2857: Twilio - Putting AI at the Heart of Customer Engagement

[00:00:00] Have you ever pondered the pivotal role that AI plays in transforming customer engagement

[00:00:07] and also driving personalization to new heights?

[00:00:11] Well, in today's episode we're going to dive into the intriguing intersection of AI technology

[00:00:18] and customer interaction strategies.

[00:00:20] And I've got a great guest joining me today.

[00:00:22] Her name is Sam Richardson.

[00:00:24] She's a seasoned customer engagement consultant at Twilio and Sam brings more than two decades

[00:00:31] of expertise in enhancing customer engagement for some of the world's leading brands.

[00:00:36] And with a deep dive into the recent research revealing that only a third of UK organizations

[00:00:42] are prioritizing customer engagement in their AI strategies, I want to uncover the barriers,

[00:00:48] opportunities and transformative potential that AI holds in redefining how businesses can

[00:00:54] connect with their customers.

[00:00:56] I also want to explore Twilio's recent findings that highlight a crucial gap in aligning AI

[00:01:02] initiatives with customer-centric outcomes.

[00:01:05] And yes, there is a fair amount of skepticism and financial pressures out there that are

[00:01:10] increasingly being cited as significant barriers to ALA adoption.

[00:01:14] So I want to find out how organizations can move beyond those challenges to harness AI's

[00:01:19] full potential.

[00:01:20] But I've revealed far too many spoilers already, haven't I?

[00:01:24] So I'm really looking forward to getting Sam on the podcast today.

[00:01:28] But before we get today's guest on it's time for a quick shout out to the sponsors

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[00:02:24] So once again, kiteworks.com and now let's get today's guest on.

[00:02:29] So buckle up and hold on tight as I beam your ears all the way to Newcastle where

[00:02:34] Sam is waiting to join us today.

[00:02:38] So a massive warm welcome to the show.

[00:02:40] Sam, can you tell everyone listening a little about who you are and what you do?

[00:02:45] Yeah, sure.

[00:02:46] Thanks for having me Neil.

[00:02:47] So my name's Sam Richardson and I'm director of exec engagement over at Twilio.

[00:02:52] Before I come onto what Twilio is and who they are, I've had probably about well

[00:02:57] too many decades to count working in technology transformation for customer experience.

[00:03:04] So I've seen all sorts of different changes in those two plus decades that I'm sure we'll

[00:03:10] touch on.

[00:03:12] Over at Twilio, as a leader exec engagement programs across Amir and APJ.

[00:03:16] And what that means really is that I do a lot in terms of thought leadership and

[00:03:21] engaging with senior people in our most important customer organizations to help them think

[00:03:27] about nominally what next.

[00:03:30] So it's a great role and I thoroughly enjoy it, especially working for a company like Twilio

[00:03:37] who really defined the category for CPASS.

[00:03:40] And now we bring together kind of the best in class communications with best in class

[00:03:44] data through our CDP and really bringing those two entities together to drive the

[00:03:52] future of customer engagement, very day to driven customer engagement kind of that's

[00:03:57] what we believe the future will be.

[00:04:00] And AI layer over the top of that.

[00:04:02] And I'm sure that's not the only time we'll say those two letters today.

[00:04:07] Yeah, and I'm so glad you did say that.

[00:04:09] I mean, it's great to have you on the podcast today and Twilio will be a household

[00:04:14] name. There's so many people listening.

[00:04:16] And I love the word you use there as well.

[00:04:17] You said you help people or help organizations discover what's next.

[00:04:21] And for most business leaders, AI is not only what's here, but it's also what's

[00:04:26] next and what will be next for the foreseeable future.

[00:04:29] But I think since it exploded, what just 18 months ago, the world seemed to go nuts

[00:04:34] almost overnight on Gen AI.

[00:04:37] A lot of businesses have sat on the sidelines wondering what they're going to do next.

[00:04:41] Some say we don't want nothing to do with this.

[00:04:43] Well outright ban it.

[00:04:44] We don't want our company data being on there than the API's came out.

[00:04:48] And you must have observed so much skepticism, financial pressures and

[00:04:53] indeed infrastructure limitations as major barriers to AI adoption.

[00:04:58] So I've got to ask from your perspective, what are the most effective

[00:05:02] strategies organizations can employ to overcome these challenges and maybe

[00:05:06] start fully harnessing the potential of AI for customer engagement?

[00:05:10] Because I don't think they could just bury their heads in the sand

[00:05:14] and hopefully goes away.

[00:05:15] And it's just another fact.

[00:05:16] It's here to stay, isn't it?

[00:05:18] It is here to stay.

[00:05:19] And I think that that would have been like denying that the internet

[00:05:23] was ever going to be a thing.

[00:05:24] You know, it's for me is that that equivalence in terms of transformation and change.

[00:05:30] I think that with organizations, you're right, skepticism is a really interesting

[00:05:36] word because I still think an enormous amount of people still are skeptical.

[00:05:41] They're thinking, is this the metaverse?

[00:05:43] Because remember, we were talking about metaverse a lot, which is not.

[00:05:46] And also part of the metaverse because I think it will come back.

[00:05:49] But I think organizations really have to start inside first and really start

[00:05:56] with that education literacy.

[00:05:58] I mean, even in our own family, right?

[00:06:00] I look at me who is, I would definitely say I'm an AI optimist.

[00:06:04] Look at my sister who's terrified of it.

[00:06:06] And that's just in one tiny little microcosm of our family.

[00:06:10] So I think that organizations really have to start with that AI literacy.

[00:06:15] They should be prioritizing it to employees, helping them understand

[00:06:19] how it can help their everyday work.

[00:06:21] Even in terms of rolling it out, you know, think about your employees first,

[00:06:25] especially those that our customer facing.

[00:06:27] Think about those first.

[00:06:28] Think about how it can help them build up that trust and transparency

[00:06:32] and that literacy as you go.

[00:06:35] I think that once you've once you start to do that,

[00:06:39] once people are more involved with it, then you can start to be really clear

[00:06:43] on what the value is, not necessarily the ROI.

[00:06:47] Because again, I think we get tripped up with that quite a bit in technology.

[00:06:51] And this is especially I think we have to think about being really clear

[00:06:54] on what the value is to employees as well as to customers.

[00:06:59] And I think you mentioned infrastructure as well.

[00:07:01] And I think that infrastructure is a huge blocker.

[00:07:04] So once you've taken care of for me, once you've taken care of

[00:07:07] that kind of education piece and really need to get a look at that infrastructure,

[00:07:12] it's interesting at Twilio because we tend to meet, you know,

[00:07:15] we have all 300,000 plus customers from all shapes and sizes,

[00:07:19] from one man to one man startups right the way through to enormous global organisations.

[00:07:26] The thing that they tend to have in common is that they're really

[00:07:32] diligent and thorough about the tech stack and modernising the tech stack.

[00:07:36] Those organisations we meet who tend to be slow to adoption.

[00:07:39] A lot of it is because their tech infrastructure is legacy.

[00:07:43] It's heavy. It's out of date.

[00:07:45] They kind of have a rip and replace mentality.

[00:07:48] They're kind of stuck by it.

[00:07:50] So I think the next place is really to have a look at that tech infrastructure.

[00:07:54] And then third, it's got to be the data

[00:07:56] because that data architecture is going to be absolutely critical.

[00:08:00] And you could be the most optimistic organisation in the world.

[00:08:04] But I think unless you've got your data, really unless you're on top

[00:08:08] of really making it clean, architecting it well,

[00:08:12] then you're probably going to hit some limitations

[00:08:15] in terms of what you can achieve with any initiative that you've got.

[00:08:20] And that will only then compound that skepticism

[00:08:23] with your employees that you had before.

[00:08:25] Again, I've been I've been lucky enough or unlucky in some cases

[00:08:31] to be involved in an awful lot of tech rollouts.

[00:08:33] And where I've seen it really not land and really not be adopted

[00:08:37] and fulfil its potential is when the employees have lost faith

[00:08:42] in what it is and just think it's well, we've seen this before.

[00:08:44] We've been here before it hasn't worked.

[00:08:46] So it's really this cycle of infrastructure, data, company culture

[00:08:51] and education.

[00:08:52] And I think that that loop needs to keep going around and round

[00:08:56] and round to really make the most of what could be game changing technology.

[00:09:02] Yeah, I completely agree with you.

[00:09:04] And I suspect much of the skepticism is as well from business leaders

[00:09:08] that have been burnt in the past when they focused on technology first,

[00:09:12] rather than the problem and using tech for tech's sake

[00:09:15] and running into things like garbage in, garbage out.

[00:09:18] And I suspect with nearly half of IT decision makers now focusing

[00:09:22] on technology before considering things like how does it actually serve

[00:09:27] customer outcomes and how companies can ensure that AI strategy

[00:09:31] aligns more closely with the real needs and preferences of their customers.

[00:09:35] These are steps that have been traditionally almost neglect to

[00:09:40] but this is what I've seen in my former IT career.

[00:09:43] Is this what you're seeing too?

[00:09:44] Yeah, as it ever was.

[00:09:45] And yeah, same as some things just never change.

[00:09:50] Yeah, I think like you say, nearly half of IT teams

[00:09:54] to start with the technology first and get very excited at that

[00:09:57] and then look for ways to implement it and then kind of thinking

[00:10:00] about CRMs and things, shoehorn all of the processes and the customer

[00:10:05] journeys around what the technology would be.

[00:10:08] And let's face it, the reason why we see a crisis today

[00:10:12] and I am going to call it a crisis, which is a word that's been

[00:10:14] banded around a lot in the last four years, I know.

[00:10:16] Yeah.

[00:10:17] In customer experience and customer service today is I personally think

[00:10:21] because a lot of technology was introduced patched together.

[00:10:26] It siloed.

[00:10:26] It doesn't talk to each other because of exactly that.

[00:10:29] They started with the tech rather than what the customer needs really were.

[00:10:34] Easier said than done right because that work to understand

[00:10:39] what the customer outcomes are that you want.

[00:10:42] I think only about just over a third of organisations actually do that.

[00:10:46] It takes a lot of work to understand your customers.

[00:10:49] It's not just the data.

[00:10:51] It takes a real skill to understand who they are, communicate with them,

[00:10:55] understand what outcomes you want to generate and then be able to work

[00:10:59] backwards from there.

[00:11:00] Much easier in a greenfield site as well, I think,

[00:11:03] which is why we see brands like Octopus Energy doing really well.

[00:11:07] You know, they were able to build their platform with the customer outcome in mind,

[00:11:13] which gives them an advantage immediately over something that happens the other way around.

[00:11:19] So I think that it's difficult.

[00:11:22] I think, again, it comes back to being cultural

[00:11:26] because some of it depends on how cohesive an organisation is,

[00:11:29] how what the CTO's role is.

[00:11:34] If it's just technology, you know,

[00:11:37] I'm not we might see that technology led deployment rather than customer

[00:11:42] led deployment.

[00:11:44] I think at Twidio we have slightly a slightly skewed view because

[00:11:48] by virtue of our customers, they tend to be builders.

[00:11:51] And I've met some absolutely brilliant CTOs who really act as these

[00:11:57] dot connectors across the whole organisation.

[00:11:59] So they're responsible for kind of unifying an organisation

[00:12:03] and being able to understand what outcomes and be able to get to that.

[00:12:06] What outcomes do we want to achieve?

[00:12:08] OK, what technology do we need to implement?

[00:12:11] But but again, I think that that's not as we've seen.

[00:12:15] That's only about 50 percent of organisations.

[00:12:17] So I still think I think that that role of the CTO actually is really important, Neil.

[00:12:22] Yeah. And it's evolved those people who just changed their job title

[00:12:27] from IT to CTO. It's not it's not quite here.

[00:12:30] And I haven't defined it yet.

[00:12:32] You know, I'm sure you've got probably more wisdom than me.

[00:12:35] But there is something really interesting about this new role of the CTO

[00:12:39] and the roles responsibilities that come with it.

[00:12:41] I think is quite different from what it would have been even five years ago.

[00:12:45] And that pivotal in terms of I think how successful

[00:12:49] organisations will be in aligning AI with customer needs.

[00:12:54] Yeah, there's so many great examples out there.

[00:12:56] And I love how you mentioned octopus energy there.

[00:12:59] We had Greg Jackson on about three or four years ago.

[00:13:02] He was so far ahead of his time on a lot of these stuff.

[00:13:06] And they enjoyed so much success as a result, haven't they?

[00:13:09] Yeah, they are growing rapidly.

[00:13:11] They are, you know, again,

[00:13:14] I have I'm lucky enough that I'm in lots of rooms with great professionals.

[00:13:19] And it's always interesting for me

[00:13:22] the way whenever you mention the name octopus,

[00:13:25] people's faces and pardon the pun, light up.

[00:13:29] Yeah.

[00:13:29] Because they in even at the height of, you know, the enormous energy bills,

[00:13:35] octopus was still really seen as being on the side of the customer

[00:13:40] and a champion of the customer.

[00:13:42] And I don't think it's too much of a structure of imagination

[00:13:46] to can to understand that actually it's because the technology is

[00:13:51] developed around the customer and the customer needs.

[00:13:54] And that helps us feel like they're on our side of working with us

[00:13:58] as opposed to, you know, dead ends for chatbots and self service

[00:14:02] and being forced to go online when you don't necessarily want to go online.

[00:14:06] You know, I think that there's really

[00:14:08] I don't think that the role of technology should be underplayed in this sense

[00:14:13] because I think it's key to why octopus have such a place

[00:14:17] in our hearts and minds, especially in the UK.

[00:14:20] Yeah, I completely agree.

[00:14:22] And you mentioned there is from a consumer point of view

[00:14:25] when a lot of companies force you online, force you to talk to AI chatbots

[00:14:29] that we've seen a lot of bad examples that you just want to swear

[00:14:32] at it continuously till it lets you in to speak to a human being.

[00:14:36] Given the chatbots and hyper personalised interactions

[00:14:39] are seen as significant benefits of AI by both IT teams

[00:14:43] and consumers when they're done right.

[00:14:45] I'm curious, how do you envision these tools

[00:14:48] evolving to further enhance customer engagement?

[00:14:51] And are you able to provide any positive examples

[00:14:54] of where these technologies have actually transformed

[00:14:56] that customer experience that we're talking about?

[00:14:59] So I think personally what we've seen before

[00:15:02] is just those very rudimentary early stages of chatbots.

[00:15:05] You know, they were just FAQs, let's face it.

[00:15:07] And you end up going down cul-de-sacs and in retrospect

[00:15:12] I don't think we should be too harsh

[00:15:13] or we should just appreciate that this was early stages of chatbots

[00:15:16] and what they do.

[00:15:18] I think what we see now with more and more natural language chatbots

[00:15:23] especially those whereby we're seeing it really plugged into large language models

[00:15:28] the generative chatbots that we're seeing emerge

[00:15:32] they're going to get really good.

[00:15:34] Both from a voice basis and we work with great partners like Polly AI

[00:15:38] who've got fantastic voice chatbots

[00:15:42] you know, really doing some impactful things

[00:15:45] as well as then the more written, the traditional chatbots

[00:15:49] and I'm going to come back to Octopus again

[00:15:51] because they've done it really well.

[00:15:55] They worked really hard to apply

[00:15:59] a chat to apply AI across their email responses

[00:16:04] and not necessarily a chatbot per se

[00:16:05] but I think it gives us a good indication of where we can go with this.

[00:16:09] They saved so much effort and time from their employees

[00:16:14] by training a bot to be able to handle email queries

[00:16:18] that they actually saw customer experience stats go up

[00:16:23] because ultimately what we want as customers is a resolution.

[00:16:28] And this was able to get the right resolution quickly.

[00:16:31] So I think that that's a really good example.

[00:16:33] I think that IKEA have good examples of chatbots

[00:16:36] and what I particularly like about IKEA

[00:16:38] is that they're using it almost in the way that it should be used

[00:16:42] because they are reskilling people

[00:16:44] that would have dealt with mundane queries

[00:16:47] in order to be able to handle more of those sort of complex queries.

[00:16:51] So I think there are some really good examples out there.

[00:16:54] I think in the next 12 months

[00:16:56] it's going to get better and better and better.

[00:16:58] Both from a voice prospect as well as perspective

[00:17:02] as well as a traditional kind of chat perspective.

[00:17:06] Purely because it's getting easier to implement.

[00:17:09] Now it's just very much an AI based implementation.

[00:17:12] The large language models with GenAI

[00:17:16] when you apply those and you've got great natural language in there

[00:17:21] they're getting better and better and better.

[00:17:23] You probably know it from your own everyday interactions

[00:17:25] with OpenAI or Pi AI or whatever it is that you decide to use

[00:17:30] they're getting better and better and better.

[00:17:31] And I think that we will see a massive maturity

[00:17:34] in terms of this market.

[00:17:36] And I think as long as customers get the resolution they want

[00:17:40] more customers will use it as well.

[00:17:42] I don't think it's fair to say that we hate dealing

[00:17:45] with robots or bots.

[00:17:46] I just think that again,

[00:17:48] they've not been very good at solving our queries before

[00:17:51] and ultimately as customers that's what we want.

[00:17:53] So personally think we're on the

[00:17:56] I think we're going to see

[00:17:58] they will finally fulfill their potential.

[00:18:01] Yeah, and I think so much of that goal

[00:18:03] that they're able to unlock now

[00:18:05] is because of all this vast amount of data

[00:18:08] that is collected on a daily basis.

[00:18:12] Previously that was all just hidden away

[00:18:14] somewhere nobody knows what to do with it.

[00:18:15] It was hidden all over the place

[00:18:17] and so many insights hidden in there.

[00:18:20] But just for any business leader that's not aware

[00:18:23] can you elaborate on how AI can be leveraged

[00:18:25] to not just collect that data

[00:18:27] but intelligently use that data

[00:18:29] to create more meaningful and personalised customer interactions

[00:18:32] because that's where the magic happens, isn't it?

[00:18:35] Yeah, absolutely.

[00:18:36] It's not just an again.

[00:18:37] Again, I think we shouldn't be too hard on ourselves

[00:18:40] in the past because this was just very early days

[00:18:43] of us understanding how to harness

[00:18:45] and make use of the last

[00:18:47] and completely incomprehensible volumes of data

[00:18:53] that we've now got on organisations have now got.

[00:18:55] It is no mean feat to make that clean, readable and actionable.

[00:19:00] So it's no wonder we struggled with that.

[00:19:02] However, I think now what we're seeing is

[00:19:05] with the maturity of customer data platforms

[00:19:08] and things like this,

[00:19:10] that ability to be able to surface relevant data

[00:19:13] about you, Neil,

[00:19:15] and be able to use that

[00:19:17] to then build up a profile,

[00:19:20] understand who you are,

[00:19:22] make some not guesses

[00:19:24] but a little bit more educated than that,

[00:19:27] be able to be a lot more predictive

[00:19:29] about not just the group that we've assigned you to

[00:19:32] but you as Neil,

[00:19:35] what probably are your preferences?

[00:19:37] When do you like to be contacted

[00:19:38] and really start to apply some intelligence

[00:19:41] to that communication that we power?

[00:19:43] This then starts a flywheel

[00:19:45] because the better the communication,

[00:19:47] the more likely you are to give more data

[00:19:50] and more first party or zero party data,

[00:19:52] the better that then builds up your profile,

[00:19:55] the more then you're able to kind of power this flywheel

[00:19:59] so that you're engaged when it gets better

[00:20:01] and better and better

[00:20:02] and we can collect more information about you

[00:20:04] that becomes relevant.

[00:20:06] I think the trick here is not to make that creep,

[00:20:08] obviously we don't want to make that creepy

[00:20:10] or intrusive in any way.

[00:20:12] So I think it's about keeping some pretty,

[00:20:16] we're going to have to be pretty good

[00:20:17] at keeping good design principles here

[00:20:19] and saying, actually these are the boundaries

[00:20:22] we don't want to push.

[00:20:23] We always wanted to just be relationship building.

[00:20:25] We don't want it to be intrusive.

[00:20:26] We don't want it to be too personal.

[00:20:29] It's just got to be something that is relevant

[00:20:31] and serves the customer well

[00:20:33] and I think that that's always worth bearing in mind.

[00:20:35] I think the other way that AI really helped with that

[00:20:38] so there's that very personal one-to-one level.

[00:20:40] I think it also is going to be

[00:20:42] it's transformative for marketers

[00:20:45] because all that effort that would go in before

[00:20:47] in terms of building up audiences,

[00:20:50] building up predictive models,

[00:20:52] be doing all of that hard work

[00:20:54] in order to target groups of individuals

[00:20:58] with particular campaigns.

[00:21:00] What we're seeing with our segment CDP

[00:21:04] is a lot of that back work is,

[00:21:07] that's just being taken away

[00:21:08] because AI is absolutely capable

[00:21:13] of not only doing that for you

[00:21:15] in a fraction of the time

[00:21:16] but also again,

[00:21:17] it's that power of the generative learning.

[00:21:19] Keep learning what works, what works

[00:21:21] and being able to process,

[00:21:24] make as long as I make every bite count

[00:21:27] rather than big groups and sway.

[00:21:29] So I think it's really exciting.

[00:21:30] I think it will be transformative

[00:21:32] because again,

[00:21:33] we'll finally be able to understand

[00:21:35] what we mean when we say personalization.

[00:21:38] I think that there are hundreds of different interpretations

[00:21:41] of what it is

[00:21:42] and some people do it really well.

[00:21:44] Some people treat it as a recommendation engine

[00:21:46] but I think that AI will help us

[00:21:50] be able to build up more of those personal relationships

[00:21:54] which I think again,

[00:21:56] is where we see personalization falling down

[00:22:00] because it's still a huge,

[00:22:01] I think something like 80,

[00:22:04] in the 80% upwards of customers

[00:22:07] say that this is what will make a huge difference

[00:22:10] to the relationship they have with their brand

[00:22:11] and yet we know that around 50%,

[00:22:15] only around 50% of organizations do this

[00:22:17] to any kind of credibility

[00:22:22] or any kind of effectiveness.

[00:22:24] So there's a delta there too.

[00:22:26] So hopefully we'll see that delta kind of narrowing.

[00:22:29] And I think as well for business leaders,

[00:22:31] there's certain amount of confusion

[00:22:33] and complexity that they have to navigate around

[00:22:36] especially with the research out there

[00:22:38] at the moment indicating a clear split

[00:22:40] between operational efficiency

[00:22:42] and organizational growth, driving AI adoption.

[00:22:45] So I've got to ask,

[00:22:47] but any business leader listening,

[00:22:49] how should they balance these objectives

[00:22:51] while also developing their AI strategies?

[00:22:54] Is that a way to ensure that both goals are met

[00:22:56] without compromising on customer engagement

[00:22:59] because again, quite a tricky balance.

[00:23:01] It is tricky balance

[00:23:02] and I don't think it's one

[00:23:04] that that many organizations have got right now.

[00:23:07] And I think when you're looking at customer engagement

[00:23:09] and customer service,

[00:23:10] there's no doubt that there's a lot of pressure on it

[00:23:12] at the moment.

[00:23:13] We know that standards are declining.

[00:23:15] So that standard is declining

[00:23:18] because the complexity of nature of queries,

[00:23:21] attrition rates in contact centers, customers,

[00:23:23] I don't know if we are becoming more demanding

[00:23:25] or we're just frustrated

[00:23:27] because so much of the burden for self-service

[00:23:30] has fallen to us, but it's really hard to do.

[00:23:34] So I think that at the moment,

[00:23:38] there is a real pressure

[00:23:40] to being investing in AI

[00:23:43] for operational efficiency.

[00:23:45] I think it's a way that business leaders looking,

[00:23:49] CTOs, CEOs, CFOs are looking to say,

[00:23:52] this is how we're going to take some cost out of the business.

[00:23:55] I think it will be a very disciplined organization

[00:23:58] that is able to say, hang on a second,

[00:24:00] before we do that,

[00:24:01] let's really think about what we want to achieve here

[00:24:04] and think about what experience we want our customers

[00:24:08] to be able to have.

[00:24:09] I think for some organizations,

[00:24:11] that's probably a luxury position at the moment,

[00:24:14] but ultimately, we know that that's where

[00:24:17] that's at the heart of a good strategy, right?

[00:24:19] Understanding what it is you want to achieve.

[00:24:22] We talked about it earlier.

[00:24:23] What outcomes are you aiming for?

[00:24:26] And then how can we do this

[00:24:28] and how can we utilize AI to both create that efficiency?

[00:24:32] And I suppose the other flip is,

[00:24:34] if organizations can just use it

[00:24:37] to take out some of the hard work through voice barts

[00:24:42] or chat barts or fantastic,

[00:24:46] even IVR experiences or something like that,

[00:24:48] then at least it frees up some capacity

[00:24:51] for human agents to be able to perform more

[00:24:54] of that customer engagement role

[00:24:56] than be able to better service customers.

[00:24:59] So I don't think that there's a straightforward answer.

[00:25:02] I think it always has to be this dance between the two.

[00:25:06] You know, if we take some cost out,

[00:25:09] hopefully that will free up more agents

[00:25:11] and then we can keep taking cost out

[00:25:13] and we can keep freeing up more agents.

[00:25:15] So it feels like it should be a dance.

[00:25:18] My worry is that we'll go too far

[00:25:19] in the operational efficiency

[00:25:21] given the pressures that are on organizations today.

[00:25:25] And of course, if we go back just 18 months,

[00:25:27] I think Gen AI blindsided most business leaders.

[00:25:31] So it makes it almost impossible to predict the future,

[00:25:33] especially with the pace of technological change at the moment.

[00:25:36] But if we do look ahead and have a little gaze

[00:25:39] into a virtual crystal ball,

[00:25:40] are there any emerging trends or advancements in AI

[00:25:44] that you anticipate or excite you

[00:25:46] that maybe will have this significant impact

[00:25:49] on how brands engage with their customers?

[00:25:51] Are there any innovations on the horizons

[00:25:54] that businesses should be preparing for now as well?

[00:25:57] What excites you about that, Rona?

[00:25:59] Why? What excites me is probably thinking about it

[00:26:03] in a slightly different way,

[00:26:05] which is flipping the question around and say,

[00:26:08] how are us as customers going to engage with brands?

[00:26:12] Because let's say we have more and more control of our data

[00:26:16] and we can decide what to do with it.

[00:26:19] Tech becomes more interoperable

[00:26:21] because at the moment it's still quite siloed

[00:26:24] and I think in the UK we've seen the benefits

[00:26:27] of like open banking and things like that.

[00:26:29] And I think it would be really interesting to say, right,

[00:26:32] if we keep expanding that notion

[00:26:34] and we get more control of our data,

[00:26:37] I don't know what the future will look like,

[00:26:39] but I do, I can't help but wonder,

[00:26:42] if we're in control of the customer journeys ourselves,

[00:26:46] even if we've got our own bots, can you imagine?

[00:26:49] Bot-to-bot servicing is rumoured to be on the horizon.

[00:26:54] Then I think it's really interesting

[00:26:57] because I think it asks fundamentally different questions

[00:27:00] to poor organisations about their understanding

[00:27:02] as to what a customer journey is.

[00:27:04] And I think that that for me

[00:27:06] is where it starts to get really interesting

[00:27:09] because again, a lot of technology has been applied

[00:27:14] to make existing processes slightly better.

[00:27:18] I think what I'm looking for and excited about

[00:27:21] is when that starts to flip on its head

[00:27:23] and we can completely reimagine customer journeys,

[00:27:25] we don't know what that's gonna look like,

[00:27:27] but I think that's probably a fundamental shift

[00:27:30] that's on the horizon.

[00:27:31] It sounds a bit woolly

[00:27:32] because I don't know exactly what that will look like,

[00:27:34] but my hunch is we as consumers,

[00:27:39] the trick is to take some of this self-service bird

[00:27:42] away from us.

[00:27:44] And I think that that's probably,

[00:27:46] that for me is something that's on the horizon.

[00:27:49] Excellent in times ahead and it isn't going anywhere.

[00:27:52] So for that 20% of organisations

[00:27:55] or people from those 20% of organisations

[00:27:57] that might be listening that are still set

[00:27:59] on the sidelines of AI implementation,

[00:28:02] any advice that you'd offer to give them

[00:28:05] that would help them begin their journey towards

[00:28:07] integrating AI into their customer engagement strategies

[00:28:10] and any tips on how they can ensure

[00:28:13] that that approach is both customer centric

[00:28:15] and poised for competitive advantage too.

[00:28:18] I appreciate it's a huge question

[00:28:20] which is a podcast episode, I think so.

[00:28:23] Is there any advice you could give?

[00:28:25] I think first of all,

[00:28:26] you know, don't,

[00:28:28] first of all, don't be afraid.

[00:28:30] We've been here before with the internet,

[00:28:33] you know, we're able to adjust

[00:28:35] and actually great leaps forward

[00:28:37] in humanity always come with technology leaps forward.

[00:28:42] So, you know, you've got to get stuck in

[00:28:44] and get involved in some kind of level,

[00:28:46] but I think the first is understanding

[00:28:49] what kind of level that is for your organisation.

[00:28:52] I think there are three things

[00:28:54] that are really important

[00:28:56] for an organisation to get in place

[00:29:00] and that is, and we talked about them earlier, right?

[00:29:02] So it's the, your tech infrastructure,

[00:29:05] it's your data architecture and it's your culture.

[00:29:09] And I think that those three things

[00:29:11] are really important in terms of culture

[00:29:13] that's employee and customer well balanced.

[00:29:17] I think lots of organisations claim

[00:29:20] to be customer centric organisation.

[00:29:22] They're not, as we know,

[00:29:25] but that's also because it's easier to say

[00:29:28] than it is to do.

[00:29:31] So I think for me, if I was to pick one of those things,

[00:29:35] your data is probably the number one priority

[00:29:38] before rolling out AI

[00:29:40] to make sure you're getting good stuff out

[00:29:43] and good, you know, your inputs and outputs

[00:29:45] are equally as good as each other

[00:29:47] because we know so far,

[00:29:49] especially with large language models

[00:29:51] that rubbish in makes rubbish out.

[00:29:54] So I think that if any organisation is going to start looking

[00:30:01] at how they can use AI,

[00:30:02] I think that data is a really, really cool way

[00:30:06] to start off it and ask that question,

[00:30:08] is our data in a good enough shape to start doing this?

[00:30:12] And then kind of work from that.

[00:30:15] Once you've done that analysis,

[00:30:16] then start to think, okay,

[00:30:18] now what's going on in our organisation

[00:30:21] and where can we test and learn this in a really small way?

[00:30:24] You know, these don't have to be big things.

[00:30:26] It can be very small.

[00:30:28] You could just apply it to one reason for contact

[00:30:32] or one small process or one,

[00:30:37] you know, just one product line.

[00:30:39] You don't have to be big with this.

[00:30:41] You can start small, keep iterating it.

[00:30:43] I think the strength of that test and learn

[00:30:47] will be who you've got involved as well.

[00:30:50] Again, silos aren't going to work here

[00:30:53] because you need all parts of the business involved

[00:30:55] in order to really understand this working

[00:30:58] where we have the outcome that we desire,

[00:31:01] have we got all the parts we need

[00:31:03] and pulling all of those different

[00:31:04] different parts of expertise together.

[00:31:07] So I think, you know, very much data first,

[00:31:10] then start some experiments,

[00:31:13] start some small experiments,

[00:31:14] see what happens, test it

[00:31:18] and then, you know, before,

[00:31:20] don't just do it for the sake of doing it

[00:31:22] but make sure you're really clear and considered

[00:31:24] about what it is that you want to achieve with it.

[00:31:29] So I think it's not easy to get started right

[00:31:31] but we're all in it, we're all learning together.

[00:31:34] So I would say probably the other thing

[00:31:36] is lean on people who might be slightly ahead of you.

[00:31:38] You know, I think collaboration is really

[00:31:40] the name of the game now.

[00:31:44] We have to start collaborating with each other

[00:31:46] and learning from each other.

[00:31:49] And I think that's a powerful moment

[00:31:51] to end our conversation today.

[00:31:53] So a huge thank you for sharing your time

[00:31:55] and your insights,

[00:31:56] signing with myself,

[00:31:57] for everyone listening around the world today

[00:31:59] and as a fellow East Midlander, as a thank you,

[00:32:02] I'll see if I can offer you,

[00:32:04] I don't know, a chip cob or a P mix

[00:32:06] but I think we can dream bigger than that.

[00:32:07] So some of the biggest names in business,

[00:32:10] BC funding and tech have either been guess

[00:32:12] or listened to this podcast.

[00:32:13] So if I was to ask you,

[00:32:14] is there a person you'd love to have

[00:32:16] a private breakfast or lunch with?

[00:32:18] Who would it be and why?

[00:32:20] Because he or she might just be listening to this

[00:32:22] and let's see what we can manifest together

[00:32:24] but who would he be?

[00:32:25] Well, I might go slightly left field with this.

[00:32:29] Now in the tech world,

[00:32:30] I would love to have a sit down with Azim Azar

[00:32:34] because I think he's brilliant.

[00:32:37] However, if you were really forcing me

[00:32:39] to have a breakfast or lunch

[00:32:40] and maybe breakfast running into lunch with somebody,

[00:32:43] I think I would pick the historian.

[00:32:47] So I'd probably pick somebody like,

[00:32:49] he's like the business of BC world

[00:32:51] but I'd pick somebody like Peter Francopan

[00:32:53] and I tell you why,

[00:32:54] because we are in the moment of an,

[00:32:57] it's not unprecedented change actually,

[00:32:59] we need our historians to kind of remind us

[00:33:02] of all of the great leaps forward

[00:33:04] that humans have made before

[00:33:05] so we can put it into context

[00:33:07] and understand what's happening.

[00:33:09] So I think I'd quite like to have some meals

[00:33:13] with Mr. Francopan because I think

[00:33:16] just talking about that history of the world,

[00:33:19] the evolution, the silk roads,

[00:33:22] the industrial revolution really helps us put today

[00:33:26] into context and probably makes it a bit easier

[00:33:29] to navigate what's ahead

[00:33:32] and kind of have a bit of faith

[00:33:34] that it probably will be all all right in the end.

[00:33:37] What a great answer

[00:33:38] and I think it's such an important one

[00:33:40] because there is so much fear and anxiety

[00:33:43] about the world of tech

[00:33:44] and where we're heading at the moment

[00:33:45] but as you've said a few times,

[00:33:46] we've been here before

[00:33:48] from the arrival of the internet more recently

[00:33:50] and the arrival of smartphones and app stores

[00:33:53] and digital disruption.

[00:33:55] We've been here,

[00:33:56] I did a Google search recently,

[00:33:58] I think it was 20 jobs

[00:34:00] that didn't exist 20 years ago

[00:34:02] and it's all things that we take for granted now,

[00:34:04] things like cloud engineers, social media managers,

[00:34:08] podcasters, there's so much.

[00:34:12] Yeah, yeah, well my first job,

[00:34:14] I was managing the fax machine and the TELX machine.

[00:34:18] Wow.

[00:34:19] There we go.

[00:34:20] Incredible.

[00:34:22] Well, for anyone listening

[00:34:23] that would like to find out more information

[00:34:25] about you, Twilio, the work that you're doing there,

[00:34:28] where would you like to point everyone listening?

[00:34:30] The Twilio blog is a great place to go

[00:34:32] because we have got all sorts of wonderful resources on there,

[00:34:35] not just for developers

[00:34:36] because we're a very developer.

[00:34:38] We love our developers at Twilio

[00:34:40] but it's not just for developers.

[00:34:42] There's also some great tips on customer engagement

[00:34:46] and best practice

[00:34:47] and what you should be thinking about next.

[00:34:50] So the Twilio blog is a great place to be

[00:34:52] and then obviously the socials, LinkedIn,

[00:34:55] I think we're on X and Twitter

[00:34:58] whatever we want to call it these days.

[00:35:01] So you can find us in all the usual social places.

[00:35:05] We covered so much in a short amount of time today

[00:35:07] and the one thing I was going to discuss

[00:35:09] we didn't have time, there's a great quote from you.

[00:35:11] I think it's a moment to finish on

[00:35:12] and it was about AI

[00:35:14] and I think you said when AI is used

[00:35:16] to its full potential,

[00:35:17] it allows brands to know every customer

[00:35:20] like they are the only customer they have

[00:35:22] and I think it's a beautiful moment to end on.

[00:35:25] So thank you for sharing that

[00:35:26] and your incredible insights today.

[00:35:28] I really appreciate it.

[00:35:29] You're spending time with me today, Sam.

[00:35:31] Thank you for having me, Neil.

[00:35:33] So thank you to Sam Richardson.

[00:35:36] Fantastic conversation.

[00:35:37] So many golden insights there from today's guests

[00:35:40] and I think it's clear that AI

[00:35:42] is not just a technological advancement.

[00:35:45] It's almost a catalyst for building deeper

[00:35:47] more personal connections with customers

[00:35:49] and that journey towards integrating AI

[00:35:52] into customer engagement strategies

[00:35:54] is filled with challenges

[00:35:56] but also it's abundant with opportunities

[00:35:58] for innovation and personalization.

[00:36:01] And as we all collectively look to the future

[00:36:04] how will you and your organization leverage AI

[00:36:08] to enhance customer relationships?

[00:36:10] How will you drive engagement?

[00:36:12] I invite you to join the conversation

[00:36:14] share your thoughts on how AI is reshaping

[00:36:17] the landscape of customer engagement in your industry

[00:36:20] and it's nice and easy to do

[00:36:22] well, the easiest guy in the world

[00:36:23] for a tech blog writer outlook.com

[00:36:25] Twitter, LinkedIn, Instagram

[00:36:27] just at Neil C Hughes.

[00:36:29] Don't just hit connect or follow though

[00:36:31] I'm not the follow me I follow you guy

[00:36:33] I kind of wants to meaningfully connect

[00:36:35] and talk to people that listen

[00:36:37] to these podcasts every day.

[00:36:39] People like you.

[00:36:41] So please don't forget to subscribe

[00:36:42] to the podcast for more insightful discussions

[00:36:45] on the intersection of technology

[00:36:47] and real world solutions.

[00:36:49] So if you enjoyed it today

[00:36:50] come back tomorrow we'll do it all again

[00:36:52] with a different guest

[00:36:53] Well, thank you for listening as always

[00:36:55] and until next time

[00:36:58] Don't be a stranger.