Leveraging AI Across Support TouchPoints
Join for an engaging conversation with Jason Lowe, a seasoned expert in the world of customer support and Contact Center as a Service (CCaaS). Jason has a wealth of experience in driving revenue growth and enhancing agent performance through innovative strategies. In this session, we'll explore the transformative power of AI across various communication channels. Jason will share insights on how to leverage AI effectively to enhance customer support, no matter which touchpoint your customers prefer. Whether it's phone, chat, social media, or email, you'll discover the multichannel magic of AI.
(upbeat music)
And welcome back to the AICX virtual summit
with me today in this session is Jason Lowe.
Jason, how are you doing?
- I'm doing good, Brian, how are you?
- I'm doing well myself.
Well, let's just get right into it.
Again, I think we have 20, 25 minutes here,
but first let's start off with just the basic introduction.
Jason, can you tell us a little bit about yourself
so the audience knows where this expertise is coming from?
- Sure, you bet.
So I got in the AI space a little bit indirectly
because of my experience in the CX space.
So I wrote code for a decade in a previous life
and then I got into sales engineering
and product management with some prominent players
here in the CX space and did that for about 12, 13 years.
And now I am at a technology solutions distributorship
named Tilaris where I am a solution architect
for contact center and AI.
So that's how I got into it and that's why I'm here.
- Okay, so one step back before going two steps forward,
can you tell us a little bit about Tilaris as well too,
for those that don't know?
- Sure, you bet.
So Tilaris is a distributorship for technology solutions.
We are here to support our technology advisor partners
that need someplace to go to for the products
to source for their customers
and also if they have a need for technical resources
or people to help with really any kind of a process,
whether that's the sales cycle or project management
or different things like that.
So Tilaris is here to help our technology advisors
as best we can and we have a portfolio of products,
one of which is one of our favorites, which is customer.
- Thanks for that.
Well, again, I think the audience can see now
that Jason and I have talked before
and I thought that with Jason talking to so many,
I mean, we were talking about hundreds and hundreds,
maybe even thousands of merchants here that Jason talks to
and then the amount of technology that Jason has to consume
and to understand to kind of connect the dots,
I thought this would be a really interesting dialogue
between us two.
So maybe first, let's set the stage a little bit.
We have so many different channels, so much AI,
actually right before we started getting on the call,
we just talked about trying to stay up to date
on all this AI technology.
Like when for you did you actually start saying to yourself,
like, okay, this is the technology,
this is kind of the part I have to play.
And like just kind of walk us back,
like what was that like where it's like,
okay, I got to get into AI,
I have to understand all this,
even before the technology vendors were asking you questions.
- So AI--
- When did that happen?
- I think goodness, it's been a long time.
So way back in my product management days
for a prominent CX platform,
AI was starting to become a thing.
That company that I worked for
had just made an acquisition
for a speech analytics type of product
that was being used pretty heavily.
And it was obviously something that was going to have
a major impact on the feature set
of that platform moving forward.
And then when I moved back into sales engineering,
there are all of these different products in CX
specifically where AI is prominently used,
whether we're talking about artificial intelligence bots
or whether we're talking about virtual agents
or whether we're talking about speech analytics
or data analytics as it relates to agent performance
or real time notifications for tonality analysis.
If a supervisor needs to know if an agent's
getting into a yelling match with a customer
or something like that,
all of these things are being done with AI.
And so over the years,
it has just become more and more prominent and prevalent
in the different features that are being used
in the CX space today.
And so at Tilaris, when I originally started getting
into contact center and CX,
it became obvious with the plethora of providers
that we have the same phenomenon I was observing
when I was working for the other one in product management.
And so I really just felt like,
you've got to go this way.
AI is the wave of the future.
AI is something that is happening.
We're hitting another industrial revolution, if you will.
A lot of people are calling the advent of AI
as the fifth industrial revolution.
And I can't say that I disagree at all.
And so that's why I decided to get into it
and really start learning a lot about it and focus on it.
- That's a big statement there.
Let me actually kind of go a little bit deeper on that, Jason.
Why do you think this is such,
you said it's the fifth, right?
You said like the fifth as an,
is that what you just said?
- I think so.
And that's just my opinion, right?
I mean, the first industrial revolution
was really the steam engine that really changed the world.
The second one being the advent of electricity
and electrical products.
The third being computing in general.
And then the fourth being connectedness, you know, wireless,
being able to put things in different places.
But AI, this is really an inflection point for human history.
I don't think anyone is under any illusion
that AI will not significantly impact their life
and the quality of their life moving forward
because the advent of AI in a usable form is now.
And the rapidity in which technological advancement
is happening is dizzying.
I mean, there are things happening on a daily, a weekly basis.
And it's that upward scale.
It's that exponential scale.
It's Moore's law.
Things are just happening a lot faster
than anybody really anticipated.
And it's happening right now.
This is a very special time in history
to be watching this happening.
- Hmm.
And so do you think it's the pace?
Like, I guess what's interesting to me in your background
is kind of like, you've seen this happening for years now.
It's not just that in the last,
you know, it's not just in the last year
where this is AI talk for you.
You've seen this, especially in the context center.
But I was gonna ask you, like,
well, what's the difference in the last 12 months
that didn't exist before that?
And it just sounds to me, and let me not put words in your mouth,
but the pace of AI and the innovation that's happening now.
Is that correct?
- Yeah, well, and I think you're leading this horse to water,
and I'll definitely take a drink.
We're talking about generative AI specifically,
LLM. (laughs)
You know, chat GPT was a relatively unknown quantity
for, you know, a year or two after it was initially debuted.
And then with the release of chat GPT 3.0
and then becoming much more publicly accessible,
it really became crazy,
at least as far as advancements and capability
in this generative AI stuff with LLM.
And it's not just LLMs that,
where it was really taking place.
You're talking about content generation,
specifically, you know, picture generation, graphics,
videos, mid-journey as a platform.
If you were to look at a picture where you asked mid-journey
for a picture of a girl walking through a field, you know,
12 months ago, you'd be flipping a coin to find out
if the girl had seven or eight fingers on her left hand
and three fingers on her right hand and three legs
and, you know, and wearing different things.
And whether the field actually had flowers
or not, even if you said flowers.
I mean, there's all of this stuff
that was just really not reliable.
But then through the power of the feedback loop
where we could provide it feedback on what it's doing
and whether or not it's good,
really has allowed AI in its modern form to learn a lot.
And now you can barely tell the difference
between an AI-generated photograph
and an actual photograph being used today by mid-journey.
It's really quite fascinating.
- Yeah, I was gonna say like if you just a year ago,
if you wanted to create that image,
you'd probably move faster at the pace
of just creating it yourself.
Now there's no question within one click,
you can get exactly that.
- Absolutely.
- Okay, so let's take the conversation
to the next step, Jason, which is your conversations,
which with these merchants of yours and customers,
I guess, are there any common themes
that often come up with like those first questions
when they want to understand AI and CX together?
- Can you tell us a little bit about those first conversations
that you're getting, like what merchants are coming to
and what that is like?
- Well, with the merchants or with customers?
- Sorry, with customers.
- Okay, well with customers, it's really interesting.
I'm recognizing a phenomenon.
This is something that has really been happening
a lot over the last couple of months, Brian.
We have tech advisors that are in there
serving their customers in a lot of different ways,
more so than CX in a lot of different areas.
And these customers will have a president or a CEO
or a senior leader in the company that will pick someone
from the IT staff or the CX staff and say,
"Okay, I'm designating you as the AI champion
in this company.
I want you to implement AI anywhere
that it can possibly be implemented.
Here you go, go to it, have fun."
And the person just looks at them like confused,
like, "Where do you want me to start?"
And then the CEO goes, "I don't know.
I just hear all this AI stuff.
Go make it happen."
And so that person invariably turns to their tech advisor
and says, "Help, I need some help.
I don't know what to do here."
And then the tech advisor comes to us
at the Technology Solutions Distributorship and says,
"How can we help this person?"
And so a lot of the initial conversations,
if they're not surrounding CX,
they immediately go towards CX
because AI and CX is in its most mature,
marketable, packagable, usable form.
This is where AI is showing the greatest value creation.
I mean, in 2023, in the retail industry
where CX is so important,
you're getting pretty close to a trillion dollars
worth of value being generated by AI
in that particular category.
And so conversations head in that way,
but by no means are certain to go in that way.
Obviously, we're having conversations
about all sorts of other things as well
and just exploring what they want to do with AI
and the use cases that they need to tackle moving forward.
- Can you expand on that use case
that you just talked about retail
with the amount of value that's created in CX?
Can you give us a few examples
that first comes to mind about that?
- Well, when it comes to AI specifically in CX,
you need to understand a few of the different channels
where it's being used.
And by channels, I'm talking about
that multi-channel, omni-channel type thing
where you have voice, which is obviously very important.
And you wouldn't think this,
but voice is actually the communication channel
that is least tackled by AI right now.
Right now, Forbes, okay, I'm gonna go to a Forbes study
that was done earlier this year
where they were finding out how businesses
are using artificial intelligence
at various customer touch points.
And it was really interesting to find out
that voice is the lowest.
Phone calls, 36% of companies are using AI
in touch points with voice.
And that's a lot, but that means 64% of companies are not.
Whereas if you go to instant messaging,
like web chat bots, different things like that,
73% of companies are utilizing AI in those channels,
61% in emails, 49% in text messages.
So obviously these text-based communication methods
are the ones that are being tackled most rapidly right now
as opposed to voice.
- And is there a purpose behind that?
Do you think that's on accident?
Or is there a reason why voice was 36% is what you said?
- I think a lot of people are having a hard time trusting voice
just simply because for many, many years,
there was this prevalent attitude of,
hi, how can I help you today?
Representative, great, can you tell me what you need
so that I can send you to the right person?
Representative, just when they were talking voice,
they didn't wanna talk to a bot.
But I think that text was a different method
because text is a little bit more
of a casual type of conversation
that can take a little bit of time
and it isn't as immediate as a voice conversation.
And so people tended to be a little bit more patient,
if you will, a little bit more accepting
of text-based communication with AI.
And so through that, inadvertently,
it made them more comfortable with AI
as a communication method or a person, a communicator,
an entity to communicate with, to achieve certain outcomes.
And so I think that's leading towards voice
now becoming something where AI is becoming more
and more adapted and more and more accepted.
But it is just taking time.
Plus, AI and text was a lot easier to implement.
Thinking about AI and voice,
you need all of the power and capability of AI and text,
and then you have to feed the text
to a speech rendition engine.
It doesn't mean that it's any different,
it just means it's all of the text stuff,
plus a little bit more.
So once they really got the text-based communication down,
they debuted that, now we're playing catch-up
on the voice side because you've tacked on voice generation
with that capability.
- So what are the,
so let's kind of take a step towards
all the multi-channels again.
What are the questions that you would want customers
to be asking to help them understand
and help you understand on what channels come first,
and what's it worried about first?
- I don't know what they're thinking about.
- Questions from customers,
I think that's an interesting one to try and cover.
Oftentimes they don't know what to ask.
It's really kind of fun because they,
if they either know that AI can be used in CX,
and so they're kind of moving in the direction,
or they're unsure, or they're not sold on whether or not
there's an ROI or a TCO associated with AI
in specific channels.
And so it's kind of fun where technology advisors
and me specifically in conversations when I have with customers
is what kind of a problem are you trying to solve?
And I realize that's kind of a standard salesy type thing
to say, but when you're dealing with a new technology,
that really does kind of boil down to being
the ultimate question to ask.
What is it that you're experiencing problems with?
Where do you want to save money?
What kind of problems are you trying to solve?
And then you can get into more specifics.
And like, I'll give you a use case example here.
So I had a customer who was really trying to reduce
the cost in their contact center because they had 80%.
They actually went through and had their agents
fully disposition these different calls.
And it was a company that was shipping product.
And they found out that 80% of the calls
that were coming in were nothing more than people
calling and asking for a status of a shipment.
And so they came to us saying,
there's got to be something we can do to automate this somehow
so that it's not being handled by an agent.
Is there an agentless way for this to be tackled?
And so we did exactly that.
We had a situation and this was phone call specific,
not tech space specific.
So it's a little bit,
maybe it from our earlier conversation.
But we were able to introduce them
to a artificial intelligence bot provider
that would do what Delta Airlines does.
And Delta, I'm sorry if you're seeing this.
I'm invoking you in a good way.
Okay, Delta, when I call Delta, what I love, they say,
thank you for calling Delta Airlines.
Welcome back, Jason.
I see that you have a flight departing tomorrow
at 12.05 PM.
Are you calling with questions about that?
And then I just say yes or no.
And then they'd ask me how I can help be helped.
And then I can continue my conversation
with this bot entity.
And we decided to take that model
because Delta does it so right.
And say to the customer,
what if when they call in and you recognize
who's calling in, you do a quick data dip
to see if they have a shipment on the way.
And if they do, greet them and say,
thank you for calling.
Welcome back, Jason.
I see you have a shipment that is expected to arrive
on Thursday at 12 PM.
How can I help you?
And it turns out that they implement that.
And suddenly their abandoned call volume
went through the roof because people were calling in.
They were having their question answered
within the first 15 seconds of being on the phone
because this bot was saying to them
what it was they were calling about.
And then they were hanging up the phone,
drastic savings in labor,
drastic savings until the F&E bills
because it was less time on the phone,
all in all a really good use case scenario.
But it started out with them recognizing a trend
that might possibly be solved with automation
or artificial intelligence or virtual agents.
- Well, I think that you have to look,
I guess let me clarify for the audience here
because I think this is insightful for me
as well too.
You have to look inward first
and you kind of answered the question, Jason,
which is that these customers should ask,
well, what's the first challenge?
I know it's basic, but it's really,
it is insightful here because you have to look
inward first about what challenges you want to tackle
first and foremost because in all my conversations so far
speaking with customers as well,
it's like a lot of people now start with the solution
which is like, well, we gotta use AI.
And that might not be the case.
And actually I wanted to bring it up to you
where it's that, should people always be thinking
that AI is the solution to any sort of problem right now?
And is that the wrong way to think?
- I think so.
I think you're correct.
I think it's the wrong way to think.
I think that there will always be a place for the human.
And so what people can look for when they're looking
inside their walls is look for those repetitive tasks
that might be more easily done by automation
or by some sort of a technical entity.
You're not going to be able to eliminate the human completely.
We're not to that level.
We're still in the artificial narrow intelligence phase.
We haven't reached the artificial general intelligence phase
which is where we get an equivalent to human being in AI.
And so there's just some things that AI simply cannot do.
So if they're looking internally for things
that they want to try and improve is
what are those repetitive tasks?
What are those repetitive actions?
Whether there's something that humans are doing repeatedly
in CX communication or manufacturing
or some other process,
what is this thing that's happening consistently regularly?
It could be guided by a human.
It could be influenced by a human.
But there's still these regular tasks
that you can look at and say,
"Huh, maybe there's a better way to do this
"that might save a little bit of money
"and that artificial intelligence could help with."
But again, keeping in mind,
you talk to an LLM for five minutes.
You can get them twisted around pretty quickly.
You can get an LLM to contradict itself very fast.
There's just, it's not perfect.
Human beings still need to be involved in that loop right now.
- Yeah.
I kind of want to take this more out of curiosity for me
and I hope the audience is well too.
One step forward in this example
and in case study that you just used with Delta Airlines,
thank you Delta.
But now that you've solved in this scenario,
the problem of answering the questions,
so you probably saved time with all the agents
that are getting the constant question coming in
and spending that money on the agent.
Now that you've solved it on the phone,
would you recommend then also figuring out,
well, how do we reduce just the number of phone calls
coming in about the same question?
Like do you try to then take it one step further
and say, okay, how could we be more proactive
so we don't even get that?
We answer that before they think about calling us.
- That's a fair question.
- Or do you move on?
- It's definitely the right thing to do.
I think that it depends on a use case by use case scenario.
And sadly in my scenario,
we were dealing with people that were,
how can I put this kindly?
Scared of tech a little bit?
Maybe a little bit tech avoidance type things
so they were very much,
the demographic that was being served
by this company that was shipping product
was generally, sorry mom,
an older generation that is just not as comfortable
with anything but voice.
They come from a generation
where if they wanted to find something out,
they picked up the phone and they called.
But Brian, you're absolutely correct.
You definitely can analyze and see,
can we send them messages?
Can we send them texts to give them updates
so that they're proactively being notified of?
In this case shipments,
before they feel a need to call
and find out what's going on with their shipment,
can we give them a status every step of the way?
Can we send them email confirmations
or text confirmations of different steps of the process?
There's definitely things that you can do
to try and reduce the amount of phone calls
and how you do that is reduce the amount of confusion
or lack of knowledge in what's going on
and pure visibility.
Alternate methods of communication
are a great way to achieve that for sure.
Okay.
Yeah, it's your point, right?
There's people that,
like you don't want to change the channel
when people recommend one channel or the other.
But the thought of being more proactive
and I think AI has a big impact
for the proactiveness of messaging
rather than the reactiveness of answering questions
all to something to think about
and when to get your opinion on it.
I think as we kind of hit so many different channels here,
I'm kind of curious on your thoughts around SMS
and if you don't have,
I know we've never talked about this before,
but curious if you do have thoughts around this.
And the reason why I say that is because
I see a lot more companies trying to utilize SMS
part of either retention, customer loyalty channels.
From your standpoint,
do you see this as well too?
Is this something that you think will be more and more
utilizing SMS?
Do you think we're at a peak?
And just curious what your thoughts are on that.
I think SMS is quick and it's handy and it's easy.
And so I think a lot of people really like it.
I think the younger generation grew up
using SMS texting versus other things.
And so it's an area of comfort for them.
And so as the consumers kind of get older,
it's an area that I think can certainly grow.
There are concerns.
There are safety, well, okay, let's not say safety.
I'm talking about cybersecurity safety concerns with SMS
because it may not necessarily be as secure
as many people want it to be.
So I think in the long term,
it could be a little bit of a thing now,
but it may end up progressing to something
a little bit more secure.
This is why I think WhatsApp is being used quite a bit
by a number of different companies or Apple Business Chat.
You know, Apple Business Chat is still texting,
but it's done using iMessaging.
It's not done through simple SMS.
It's MMS.
And so I think progression to MMS is going to happen.
Whether that takes the form of just straight MMS
texting capability or possibly within other apps like WhatsApp
or Apple Business Chat or proprietary applications,
I think it'll change based on the market
and the industry that you're in and the comfort level
of the demographic that's being served.
But SMS is great for now,
and it's definitely the foundational aspect for what's going to happen
in the future as cybersecurity concerns
and confidentiality concerns get addressed
in those types of communication.
Yeah.
Well, I think what's really interesting is that
I see as a marketer myself, like I see SMS,
and I think it started in the top of the funnel,
like with new customers.
And that's not like, it's not the best experience, right?
We're talking about customer experience, like SMS,
when you don't know the brand too well,
comes off as spam, in my opinion,
and in the conversation that they have a lot of merchants.
And you see in the last few years,
they're trying to move this channel then more towards
the customer loyalty channel, which has a lot better
of a connection there with the customer when you already know
about the brand, and you're okay with an SMS message now.
And I see a lot more success when it comes to, again,
improving your customer experience across multiple channels,
and you have to understand what's the right channel for you,
which is why I brought that up.
So, I guess like we hit on voice a little bit, SMS.
I know you touched on email.
Any other thoughts on like,
email when it comes to utilizing AI on that channel?
Content generation is,
it's reaching an interesting stage.
LLMs are fantastic, but oftentimes they can hallucinate.
And so this has been a problem where LLMs have been
slowly and cautiously incorporated in anything
that's customer facing, because there's the possibility
that this LLM might misrepresent the company.
However, there's a newer phenomenon that's becoming
all the rage right now, which was addressed at the OpenAI developer
convention, OpenAI developer convention, not a contest,
although I'm sure they--
You got it.
--contest with each other in writing super cool code.
But in this convention, the phenomenon of retrieval
augmented generation is really becoming rapidly adopted.
And a lot of the players in the CX space are starting to really adopt it as
well.
That takes accuracy from low levels to super high levels.
In some cases, as high as 98% or more, which is a little more palatable
and a little less dangerous for companies to allow
when you have these things representing their company.
So that's just going to improve over time.
So back to your original question of emails.
You know, emails are different.
It's not just a single one line or two line SMS.
It sometimes could be a little bit more involved.
And AI currently is used for intent recognition of what the email might be
about. And will-- I ate it and guide it in being routed to the right people
or into the right queue.
In some cases where it's a really simple scenario,
you might allow the AI to respond to it.
And hopefully LLMs can be used so that it sounds a little bit more human
and a little less templated in this interaction with these people.
That'll happen over time.
And eventually, I think we'll get to the place where emails will automatically
be dealt with
just like voice bots are dealing with phone calls right now.
Or chat bots are being done with web chats and with SMS.
I think it's rapidly approaching that scenario.
So I guess to clarify, your recommendation still for right now is to let the
agent
still be in control of all of that automation.
You can have in the background, hey, maybe the AI bot can summarize the
response. Maybe the AI bot can give an actual email.
But still, for right now, have that agent at least be kind of approved
and kind of being in control of how that conversation kind of flows out.
Would that be a correct way to think about that?
Yeah, I think that the feedback loop becomes really, really important
in the early stages of this.
And so having that human in the loop to test it and say, okay, yeah, that was
good.
Or no, that was bad.
It's really going to go a long way in training these AI elements
until they can reach a point where they can be, geez, listen to us,
we're talking about these other entities, where they can be self-sufficient
and not rely on a human to really double check them.
That training element is going to be a big thing for a long time.
And until we reach that point where we feel that confident,
that human does need to be in the loop.
And you're seeing that feedback loop every day.
I mean, if you go and go to chat GPT or something else to help form that body
of that email, there's the thumbs up or thumbs down, you want to help AI get better in a hurry
Keep giving the thumbs up and thumbs down.
That'll just make everything advance that much faster.
Now, so we got to wrap things up, but, and I hate to ask this question at the
end, but it's like, is it from an agent's perspective,
is it of their interests to be a part of this feedback loop
when it seems like the ultimate goal is to have the AI bot kind of replace the
agent at that point?
No?
That is more than a fair question.
The economic creative destruction that AI is going to cause
could end up being relatively significant.
I think the best way that you can look at this is, you know, what AI is
expected to do.
Yes, AI is going to eliminate some jobs, but AI is also going to create jobs.
I mean, it's expected that the global AI market is going to create
97 million new jobs by 2025, and that's not an insignificant number.
It's going to boost global economic productivity by 15.7 trillion by 2030.
I mean, so there's a lot of opportunity there.
If someone is hunkered down and they want to be an agent and that's all they
want to be,
yes, it could be dangerous to them, but there are always going to be
opportunities with AI out there to work hand in hand with AI or side by side with AI or in
areas related
to AI in customer experience.
The human is not going to ever go away completely.
It's just not.
It's just simply not.
So there's a little bit of danger, but I don't think it can be understated that
there's still
opportunity there.
Yeah.
And I guess I'm going to assume that most managers know this, but I think it is
important to have that understanding, have that conversation if you are
managing agents
because asking them to provide feedback one way or the other, again, my
assumption is
that they are also asking themselves like, what I'm asking to do this for what
type of
future.
And so I think it's really important for everyone to have that conversation,
know what the next
steps actually are and what the ultimate goal is so everyone could be on the
same page.
Well, right now it's a good paradigm because the feedback that they're
providing is oftentimes
making it so that there are tools that help them do their job easier.
They're not yet to the stage where they're going to be completely replaced, but
the feedback
that they're providing might, for example, make it so that this real-time agent
assist
AI element that's feeding them answers because it's listening in on the phone
call and then it's providing them resources to help them do their job.
If they're giving the thumbs up and thumbs down, it's more likely that the AI
assist is
going to give them the right things to do their job and make their job easier
and make the phone
calls last a shorter period of time and make them look better to the customer,
look better to their
manager and supervisor and yeah, you're doing a great job even though they're
letting AI do
all the work.
I mean, it's definitely not to that replacement stage yet.
If it's framed in the right way and the way it should be framed because of the
way the technology
is doing things today is let it help make your job easier and do your job
elements that are a little bit more difficult for you.
Does that make sense?
Thank you.
Yes.
And thank you for ending the conversation that way rather than doom and gloom
but more opportunistic
of what the agents experience can look like in the future.
I really do appreciate that, Jason.
You bet.
All right.
Well, we'll wrap things up here, Jason, again, thank you so much for your time.
And we'll talk later and thanks again for the session.
Thank you.
Appreciate it, Brian.
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