if a brand sends you a message about a package delivery and you decide to call the company back, then the contact center agent should know that you are calling about that package delivery.

And the third one that we see is what we call human plus. And here the idea is that artificial intelligence becomes more useful, and bots actually support the conversations that we have with human agents rather than replace those agents. So the combination of a live agent plus the power of artificial intelligence will make for better conversations that improve customer service and make agents more productive.

GK: That’s an interesting point you made about AI enhancing and making agents more productive rather than replacing them because I think that’s a fear that’s out there about AI becoming so advanced that human beings are no longer needed.

FK: Totally, yes. No, we think it augments the human interaction. And it makes it more relevant. It makes it more interesting and more productive and actually more natural, as well.

GK: So what’s fueling these trends as you see it? And why do you believe they’ll be so impactful because you identified three among a lot of different developments going on in communications?

FK: Yeah. So, these trends are being fueled by the need of companies to provide a better experience for customers and also, frankly, by the recent advancements in technology. Specifically, we think cloud communication platforms, artificial intelligence.

So if we look at cloud communication providers, we see that they are making faster progress. They’re innovating faster than traditional equipment vendors. And because their capabilities are now available as API building blocks rather than just packaged applications, companies are able to more rapidly innovate. And then with artificial intelligence, we think that AI is now at a point where most consumers are comfortable having conversations with computers. And so that’s fueling that trend as well.

So, these advancements, we believe, will have the most impact in B2C-type industries, especially the ones that are experiencing the most intense competition and where improving the customer experience is critical to retaining customers.

I’d say, for example, industries that are being disrupted by the digital natives, such as financial services, transportation, travel and hospitality, and retail, to start, these companies need to defend their customers from the digital natives that are disrupting them. But over time, we see every industry adopting these same trends.

GK: Thanks for that overview, Francisco. So let’s dig a little more deeply into each of the trends that you identified. And I’ll switch over to you, Roland, and ask for you to just describe in a little more detail what contextual communications are.

RS: Sure. So probably the best thing to do would be to start with kind of a formal definition of contextual communication. And so quite a long-winded one would be something like contextual communication is the bidirectional transfer of information between two parties where both parties are aware of the relational, environmental, and cultural context of the exchange. And that’s kind of a very formal definition. But if you wanted to distill that down into something, it’s really about both sides actually knowing what the conversation is about.

For instance, if you got a call from somebody, and the CLI was blocked the identity of the call was blocked, it said “unknown,” there would be no context to that information. And so you’d say, “Hello. Like, who’s talking? What do you want?” And all of those questions kind of allude to building a context around the conversation.

But if you received a phone call, for example, from somebody within your address book, say, from your friend, like John’s phoning you, you kind of know what that’s about. So there’s a bit of extra context in there, but you wouldn’t actually know what John wanted to speak to you about.

And if we kind of extrapolate that further and thinking of customer interactions, if we start making calls from within apps and people on the other side who are supporting those calls know that, for instance, somebody is calling from within an app, they know who’s calling and why they’re calling. So that’s kind of a super overview of the continuum of context within a conversation.

GK: And you sort of alluded to this towards the end of your answer, but thinking about that within the context of customer engagement, if I’m from a brand and I want to have a conversation with my customer, what does that look like just in terms of a use case or scenario?

RS: Sure. So just a little bit on that question, if we think about two forms of communication or at least the way in which they’re used, we think of comms as core. And by comms as core, I mean really the companies like Viber, WhatsApp, Skype, where, for instance, I would just call Glen or Francisco, and we’d have a general conversation just like we would on a normal telephone network. There’s not much context around that. Whereas, if, for instance, we start talking about companies that use what we call comms as a feature, we’re really talking about things like sharing economy or symmetrical marketplaces, I guess companies like Airbnb or Uber, where comms is really a feature within the application itself.

And so if I’m a driver in Uber and Glen’s a passenger and Glen is trying to get a hold of me to find out where I am and I receive a call, there’s a lot of context around that conversation already within that app, right? I’ll know that Glen is a rider. I’ll know that he’s booked. I’ll have his rough location. And we’ll be able to have an immediate conversation around the context of what we’re trying to achieve, which in this case would be ride-sharing. So I think that’s how contextual communications is gonna evolve certainly from a comms as feature point of view.

GK: Talk a little bit more about the technology that would need to be there to enable this. So we’ve talked, I think, at a pretty high level, which gives great context. What has to be there under the covers to make this work?

RS: Sure. And so if we go back to pre-internet days, I guess the main technologies that we’re all used to were normal telephone calls, right? We used to call each other on what’s commonly referred to as the PSTN, the public switched telephone network. But these new… kind of the whole app economy has brought quite a few new technologies that, for instance, we’ve been using within this call, right? And one of those technologies is a technology called WebRTC, where the RTC bit stands for real-time communication.

And these technologies are a group of protocols and codecs and technologies based predominantly around IP communications. And so you’re able to have very high-quality, very high-definition video, very high-quality audio—higher quality than the PSTN itself due to the technology involved. And these are now being rolled out for various platforms, available for various platforms mainly around iOS, Android, and on the web. So, for instance, the conversation we’re having now on this broadcast is really around WebRTC that we can use to speak to each other over great distances, obviously, over IP.

“it’s really kind of a democratization of high-quality communications that are now enabling these quite exciting use cases.”

And so these technologies have really brought down the barrier to entry to what’s traditionally, 5-10 years ago, would have been really high-end broadcast quality, really expensive communication products. So it’s really kind of a democratization of high-quality communications that are now enabling these quite exciting use cases.

GK: I want to transition to another trend that seems closely related to what you’ve been talking about, and that’s omnichannel conversations.

RS: Sure. So take a step back and think of just, like, a single-channel retail experience. People used to go earn their money and then go to the high streets and go to a shop and buy stuff and leave, right? And then as society evolved, we started having more and more channels where potentially we had multichannel environments where you could go and buy things in a brick-and-mortar store, but you could also have a web presence.

And an omnichannel is really any customer contact point that you could really think of. So it could be bricks-and-mortar, online, TV, mobile. And if you think of a customer user journey, there are now multiple—kind of omni—points of customer contact. Someone could be having a conversation with somebody on WhatsApp discussing…let’s say they’re buying a pair of jeans, talking about some jeans. They might Google it on their phone on the way to the shop. They might go to the shop and actually have a look. They might use an app from the store to maybe make a purchase decision. And they might at some point on the web wanna return those products. So we have this whole kind of omnichannel customer contact experience.

“if you think of a customer user journey, there are now multiple—kind of omni—points of customer contact.”

An example I’ve given you now for retail, but I guess it pertains to service sector type products as well. And what is really useful is technologies that allow the retailers to have a consistent view of the customer along that journey.

We’ve all experienced, for instance, when, let’s say, we’ve gone into our bank and we’ve spoken to them about our account or something like that, and then a couple of days later, we’ve called them and tried to discuss the same problem that we’re having. And we have to recreate that context again. We have to say who we are. We have to give all these weird password hints, authenticate ourselves. And that is a negative user experience having to recreate through all these omnichannels, recreate that context of who we are and what we’re trying to do.

So what would be great is if we could start to see products where, regardless of the channel that we interact with brands and service sectors, that the context is always easily replicable. And we don’t have to recreate. We don’t have to get into what we call these context recreation loops. And if we can achieve that, I think this really leads to much higher engagement, better user experience, and overall better customer engagement.

“We don’t have to get into what we call these context recreation loops.”

GK: And I know a scenario that a colleague of ours had described that really made it clear to me was the idea of a business traveler who has some rewards program, because they travel frequently, but that rewards program ties in flights, and it ties in hotel. It ties in a number of different services. And, like you said, the touch points for all those services are on the phone. They’re directly in person. And if the company that offers that rewards program could have a single view of that customer in all of those touch points and provide the appropriate context each time they go to the car rental place or whatnot, the user experience would be so much better. And I think you’re completely right about the engagement of that user.

RS: Exactly. And that’s what we try to build at Nexmo, right? We’re very focused on this whole concept of contextual communication. We’re working very hard on building contextually aware APIs right now. And the interesting thing in this, there’s kind of an anthropological reason for this, right? So whenever we interact with a brand who seems to know what we’re trying to achieve or who recognizes us, there’s what we call these kind of dopamine events that occur. So there’s actually quite a biological reason why these things are successful.

“We’re working very hard on building contextually aware APIs right now.”

GK: I think I’ve experienced the antithesis of that.

RS: It works both ways, so…

GK: All right, so the other trend, and Francisco, I’m gonna return to you, this is the final trend, was the human plus conversations. And you explained up front about what it is, but maybe just dig a little bit deeper into how maybe a human agent in that scenario can tap into an AI service and become more productive with that kind of access.

FK: Yeah. I mean, the idea with human plus, as I mentioned earlier, is that artificial intelligence can be used to augment the capabilities of human agents, not replacement. So we’re all familiar in the past with the traditional use of machines to automate highly repetitive interactions, especially within a contact center, right? So in the past, if we wanted to check our balance, our bank balance, we would have to wait in queue, then finally talk to an agent, and then, finally, find out what our balance is, after probably a lengthy conversation to figure out who I am and why I’m calling, right?

“artificial intelligence can be used to augment the capabilities of human agents”

And so, we’ve seen things like IVR in the past automate those kinds of very repetitive, mundane type of interactions. And so machines have already automated those kinds of capabilities. What we see with human plus now is the ability of machines to help not only automate more complex interactions that are maybe not repetitive in nature, that require more cognitive ability, but also help the agent solve those highly complex problems that come up occasionally in a contact center.

So let’s see. As an example, let’s say that you’re talking to an agent. And then an AI bot is magically listening into the conversation. And you get to the point where the agent doesn’t have an answer or doesn’t have all the context for the conversation or for the question that the caller is asking about. And you can imagine the AI bot quickly doing a query behind the scene and then popping up information on the agent’s screen so that the agent can guide the user through the answer to his or her problems, right? And this will all be done without the user really realizing that there was an AI bot behind the scenes helping this agent.

Another example that you might imagine in a contact center is sentiment analysis. So imagine again this AI bot magically listening to a conversation where I as a customer may be calling my bank, and, for whatever reason, I’m upset about what happened, trying to get a fee overwritten or something like that. I’m getting upset. Then the AI bot behind the scenes can detect the fact that I’m upset and automatically notify a supervisor. A supervisor can then quietly be conferenced into the call and then, behind the scenes, help the agent so that the agent in the end provides a good experience for the consumer.

So the bot is working behind the scenes, just analyzing what’s going on with the call, and, if necessary, taking action, whether it’s providing information on a screen or conferencing in someone else, maybe even taking notes or transcribing a call for future analysis.

“the bot is working behind the scenes, just analyzing what’s going on with the call, and, if necessary, taking action”

GK: I’m asking for these use cases and scenarios. And they all sound great. But it’s also, I think, worth pointing out, and, Roland, maybe you can say a little more about this, that in an API economy, really the brand or the business is armed with the API calls to deliver these different kinds of communications messages, but they can build anything they can think of on top of that.

RS: It’s a strategy that we’ve taken at Nexmo, right? So, for instance, when we launched our WebSocket endpoints for a voice API, it really allowed us to…well, and our customers as well…to leverage all the best in class AI products out there, things like IBM Watson, which we did a great integration with the Intu project. And I think as long as you get access, voice is such a natural interface. It’s probably, obviously, the most natural way that human beings connect with each other.

So just alluding to the stuff Francisco is saying, there’s countless use cases where we could leverage, or our customers could leverage, best-in-class AI engines. And as neural networks and as AI technology progresses, I think we’re gonna see some really great things, like real-time translations. So you’ll be able to do… phone any store in the world, regardless of what language they speak.

“as neural networks and as AI technology progresses, I think we’re gonna see some really great things”

In fact, Vonage has a kind of proof of concept application that does that already, where it’s almost like a real-time Babel type product where you could speak to people in different languages. And you get in the background, like, a third person saying the translation. I think it really opens up the scope for, as we mentioned earlier, augmenting existing human interactions. It really allows small organizations to scale very large.

As Francisco talked about earlier, you won’t even know when the transition has happened between, say, an AI chat bot, where you’re asking about certain products. And it becomes a point where it transitions to a human operator, which will really help to triage and scale their…in the case of like, say, a support infrastructure, really scale beyond what traditionally they would be able to offer from just pure human basis, so really exciting stuff.

GK: So what I’d like to close with is let’s say I manage a product that makes contact with our customers or the head of digital experience at Company XYZ. And these trends sound like something I really need to leverage for my own products in reaching out to my own customers. So I’d just like to get from either one of you, whoever wants to start first, what are the considerations from a business aspect that decision-makers on the business side need to think about if they want to harness these trends?

RS: I’ll jump in. So I’ll start with what I’ve just said in terms of if I have, for instance, a scaling-type issue, what technologies can exist where I don’t just have to add more agents and, therefore, increase my cost base? I think there are really intelligent things we can do now on the cognitive computing side of things. And I would just say really focus on how I can delight my customers by the examples that we gave earlier, maintaining context between the interactions at the various touch points between my brand and my consumers. I think those kind of problems are really addressable now with the kind of technologies that we’ve been speaking about. And, ultimately, that’s really gonna lead to high customer engagement and higher customer satisfaction.

“I think there are really intelligent things we can do now on the cognitive computing side of things. And I would just say really focus on how I can delight my customers”

So cognitive commerce is a really big topic to look at now. Contextual communication is another, obviously, one we’re mainly focusing on in this call. I think those two areas certainly would be something people should be looking at.

FK: I’d like to add a couple of comments to that, Glen. So I would say in terms of advice for especially the large enterprises that feel like they’re under threat by new digital natives, the digital natives have the advantage that they’re starting from scratch. And they don’t have much of anything in terms of legacy. So they have all built their customer engagement platforms all based on API building blocks.

So the advice for the larger enterprises is to start experimenting with API building blocks and start small. So every company already has interaction with a number of channels, primarily voice and probably email. So start with one new channel. And the next channel that you add, maybe it’s a social interface to WeChat or to Facebook Messenger or to LINE. Rather than deploy a packaged application, as you may have done in the past, experiment with building blocks, API building blocks, for that one interaction channel.

“the advice for the larger enterprises is to start experimenting with API building blocks and start small.”

And as you gain more experience, you can then, over time, begin to innovate around the existing layers of channels, whether it be IVR or the customer service desktop as well, so that you can then integrate all the interactions in an omnichannel way so that you can retain context across all the conversations in a way that’s supported with AI bots. But don’t try to solve the entire problem all at once. I would say start small and then expand from there.

GK: Okay, thank you, Francisco and Roland, for a great discussion. Francisco Kattan is, again, head of platform marketing at Nexmo. And Roland is director of voice products at Nexmo. If you’d like to find out more about all of the innovation that’s happening in the communications space, you can always read more at the Nexmo blog. That’s nexmo.com/blog. And we’ll see you next time. Thank you.

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