Welcome, and thank you for joining us for today's webinar.
I'm Kim Davis, editor at large at Martech.
The topic today, turn your customer insights into personalized high impact
email, and it's presented by Zeta and Martech.
Before we get started, a few viewing tips for you.
If you have any audio issues, you can click the audio icon on your screen.
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you can use the q and a section to communicate with us.
You can send questions and comments directly to the
speakers about the presentation at any time.
So I'd like to introduce Cara Trevunovich,
GVP, strategic solutions at Zeta Global,
and she's going to introduce you to the rest of the panel.
Great.
Thanks, Kim, and thanks to everyone for joining us today.
I think that, you know,
a really great way to start this is always with a quote.
Right?
We hear this a lot from clients when we're talking to them.
You know, getting your hands on data today isn't really
the problem.
Even being able to find some nuggets of insight that, you
know, in that data is happening.
But what does one actually do with that information,
and how are they using it to drive their email programs?
We get this question a lot. So now what?
According to a recent study by the CMO Council,
only six percent of marketers actually believe that they can
complete a three hundred and sixty degree view of their
customers from all the accessible data sources that they have.
And only forty three percent of them report that, you know,
they they can't really do anything with it.
They can't turn it into real time action.
And so we're really kind of struggling today with the all
the data that we have and what do we actually do with it.
So I think it's a really good opportunity to level set a
little bit on on what really is, a CDP.
As we talk to clients today,
everybody has a little bit of a different definition of what
they want their CDP to do, what they expect of it,
which is partly to blame for the challenge that we have in
figuring out how to maximize its value.
So if we think about what the right CDP should be able to do
for you, it should help you ingest and integrate your data seamlessly and accurately,
but you have to remember it's a garbage in garbage out scenario.
It helps to identify customers and manage profiles.
So connecting disparate identifiers from scattered
platforms and devices to real time counterparts and their
real life personas.
And then being able to apply, like,
deterministic and probabilistic matching so that you can
consolidate those customer profiles solving what we call
an identity crisis.
It also helps to complete real time analysis and segmentation.
Right?
You can understand your customer behavior, preferences, needs,
uncovering patterns that uniquely define these segments
of your audiences to help inform you how to communicate
with them as you move forward.
And finally, activating data and executing campaigns.
So this is where we start to see a lot of overlap with ESPs,
but the right CDP will allow you to seamlessly leverage real
time data across your MarTech and AdTech stacks,
not only to understand the customer behavior and
preferences in real time and at scale,
but really to execute that customer experience immediately.
And so we are joined by a great panel of folks
today to, help us explore what are these opportunities.
So as we navigate the convergence of your ESP and your CDP,
we're gonna talk a little bit about how this can help you
unlock the full potential of your customer data and your email program.
So, as Kim said, I'm Kara Trudunovich.
I lead our customer experience team at Zeta Global,
and I'm joined today by Jim Maroney,
the senior manager for customer data platforms and MarTech at
Accenture and Roy Wallen professor at
Northwestern University,
as well as the president of a CDP agency called Hamza.
Together, we're gonna help uncover how the relationship between your
CDP and your ESP can enable more streamlined marketing
flows, help you increase ROI, you know,
by those customer views and more and create more precise
personalization and segmentation.
So with that, I'm gonna hand it back over to you, Kim,
our moderator for the day for the first question.
Sure. Let let's start with the basics.
What are some of the prevalent challenges market challenges, I'm sorry,
marketers face today in effectively utilizing customer
data across their marketing efforts.
And I'm gonna ask Jim to kick off with this.
Yes. Thank you. Thanks, Kim.
So there are definitely a few issues that that we see
marketers facing today.
I mean, one of the larger ones is really the the data and
technology silos.
We have customers now who are engaging across multiple touch points.
We have very complex journeys.
It's no longer, you know, going from step a, b, and c.
It becomes a a real,
I would say, labyrinth, of possibilities for for the customer.
And, you know,
when you have customers that are really engaged in your brand,
the irony is that you have such a complex amount of data and
and such a large amount that you end up having the worst
data on your best customer.
And, you know, how do you get that message right?
And you wanna make sure that you, you know,
connect people in their households to make sure that
you you're you're giving a great message.
And I had a recent example actually where, you know,
I took my car in to be serviced, and they did an oil change for me.
And a few days later, my wife received an email, you know,
coming for an oil change.
And that just shows you that you have a lot of places that
do not connect data across their enterprise.
You have, you know, very complex ecosystems.
Any way we can simplify that would be great.
Also, another issue is that the time to value because now you have
very ambitious plans.
You have their digital transformation coming in very rapidly.
It's just a matter of how do you size these use cases effectively.
You know, most people go with this saying, you know,
we're gonna do as much as possible where that may not be
the best way to to initiate your change.
And then also the last one is really about that partnership
internally and, you know,
you have complex technology and complex organizations.
And it's really important for, you know,
the the technical groups and the nontechnical groups to
really understand what's needed because what'll end up
happening is the technical group goes off on their own,
purchases a product that marketing can't use,
and marketing goes off and purchase something that doesn't
fit into your IT landscape.
And it's really a matter of getting that partnership right
so then you have support from all sides of of the of the, organization.
I'll jump in.
I think that as we look at some of this too, I I yes.
You know, the data can be a challenge,
how you're democratizing it,
the technology that you're leveraging.
But I also think a lot of the challenges that brands have
today stem from
organizational challenges.
Right?
Like, I mean, organizations today aren't really structured to operate in
a way that you can use a single dataset holistically,
and complimentary.
And I I do think that that is, you know, something that as as
brands are really looking at, how do we better, you know,
talk to our customer and create that, you know,
holistic approach,
that, you know, that organizational silos are part of the problem.
And and it's not really just in the
how you use the data or how you access the data,
but it's also in having contradicting
goals and objectives as businesses,
and really not not being encouraged
to optimize that current, you know,
experience across the aisle from each other.
And so I do think that as brands are looking at, you know,
how do we centralize our data and what is that gonna mean for our customer,
you also have to address the what does it mean for your organization.
Oh, I'd like to add to that too.
I mean, when you think about take a step back with how customers look at brands.
You know, there's a value exchange there.
They're telling you who they are
because they're expecting value to come back.
And so the more that they tell you with filling out profiles
and, and, revealing their email address,
which is a big step sometimes.
They're expecting something as a reward for that.
There's a trust factor, but then,
as brands deliver on those more relevant experiences,
then consumers will, you know, reveal more, refer the brand,
talk to their spouse in the household, you know,
and there's more, you know, I'd like, Jim, your household, use case.
But the the thing that's important, I think,
is as marketing leaders, you know, is,
whether people are anonymous visitors or devices or they're,
you know, these are real people.
These are not email addresses,
and they're looking for those kinds of experiences.
So how do we deliver on that?
Let's say we are bad at this and we don't have CDPs.
You know, Cara, to your example, you know, we're gonna
deliver disjointed
frustrating experiences and people are gonna say, well,
this is just a place where I can get deals or I'm gonna go,
you know, my preference is for your our driver, your competitor.
So what the CDP is doing is not just identifying people, but
now you can see them across different email addresses.
We know one is a mobile device.
We know this is the one that's responsive.
We know that the these kinds of messages resonate with that
person in a given day or time of day and and so on.
So all of those kinds of insights come back,
and customer data is the foundation of that.
Customer data gives us, training, if you will,
for the AI and personalization algorithms that we're so in
love with at the at this point.
Without the customer data,
it's just a whole bunch of communications that customer
are are gonna say, like, you don't know me.
You didn't listen to me, and I don't see the value change here.
So it's a frustrating experience.
It's just I think that that value exchange conversation is
so important because,
and and I think you have to you have to take as a marketer,
you have to take a step back a little bit sometimes and say,
what's the intent of my ask versus what's the value of this
going to be to the customer?
And I it's I have a a an example.
And so in profile collection,
I worked with a client once who wanted to collect,
language preference.
And they had every possible language from Arabic to
Swahili, everything in between.
I wanna say they were, like, forty eight language options.
And, people started selecting their options and nobody was getting
their email and language.
And so it triggered this this chain of events that had an
influx of calls into the customer service center.
And people were very frustrated because they said,
I chose this language preference.
And when the client when we asked the client why they
weren't, they said, well,
we were never going to send it in in in language.
We were just curious.
Nice to know.
Yeah.
It just shows the importance of if you're going to collect
data, there needs to be a use for it.
And because it is that contract with the client with the
customer because they also do have so many options these days
where they can go to to one retailer versus another.
And if you don't get that experience right,
you're losing the you know,
you're not creating those moments that matter,
and you can easily you know,
one bad experience can have a ripple effect on your business.
And so that's very important to make sure that you have that.
So it's not just a matter of having clean data.
It's it's, well, how do we activate that data properly,
and how do we have a a proper strategy?
Just because we can communicate with the customer in many channels,
we have to understand which is the best one at the best time,
you know, the right message, the right time,
the right channel,
time.
You know, the right message, the right time,
the right channel is really the the mantra that we we all
should be following.
Yeah.
I think we've already opened up the issue of integrating email
service providers with customer data platforms.
I was gonna ask, Cara,
how does that integration enhance campaign
personalization and engagement with customers?
Yeah.
I mean, you know, so, a,
you can't really have a centralized view of the customer,
without centralized data and and having the ability to be
able to truly understand, what those behavioral actions are,
what are the intent signals.
But really being able to do that in a real time capacity
across channels is is really important.
But, you know, I mean, as you think about it, I mean,
you're also only as good as your your your slowest
integration too.
Right?
And so having that kind of connection
in in a in a channel that is, relationship based.
Right?
Email, for all intents and purposes, is a relationship channel.
And you you have a relationship with the customer.
It works best when you have a relationship with the customer.
And, you know, when there is latency,
that it is experienced with the data,
it actually can impact that relationship with the customer.
It is a channel that can leverage,
in a conversational way more than any other channel.
Your customer can respond,
and you can understand things about them,
and it really is a conversation.
So sometimes marketers treat,
treat the email channel as a bad blind date.
Right?
Like, you sit across the table from somebody and they just tell you
all about themselves and only talk about what they wanna talk
about, walking away from that conversation,
never having learned a thing about you.
Email is a channel where you actually can learn about each
other, not just from your interactions in channel,
but in your interactions with the brand and their totality.
And when there's a disconnect in that, you know, experience,
it is it is negative.
And so things like being able to have your real time points
balances show up in your email as a loyalty customer,
and it not being incorrect or five days late,
is really important.
You know, being able to understand that you were just in for an oil change, Jim.
Right? Don't send me a a hey. Come in. We miss you message.
Right?
I worked with an airline once who,
made sure they integrated their their seating systems and and their traveler,
with their loyalty program and their email engagement to say like, hey,
if you got stuck in a middle seat and you're a loyalty
member on your Monday commuter flight,
we're gonna give you extra bonus points and we're gonna
feature them in your email.
So all of the places that you can create that customer
centricity, is really important.
And it and sometimes it comes from unexpected places.
Same airline, you know, use suppression logic,
which we don't always use, well in email.
You know, you had a bad experience on your flight.
It was delayed significantly or we lost your luggage.
Maybe we shouldn't send you a promotional email today and
suppress customers from, you know,
those types of opportunities.
And so I think it is really being able to understand the
experience a customer has with your brand,
and and the integration between those systems in a real time
capacity allows you not to step in it, truly when, you know,
when something goes wrong or when something goes right so
that you can have that, you know,
positive experience and relationship.
And, you know, you've covered it well on on a business side,
but from an operational perspective too, I I mean,
again, as I mentioned earlier,
we have these complex landscapes and being able to, you know,
reduce one point of integration and to tightly couple your data
with who you're sending it to is such a big check is such a
big thing because now we could leverage that response data
and say, let's not send it to people.
We just sent a message recently,
or we sent a message and something went wrong.
Let's get something out there.
Or if we're just doing some reporting metrics on the
marketing side, we're sending a million emails,
but by the time it gets to the ESP,
it's filtered down to seven hundred thousand.
It's not really, you know,
a a great way to plan your campaigns either.
And then the additional with, you know, all the compliance,
you know, we have the GDPR, CCPA, etcetera.
You know, the less we have to move data around also, the better.
And so that also gives us a way to start to, you know,
add that layer of governance by tightly coupling the CDP with the ESP.
So I love the examples you guys were using.
You know, like, what it touches on is the context of what's going on with the customer,
and these are all moments that they have with the brand.
What does that have to do with email?
So we don't look at the world from an email address perspective.
You know, let's it's a Tuesday.
It's time for a campaign. Out they go.
Here's everyone that with a valid email address.
You know, here's a twenty percent off like we always do.
But that's ignoring all of the experiences,
and that was a great example about, you know,
a customer service con contact.
So what I think we need to do with customer data platforms is
get ourselves out of an email address mentality and get
ourselves back into the customer mentality.
There are moments with the brand.
There are, all these different relationships and experiences.
That's more data that's getting collected that the
communication now can go out this.
Somebody just mentioned a relationship medium can go out
and say good news, bad news, whatever it is,
but it's reacting in real time to what's going on with the customer.
Not the least of which is customers show up in lots of
different places, and those are mobile devices,
different email addresses, contextual within the
household, and all these things matter.
And so it's,
you know, building that relationship based on what's going on with
that customer, and that's where AI and these kinds of,
you know, real time operations, Jim,
to to to your point about streamlining and automating.
It's not just a matter of using the data that we collect.
It's also being able to react and to optimize those positive experiences.
And sometimes that's just lay off for a second and let
people, you know, have a different touch point,
and that could be more of a human touch point if it's a bad
experience, for example.
Very good ideas. Yeah.
So question for Roy. How do we know it's working?
The integration of the ESP and the CDP.
How what are the what are the KPIs,
and how do they reflect improvements in ROI,
customer engagement, and brand loyalty?
Well, I've spent my whole career with that very question,
Kim. How do you know any of this stuff works?
I mean, people are just gonna buy what they need. Right?
Like, what's the purpose of advertising?
You know, push the clock back.
How do you know any of this stuff makes any difference whatsoever?
So, I teach marketing metrics at Northwestern,
and let me try to boil this down to that my approach this.
First of all, what you measure is what you think is important.
So it's important for us as leaders to say these are the
business outcomes we're looking for.
Right? Now how do you prove that it works?
There's plenty of techniques for improving the
incrementality, and that's AB tests.
And I wanna talk about AB tests on steroids, which is like,
what if you did fifty thousand AB tests all at once, you know, in real time?
But with just the the very basic
different versions going out or different versions going out
related to a benchmark or a a holdout group,
there's lots of techniques there.
I think the big thing to go, to remember is we're measuring
not we're not just measuring clicks and not just measuring media.
We're measuring ideas.
So these are strategies like competitive strategies,
offer strategies, channel strategies.
So this is my challenge to anyone who's listening to this
to raise their game to say,
what we will measure are more business outcomes and higher
level ideas, And there's lots of ways to operationalize that.
We can look for pay per click and email click through rates
and things like that.
All very interesting.
But my challenge is to boil this down into whether you're
measuring email or customer data to elevate the KPI to
an executive and to prove the value by looking for business
outcomes, incrementality, ideas, test and learn, and all this,
kind of a strategic approach to measuring the effectiveness of
your communications.
And many times that's email, but it's not always email.
That's what a customer data platform is good at.
Well, and I think some of the I mean,
I there's so many things to unpack on this topic too.
Like, I think some of the challenges that I mean,
so if you think about, to your point of incrementality.
Right?
I started my career way back in the day with direct mail.
And, you know, if you think about it, right, personalization,
as a topic was born out of costly marketers.
Not because we wanted to be really great, you know,
experiential marketers for our clients.
It was how do we reduce postage costs?
How do we minimize our printing costs so that we can identify
the audience of people who are most likely to respond in an
incremental way?
And and that was really, you know, kind of the the driver.
Today, you have to deliver personalized experiences to
customers because they expect it.
They know that as brands we can do it, and they expect it.
And so I think sometimes because email is such a
measurable channel,
we do ourselves a big disservice because we're like,
well, I wanna know how did this subject line affect the the
outcome here, or how did this this specific blue button
drive conversion over the red button?
And the reality is is that you have to look at the experience in its totality.
You either delivered a very personalized relevant
experience to the customer or you did not.
And and what was the outcome of, you know, that
experience for the customer?
And I do think that, you know, it is it is challenging
today because we want to get into the minutiae of the
measurement and and because they we've been able to,
we wanna continue to do that.
And so I agree.
I think we need to challenge ourselves in thinking about
what is the business outcome that we are trying to accomplish.
And and we have to when you're doing that, you can't just say, okay.
We're gonna we're gonna improve our open rates today.
And and we're gonna do these really cool things because
sometimes your hypothesis is wrong.
And I'll give a great example.
Worked with a handful of retailers,
and the hypothesis was that if we created a more
personalized subject line, we would drive an increase in open rates.
And that is the theory that a lot of people have. Right?
We went through all of the testing.
We created these very personalized subject lines.
They were very unique.
We saw a zero zero difference in open activity from
those that were really personalized to those that were not.
And had we stopped there with our analysis,
we would have thought that it was a failure.
The reality was is that what we saw was that those who
received a more personalized subject line actually had a
higher rate of visitation to the website because the subject
line was very relevant to them.
It had, like, a billboard effect. Right?
And and I knew exactly what I needed to do.
I went to the website, and I converted.
And that's what we tracked was conversion.
And so those that had a more optimal subject line converted
at a higher rate,
visited the website and stayed on longer at a higher rate than
those who had suboptimal subject lines.
But it wasn't the outcome we expected.
And so if you're not really tracking against what your true
business outcome is,
if you're not establishing your hypothesis,
and if you're not defining what your actual definition of
success is, then you get all mixed up in the muck, and,
you know, it becomes about the blue button.
That's a great example.
Yeah. And and and I agree.
Like, a lot of times when when we hear KPIs, you know,
you ask what's important,
and then you get thirty different metrics.
And, obviously, those are not KPIs if you have thirty of them.
I mean, realistically, it's measuring, you know,
how well did we give the customer a great experience?
Do we see see customer satisfaction rising?
Do we see, you know, revenue rising?
Do we see engagement rising?
Or or really, you know, your high level metrics?
And then how do we break those down definitely do vary by your your use case.
So I definitely agree on that.
It's just a matter of, you know, trying to define those, you know,
those dashboards or those those information in a digestible,
way so you can make strategic business,
decisions based on that.
It's very difficult to do it against, you know,
thirty different metrics.
Well, then sometimes sometimes it's gonna vary from communication
to communication too.
Like, the one that always drove me crazy was when clients would
have very purposeful,
newsletters that had all the information in it that they wanted to share,
but then didn't understand why they didn't have a click
through rate or conversion.
Well, that wasn't the purpose of the message.
The purpose was information. It was brand awareness.
It was a different metric of success.
And so, you know,
there are sometimes you have to look very purposefully at the
intent of what that experience is intended to drive and and
have the right KPI associated with it.
Well, here's a question specifically about CDPs,
so I'll direct it to Jim.
How can marketers leverage CDPs to conduct real time analysis
and segmentation, which allows them to optimize
and adapt their campaigns in response to a swiftly changing
behavior of the customers.
Yeah.
So, you know, unlike a silo system like like a CRM, a
CDP is really spanning across many touch points and really
getting all the the places where our customers can
interact with your brand.
So it's really trying to show that complete picture.
And, again, since it's a very fast moving environment,
the customer is expecting, you know, quick feedback,
and so we have to understand what works and what doesn't
work fairly quickly.
So, you know, ways to do that is make sure that we have the the ability set up.
We have the organization set up.
We have the technology set up.
We have the ability to, you know,
dynamically create segments versus, you know,
static list or rules.
We have to understand, you know,
when that customer is going to churn.
And, you know, an example I had,
a little while ago, I was at my son's swim meet,
and it was at the end that I said, you know,
I need to buy a few, you know, basic apparel,
some some t shirts, etcetera.
So I jump on my phone.
I start to, you know, make my purchase,
and then I put in my coupon,
and then I hit I hit the send and coupon expired.
So I'm like, alright. It's basic.
I can go to another retailer and find this information.
So I go to another retailer, and within that time,
I receive an email saying, hey.
We noticed that, you were buying something.
Here's a here's a coupon for, you know,
whatever the percentage off was.
And then just because I got that message at the right time
versus, oh, we see you have items left in your cart,
but they were able to contextualize,
they were able to to to know there was an immediacy that I
was ready to purchase and I just was a day off of my coupon.
So they sent me another one, I made the purchase,
and now I still purchase from them.
And so just that example alone just shows you how being able
to, you know, identify the those moments that matter,
identify the right touch points, and say,
if we don't do something quickly,
we're going to we're going to lose that sale.
We're going to make a a worse experience,
and we're not going to, you know, satisfy the customer.
You know, by doing that and being able to analyze real
time, it's very important.
And, again, real time does vary.
I mean, in in the case like that, you know, seconds do matter.
In other cases, minutes do matter.
In other cases, hours do matter.
But just to make sure that you get that message off in the
proper time and in the proper context to your,
customer makes a difference.
Jimmy, you're on a roll with these great examples.
I gotta tell you.
So I wanna build on that. So I call it always on testing.
And, I think about how we let the technology
look at and analyze thousands of combinations of whatever
we're interested in.
That could be messages, offers, delivery times we talked about before.
And this is where we go from a AB test to, you know,
thousands and thousands of testing.
We already know that triggered communications based on
behaviors works, you know, one x, two x,
four x better than outbound.
We already know that. So how do we scale that up?
And I think about testing as this always on thing,
but I wanna go back to something really important that
Cara said, which is what are the business outcomes?
It's not just increasing,
energy and heat and, clicks.
There's we have business outcomes that we've identified
as important, and that could be customers are buying more.
There's an attachment there.
Or customers are buying more frequently. They came back.
Or in to Jim's example, they stayed with us longer, and they
we prevented churn and so on.
So I think of the technology has a job that they can do really well,
but we as leaders have a job to define those outcomes and to say, you know,
we're gonna go back to what those outcomes are when we
start reporting out on the incrementality of the overall
investment in this techno technology.
Yeah.
And I think too I mean, yeah,
there are absolutely those moments where,
you know, the the the minute matters or the second matters.
There's also a scenario where being able to contextualize
somebody's interaction with you over a period of time is really
important as well.
Right?
So, especially on something that a purchase that people are going
to research quite a bit or something that is a a high a
high value purchase.
I the example I always use is, you know, hotel company.
And this is this was my own personal experience. Right?
Hotel company, I travel with all the time.
Loyalty member frequent their website.
I use them both for business and leisure travel.
Have never stayed with them in a property in Hawaii because
I've never been to Hawaii.
I'm on their website, you know,
trying to figure out which island I wanna go to.
And over the period of thirty days,
I spent a significant amount of time on their website looking
at hotels on different islands.
It was clear I had no idea where the hell I wanted to go.
Wonderful opportunity for them to understand or recognize this
series of behaviors to say, hey, she might need some help.
Right?
And this is where you can be a valued adviser, a trusted
adviser, and a customer experience to say, hey.
If you're looking at different, you know,
destinations in Hawaii based on where you've stayed and
traveled with us before, you might really love these places.
Right?
They know so much about me, and they didn't instead of looking
at, not just one signal,
but a series of signals in my behavior contextually,
they they they left that opportunity on the table.
And quite frankly, I didn't end up in Hawaii.
I ended up in Cabo, and I didn't stay with them. Right?
So
there are these moments where you can really help the
customer solve a problem,
and you can understand that problem based on their behavior
and really help move that along.
And I think that there are these that there are those
moments and those opportunities to to do that.
And I think that sometimes as marketers,
we are looking so myopically through a very singular lens
that we miss some of those bigger opportunities.
Well, of course, you're you're facing an enduring challenge with the
kind of strategies we're talking about,
and that's overcoming data silos and ensuring there's a
seamless integration and sharing of data across the
various platforms in the tech stack.
What are you gonna do about that, Roy?
Uh-oh.
Back to me again.
Well, I I think of CDPs and data silos as a challenge, and
the challenge is for us as leaders to step up and lead.
And so I think about marketing leadership,
and that's what I teach at Northwestern.
And CDP projects are a moment for marketing leaders to emerge.
So what does that mean?
It means don't buy this on your own and create more silos.
That means partner with technology.
And sometimes if technology is leading the initiative,
we may get into a moment of composable CDPs, best of breed,
components that go into what you've already built.
Great. Let me be a partner.
That doesn't mean I work for you.
That means I have to be articulate about what are the
use cases and what are the marketing outcomes that we're
looking for from whatever we built.
Sometimes marketing is in the lead,
but we never do it in a vacuum.
We always collaborate with technology leaders,
and they want us to lead.
They want us to be articulate about not just use cases,
but how they roll up into a business case and and how we're
gonna prove the value.
We've been talking about that.
Zeta is particularly good at looking at use cases and business cases.
There's a CDP institute, library,
which has some great content on that for anyone listening,
you know, that wants to to to get more.
But I say, take this as a moment to articulate, you know,
what are we going to achieve with this piece of technology?
Use cases, priorities, test plans, personas,
and it's also there's just one more little point here on personas.
It's a moment for marketing leaders to go back to customer
service, you know,
people on the phone on the front lines and say,
these are the people you're talking to according to our research.
These are the messages that resonate.
These are their pain points.
This is why they're frustrated.
This is how they buy from us and what their competitive choices are.
All of a sudden, people in the firmer are like,
that's really valuable context.
Thank you for doing that.
So, again, it's a moment for marketing leadership,
and that's a way to break down those silos.
The the we started today with data is everywhere. You know?
But now how do we make some sense out of it,
and how do we recommit to customer centricity?
That's our moment to shine.
And I think when when we talk about silos, like, you know,
we did talk about this early on.
Right? You've got data silos.
You've got organizational silos,
and then you have organizational battles.
And, for whatever reason, IT, your tech teams,
and your marketing organizations
seem to be in constant friction and and consequently to your point.
Right?
This is who you're gonna have to be working with the closest
to actually solve this problem.
And and so it is time to, you know, make if you haven't yet,
befriend your your IT team as marketers,
and IT leaders need to befriend their marketing counterparts
because, you know,
it is together that that these types of
problems are going to find a resolution.
It's and it's going to ease the challenge just not just across the, hey.
We've got this social team and this display team and this
acquisition team and this email team.
It's it really is about making sure that everything is
set up in a way that you can democratize that data across
the organization,
and and in the right way,
in a privacy compliant manner that gives people the access,
they need when they need it.
But it is gonna require tight partnership between,
IT and marketing to make that happen.
Yeah.
And also too, it it does require strong governance and definition
because, you know,
just because you can bring data in doesn't mean you should.
Just because you can access the data doesn't mean you understand it.
And it's really important, you know,
for that collaboration that we spoke about is, okay.
Well, what does the state mean? Do we need it?
Is it accessible?
What's the value it's going to to drive for us?
And then we also have to make sure, you know,
can we secure this data?
Just, again, just because we can bring it in,
we have to make sure we can secure it because, you know,
with first party data now becoming prevalent and the
third party data, you know, the cookies being deprecated,
there's a lot of trust that the customer is giving us.
You know, that if they're gonna give us that information,
we have to make sure that we're using it wisely and that we're
securing it, that we're not going to have a breach,
and that we're, you know,
going to use it for purposes that that they're expecting it to.
And if we don't do that, you know, that's a easy way for
the customers, you know,
to lose trust and your brand to lose trust.
You know, in a in an organization that's, you know,
large and and complex, you know,
most of the issues tend to, you know,
not actually be technical.
There there's there's a lot of that, you know,
whole people process technology,
and it's really comes down to the a lot of times the process
of how do we get this data together because I could dump
it all into a data lake.
Great. But is it useful?
And so we just have to make sure that we have cope with a
strategy that, you know, we bring in the right people.
We bring in we have the right partnerships,
and we're able to take that data,
activate it securely and wisely and make sure that we,
you know, come out with a successful outcome for the client.
Well, I have one last question.
I have to say it really is a hot topic in the MarTech space
right now, And that's how you anticipate the role of CDPs
evolving in marketing.
Are there any emerging trends or technologies marketers
should be looking out for?
Absolutely.
I you know, I think that, you know,
the CDP is really kind of just the it's the jumping off point
for everything that is is coming.
Right?
I mean, really being able to have that data centralized and have it
aligned and being able to see that customer holistically
is is step one of what's to come.
And when I get asked about this a lot of times, I I I flash
back to the minority report.
If you guys haven't seen the minority report,
it's a great movie.
Also a little creepy,
but there's a scene in the movie where Tom Cruise is
walking through town,
and all of the advertising is changing as he walks by
specifically for him.
Right?
And and it is across his experience everywhere he is in
home, in town, in office.
And and while it's a little bit of a ways away, it is the
culmination of everything that we talk about.
Right?
Personalized one to one experiences across multiple
channels, leveraging AI to help with the predictive nature of
what somebody is going to want or need next.
Not reflective of their historic,
behavior, but leveraging that historic behavior to inform.
And I think it's really important to start thinking
about these things is how do you leverage what you know
about somebody in the past?
How do you marry that with what signals they are displaying
today at this moment in time?
And what is the predictive value that that brings to, a relationship?
And I think it's important to not think about that just in
a marketing context, but also in how you affect your
customers experience in its totality.
And I'll give two quick examples.
One, worked with a client who
leveraged AI, and everything they knew about them
to not inform how they marketed to them,
but to inform who answered the phone when they called customer service.
Right?
Are you somebody who tends to need a little more help or you
need more time or you tend to get angry?
And let me put somebody on the phone with you who immediately
is going to be able to answer your questions.
Based on what you purchased last,
do we believe that your needs are gonna be pretty simple,
and we can put you through an automated chatbot that will
answer your questions?
And and really being able to optimize that customer service
experience, it had nothing to do with how they marketed,
but had everything to do with how the customer responded to
their brand at moments in time,
which does impact then how they interact with your marketing.
Right?
The other is is, you know, looking at, you know,
sometimes you get caught up in past behavior.
And depending on your brand,
just because what I do with you today
doesn't doesn't put me in a box to not do something else with
you in the future.
And so I worked with a big box
warehouse retailer that,
the majority of what people bought was boxed wine,
cigarettes, and toilet paper.
That's what people bought. Right?
That's what they buy in bulk, especially during COVID.
And when they started doing, you know,
predictive models on what is somebody gonna buy next,
it came back with six kinds of cigarettes and a box of wine.
But listen, they're gonna buy that anyway. Right?
So how do we leverage their behavior to predict what else
they might need from a brand?
And started looking at their other behaviors and started
recognizing that they're they needed things like patio
furniture, or they needed a new grill, or, you know,
other things that were higher margin and not what they were
just gonna buy from me today,
but what we could shift them into.
And I think that it's important to not lose sight of that
predictive opportunity,
leveraging, you know,
AI and machine learning and decisioning to help us better
inform those experiences, but it is all centered on a
foundation of valuable and and accurate data.
Because as I said at the beginning, it's a garbage in,
garbage out scenario.
Yeah.
And to to that point, it's really, you know,
we're we're seeing the shifts.
It's not about selling product.
It's about enhancing that customer experience to get down
to that, you know,
that segment of one essentially now and and to really to to
target that that message.
And and, you know, from a another CDP perspective, you
know, we're also seeing a lot more focus on data,
and we're we're seeing, you know,
ways to to simplify your technology and and marketing landscape.
You know, you're seeing composability now coming in.
You have a lot of companies who have a a snowflake as their back end,
or they have some other platform that they don't wanna
move the data out because compliance and privacy is
becoming more, you know, transformative,
and you're seeing it more prevalent across.
It it started, you know, in GDPR.
Now it's in probably twenty something more countries now,
and it's just growing.
In in the US,
we're seeing it roll out state by state on a regular basis.
So it's only a matter of time before it becomes, you know,
a global standard.
And, you know, we also want to make sure that, you know,
we make it easy for people to get data in.
So you're seeing these, you know, what they call zero e ETL,
which makes it easy for someone to bring that information
because, you know, really,
that time to value is so important that the that the
landscape is changing so much that we wanna make sure that we
have a CDP that we don't take twelve months to implement,
that we get some results out fairly quickly.
And, you know, last point is also we're seeing AI become more prevalent,
whether it's, you know, helping to do product recommendations,
helping to understand what segments we should build,
helping the user to make better decisions within platform itself.
And all those features are just starting to grow to to really
start to become a a more holistic approach and to really
start to get that experience for the customer to to be,
you know, optimal.
So Yeah.
Great examples.
I guess, you know,
the way I approach this is I'm really excited about the future.
You know, all this disruption and all this hype about artificial
intelligence, again, it's our moment as leaders to say, okay.
What does that actually mean?
So there's, improvements in the models.
There's more predictive ability.
But how are we gonna harness that?
So I think this is our moment to say,
let's get out of this campaign mentality and get more into the
customer and relationship mentality.
It's a moment to lead to say, okay.
Customer data is really important.
Okay. Why? How do we apply that?
All these digital activations and, Carrie,
you mentioned a digital signage.
Okay. How are we gonna do that?
I mean, we all remember the minority report moment.
So what does that mean to our customers,
and what are we doing to,
plan for that and to experiment into that?
So it's a moment to say, you know,
all this AI is gonna come around into different outcomes.
Why is that important?
So who else is gonna do that except us as marketing leaders?
We have to articulate this is how we're going to meet the future.
So really exciting conversation, you guys. Yes.
Exciting times and, great insights there.
We have to wrap up now.
On behalf of Martech, I'd like to thank Cara, Jim, and Roy for
the conversation and everyone out there for attending.
We hope you join us again soon.