The CX Puzzle: Solving One Piece at a Time Part 2

You can't escape in CX. You can fluff all you want. At the end of the day, the customer's either happy or not. There's no way to fluff it.

Welcome back to Simply CX, where we bring you customer voices and expert insights. I'm Nicole McKinley, Leader of Global Customer Experience at Microsoft. If you listened to part one, you heard Chris Lipman share how e& is embedding customer experience into every corner of the business, from using NPS as a universal metric to making CX a company-wide responsibility. We wrapped up with a powerful story about their Beyond the Desk initiative, where C-suite leaders spend a day in the call center talking directly with customers. It's all about staying connected to the real customer experience. Today, in part two, we pick up right there with Chris reflecting on what he learned from taking calls himself and how that sparked real change. We'll also dive into the role of AI in CX, the risks of voice bots, and the puzzle of keeping up with ever-rising customer expectations. Let's jump back in.

Chris, we were talking about Beyond the Desk. It's such a powerful example of not only living in the shoes of your customers and experiencing firsthand what they're going through, but also your employees, right? And seeing the day in and day out, lived experience, and then the fact that you had executives taking action as a result of that and driving positive change is even more amazing.

I couldn't have said it better myself. It's a really key point you've said there because if there ever is an escalated complaint or something and it's because the call center agent made an error, it's like he made a mistake. That's it. What are you doing about it? Well, we've coached him, and hopefully, he doesn't make the same mistake again. That's it.

Or, oh, by the way, he had 20 different systems that he had to toggle between.

Exactly. Exactly. And the guy's only been taking calls for two months. There's no need to respond that way. And I think that when they see the complexity and the breadth of knowledge that these agents have to have and they need to answer and customers are impatient and they want the answer now, it's such a valuable exercise for a range of things. It's really invaluable.

I love it. So did you do it?

So I did it on a trial run before the actual C-suite got there to make sure it went okay. So I went through the training, and I did it. And on the first time I did it, I actually got a perfect NPS score from one customer who loved me, which was great.

Very nice. Congrats.

Yeah, I was super happy. Second time I did it also with the rest of the team as well. And so the CEO is committed to do this every six months with the whole team just to make sure we stay in touch with the reality of what our customers are experiencing and seeing. And one of the reasons that this division was created is that they were seeing scores, but when you go to social events or functions and the level of complaint and angst that was coming from customers did not match the scores that they were being shown. And so there was some credibility, well, is this really real? And so this is something that will definitely be ongoing.

Yeah. Making it real is super powerful.

You can't escape in CX. You can fluff all you want. At the end of the day, the customer's either happy or not. There's no way to fluff it.

So what was your biggest takeaway from your actual managing and taking of calls? Was there any one thing that jumped out for you?

There was one particular product issue, which I identified from the call because I actually got two calls of the same type, right? You've got to think those calls are distributed randomly. It's just first in, best dressed. So to get two calls of the same type made me very suspicious. And so I started drilling into it. And it's actually exposed a bigger problem, which we were unaware of. And we were unaware of it because most of the fixes for this occur at automated or at IVR level, which means they don't flow through to agents, but actually quite a significant problem. And so I can't detail it because it's still in flight, but it exposed that particular issue.

Yeah.

Great. So now you're fixing product as well.

Fixing everything.

Fixing the world, one call at a time.

Oh, new tagline. I love that. So looking ahead, you touched very briefly on AI. And obviously, AI is here to help us all fix the world as well. How are you and using AI? And what does the future hold for how you're envisioning AI will help you in transforming customer experience further?

It's a hot topic right now. I mean, isn't it? Everybody's talking about AI. And some of it is on the Gartner hype curve, most definitely. But some of it is very real. It's certainly a far more advanced product than it was 18 months ago to two years ago. It's a completely different league, which is why people are so excited about it. But I think for me, it is the customer acceptance of that AI, if it's going to be front-facing customers, is really key and critical. And most organizations that I've interacted with, including pretty much all of the big ones, are not focused on this at all. For me, it's a massive blind spot because we know from bitter experience, and this one I can detail, is that if the customer doesn't like the tech, they won't use it. If you force them to use it, they'll give you horrendous NPS calls and make it very clear that they're not happy with your organization, which opens up for competition to do something different. And so We had this product on entering the contact center called the Virtual Assistant, which was a voice-operated bot. A lot of the US banks do this in the IVR. I personally find them very annoying when I hit one of those because they don't understand me half the time. But what we found was the technology was fine. The technology was A-OK. The technology was working as intended and giving the correct answer 85% of the time. Customers were giving this minus 50 NPS. Now, minus 50, you've got nowhere to go. There's nothing to build on. It's not tweaking. You need to reconsider the whole--

Reset.

You need to stop and reconsider and stop. And so what we saw is that between the virtual assistant and old-school IVR, there's a 70-point NPS difference. So the decision is a no-brainer. Just kill the virtual assistant, go back to old-school IVR, and customers are 70 points happier at that point of their journey. And so for me, this is a parable in terms of AI, because the other thing customers don't like is they don't like dealing with voice bots at all. And we see this very clearly. They just don't like it. Now, in text, it's a different because, sorry, one part I left out, in that automated system, that same bot in text format gives very decent NPS scores. And the only differentiator is the customer doesn't know that they're dealing with a bot because it's exactly the same engine, exactly the same software, giving exactly the same answers, but there's a massive difference between text and voice. The danger with AI, if it's front-facing, is the customer acceptance of that. And the customers are very jaded against voice bots because of the really, really poor experience of the last 5 to 10 years of trying to make this work where it's really very poor.

It's way better now, but there's instant customer dislike. Instant. That's for front-facing. And we're developing products and bots to be able to do this with the key metric being MPS, with the customer acceptance is a key metric. For non-customer facing, it really helps us like if there's a network issue and certainly in our fixed network or in a mobile network, there's so many parameters and AI is really the only way to drill this right down or give us the ability to tailor a network solution for a specific customer proactively without the customer asking. For example, we haven't done this yet, but if you're roaming overseas, you're using another carrier network, not ours. We just signed a commercial deal with these guys. The ability to determine that you're having a negative experience and change your networks without you asking so that you get a better one without you even knowing is something that is reliant on AI to do, to recognize this and actually trigger it and do it. There's more primitive ways of doing it, but they're not that effective, to be honest, so this is much better. Or recognize that you're moving into an area where, traditionally, customers are not happy and proactively do it as you're moving into that area as an example.

So there's lots of different ways, the ability to anticipate what a customer's NPS score is. And to be honest, we've done some of this without AI, but with AI, it should get even better. So we can, within a reasonable degree of accuracy, predict what a customer's NPS score will be before they tell us. So this is critical, that with AI, we'll get even better, and it will allow us to trigger things where we know you're not happy before you tell us you're not happy, and we know the reason why with AI, within a very good range of accuracy, and so we can affect things. We can send you a message, communication, because customers sometimes have a VPN on, for example, and they're getting a horrible network experience. Not our fault. You need to switch your VPN off. So we can do that, all the way through to adjusting your network or moving you to different routes so you get a better experience or understanding what customers use the most to cache content locally. It's really near infinite, the number of cases that we can come up with to impact the customer's experience in a positive light using AI.

Super helpful. So AI is a key enabler, not a replacement for the human personal interaction. Also, AI for predictive and proactive? Is that kind of the key areas of focus that you have?

Predictive and proactive, definitely. I think there are some use cases where, if you get it right, you can actually replace the human agent in some cases. There's use cases which are pretty simple and pretty basic. A human does not really add much value to those things, but you can get the message across to the customer. You give them the answer that they want and deliver a good experience. There is some case for that. So I think it's, from that all the way through to predictive and proactive experience and service and everything in between is very exciting.

Exciting space, exciting opportunities. And the key that you're really touching on is ensuring that, as you're introducing AI, as you're identifying those new opportunities, you're keeping the customer at the center--

Have to.

--of the experience you're designing, right? And ensuring that the customer's expectations are being achieved or exceeded in whatever AI capability you implement.

Absolutely, and I can tell you, all the projects we're doing, and we're out to market for a couple of more, the key metric is the before-and-after NPS because just delivering the technology is of little value if customers aren't happy using it, and it falls right into the example that I gave: the technology works fine, customers don't want to use it, it's got very little value to us. And so this is where customer centricity is key and core to our mission. And certainly, with AI, it just has to be because the technology without the experience is useless; it's of no value.

Super valuable perspective. Thank you, Chris. As you look ahead, and I know, again, you're a fan of puzzles, what's the big puzzle that you're focused on solving for END?

As we improve customer experience and we've come a long way, the good thing and the frustrating thing about CX is, as you move customers' expectations, customers' expectations continue to go up. And so if you've hit a nice place and you just plateau and don't do anything, you will eventually start to go down, just doing the same things. What was exciting [inaudible] and wow, suddenly becomes an expectation, and now you need to do more and more. And so for me, it's understanding that-- because in some of our products, we're really at that point where we're getting very decent scores. Customers are clearly very happy, [inaudible] rates are down. Spending for happy customers is up. And this is clear. It's about how do we continue to maintain that trajectory? How do we keep evolving in that? So this is the key puzzle. But this is not every product, and it's not necessarily consistent. And so, for the products that lag, there's still a lot of puzzles in trying to work out the why. We see some negative scores, and we've done some things, and some things work, and some things don't, which means we still have not cracked that puzzle. So for me, this is really critical, and bringing the organization along and keeping the organization engaged with this.

I know we already touched on AI, but that's the bit that keeps me awake at night. It's that translatability of AI into something that humans will accept, and in what format they will accept. And you can do really cool things. I mean, we showed at last year's [inaudible] conference, a holographic agent which is going to go live, which we'll use in stores. And it's really cool. Will customers actually engage with it? I don't know. We think so. And we're building it that way, but we don't know. And so the sad thing is, you can go to all the effort and have all the good intentions on the planet, but if a customer doesn't like it, they don't like it at the end of the day. And I guess it's that degree, right?

And that's what keeps me awake at night with AI, as there's a lot of pressure to move towards both customer-facing and non-customer-facing. The customer-facing part is probably the bit that keeps me awake at night at most. Getting an interface which customers will actually accept and actually transact with and be happy doing so. Now, if we can crack that puzzle, you're effectively turning an analog channel into a digital channel. It really changes the entire paradigm from a service point of view, but also from an experiential point of view, shifting it as well.

One final bit on this topic, for all the various gaps and puzzles where we know what the problem is, it's where can we actually apply AI? Is there an AI solution that will fill this gap? Whereas traditionally, we would do something manually, or we would work it out algorithmically, but it's something which is very difficult to do on a real-time basis. The advancements that it can actually bring to improve overall customer experience beyond the service component, but into the experiential component, and actually tell us proactively why the customer is potentially not happy. This is the biggest puzzle of all, the biggest puzzle of my career, actually.

Well, it's exciting times, and I think you said it well. AI has the opportunity to help you better understand your current puzzles. It has the opportunity to solve really complex puzzles and then really transform how we deliver experience to customers. So it's exciting, and I'm super confident with your leadership and all of the innovation and work you've done to create a customer-centered company that you'll be successful. So again, thank you so much.

Thank you so much, Nicole. And thank you for the opportunity to speak on this platform. It was very engaging. And as you can say, I love geeking out and talking on this topic. I can talk for another hour.

I know, me too. [music]

Thank you for listening to SimplyCX. I'm Nicole McKinley. Our show is produced by Larj Media. That's L-A-R-J Media. Special thanks to Luya Polka and Elizabeth Machado. To find out more about today's guest, check out the links in the show notes. If you have your own challenges or questions about CX, email us at SimplyCX@microsoft.com. And please share today's episode with someone you think could learn from it and follow me on LinkedIn to keep the conversation going. [music]

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