Paul AinsworthPaul AinsworthAugust 13, 2019
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18min4040

A thought leader and visionary when it comes to bleeding-edge Customer Experience technology, Chris Connolly is an interesting man to know.

A man fortunate enough to be Vice President of Product Marketing at Genesys, his genial Aussie exterior belies a knowledge of exciting CX innovation that will make your head spin. That knowledge was among the fuel that fired this summer’s Xperience19 conference in Denver, Colorado, where the latest advancements in CX and call centre products were divulged and debated.

The hugely successful gathering was also where Chris (pictured left) spoke to Customer Experience Magazine about his role at the organisation which is changing how customers interact with brands forever, and as he explains, that’s an ongoing evolution – one that will never cease as long as creativity and the ability to identify and incorporate excellence remains a central tenet of Genesys, which is sponsoring the 2019 UK Customer Experience Awards.

“I try and tell great stories about our amazing products,” is how Chris modestly describes his role, which involves keeping the company at the forefront of the technology curve as Customer Experience continues on its unstoppable rise to become the key differentiator for firms jostling to outshine others in a crowded commercial playing field.

It goes without saying that artificial intelligence (AI) plays a central role in keeping Genesys products, such as PureCloud, at this forefront, and Chris, currently based in Raleigh, North Carolina, tells us he believes that the time is right for innovation in company structures to match the growth in technological prowess.

This, as he explains, is all about establishing trust – and not just for customers.

“We have done research, and engaged in debates around the world which are focused on enterprises and how they perceive AI as affecting their customers, and their workforce,” he says.

“Through those debates, there’s a concept that’s becoming more popular in organisations – the role of Chief Trust Officer.

“They wouldn’t be in HR – they would be there to make sure data is clean; to make sure it’s not biased; and to make sure the bots are not taking the organisation down paths they don’t want to go. They could also look at human aspects, such was what happens if an employee is displaced by a piece of AI or automation, in which case they could have that trust officer on their side.”

As current AI tech has the ability to transcribe conversations in full and mine them for data to enable actions such as targeted advertising, there is, as Chris says, a concern over being able to trust the endpoint that you are talking to. 

“Some of the newer voice endpoints in your home, such as Amazon’s Alexa, or Google Home – they are listening to what you say, so do you trust Amazon to choose the brand of paper towels you put in your shopping basket?”

Speak up? Endpoints in your home, such as Amazon Echo, are listening to you

However, talk of trust and AI ethics can oftentimes overshadow the positives of the world of CX tech, and there is plenty of those to choose from.

Chris, as VP of Product Marketing, is all about that, and is excited to share details of the innovations Genesys has been working on for its wealth of global clients.

“One that comes to mind first is something we call predictive routing. There was a TV show in Australia in the 80s called Perfect Match, similar to Blind Date in the UK, which tries to pair a contestant with their ideal dating partner. Well  predictive routing is a little bit like that. What it does is look at everything we know about a customer when they call.

“So as that ringtone is ringing in your ear, we have a wealth of information about you – what you’ve done, what you’ve purchased previously, how many times have you called, how quickly you speak…that is all pulled up in real-time. Then we also know a ton of information about employees in the workforce – what training they have been on, who was the trainer that trained them, how many days off do they take a month, do they speak quickly, are they male – a ton of information!

“Predictive routing matches that customer and that employee together using machinery. And so, what I think people don’t realise is there is so much intelligence now that goes into who you speak to when you call an organisation or when you chat with them. It’s revolutionary in terms of what’s there.

Clever calling: Contact centre innovations include ‘matchmaking’ a customer to the ideal agent

“Added to that – and this is something people kind of know, but I don’t think they realise the ease in which organisations are able to do it – is understand your digital footprint on a mobile app or website.

“We can see in real-time genuinely every click that you make, where you are, what your screen is browsing. We can tell what you’re looking at with your eyeballs based on where the page is scrolling to.

“All of that information is being pulled in now to engage you better. Engage, in this sense, might be a piece of content, and that’s sort of traditional, but increasingly AI tech is being used to predict things like – should you speak to a human?Should you speak to a bot? What should the bot say? Should we rout you to another piece of content?

“The visibility and clarity surrounding your digital footprint when you turn up to someone’s dot com is amazing. I don’t think people realise that there are folks sitting in a building somewhere watching their web traffic in real-time.”

Tracked: Your digital footprint on a site can be observed in real-time

That might, of course, nudge us as wary customers back to the issue of trust, but Chris is what he describes as an “evangelist” on the idea of convenience trumping privacy for the vast majority of consumers. That’s not to say that extra protections shouldn’t be implemented to ensure responsible use of our data, hence his championing of Chief Trust Officers earlier in our conversation.

“This generation – in fact all generations almost – will happily yield their private info over if it makes things easier,” he says.

“And yes, it’s not for everyone and there will be hold-outs, but on the whole, they are giving it up. That said, this is where we need a bit of regulation, both from governments and from industry; self-regulating, for an organisation to be smart enough to know they have a responsibility not to abuse that power.”

Chris refers to the ongoing industry debate around data collection – how much “protection” does a firm like Genesys bake into their products, versus letting the buyer of the product choose it for themselves.

“We have to walk this fine line. So the steps we are taking include being very open and transparent about our AI  principals and ethics standards. We are publishing guidelines on what you should and shouldn’t do. We have debated that with industry analysts and lots of different customers, and have gravitated to a set of principles regarding transparency and responsibility.

“Another step is from a pure technology perspective: we are providing tools for anonymised data. So when data goes into our Genesys cloud, we strip it of anything sensitive and just put a number in place. Our clients still know who it represents, but we don’t, and that keeps us protected, and therefore customers protected from data breaches also.”

Thanks to his role at the coalface of creativity at Genesys, Chris is ideal to probe for tidbits of tech trickery – magic that will pilot our customer journeys as they wind ever-onwards to a future featuring myriad possibilities.

So what’s on the horizon? What’s the Genesys genius we can expect down the line, but “aren’t quite there yet” with?

“I feel like we’re so close to two things: one is what I’ll call interaction summarisation, and this is using sequence-to-sequence learning, or machine learning. This is when you provide a pattern and say ‘given this pattern, I want you to produce this pattern’. The inputs are words, so you give it text and say ‘here’s a sequence of words – I want you to reduce that to two sentences’.

“Where we are now is that we can do real-time streaming of audio into automated speech recognition and we can get the transcripts back in real-time – that’s achievable today.

“The next step is taking the conversation you are having with a bot, either by voice or by text, and summarising it to ‘this is what you’re actually talking to us about’. 

“What that then allows is for the employee to essentially do a ‘hands-off’ interaction. So the call might drop into their ear and they have a great conversation with the customer. Normally, at the end of that call they have to go ‘wrap’; they have to tag it – did you buy this or that? There’s follow-up notes to consider.

“Well with interaction summarisation, all that goes away.

“Now we have a conversation and the AI is listening to the call. It transcribes it, and the interaction summarisation says what’s going on and what’s needed as the follow-up. So the agent is basically hands-off, and that’s a very cool new way of working.

“Imagine not even needing screens, because it’s all done for you. So we are really close to that tech – that sequence-to-sequence learning or summarisation.”

The second innovation close to changing the face of customer contact forever, Chris states, is journey forecasting – tech that can replace the use of the Erlang C formula, which ‘predicts’ waiting times for callers.

“Where we are today is we have models being run to do forecasting, like workload demand forecasting, which can be applied to anything – such as how many street lamps are going to be broken in a particular city, or how many garbage bins will be intact after a storm.

“In the contact centre, it can be used to predict, for instance, how many agents you’ll need tomorrow. That’s current state, but we are on the cusp of journey forecasting, which goes beyond that one interaction. 

“Let’s look at the example of an expecting mother. In that pregnancy journey there are lots of milestones that happen – for instance, calling about health insurance. It’s not one interaction with the healthcare provider – it could be 10 over the nine months. We have the math now to forecast journeys and every business process along the way. We will also be able to forecast the impacts and the resource demand. That is so close, like within a 12 to 24 month window.

“The problem with manually mapping customer journeys is that no matter what you invent, a customer is going to do something different. So what’s happening is we can apply machine learning to do pattern recognition. It will actually have more of a profound effect on the workforce than the customer.”

With passion for his products on full display, Chris is a true advocate for the advancement of Customer – and Employee – Experience, and brands can feel safe in the knowledge that the quest for improvement with Genesys will never come to an end, no matter how many technological milestones are reached.

 

 




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