Dan Jenkins is the founder of Nimble Ape Ltd, based in the UK. Nimble Ape is just over two years old and concentrates on building solutions around real-time communication for our clients. Dan's known for working with Node.js and real time communications such as WebRTC. As a Google Developer Expert in Web Technologies, he's seen as an expert in WebRTC. You'll see him speaking at numerous conferences throughout the year talking about building scalable web applications, WebRTC and of course Asterisk.
Could you summarize for our readers your profile and your role in the Asterisk community?
I'm the founder of Nimble Ape. Before Nimble Ape, I was a software engineer, building scalable APIs and integrations into Asterisk; this is where I really joined the Asterisk community. I'm a web developer, not a telecommunications engineer - this benefits and disadvantages in varying situations! In 2014 I was part of the team who built the Respoke Platform (Digium's Web Communications Platform). I've also spoken at the last 4 Astricon Conferences.
Mr. Jenkins, what’s your view on the future of the Asterisk call-center industry in the next two years?
I think we're going to see a major shift in how contact centres operate; notice I said contact centres and not call centres. Call Centres have changed dramatically and no longer just deal with inbound and outbound calling. They deal with many other forms of communication and I'd expect this to grow as customers figure out that they want new ways of being informed and helped through problems or even sales. WebRTC is going to be a big part of this for numerous reasons; from being able to offer a online CRM system with calling built in, to being able to connect with your customer in a different way with a different experience. Because of the use of WebRTC, we're going to see more uses of online APIs such as speech to text, sentiment analysis and emotional analysis - for analysing your customer and what they want, but also from an internal contact centre point of view; are my agents giving the right experience to my customers? What does this mean for Asterisk? That's to be decided. We've seen Asterisk become a media-engine in the past couple of years which means we're able to use it for it's awesome core and build applications around it. We'll definitely see more people building applications around Asterisk.
What kind of benefits do you think professionals experience with call-center monitoring suites like QueueMetrics?
QueueMetrics gives an insight into your contact centre that is actually very difficult to get elsewhere, but in a changing world where we don't use Asterisk's built in queueing mechanisms, and we build applications around Asterisk, we'll need to start building integrations into QueueMetrics too, to be able to carry on utilising all of that stored information. This can be done today and mustn't be forgotten.
What are the key factors which make a successful Asterisk based call-centre?
Reliability and reporting; for both your customers and your business. Whatever your business does, you have customers and you need them to be able to get through to you, or for you to get through to them. If you don't have that reliability then you've got an issue. On the other side of the coin, your business needs to have faith in Asterisk and the fact it is Open Source. If you don't have reliability then people lose faith. I was in a scenario around 5 or 6 years ago where our migration to Asterisk didn't go smoothly and we were having reliability issues with Asterisk - this was the key concern with the system and we were close to losing all faith with Asterisk at one point.
What are your thoughts about the strategic role of call-center analytics?
Analytics in the Contact Centre are your most vital part of operation; there's no point in having agents on the phones if you've got them doing the wrong things, and half of your customers are getting angry with you because you weren't able to see the data and act on it. However, the data you have access to grows every single year. With new forms of communication such as live chat, where you have the written word in-front of you, you're now able to analyse that written word and get more information from it - not just "When do all our live chats come in". We can now answer, "What mood were our customers in when they started chatting us" and "What was the underlying chat about specifically". As we grow the technologies our contact centres use, the information we have access to grows as well. As soon as you move away from a phone number and start integrating calling into your apps or websites using WebRTC, we can access even more information and get an even better picture of our customers. Analysis of data is only going to grow in complexity and I hope that tools such as QueueMetrics are able to keep up with it.