September 26, 2024 • 27 mins
AI is everywhere but we in the marketing world are only scratching the surface of what is possible. We’ve seen the public at large test out these new tools from generative AI like ChatGPT and Dall-E to the more niche sectors of predictive AI.
Now, we’re seeing marketers start to experiment and ideate as they start building out new campaigns.
In this episode, Brett is joined by Oliver von Wersch, a Partner at Statista, and Crystalyn Stuart-Loayza, the Chief Digital Officer at Citizen Relations & Mekanism. They’re talking about a comprehensive survey of 200 CMOs on the future of data, marketing, and AI.
If you’re thinking about how to integrate AI into your marketing processes, and how AI will shape the Marketing Departments of the Future, you won’t want to miss this discussion on how to prepare for this shift.
-Subscribe to Partners in Possibility on all podcast platforms to get your finger on the pulse of marketing!
Are You Ready For Marketing And AI Report
Now, we’re seeing marketers start to experiment and ideate as they start building out new campaigns.
In this episode, Brett is joined by Oliver von Wersch, a Partner at Statista, and Crystalyn Stuart-Loayza, the Chief Digital Officer at Citizen Relations & Mekanism. They’re talking about a comprehensive survey of 200 CMOs on the future of data, marketing, and AI.
If you’re thinking about how to integrate AI into your marketing processes, and how AI will shape the Marketing Departments of the Future, you won’t want to miss this discussion on how to prepare for this shift.
-Subscribe to Partners in Possibility on all podcast platforms to get your finger on the pulse of marketing!
Are You Ready For Marketing And AI Report
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
It's really about how as an organization we can use
the power of AI and predictive technology to move our
business forward. And when we get to that altitude, we'll
start to I think CEE cmos really understanding the value
of that investment because it's fundamentally changing the impact of
everything we do in marketing that single channel.
Speaker 2 (00:29):
In an ever changing world. That's all about stained connected,
building connections and seeing where the next collaboration takes a
marketing campaign from an initial brief to the follow through.
What paths are going to make a campaign success more
than a possibility. Hi, I'm Brett Marshand, CEO of Plus
Company is Partners and Possibility. AI is everywhere, but we
(00:54):
in the marketing world are only scratching the surface of
what is possible. We've seen the public at large testo
new generative AI tools like Chatgipt and Dally to more
niche products that use predictive AI to do all kinds
of things. Now we're seeing marketers experimenting and ideating as
they start building out new campaigns for their brands. In
(01:15):
this episode, I'm joined by Oliver von Wersch, a partner
at Statista and Crystal, and Stuart Louisa, the chief Digital
officer at Citizen Relations and Mechanism. They're talking about a
comprehensive survey of two hundred cmos on artificial intelligence, marketing
Measurement and the Marketing Department of the Future speaking of AI.
(01:42):
I think the finding was that forty three percent of
marketers understood and saw benefits in AI, which means I
guess fifty seven percent don't. So what's going on there? Oliver,
maybe talk a little bit about that.
Speaker 3 (01:55):
Yeah, it's the same what happen. I think if you
would ask questions about advertising identifiers and first body data sets,
because everybody knows that it's needed. That's the case for
I as well. Everybody knows that that you should experiment
and you should II tools in your organization by means
(02:16):
of campaign effectiveness, attribution measurement, reporting and so on. But
you still have the alternative, right, it's still there, and
it's the tech stack, and the setup is running and
has been running for for years and years successfully, and
so maybe some things just have to happen and to
(02:37):
make you react.
Speaker 2 (02:39):
In the end, what do you see as the challenges
and implementing a you know, AI as part of their plans.
Speaker 3 (02:44):
Things that are more easier than others. So using AI,
for example, creative generation or creative personalization is a relatively
easy task. You can implement that isolated or stand alone
into into your tool sets and into your processes. If
it comes to multi channel or multi multi point attribution,
(03:11):
that's a different story, right, because you have to attribute
and then to evaluate all the different attribution points which
are analogue, which are digital, which are digital digital with
cookies which are in app or CTV and so on,
and to just say like hey, let's throw throw this
all away or in my thoughts, throw it away and
(03:31):
put AI instead, that is that is a huge process.
So for example, also one point we found was that
that the cmos are hesitant to like hand over the
the spending distribution over channels to the AI, which is
like the holy gray of the of the of the
operative media planning as we know. So that's completely understandable, right,
(03:56):
So if I still have the alternative, if I still
have the systems and the teams up and running, who
would do it in that way? Right now? I don't
simply press the button to switch it.
Speaker 2 (04:09):
And probably a feeling of lack of control too, right,
I mean, because marketers and agencies, by the way, you know,
want to have a clear say and what they're going
to do, what channels they're going to use, what creative
they're going to use, what's going to work and what's
not going to work. And the idea that you've got
a AI bought or model that's actually telling you what's
(04:30):
working and not working. You know, it's a little bit
scary for some.
Speaker 3 (04:34):
I presume I'm a chess player, and many AI developments,
also from deep Mind, which has been acquired by Google,
many many development companies in the space started with chess programming.
And the thing is, once the algorithm has solved, it
has solved chess, it's unbeatable, right you, No human can
(04:58):
ever beat a computer daily and the data or even
not the world champion. Maybe it's a bit comparable here.
If you hand over your campaign attribution, if you hand
over your spending distribution over channels to the AI, it's
on the one hand, unbeatable, but on the other hand,
it changes the entire organization. And there I think it's
also somehow justified to be a bit hesitant. You shouldn't
(05:22):
be too hesitant, and you should of course tests and
you should develop test cases with your partners.
Speaker 2 (05:28):
What are you hearing, Cristalin about how marketers are feeling
about using AI. I mean, I presume there's different cohorts
across your clients at when it comes to utilizing it.
Speaker 1 (05:41):
Yeah, I thought, you know, some of the inputs from
the way the cmos responded to this survey were interesting
but also aligned with what we're seeing kind of on
the ground real world scenarios. I think we're on sort
of a traditional transformation trajectory where some of like our
more early adopters, are being more comfortable with testing and
(06:02):
bringing more parts of their business from creative which is
usually the easiest, through to more day to day workflows
and into much more complex decisions on how they're managing
their overall business. But I think what we're seeing as
we look at that traditional sort of curve of adoption
is there are factors of fear that certainly come into play,
(06:25):
but there's also factors of leadership and the need for
leaders to be bought in and brought along. There's a
need for legal and regulatory teams at our largest scale
companies to be brought along in the process, both to
minimize risk but also to forecast challenges, especially with some
of the technology still being fairly unstable, and I do
think that the priortization of the investment is still an
(06:48):
important factor for cmos. Many of them have so many
opportunities for where they could integrate AI into their mix,
but understanding where to spend and at what scale seems
to be a significant contributor to or a barrier to
why many have yet to actually action the way we
know the technology is capable of supporting them.
Speaker 2 (07:11):
Speaking of creative you both mentioned that both that marketers
are using it for creative optimization and generation. You also
talked about it Crystal and just now. I also thought
it was really interesting that I think fifty three percent
of marketers said that they actually see more creative roles
with AI versus last, which kind of I mean, on
the surface, seems counterintuitive.
Speaker 3 (07:30):
So yeah, this is kind of everything that gets automatized
freeze resources. Right. So, if you look to philosophers in
the nineteenth and century, it was about industrialization and what
the industrialization could like free unlock potential and time of
(07:51):
people for creative for painting and playing music and so on.
It was the same with digitization, and it's the same
with I guess AI distribution of AI. It's the next
revolution and it is binding resources when you are implementing it,
but in the end it is unlocking your personal resources
(08:13):
because in the end humans will have more time for
other things, and those things likely could be a creation
and ideation.
Speaker 2 (08:21):
Crystal, you've talked about the democratization of creativity with AI
to me in the past. Maybe just talk a little
bit about what you mean by that.
Speaker 1 (08:30):
Yeah, I mean, I think what we're sort of seeing
as part of one of the best upsides of AI
and creative is the democratization and the ability for a
number of different team members to enable new forms of creativity,
whether that be able to produce higher volumes of content
at scale, to be able to rapidly spect or prototype
(08:53):
content without having to have a long course in photoshop,
being able to generate images like insight of PowerPoint dex
with ease. Everybody is capable of really supercharging their own
creative powers. But I do think the stat around fifty
three percent expect an increase in creative roles is probably
also reflective of a shift in the types of creative
(09:15):
roles that we'll probably see in the future as we
connect more data and more insights around consumer into our
creative process. We'll probably start to see the rise of
kind of a new class of creatives, those who not
only understand design systems that help us activate a visual
idea across a lot of platforms in AI, but also
(09:37):
those who understand a bit more of the analytical bridge
with creative and can make more adjustments to the way
they're thinking about both messaging and creative pairings. And we
see that trajectory anyways, as we see an increase in
personalization and the desire to have more personalized content as
part of what we offer beyond the sixty second spot
(09:58):
and the big production element. So a new breed of
creative class I think is certainly emerging. And it's a
really exciting time, I think to be a creative.
Speaker 2 (10:08):
And presumably you can test ideas really quickly with AI too,
right in minutes and instead of waiting to do a
focus group and waiting to put it in the you know,
a creative assessment survey or research, and that I mean,
it's got to be powerful for creative people if you
think about it being able to go to whether you're
(10:30):
internally in marketing and going to the rest of the
organization or you're an agency going to the marketer to
be able to say, listen, we know this is going
to work well.
Speaker 1 (10:37):
Between what we know in retrospect about how programs have
performed and also the predictive capabilities of AI, we're able
to get a lot more inputs into the way we
shape our creative So between the ability to have better
insights on past performance and how consumers are responding to
creative and also the predictive capabilities of AI, we're starting
(10:58):
to see this sort of emerging capability of creatives as
analysts able to intake data and work with AI to
help generate stronger messaging and stronger design, which I think
is going to be unleashing kind of a new breed
of creative analysts, which is very exciting.
Speaker 2 (11:15):
What else in the surveyed, like did you find interesting
or unexpected?
Speaker 3 (11:23):
Yeah, it is like the the kind of implementation of
artificial intelligence on different levels. That was the most interesting thing,
So that the marketers basically said, yes, it is relevant,
Yes we are experimenting, Yes we are we are using
(11:43):
it for certain topics, but no, we are not in
place right now. We feel not in place right now.
To have an integrated strategy to implement AI into our companies,
which is yeah. And if I compare that again to
the media companies we have talked to, it's this same impression.
There there are kind of a few a few leaders
(12:07):
in in strategic implementation and and also here we find
we found leaders in strategic implementation who have a full scope,
who are invested in investing in all AI possible AI
use cases. But the majority of companies were like hesitant experimenting, yes,
and also aware of the strategic relevance and the long
(12:29):
term relevance, but experimenting in a in a limited playing field.
And that's the most interesting question is how how how
does this evolve over time?
Speaker 1 (12:39):
Right?
Speaker 3 (12:40):
So when when do you get the full scope in
in into your into your plans and hope who will
be the first? Right? So, if if one f FM,
c G would be the first in in fully implementing
it everywhere, there will there will be followers, and they
and and and the competitors will then act more quickly
(13:01):
like in any other kind of development in the internet. Right,
if you if you have a first mover, then the
first move has a competitive advantage.
Speaker 2 (13:10):
Chrisline, anything you from particularly interesting in there that we
haven't talked about.
Speaker 1 (13:14):
I think it's really interesting that we saw in the
survey results that a number of cmos felt comfortable leveraging
creative innovation in AI as part of kind of the
play and unleashing creativity, and some have started to look
at ways to use AI as a part of their
reporting process and maybe lightly into attribution. I think the
(13:35):
big middle ground that really will unleash AI at scale
is as many of our cmos begin to leverage AI
for day to day workflow automation. You know, there's been
huge movement in the last several months around releases of
AI features inside of our primary tech platforms, you know,
Google's Gemini, Metalama III, a lot of open AIS, no
(13:58):
GPT advancements, They're even bigger and bigger and bigger announcements
that happen each month. But once we start to see
some of that work take place in automating our day
to day workflows, then I think cmos can start to
move towards more transformative uses of AI. So I think
we're getting into a timeframe where automation is going to
(14:19):
be an important use for AI, but next will be
transformative motions doing things differently than we may have done
them in the past. And we all know that that
takes time for big organizations, not just to automate, but
then to transform the way they plan, the way they measure,
the way they optimize, the way they reimagine our relationship
(14:41):
with customers, and that will take time and operational shifts.
Speaker 3 (14:46):
Yeah. One interesting thing I found is how if you
look at the cuculs era which comes comes nearer, measurement
is definitely an issue, right, So it's already now it's
an issue with all the channels and all the different
the way of the do you have cookies and IDs
and apps and services and so on, But it will
be a big issue. So that that some people in
(15:06):
the industry started talking about probabilistic measurement, right, so you
guess which means which is like the fallback in in
in analogue media categories. And that's interesting because that has
to be done and that is crucial because if you
can't measure, you don't know about your campaign success and
(15:27):
then it's and then a few things are messed up.
Speaker 2 (15:31):
Yeah. In a former podcast, we talked to Aviy Goldfarb,
who you know wrote a book which is all about
how AI is fundamentally about prediction, and therefore you would
think that one of the fundamental ways it's being used
is in measurement. So I think it's it's very insightful.
It's you know, one of the reasons we fundamentally put
(15:53):
measurement and predictive measurement at the at the foundation of
AOS because I just you know, I think I and
others thought that, yeah, if you're using AI to generate
new creative etc. Might make you a little bit more efficient,
but if you don't know whether it's working or not,
who cares.
Speaker 1 (16:08):
It's fair, it's a fair point. I think part of
what the challenge around measurement has been historically is that
we're still looking at measurement and silos, and so the
return on an investment in a new measurement strategy might
only be as good as where which channels you can
apply that predictive insight to. So part of what we're
trying to I think, evolve mindsets around our cmos is
(16:32):
that first we have to sort of integrate all of
the different data sources that we're using to look at
our holistic approach to marketing. We have to think about
an integrated measurement model. We have to leverage integrated audience
segments that we're all optimizing around, and we have to
set universal KPIs. And if we do that well at
the beginning, at the onset, at the strategic layer, then
(16:55):
the investment in a platform that allows us to reimagine
and measurement and predict measurement becomes much more effective than
just optimizing return on AD spend or specific channel adjustments
and programmatic It's really about how as an organization we
can use the power of AI and predictive technology to
(17:15):
move our business forward. And when we get to that altitude,
we'll start to I think see CMOS really understanding the
value of that investment because it's fundamentally changing the impact
of everything we do in marketing, not single channel.
Speaker 2 (17:30):
Yeah, and change management around it.
Speaker 4 (17:31):
It's going to be massive, right, like massive Yeah.
Speaker 2 (17:48):
Speaking about the core opportunities in the future, maybe the
most important one when we talk about sort of system
change the impact of AI is what the actual marketing
departs mint and marketing jobs are going to look like
in the future. And love to hear your thoughts on that.
Speaker 1 (18:06):
I think that it's there's a lot of different analogies
used to talk about, you know, sort of the way
the AI is going to catapult us into a new
era of marketing. I think back myself to the various
kind of decades of the web. I mean, when we
moved from radio to TV, when the sort of dot
(18:27):
com error, the way social profoundly changed our ways of working,
you know, the influencer bubble. We've seen some of these
kind of ebbs and flows in channel historically, and we
know that each one of those profoundly changed the way
we market, I mean profoundly changed the way we build strategies,
the mix of things we do. But those were essentially
(18:47):
channel changes largely. I think what's so interesting about AI
is it is a systems level change. It is fundamentally
augmenting human intelligence in a way that is going toffect
every channel that we leverage and have an effect on
each of those parts of the mix. And so I
think what is likely to happen is because of the
(19:08):
profoundness and the scale of how AI can impact our
day to day work, it would seem that we would
go faster towards AI integration as part of everything we do.
But in fact, I think we are seeing that there's
a huge learning curve, and it's probably going to take
some time for the most of our sort of majority,
(19:30):
our later majority, to actually really comfortably change their ways
of working. I say that from our vantage point working
with clients, it's going to take time for client organizations
to ready themselves. But with all of that said, the
immediate near term effects that I think will take place
are definitely going to be around automation. They're going to
be around evolving the way we plan, measure, and optimize
(19:51):
as one of the first orders of business. And they're
certainly going to be around creating and up leveling our
talent to function more like systems engineers. Know our chief
data officer, Michael Cohen uses that term regularly that we're
moving towards a time where we can engineer technology to
help us solve any number of problems in our day
to day thus creating kind of this generalist practitioner that
(20:15):
we think is probably going to represent the future skills
of our team. So we're already starting to build towards
that capability using technology and machine learning to help us
solve challenges across channel.
Speaker 2 (20:29):
Oliver, what do you what do you think it's going
to be the impact to marketing marketers in the future.
Speaker 3 (20:34):
Two very plastical or like two images. So first, working
less with spreadsheets in daily work, right, so not using
spreadsheets anymore for various reportings for planning for my manager
was once a report on the on the performance in
(20:56):
the last week of the channel. So that is taken
a way and that is solved, and that that that
unlocks time for humans and agencies and on the advertiser
side because they get rid of boring activities and they
can focus on more creative activities or have a have
an extra day off. I don't know. Secondly, it's it's
(21:21):
we we will be able to digest and process more
data than right now, and that is also giving freedom
to the to the future organization because processing power of
course will be an issue and energy consumption will also
be an issue. But in theory you are able to
process more data to drive better decisions. So that is
(21:44):
that is also on the positive side. By the way,
one next study I would love to see or to
make is the study on how AI generated ads are
perceived by consumers, because we should make it too easy
and say like here here, here is our personalization made
by an algorithm. We just play it out and if
(22:06):
one ad clicks better than the other, then is the
better performance. There will be perception of consumers towards AI
generated content and AI generated ads, and this might be
multi dimensional, so it's not only clicking it, but it's
also a perception of the advertiser that does it, and
(22:29):
that's interesting. Consumers life and normal people love to play
around with a mid journey and so on, but sometimes
mid journey results are frightening, and so could AI generated
ad speed. So that's also one interesting piece of research
which has to be executed.
Speaker 2 (22:48):
I guess well, Oliver, that sounds like a fascinating research study.
I think we're I think we're talking to a statistical
about a study on AI and creative in the market
and measuring its effectiveness. So it sounds like we'll have
that study together. One last question, crystallin chance to give
(23:09):
us a plug because I know you're working on some
really interesting territory around responsive AI and you know how
that can both help your teams but also clients in
the end. Maybe talk a little bit about what you're
building there.
Speaker 1 (23:24):
Yeah. One of the important ways that we've been working
internally to leverage AI in our day to day is
by thinking about tasks that we couldn't have previously done
because they were either too manual or required too many
data sources that were disparate, that we can now accomplish.
And for example, one of the products that we've had
in R and D for the last six months is
(23:47):
called responsive content, and it actually allows us to do
something we've always wanted to do, which is listen to
what's happening in the news media and social and search
and reviews and forums and in mediately synthesize all of
that information into a topical brief that is on brand
for a brand's area of interest and expertise and concern,
(24:11):
and turn that into daily, weekly, or monthly content concepts
and briefs, along with generative content samples, so that brand
or individual executive thought leaders or smaller sized brands who
couldn't work to produce high volumes of content in the
past could really have access to this development of content
(24:34):
at the speed of culture. And what's cool about a
platform like this is that it isn't one of these
back end dashboards that you have to get in and
manage yourself daily. It just sends you an email digest
of all of the on topic content that you could
be publishing during a really relevant period in culture. And
so we love the idea that AI is really empowering
(24:55):
us to be able to do things we could never
have done before in ways that are clients can really
find value.
Speaker 2 (25:02):
So if so, let's say I'm the Adida's client, which
Adidas is our clients, you know, and it's it's during
the euro I could now based on what's being discussed
and what's in the news in real time, it would
send me a and obviously a data sells lots of
(25:22):
shoes for football, it send me a list of topics
that the brand should talk about and actually generate the
content as well, and that would be on brand.
Speaker 1 (25:32):
Yeah, it'll do even better. Yeah. It can generate blog posts,
it can generate social copy with images that can then
be used by humans to adapt. It can generate any
range of content types, and really the power in doing
this is that not only does it give you on
brand examples of that content that are really designed to
(25:54):
look feel in the tone of the brand, but it
also helps to synthesize the real role that the brand
can in that topical conversation because we train it to
do that.
Speaker 2 (26:04):
I got to use this to promote partners and possibility.
Speaker 1 (26:07):
Sounds good.
Speaker 2 (26:08):
Well, listen, this has been a fascinating discussion. You know,
there's so much around this topic, and as you say,
it's you know, sophisticated, it's complicated, but it's it's you know,
it's the future. So I really appreciate your insights into
into this topic. So thank you Oliver, thank you Krystallin,
and thank you for being partners in possibility.
Speaker 1 (26:27):
Thank you, thank you.
Speaker 2 (26:31):
That was Oliver von Wirst, a partner at Statista, and
Krystal and Stewart Luiza, chief Digital Officer at Citizen Relations
and Mechanism. While there's no way to know exactly what
the future of automation and AI for marketing will be,
cmos and marketers will have to adapt to it. I'm
your host, Brett Marshawn, and this is partners and Possibility.
It's really about how as an organization we can use
the power of AI and predictive technology to move our
business forward. And when we get to that altitude, we'll
start to I think CEE cmos really understanding the value
of that investment because it's fundamentally changing the impact of
everything we do in marketing that single channel.
Speaker 2 (00:29):
In an ever changing world. That's all about stained connected,
building connections and seeing where the next collaboration takes a
marketing campaign from an initial brief to the follow through.
What paths are going to make a campaign success more
than a possibility. Hi, I'm Brett Marshand, CEO of Plus
Company is Partners and Possibility. AI is everywhere, but we
(00:54):
in the marketing world are only scratching the surface of
what is possible. We've seen the public at large testo
new generative AI tools like Chatgipt and Dally to more
niche products that use predictive AI to do all kinds
of things. Now we're seeing marketers experimenting and ideating as
they start building out new campaigns for their brands. In
(01:15):
this episode, I'm joined by Oliver von Wersch, a partner
at Statista and Crystal, and Stuart Louisa, the chief Digital
officer at Citizen Relations and Mechanism. They're talking about a
comprehensive survey of two hundred cmos on artificial intelligence, marketing
Measurement and the Marketing Department of the Future speaking of AI.
(01:42):
I think the finding was that forty three percent of
marketers understood and saw benefits in AI, which means I
guess fifty seven percent don't. So what's going on there? Oliver,
maybe talk a little bit about that.
Speaker 3 (01:55):
Yeah, it's the same what happen. I think if you
would ask questions about advertising identifiers and first body data sets,
because everybody knows that it's needed. That's the case for
I as well. Everybody knows that that you should experiment
and you should II tools in your organization by means
(02:16):
of campaign effectiveness, attribution measurement, reporting and so on. But
you still have the alternative, right, it's still there, and
it's the tech stack, and the setup is running and
has been running for for years and years successfully, and
so maybe some things just have to happen and to
(02:37):
make you react.
Speaker 2 (02:39):
In the end, what do you see as the challenges
and implementing a you know, AI as part of their plans.
Speaker 3 (02:44):
Things that are more easier than others. So using AI,
for example, creative generation or creative personalization is a relatively
easy task. You can implement that isolated or stand alone
into into your tool sets and into your processes. If
it comes to multi channel or multi multi point attribution,
(03:11):
that's a different story, right, because you have to attribute
and then to evaluate all the different attribution points which
are analogue, which are digital, which are digital digital with
cookies which are in app or CTV and so on,
and to just say like hey, let's throw throw this
all away or in my thoughts, throw it away and
(03:31):
put AI instead, that is that is a huge process.
So for example, also one point we found was that
that the cmos are hesitant to like hand over the
the spending distribution over channels to the AI, which is
like the holy gray of the of the of the
operative media planning as we know. So that's completely understandable, right,
(03:56):
So if I still have the alternative, if I still
have the systems and the teams up and running, who
would do it in that way? Right now? I don't
simply press the button to switch it.
Speaker 2 (04:09):
And probably a feeling of lack of control too, right,
I mean, because marketers and agencies, by the way, you know,
want to have a clear say and what they're going
to do, what channels they're going to use, what creative
they're going to use, what's going to work and what's
not going to work. And the idea that you've got
a AI bought or model that's actually telling you what's
(04:30):
working and not working. You know, it's a little bit
scary for some.
Speaker 3 (04:34):
I presume I'm a chess player, and many AI developments,
also from deep Mind, which has been acquired by Google,
many many development companies in the space started with chess programming.
And the thing is, once the algorithm has solved, it
has solved chess, it's unbeatable, right you, No human can
(04:58):
ever beat a computer daily and the data or even
not the world champion. Maybe it's a bit comparable here.
If you hand over your campaign attribution, if you hand
over your spending distribution over channels to the AI, it's
on the one hand, unbeatable, but on the other hand,
it changes the entire organization. And there I think it's
also somehow justified to be a bit hesitant. You shouldn't
(05:22):
be too hesitant, and you should of course tests and
you should develop test cases with your partners.
Speaker 2 (05:28):
What are you hearing, Cristalin about how marketers are feeling
about using AI. I mean, I presume there's different cohorts
across your clients at when it comes to utilizing it.
Speaker 1 (05:41):
Yeah, I thought, you know, some of the inputs from
the way the cmos responded to this survey were interesting
but also aligned with what we're seeing kind of on
the ground real world scenarios. I think we're on sort
of a traditional transformation trajectory where some of like our
more early adopters, are being more comfortable with testing and
(06:02):
bringing more parts of their business from creative which is
usually the easiest, through to more day to day workflows
and into much more complex decisions on how they're managing
their overall business. But I think what we're seeing as
we look at that traditional sort of curve of adoption
is there are factors of fear that certainly come into play,
(06:25):
but there's also factors of leadership and the need for
leaders to be bought in and brought along. There's a
need for legal and regulatory teams at our largest scale
companies to be brought along in the process, both to
minimize risk but also to forecast challenges, especially with some
of the technology still being fairly unstable, and I do
think that the priortization of the investment is still an
(06:48):
important factor for cmos. Many of them have so many
opportunities for where they could integrate AI into their mix,
but understanding where to spend and at what scale seems
to be a significant contributor to or a barrier to
why many have yet to actually action the way we
know the technology is capable of supporting them.
Speaker 2 (07:11):
Speaking of creative you both mentioned that both that marketers
are using it for creative optimization and generation. You also
talked about it Crystal and just now. I also thought
it was really interesting that I think fifty three percent
of marketers said that they actually see more creative roles
with AI versus last, which kind of I mean, on
the surface, seems counterintuitive.
Speaker 3 (07:30):
So yeah, this is kind of everything that gets automatized
freeze resources. Right. So, if you look to philosophers in
the nineteenth and century, it was about industrialization and what
the industrialization could like free unlock potential and time of
(07:51):
people for creative for painting and playing music and so on.
It was the same with digitization, and it's the same
with I guess AI distribution of AI. It's the next
revolution and it is binding resources when you are implementing it,
but in the end it is unlocking your personal resources
(08:13):
because in the end humans will have more time for
other things, and those things likely could be a creation
and ideation.
Speaker 2 (08:21):
Crystal, you've talked about the democratization of creativity with AI
to me in the past. Maybe just talk a little
bit about what you mean by that.
Speaker 1 (08:30):
Yeah, I mean, I think what we're sort of seeing
as part of one of the best upsides of AI
and creative is the democratization and the ability for a
number of different team members to enable new forms of creativity,
whether that be able to produce higher volumes of content
at scale, to be able to rapidly spect or prototype
(08:53):
content without having to have a long course in photoshop,
being able to generate images like insight of PowerPoint dex
with ease. Everybody is capable of really supercharging their own
creative powers. But I do think the stat around fifty
three percent expect an increase in creative roles is probably
also reflective of a shift in the types of creative
(09:15):
roles that we'll probably see in the future as we
connect more data and more insights around consumer into our
creative process. We'll probably start to see the rise of
kind of a new class of creatives, those who not
only understand design systems that help us activate a visual
idea across a lot of platforms in AI, but also
(09:37):
those who understand a bit more of the analytical bridge
with creative and can make more adjustments to the way
they're thinking about both messaging and creative pairings. And we
see that trajectory anyways, as we see an increase in
personalization and the desire to have more personalized content as
part of what we offer beyond the sixty second spot
(09:58):
and the big production element. So a new breed of
creative class I think is certainly emerging. And it's a
really exciting time, I think to be a creative.
Speaker 2 (10:08):
And presumably you can test ideas really quickly with AI too,
right in minutes and instead of waiting to do a
focus group and waiting to put it in the you know,
a creative assessment survey or research, and that I mean,
it's got to be powerful for creative people if you
think about it being able to go to whether you're
(10:30):
internally in marketing and going to the rest of the
organization or you're an agency going to the marketer to
be able to say, listen, we know this is going
to work well.
Speaker 1 (10:37):
Between what we know in retrospect about how programs have
performed and also the predictive capabilities of AI, we're able
to get a lot more inputs into the way we
shape our creative So between the ability to have better
insights on past performance and how consumers are responding to
creative and also the predictive capabilities of AI, we're starting
(10:58):
to see this sort of emerging capability of creatives as
analysts able to intake data and work with AI to
help generate stronger messaging and stronger design, which I think
is going to be unleashing kind of a new breed
of creative analysts, which is very exciting.
Speaker 2 (11:15):
What else in the surveyed, like did you find interesting
or unexpected?
Speaker 3 (11:23):
Yeah, it is like the the kind of implementation of
artificial intelligence on different levels. That was the most interesting thing,
So that the marketers basically said, yes, it is relevant,
Yes we are experimenting, Yes we are we are using
(11:43):
it for certain topics, but no, we are not in
place right now. We feel not in place right now.
To have an integrated strategy to implement AI into our companies,
which is yeah. And if I compare that again to
the media companies we have talked to, it's this same impression.
There there are kind of a few a few leaders
(12:07):
in in strategic implementation and and also here we find
we found leaders in strategic implementation who have a full scope,
who are invested in investing in all AI possible AI
use cases. But the majority of companies were like hesitant experimenting, yes,
and also aware of the strategic relevance and the long
(12:29):
term relevance, but experimenting in a in a limited playing field.
And that's the most interesting question is how how how
does this evolve over time?
Speaker 1 (12:39):
Right?
Speaker 3 (12:40):
So when when do you get the full scope in
in into your into your plans and hope who will
be the first? Right? So, if if one f FM,
c G would be the first in in fully implementing
it everywhere, there will there will be followers, and they
and and and the competitors will then act more quickly
(13:01):
like in any other kind of development in the internet. Right,
if you if you have a first mover, then the
first move has a competitive advantage.
Speaker 2 (13:10):
Chrisline, anything you from particularly interesting in there that we
haven't talked about.
Speaker 1 (13:14):
I think it's really interesting that we saw in the
survey results that a number of cmos felt comfortable leveraging
creative innovation in AI as part of kind of the
play and unleashing creativity, and some have started to look
at ways to use AI as a part of their
reporting process and maybe lightly into attribution. I think the
(13:35):
big middle ground that really will unleash AI at scale
is as many of our cmos begin to leverage AI
for day to day workflow automation. You know, there's been
huge movement in the last several months around releases of
AI features inside of our primary tech platforms, you know,
Google's Gemini, Metalama III, a lot of open AIS, no
(13:58):
GPT advancements, They're even bigger and bigger and bigger announcements
that happen each month. But once we start to see
some of that work take place in automating our day
to day workflows, then I think cmos can start to
move towards more transformative uses of AI. So I think
we're getting into a timeframe where automation is going to
(14:19):
be an important use for AI, but next will be
transformative motions doing things differently than we may have done
them in the past. And we all know that that
takes time for big organizations, not just to automate, but
then to transform the way they plan, the way they measure,
the way they optimize, the way they reimagine our relationship
(14:41):
with customers, and that will take time and operational shifts.
Speaker 3 (14:46):
Yeah. One interesting thing I found is how if you
look at the cuculs era which comes comes nearer, measurement
is definitely an issue, right, So it's already now it's
an issue with all the channels and all the different
the way of the do you have cookies and IDs
and apps and services and so on, But it will
be a big issue. So that that some people in
(15:06):
the industry started talking about probabilistic measurement, right, so you
guess which means which is like the fallback in in
in analogue media categories. And that's interesting because that has
to be done and that is crucial because if you
can't measure, you don't know about your campaign success and
(15:27):
then it's and then a few things are messed up.
Speaker 2 (15:31):
Yeah. In a former podcast, we talked to Aviy Goldfarb,
who you know wrote a book which is all about
how AI is fundamentally about prediction, and therefore you would
think that one of the fundamental ways it's being used
is in measurement. So I think it's it's very insightful.
It's you know, one of the reasons we fundamentally put
(15:53):
measurement and predictive measurement at the at the foundation of
AOS because I just you know, I think I and
others thought that, yeah, if you're using AI to generate
new creative etc. Might make you a little bit more efficient,
but if you don't know whether it's working or not,
who cares.
Speaker 1 (16:08):
It's fair, it's a fair point. I think part of
what the challenge around measurement has been historically is that
we're still looking at measurement and silos, and so the
return on an investment in a new measurement strategy might
only be as good as where which channels you can
apply that predictive insight to. So part of what we're
trying to I think, evolve mindsets around our cmos is
(16:32):
that first we have to sort of integrate all of
the different data sources that we're using to look at
our holistic approach to marketing. We have to think about
an integrated measurement model. We have to leverage integrated audience
segments that we're all optimizing around, and we have to
set universal KPIs. And if we do that well at
the beginning, at the onset, at the strategic layer, then
(16:55):
the investment in a platform that allows us to reimagine
and measurement and predict measurement becomes much more effective than
just optimizing return on AD spend or specific channel adjustments
and programmatic It's really about how as an organization we
can use the power of AI and predictive technology to
(17:15):
move our business forward. And when we get to that altitude,
we'll start to I think see CMOS really understanding the
value of that investment because it's fundamentally changing the impact
of everything we do in marketing, not single channel.
Speaker 2 (17:30):
Yeah, and change management around it.
Speaker 4 (17:31):
It's going to be massive, right, like massive Yeah.
Speaker 2 (17:48):
Speaking about the core opportunities in the future, maybe the
most important one when we talk about sort of system
change the impact of AI is what the actual marketing
departs mint and marketing jobs are going to look like
in the future. And love to hear your thoughts on that.
Speaker 1 (18:06):
I think that it's there's a lot of different analogies
used to talk about, you know, sort of the way
the AI is going to catapult us into a new
era of marketing. I think back myself to the various
kind of decades of the web. I mean, when we
moved from radio to TV, when the sort of dot
(18:27):
com error, the way social profoundly changed our ways of working,
you know, the influencer bubble. We've seen some of these
kind of ebbs and flows in channel historically, and we
know that each one of those profoundly changed the way
we market, I mean profoundly changed the way we build strategies,
the mix of things we do. But those were essentially
(18:47):
channel changes largely. I think what's so interesting about AI
is it is a systems level change. It is fundamentally
augmenting human intelligence in a way that is going toffect
every channel that we leverage and have an effect on
each of those parts of the mix. And so I
think what is likely to happen is because of the
(19:08):
profoundness and the scale of how AI can impact our
day to day work, it would seem that we would
go faster towards AI integration as part of everything we do.
But in fact, I think we are seeing that there's
a huge learning curve, and it's probably going to take
some time for the most of our sort of majority,
(19:30):
our later majority, to actually really comfortably change their ways
of working. I say that from our vantage point working
with clients, it's going to take time for client organizations
to ready themselves. But with all of that said, the
immediate near term effects that I think will take place
are definitely going to be around automation. They're going to
be around evolving the way we plan, measure, and optimize
(19:51):
as one of the first orders of business. And they're
certainly going to be around creating and up leveling our
talent to function more like systems engineers. Know our chief
data officer, Michael Cohen uses that term regularly that we're
moving towards a time where we can engineer technology to
help us solve any number of problems in our day
to day thus creating kind of this generalist practitioner that
(20:15):
we think is probably going to represent the future skills
of our team. So we're already starting to build towards
that capability using technology and machine learning to help us
solve challenges across channel.
Speaker 2 (20:29):
Oliver, what do you what do you think it's going
to be the impact to marketing marketers in the future.
Speaker 3 (20:34):
Two very plastical or like two images. So first, working
less with spreadsheets in daily work, right, so not using
spreadsheets anymore for various reportings for planning for my manager
was once a report on the on the performance in
(20:56):
the last week of the channel. So that is taken
a way and that is solved, and that that that
unlocks time for humans and agencies and on the advertiser
side because they get rid of boring activities and they
can focus on more creative activities or have a have
an extra day off. I don't know. Secondly, it's it's
(21:21):
we we will be able to digest and process more
data than right now, and that is also giving freedom
to the to the future organization because processing power of
course will be an issue and energy consumption will also
be an issue. But in theory you are able to
process more data to drive better decisions. So that is
(21:44):
that is also on the positive side. By the way,
one next study I would love to see or to
make is the study on how AI generated ads are
perceived by consumers, because we should make it too easy
and say like here here, here is our personalization made
by an algorithm. We just play it out and if
(22:06):
one ad clicks better than the other, then is the
better performance. There will be perception of consumers towards AI
generated content and AI generated ads, and this might be
multi dimensional, so it's not only clicking it, but it's
also a perception of the advertiser that does it, and
(22:29):
that's interesting. Consumers life and normal people love to play
around with a mid journey and so on, but sometimes
mid journey results are frightening, and so could AI generated
ad speed. So that's also one interesting piece of research
which has to be executed.
Speaker 2 (22:48):
I guess well, Oliver, that sounds like a fascinating research study.
I think we're I think we're talking to a statistical
about a study on AI and creative in the market
and measuring its effectiveness. So it sounds like we'll have
that study together. One last question, crystallin chance to give
(23:09):
us a plug because I know you're working on some
really interesting territory around responsive AI and you know how
that can both help your teams but also clients in
the end. Maybe talk a little bit about what you're
building there.
Speaker 1 (23:24):
Yeah. One of the important ways that we've been working
internally to leverage AI in our day to day is
by thinking about tasks that we couldn't have previously done
because they were either too manual or required too many
data sources that were disparate, that we can now accomplish.
And for example, one of the products that we've had
in R and D for the last six months is
(23:47):
called responsive content, and it actually allows us to do
something we've always wanted to do, which is listen to
what's happening in the news media and social and search
and reviews and forums and in mediately synthesize all of
that information into a topical brief that is on brand
for a brand's area of interest and expertise and concern,
(24:11):
and turn that into daily, weekly, or monthly content concepts
and briefs, along with generative content samples, so that brand
or individual executive thought leaders or smaller sized brands who
couldn't work to produce high volumes of content in the
past could really have access to this development of content
(24:34):
at the speed of culture. And what's cool about a
platform like this is that it isn't one of these
back end dashboards that you have to get in and
manage yourself daily. It just sends you an email digest
of all of the on topic content that you could
be publishing during a really relevant period in culture. And
so we love the idea that AI is really empowering
(24:55):
us to be able to do things we could never
have done before in ways that are clients can really
find value.
Speaker 2 (25:02):
So if so, let's say I'm the Adida's client, which
Adidas is our clients, you know, and it's it's during
the euro I could now based on what's being discussed
and what's in the news in real time, it would
send me a and obviously a data sells lots of
(25:22):
shoes for football, it send me a list of topics
that the brand should talk about and actually generate the
content as well, and that would be on brand.
Speaker 1 (25:32):
Yeah, it'll do even better. Yeah. It can generate blog posts,
it can generate social copy with images that can then
be used by humans to adapt. It can generate any
range of content types, and really the power in doing
this is that not only does it give you on
brand examples of that content that are really designed to
(25:54):
look feel in the tone of the brand, but it
also helps to synthesize the real role that the brand
can in that topical conversation because we train it to
do that.
Speaker 2 (26:04):
I got to use this to promote partners and possibility.
Speaker 1 (26:07):
Sounds good.
Speaker 2 (26:08):
Well, listen, this has been a fascinating discussion. You know,
there's so much around this topic, and as you say,
it's you know, sophisticated, it's complicated, but it's it's you know,
it's the future. So I really appreciate your insights into
into this topic. So thank you Oliver, thank you Krystallin,
and thank you for being partners in possibility.
Speaker 1 (26:27):
Thank you, thank you.
Speaker 2 (26:31):
That was Oliver von Wirst, a partner at Statista, and
Krystal and Stewart Luiza, chief Digital Officer at Citizen Relations
and Mechanism. While there's no way to know exactly what
the future of automation and AI for marketing will be,
cmos and marketers will have to adapt to it. I'm
your host, Brett Marshawn, and this is partners and Possibility.
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com
The Breakfast Club
The World's Most Dangerous Morning Show, The Breakfast Club, With DJ Envy, Jess Hilarious, And Charlamagne Tha God!