The greatest challenge in implementing AI is cultural change

Interview with the VP Customer Experience Transformation of Liberty Global about changing customer expectations and the role of AI in today's CX landscape.

Rhona Bradshaw is the VP Customer Experience Transformation for the consumer organisation at Liberty Global and is responsible for designing and enabling the future customer experience.

Prior to her role at Liberty Global, she was Director of Digital at Virgin Media, where she was responsible for the digital agenda within the business. Before joining Virgin Media, Bradshaw was the Head of Brand, Marketing, Digital and Communications at UPC Ireland, the Irish business of Virgin Media’s parent company Liberty Global.

In this interview for CX Network, Bradshaw discusses the real impact of artificial intelligence on CX today, the rise of customer expectations, and finding the right balance between automation and the human touch.

Zarina de Ruiter (ZDR): Thanks for joining us at CX Network today. With the continued rise in customer expectations, how do you ensure that at Liberty Global you keep up with the changing customer demands?

Rhona Bradshaw (RB): We’re trying to make sure that everything that we do is very much a customer-centric organised way of thinking. We tend to spend a lot of time obviously at conferences. We also spend a lot of time reading a whitepapers that are published around trends in the business, trends in the industry, what customers are enjoying or not enjoying.

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On top of that, we spend a lot of time listening to our call centre agents, listening to the surveys that we take; the satisfaction surveys, NPS surveys. We do a lot of research as we define new products and as we are evolving some of our marketing campaigns we spend a lot of time talking to customers as well.

It’s definitely a mixture of all of those things. We recognise that the pace at which customers’ behaviour is changing is rapid at this point in time. It used to be the case five or six years ago that there would be clear moments across the year or, indeed, in the life cycle of a customer where change would happen and it would usually be spurred on by technology enhancements or a new product being developed.

Whereas now it’s very fluid; it’s very experience orientated. It tends to change quite quickly as you start to see customers engage with new brands and new types of experiences, as they start to leverage technology much greater. Customers are definitely leading the way much more, so we’re trying to stay as close to it as possible.

“The pace at which customers’ behaviour is changing is rapid at this point in time.”

ZDR: You hit it on the head when you said it’s about continuously talking to the customer as well and not just assuming, which still happens quite a lot.

RB: People understand a lot about what it is that’s driving the changes that they’re seeing from a customer perspective, and we probably don’t give ourselves enough credit for that, given that we are all industry specialists; we’ve been marketing and delivering experiences to these people for quite some time. We ourselves are quite capable of reading the market and reading what they are trying to enable from the products, in terms of what they’re buying.

The reality though is that it’s sometimes the nuances or the more implicit requirements that customers have that we don’t tend to be as close to, and that’s where the conversations are super important.

It’s where you start to realise that general demographic data or even life stage data will give you one sense of the story but it’s only in speaking to the individuals where you actually start to realise the colour that starts to form.

We can be quite generic in thinking about millennials or the older demographic and put them in a box but sometimes it’s the elements around the edges that really give you the flavour of what really makes them tick.

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ZDR: You mentioned the pace of change when it comes to technology and there’s a huge amount of talk within the industry around artificial intelligence (AI) and automation to help meet customer demands and expectations. But I haven’t really seen much of a result yet.  At this stage what do you think are the realistic opportunities for these technological advancements within CX to really drive through improvements?

RB: You haven’t seen a huge amount of impact from AI, predominantly because we still tend to think of AI as being quite futuristic and being quite disruptive and we’re still trying to grapple with how we can genuinely embed AI and the different levels of AI into a more operational context.





Where we’re starting to see impact from it, is when we start to think of it as being a part of our web chat experiences or where we start to see how we can move customers into more self-service orientated experiences. The AI world is starting to be more behind the scenes than it is necessarily something that we are upfront and explicitly calling out to the customer.

We’re spending a lot of time thinking about it from a back office perspective – how we automate it, making it much more dynamic, much more real time – so that when customers do want to interact from us from a self-service perspective or automated perspective, they don’t feel the lag or the interruption in their experience because essentially it’s only the front end that’s created to be self-server orientated and then the back office is still being managed quite manually, or traditionally.

We’re spending time focussing on it from that perspective as well as considering it from a chat point of view. For example, how do we enable a more real time, 24/7 chat experience that customers want more and more every day without the expense of overheads, of having actually real time agents sat waiting for the conversations to come through?

We’re leveraging some chat bot technology to try and determine how we can create the initial experience to be much more automated, much more bot orientated and then hand over to human interfaces when the time is needed.

We’re trying to think very much from an operational standpoint – the role AI can play in enhancing that operational perspective rather than necessarily thinking about how AI and bots and machine learning can take over completely and be disruptive from an experience point of view. It’s because the educases are so different and out there, that actually we haven’t necessarily seen a huge amount of impact from it yet.

As the AI vendors and partners start to recognise the need to make it much more practical, pragmatic and tangible, we’ll start to see a lot more of its benefits come through.

“We’re still trying to grapple with how we can genuinely embed AI and the different levels of AI into a more operational context.”

 
ZDR: One of the challenges that we come across is how to find that balance between automation and the human touch, and you mentioned how the initial experience should be more bot oriented and handed over to humans when needed.  Is there any other advice you can add here?

RB: We have to understand the customer, to understand the level of automation versus human interaction that’s required. And as a business we’ve got to understand the complexity of some of our processes and services, which drive the need for some of those human interfaces and therefore reduce the ability for us to be able to drive more automation.

It’s two sides of the same coin. It’s understanding that there are certain things that customers will do quite easily without a human and are quite open to interacting with some sort of artificial intelligence, to get to the end of that journey.

Then there are certain things that humans – due to either the complexity of the issue or indeed the importance or the value of the issue – would just prefer to have conversations with humans.

By understanding that, a business can really start to determine the cost of enabling those types of interactions and whether or not there is a need for the business to think somewhat differently about when they choose to present something that’s quite artificially automated, or whether they choose to actually put a human into it.

By understanding the customer, the business can start to really figure out where it makes sense and where it doesn’t.

“We have to understand the customer, to understand the level of automation versus human interaction that’s required.”

ZDR: Absolutely, there isn’t a one size fits all because each business has a very different requirement when it comes to the challenges the customer might face. They have to take it on a one-to-one basis; what works for that particular business, what can they do with humans, what can they do with bots?

RB: Yes, that’s fair. The behaviours that we as businesses and brands experience with our customers are in some ways learned, so we have taught them to behave in that way when interacting with us, and some of it is nature and that’s how the customer would prefer to interact.  It’s about trying to understand at what point businesses can encourage consumers to choose a different path, and behave in a different way, and AI can play a great role in that respect.

It’s just inevitable that human interaction is going to be a better interaction and if we can figure out the differences where we can learn from other groups and other brands and vendors that can be applied to our world and our challenges, then great. If we can also understand where we are different and where we are allowed to have a different type of experience, then that’s also beneficial and benefits both the business and the customer at the end of the day.

ZDR: From your experience, what are the biggest challenges when it comes to implementing automation or artificial?

RB: The greatest challenge in implementing artificial intelligence or any kind of major change is mindset and cultural change. As with customers, we have grown as a business and have become used to doing things as a business, because of the journey that we’ve gone on and the way in which we set ourselves up.

Automation and AI really requires the business to think quite differently about how it approached its problems in the past, how it solved those problems now, and whether or not there’s a different way of achieving the same results. If you as a business aren’t prepared to challenge your thinking and really disrupt the status quo, then implementing successfully any kind of technology that requires you to give over more autonomy to that technology becomes much harder.

For me, the biggest challenge is the mindset that’s driven both culturally from a business perspective in terms of the opportunity that the business sees this kind of technology to bring, but also the min-set of recognising that you may not have all the answers but the long-term benefit will outweigh the short-term challenges that present themselves.

I don’t think we’ve overcome it yet, but we are becoming more aware of the importance that artificial intelligence and technology as a whole has to play on the long-term future growth of the business that we’re involved in.

I believe because there’s a clear recognition of the importance of it and the philosophical nature in terms of our future strategy, which in itself is starting to unlock some broader and more open conversations than maybe we’ve been having in the past.

We’re able to kick-start proof of concepts and conversations around how we can solve something in a different way, and really start to see how we begin to infiltrate the kind of business DNA much more than we have done in the past with other new technologies or new ways of operating.

“The greatest challenge in implementing artificial intelligence or any kind of major change is mindset and cultural change.”

ZDR: What has been your greatest AI success story to date at Liberty Global?

RB: We’ve carried out a couple of proof of concepts where we’ve essentially built a bot that can interact with the Google Home, Alexa and other digital assistants, and the customer account section of the website and the app. We’ve been able to illustrate how customers could ask Alexa what their bill is and pay their bill and what they spend in terms of their telephone usage and on demand data usage.

I’m most proud of the way in which it’s been done because it’s been done very iteratively, very agile, very much with a very open mindset in terms of what the outcome could be, and very collaborative in the way in which we’ve done it with the groups involved.

We’ve definitely started to illustrate that there is a way of leveraging these tools to be very business beneficial. I’m most proud of the fact that we did it in a way that allowed us to put into practice all of the things that we talk about strategically and the importance of a digital mindset and being disruptive and challenging positively.

It’s been great to see that come through and in the next stage, we can start to really industrialise it.