April 28, 2025 • 37 mins
Unlock the secrets of maximizing your marketing spend with Talgat Mussin, a marketing scientist with experience at Google, Amazon, and TikTok. Discover how adopting an experimental mindset can revolutionize your advertising strategy and uncover the true impact of your marketing efforts. Talgat shares his journey from working in tech giants to creating his own venture focused on minimizing ad spend waste through incrementality testing and causal inference.
Curious about how to accurately measure the effectiveness of each marketing channel? Learn why many channels over-report their impact and how a scientific approach can help you make informed budget allocation decisions. Talgat emphasizes the importance of staying accountable and continually experimenting with strategies, urging business owners to look beyond the surface metrics presented by ad platforms, whose main aim is to maximize shareholder value.
Step into the future of marketing with insights on AI's transformative role in enhancing productivity and efficiency. Talgat discusses the potential of AI to accelerate learning and streamline processes like content creation, while also addressing challenges such as inflated metrics and the need for accurate measurement. Through "Incrementality Insider," he aims to bridge knowledge gaps in advertising measurement, empowering businesses to optimize their ad spend and unlock untapped potential. Join us for a thought-provoking exploration into the evolving world of marketing science.
ABOUT TALGAT
Talgat Mussin is a Marketing Scientist with over a decade of experience in AdTech, including roles at Google, Amazon, and TikTok.
He has helped leading tech companies optimize over $300 million in marketing spend and has a deep understanding of incrementality testing and causal inference. Talgat is now applying his expertise as an entrepreneur, guiding marketers to achieve clarity and confidence in their marketing investments through Incrementality Insider.
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Transcript
Episode Transcript
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Speaker 1 (00:00):
Hey, what is up?
Welcome to this episode of theWantrepreneur to Entrepreneur
podcast.
As always, I'm your host, brianLoFermento, and if there's one
thing that we can all unite onthat we do not like it is wasted
dollars.
None of us like to waste moneywhen it comes to ad campaigns
marketing.
None of us want that.
We want our ad dollars to makeus money, not cost us money, and
(00:22):
that's why I'm so excited tointroduce you to today's guest
and fellow entrepreneur, talgatMusin.
Talgat is a marketing scientistwith over a decade of experience
in ad tech.
It feels like we're getting alittle behind the scenes glimpse
into this world today, becausehe has had roles at Google,
amazon and TikTok.
He's helped leading techcompanies optimize over $300
(00:44):
million in marketing spend andhas a deep understanding of
incrementality testing andcausal inference.
Talga is now applying hisexpertise as an entrepreneur,
guiding marketers to achieveclarity and confidence in their
marketing investments throughIncrementality Insider, which he
puts out an incrediblenewsletter every single week.
(01:05):
I love the work that he does.
He's also putting out greatcontent on LinkedIn.
There's so much that we'regonna learn from him, but what I
really appreciate about hismission in business and in his
life is he wants to rescue onebillion with a B one billion
dollars in wasted ad spend.
So this is something that we'llall get to learn from, because
it's important as our businessesgrow.
(01:27):
So I'm excited about this one.
I'm not going to say anythingelse.
Let's dive straight into myinterview with Talgat Musin.
All right, talgat, I am so veryexcited that you're here with
us today.
First things first.
Welcome to the show, thank you,thank you.
Speaker 2 (01:43):
I'm excited as well.
Speaker 1 (01:44):
Heck.
Yes, we are going to learn alot of very important things
from you today, but before weget there, take us beyond the
bio.
Who's Talga?
How did you start doing allthese cool things?
Speaker 2 (01:56):
I'll start from the very beginning that I have an
economist education.
I spent some time in marketingand back in 2015, I immigrated
to the US and by some randomchance event, I landed at Google
as a contractor, worked thereas a year and a half and then
converted to a full-time role.
(02:18):
So I didn't know that I liked ituntil I tried.
So I landed to the role of themarketing experiments and I was
helping internally to developprogram experimentation and do
the GTM strategies, and overtime, I was involved in a
(02:38):
client-facing role where I washelping advertisers understand
the causality of the ads sounderstanding what truly works
and what's actually drivingimpact and that leads to the
whole career of the causalmeasurement and incrementality.
That's pretty much it andwithin the, let's say, after
(03:00):
working at big tech companiesacross Google, amazon and TikTok
, I finally came to the pointwhere I actually like to do it
on my own and then just lastyear, in in may, I started my
own thing and it's still.
It's still in the process ofdevelopment, but I see the
(03:23):
feedback from the market.
There's high demand for thisknowledge, there's opportunity
to create value by minimizingthe spend, and there's so much
that can be done in that area.
That's why I'm very excited tospread the knowledge and also
(03:44):
educate interested marketeers.
Speaker 1 (03:48):
Yeah, I love that overview, Talgat.
It's such a cool background,because what really stands out
to me is the fact that asentrepreneurs, as business
owners, we all understand theconcept of spending ad dollars
and putting together marketingcampaigns, but the verb that you
use is experiment.
You talk so much about adexperimentation and all of the
more scientific approach toadvertising.
(04:09):
Talk to us about that, becauseprobably most people don't view
it as experimentation.
Speaker 2 (04:16):
Yeah, depending on the view it.
So experimentation we allexperiment in our life, we do
some stuff.
We all experiment in our life.
We do some stuff, we observeand we try new things and we see
how it's changing the outcomeor not.
So in case of the digitaladvertising, there's like long
(04:37):
history.
My personal take on this therewas been relatively on par speed
between academia and businessback in the days when it started
(04:58):
with radio, then television,the print and different media
formats where people get exposedto ads and then, as a result,
buying product and services orbeing aware of the brand or the
different objective for themarketing campaigns of the brand
or the different objective forthe marketing campaigns.
Then what happens?
With the rapid acceleration oftechnology, specifically the
cell phones?
The adoption was so fast thatacademia, I think, lagged behind
(05:20):
in terms of the understandingand applying the scientific
approach, meaning that intoday's world, in the
multi-device, multi-dimensional,multi-network where we live,
it's really hard to understandwhat's actually driving impact.
And the only way to do itnowadays with this complex world
(05:43):
, is to run experiment andunderstand the causal factor.
Because there is a phrase Idon't really like that one, but
I think everybody is saying overand over that correlation
doesn't mean causation.
So, yes, that's the reality, alot of things correlated, and
(06:11):
the problem also thatadvertising platforms trying to,
they're doing the really greatjob, driving the business and
creating the value, but in thesame time, there is a limited
credit, performance credit whichall advertising platforms
claiming to drive.
So and there's a simple realitythat if you take all those
dashboards across all the mediaplatforms you have, for example,
let's say like you have sevenmedia channels, and then they
(06:33):
all claim some level ofattribution, if you take all
those numbers and combine themtogether, it's not going to
match to your sales, it's goingto exceed your sales.
So there is a problem of doublecounting, there's a problem of
inflating metrics, there's likemany issues so and sophisticated
advertisers nowadays they awareand know that.
That's why they they arerunning this uh causal
(06:56):
experiments to understand whatactually driving impact.
And also there is a kind ofnext layer of complexity that uh
that can be primary cause,there can be a fractional cause,
some, some channels can beamplifiers, some, some channels
can be uh just cannibalizing onthe other.
Speaker 1 (07:13):
So that's that's very complex uh web of causes and
and synergies and and then uhnegative effects across channels
yeah, tal, hearing you talkabout these things, it's
probably the first time thatmost listeners are being told
about these and it really feelslike it's from behind the scenes
, because we only see that endresult.
(07:33):
We only ever see the Facebookads platform or the Google ads
platform, and we hope to makesense of all the buttons that we
can click, but there's so muchdata analysis happening in real
time behind the scenes that wedon't understand.
So take us into some of thosecomplexities and, of course,
hopefully make it a little bitsimpler for us, because a lot of
people probably have neverheard that term of
(07:54):
incrementality testing.
You've given us a little bit ofan intro into causal inference,
but walk us through.
What are these mechanisms?
Why do you pay attention tothese when it comes to helping
to rescue those wasted addollars?
Speaker 2 (08:09):
I think the magnitude of problem depends on the
complexity of the media mix andalso spend levels.
And if you're a small businessowner and you're implementing
some spend across Google, maybeMeta, it's not going to be a big
deal for you.
The wasted portion can be verytiny.
(08:33):
But over time I think when yougrow the brand and you start
leveraging more and morechannels, the complexity and the
potential waste proportionexponentially increase.
So it's more applicable for thebigger businesses.
But also I would say thatcertain medium-sized businesses
(08:54):
can benefit from knowing this,particularly those who are doing
well in organic meaning thatthey do their social game really
well.
They do, uh storytelling, thereis some uh good brand dna and
and they drive organic traffic.
And on top of that, you know,to amplify the use paid media.
(09:16):
This is where uh things getwonky, uh, where uh advertising
it's a good ad, it's a goodmechanism for business.
Don't get me wrong, I loveadvertising, I love industry, I
see it as an oil to move economymachine faster, but everything
(09:36):
within the limits ofunderstanding what really works.
And then, when things getbigger, budget get bigger and
then spend get higher, thingsget really complex.
So I think that's a verycomplex topic.
If to try to simplify it, butI'll try.
(09:58):
I'll try to make it some simpleanalogies.
One of the analogies I think Iused several times with a client
at Help that if you take asport team professional sport
(10:19):
team and the attribution problemis similar to how coach
evaluate the players, if youonly reward the player who
actually scoring the points,then that's like what actually
happening across the board.
(10:39):
It's called last clickattribution, where the last
interaction with the ad, withthe last channel who interacted
with the user before theconversion sale, getting all the
credit.
Same if coach only creditingthe, let's say, quarterback and
then ignore all othercontribution of other players,
like defense and then somecombination of passes, then
(11:06):
there will be the problem.
So I think similar logic canapply here and one of the let's
say what will be theincrementality testing of this
particular team and the impactof certain, let's say, defense
players are not visible.
But let's do the incrementalitytests In the next game.
(11:28):
Let's remove the biggestcontributor to defense and see
how it goes.
So it doesn't matter how manyit's going to change the whole
game because it's all relativeto each other and there are so
many uh combinations of the gameand how many uh points you get
and how many uh you lose.
(11:49):
So, uh, that's actuallyanswering the question like, oh,
uh, actually, uh, it's not onlyabout the, the one who lost the
touch, the ball and scored thegoal, or got the guy the point,
but it's all it teamwork, andthere's a combination of factors
.
Yeah, this is one of the way Ican talk more, but this is one
of the metaphor I can use.
Speaker 1 (12:11):
It's such a good analogy, talga, I'll tell you,
and especially as a sports fan,a lot of sports analysts want to
say, oh, if you remove the bestplayer from this team, they're
going to miss out on those 20goals that he scores every
season.
But to your point, no, there'sso many different variables and
factors at play that otherthings will fill in that missing
gap, and so it might not be asstraightforward.
(12:31):
Of course it's not.
It's such a complex world.
I want to ask you about this,though, because a lot of people
will be hearing you talk aboutexperimentation and I'm sure you
hear this with companies andleaders, business leaders that
you advise with which is Talgat.
I don't have the budget toexperiment.
It sounds like I'm going tohave to use ad dollars in order
to get these answers, because Ihave to run these ads in order
(12:52):
to get the data back.
How do you navigate themthrough that?
It sounds to me like you have avery experimentation mindset
and you understand that that'swhat's going to bring the
positive ROI.
How much of our budget shouldwe just view as experimentation?
Speaker 2 (13:09):
I would say that in the case of advertising is not
always like this particularexample you described.
That's for the new channel,when you're trying to understand
how it works and there's a newspend like allocating new
dollars towards this channel.
But that also comes intoassumption that you already know
how.
Let's say you have already likethree, four main channels
(13:32):
Google, meta, some others youalready know exactly how much
they're contributing.
So if you're alreadyadvertising, you already have
the budget per se for theexperiment, because there is a
way, there's different way to doit.
You can turn off the ads andsee what all the impact.
There's different experimentdesigns, but idea that you need
(13:55):
to understand the incrementalcontribution of each channel
relative to the mix.
So, and if you have a big spendacross, let's say if it's more
than two channels, then youprobably need to understand
what's happening there.
Then, after you answer thosequestions, you have okay, now I
know true contribution of myGoogle channel and meta channel.
(14:17):
And there is one technique whenyou can actually, after you
done the study, you canoperationalize that learning to
the business to make it actuallyactionable.
You, let's say, you usemultipliers, so you see that
Google reporting dashboardclaiming this number of
conversion and then meta thisnumber and if you're able to
(14:42):
test each of them and you knowwhat true incremental
contribution of each channel,you can come up with
multi-privacy.
Most of the times it's afraction, let's say, out of
hundreds of reported conversions.
Through scientific experimentsI proved that it's only 60 are
(15:02):
incremental to this channel.
So attribution most of thetimes is inflated, not always
some channels under-attributing,but mostly they're
over-attributing.
And for the next channel youalso within relative to the mix.
Again, that's a problem thatyou cannot view them in a silos
Because the way how they worktogether it's like relative to
(15:22):
each other and you don't live insilos.
You treat the user acrossdifferent ad platforms.
It's usually same user.
You just bombard them with themessages, if you're able to
reach them.
Then you get those multipliersassigning to your channels and
then, okay, now I see myincremental contribution of each
(15:43):
channel, this and like, let'ssay, this multiplier, and then
you get a sense okay, now if Ispend more on this channel, I
should expect, uh, truecontribution of this much.
Then you solve so your baseline, how all this works.
Now you explore new channels.
Then, if you uh, for example,you're able to understand what's
(16:06):
true contribution of these twochannels and then you're able to
understand what's truecontribution of these two
channels.
And then you're able tooptimize budgets, meaning that
reducing the spend to a certaindegree didn't hurt your sales at
all because it's notincremental.
So now you're freed up andadditional budgets you can
allocate to a different newchannel which you never used
(16:26):
before.
Then, of course, you'restarting slowly with
experimenting and seeing how itworks, and that's iterative
process.
The more you channels utilize,the more you spend.
You continuously should beexperimenting and understanding
what was a true impact.
Speaker 1 (16:43):
Yeah, what I really appreciate about that overview,
talgad, is that a lot of people,when it comes to advertising,
they obsess about thoseadvertising analytics.
But it sounds to me like youbring that comprehensive
business approach to it ofsaying, hey, let's look across
your entire marketing mix, ofcourse, let's look at your
business analytics and let'sfigure out what's working and
what we should ramp up.
I really appreciate thatapproach that you're sharing
(17:06):
with us here today.
What I want to ask is justthinking about a business owner
who has advertised on many ofthese platforms that we're
talking about.
I always thought and hoped andbelieved that these ad platforms
, they also want me to succeed.
Of course, they have their ownengines and algorithms that are
happening behind the scenes inreal time in order to maximize
(17:28):
my return on investment as well,of course, as best as they can,
because you've already talkedabout a lot of the attribution
stuff that happens behind thescenes.
But is that the case?
Can we, as business owners,count on the fact that these
algorithms are also helping usin getting our message and our
campaigns in front of the rightaudience?
Or should we still retain thataccountability and ownership and
(17:50):
self-responsibility on our ownside and say, hey, it's us that
has to drive these changes, theiterative processes that you've
talked about.
Speaker 2 (17:59):
Yeah, good question, so very nuanced one.
I'll say this In the capitalistworld, every organization have
one objective maximizeshareholder value.
So, knowing that objective andmotivation, you should act and
then make a decision.
(18:22):
Knowing that.
So ad platforms like they, ofcourse want the business to
succeed, but in the same timethey need to provide the return
on investment and every quarterwhen they report the wall street
, which is affect the shareprice.
(18:42):
So, and that leads to the pointwhere objective is to keeping
the balance between helpingbusinesses grow but also getting
the return.
So, knowing that, I wouldn'tcount on the ad platform that it
(19:03):
will help certain business,particularly the ad platforms,
optimize for the maximizingrevenue and that distribution
can be different depending onhow the different segments of
businesses look like on the adplatform.
And logic that apply to that isthe use internal metric called
(19:28):
ARPU, which is average revenueper RPA sorry, average revenue
per advertiser, and for thatmetric, everything optimized
towards that.
So of course there is alsodifferent variables regarding
algorithm, the changes toalgorithm and and overall
advertising is very beneficialfor business, but I I would say
(19:50):
always experiment, always keepaccountable platforms and
representative platforms,because anything in life,
everything moderation.
So if you lose control, then uhthings like can get uh south
(20:12):
not in your, in your favor yeah,it's true.
Speaker 1 (20:15):
I love the way that you talk about that because it
is so important.
There are so many things thatwe can look at, that we can
control, that we can tweakinside all of our ad campaigns,
which is why I do.
I want to put you on the spotand ask you about a few of the
metrics that you pay attentionto, because I'll out myself, I'm
a data, a marketing scientist,like you, talgat, and so
typically I keep it a little bitsimple and I just look at click
(20:38):
through rate, cost per click.
I pay attention to, to thosetwo metrics, among others, of
course, and I'm always lookingat conversion rate and
percentage on the backend.
But where does your mind gowhen you look at an ad campaign?
What are some of those KPIsthat you look at?
Speaker 2 (20:55):
If I myself run the campaign, I will not be too
obsessed with the I'll call itsurface level metrics, those
CTRs and other things.
There's many variablesimpacting it.
There's internal auction.
There is also seasonality.
There's your category you'replaying with, like how tough is
(21:18):
the competition?
Because most of the ad platformauction-based and, depending on
the bids, there is a certainlike battles happening on
different level of the bits.
So I will say that platformmetrics are directional.
(21:39):
I think the most important thingto pay attention to is actual
sales, like not the reportedsales, but your CRM data, your
actual sales and understandingthat there is a lack effect
happening when it comes toadvertising Like sometimes it's
not realized this fast.
(22:01):
And also the trend nowadaysadvertising platform become very
sophisticated, platform becomevery sophisticated and it takes
some learning periods tooptimize, to know what, what
your ideal customer profile andfor you as a business or agency,
who helping you to targetspecific audience profile.
So over time, algorithm learnand I think important step to do
(22:27):
if there is a possibility toreport back your conversion, to
upload it or have a pixel inplace so that way algorithm will
know better when the conversionhappening, it will optimize for
it and then perform better.
But from the reporting side,that's like a service level
reporting From the business side.
Business side again, keeping inmind that this is all
(22:49):
attributed, it's not caused, soyou can imply causality, but uh,
that's require experimentation.
So there is no simple answer tothis.
It's depending on platform.
I would say that, uh, just uh,take it easy on the surface
(23:16):
level metrics and lookholistically and see how your
sales and conversion fluctuatesand also, of course, check
carefully what's being reportedand what actually happened.
Speaker 1 (23:24):
Yeah, I love that realistic and pragmatic view to
it, because you call those outas surface level metrics and I
think it's important for all ofus, as business owners, to
really come back to the fact andit's obviously a core part of
your mission is we are spendingad dollars to make sales and
make that revenue back.
So the fact that to you Talgayou went straight there when I
asked you the question that isultimately the most important
(23:46):
metric.
So I really appreciate that Iwanna.
That is ultimately the mostimportant metric, so I really
appreciate that I want to askyou this question because it, of
course, is coming up in all ofour conversations this year and
you and I are talking in thefirst half of 2025.
And AI everybody's using it,Everybody's wanting to get
better at it.
How's AI factoring into all ofthis?
I would imagine that it helpswhen it comes to making sense of
the data.
It can help with regards tosome of the experiments that
(24:07):
we're running.
Speaker 2 (24:13):
But of the data, it can help with regards to some of
the experiments that we'rerunning, but what's your view of
where we are with AI and how itcan best suit us where we are
right now, and what's that viewfor the future?
In which context?
As a business owner or as anadvertising platform?
Speaker 1 (24:22):
I would say for the business owners.
Speaker 2 (24:25):
Okay, business owners , I think there's a huge unlock
of productivity.
I use AI every day.
You can 10x your learning speedusing AI.
I think you can view it as youralways-on advisor.
And when it comes toadvertising, there have been
(24:47):
some bottlenecks in terms of theproduction, creating the
visuals, creating the creativeassets.
That's also speeding up theprocess.
But when it comes to measurement, I don't see, at least in the
short and midterm, ai helping tomake it better.
Make it better, maybe in somecases it's, it's making it worse
(25:13):
because mostly it's acorrelation driven and uh, it
can.
It can inflate those alreadyinflated metric even further.
And uh, and also another thingthat, with the agents and other
things happening, that there'llbe a rise of the bots, uh, which
affecting the advertisingdollars, because it's already
big portion of the bots, whichaffecting the advertising
dollars because it's already abig portion of the activity.
(25:33):
It's not the humans, it's thebots and they're able to click
your ads and waste your dollars.
So that's, I think, alsoimportant to know and understand
when it comes to budgetoptimization, important to know
and understand when it comes tobudget optimization.
But, again, from theproductivity standpoint and for
(25:53):
the business owners, it's a huge, huge productivity booster.
It helped to scale.
It helped to scale globallybecause of the like.
Let's say, using AI selling yourproduct.
Services across the board ifthere's no logistical issues.
Services across the board ifthere's no logistical issues
globally across differentlanguages.
(26:14):
So I see that AI it's anamplifier of the humans'
activity as electricity.
Back in the days Not my words,it's already been used, but I
think back in the day, every biginnovation, back in the day,
every big innovation there havebeen early adoptions and there
have also been opponents to it.
(26:34):
But I think it's easier toconnect dots backwards.
So, of course, electricitymakes sense, but back in the day
, there has been also a hardtime to adopt it.
Same with AI, hard time toadopt it.
Same with ai.
(26:55):
I think it's just like a.
There is no threat to uhbusinesses from ai itself.
It's just like business who,amplifying ai, do better than
than those who don't.
Speaker 1 (27:02):
That's my theory really well said, talgan.
I love hearing the way that youtalk about this stuff, because
there's so much noise out thereabout AI and how we can be using
it, how we should be using it,but I love that practical
approach to it that you bring inreal life considerations.
Like you've said a few times inour conversation today, it's a
complex world and, even thinkingabout AI agents, we've all seen
(27:23):
the power of agents going towebsites, doing research.
I didn't even think about thefact that, of course, those
agents are clicking ads in orderto gain that data and that
research.
So really useful to hear yourthoughts there.
I want to ask you aboutIncrementality Insider, the
newsletter that you announcedlast year and that you've been
running, and that's a core partof your mission in order to
(27:43):
teach people and really exposepeople to the fact that, hey,
this is how you can reduce yourwasted ad dollars.
Speaker 2 (27:54):
Talk to us about Incrementality Insider and what
people look forward to seeing inthere.
So since I started, there wasone very, let's say, high level
vision and after some time Ispend most of the time nowadays
with the actual working on thefront lines consulting, helping
advertisers to elevate themeasurement on the capacity as a
(28:19):
consultant.
So in overtime I was able tohone and clarify what I'm trying
to do.
Of course, missions stay thesame, but now I get the clarity
how I actually can helpadvertisers and marketeers or
whoever interested in this topic, that I'm going to make a focus
on education and education howdoes things work, how it can
(28:44):
help, how businesses can benefitfrom knowing this.
And uh, there's the two issuesI observed like.
First one, that uh, there's anot a lot, but uh, I'll say like
a some uh critical mass ofprofessionals who who know how
to do this, who have thisspecific subject matter
(29:07):
knowledge, but most of them,like 99%, working for big tech,
very attractive salaries and,let's say, like golden handcuffs
, and that knowledge is gatedinside.
It's also benefiting theplatforms.
Of course, there's a certainlevel of advertisers.
Where they reach certain levelsspent, they get access to this
(29:29):
knowledge and expertise, where Iwas a part of it, helping
advertisers to succeed, but onopen market there is a very
limited thought, leadership andsharing the knowledge.
And second one, that area byitself it's relatively new and
still developing because I think, as I mentioned previously, the
(29:54):
lack of academia behind it, soa lot of professionals learning
on the fly and this knowledgeonly now become to getting
synthesized and then coming tosome sort of broader industry
bodies were being explored.
(30:15):
So it's a very exciting topicoverall, but there are so many
gaps that exist and my missionis to address those gaps,
helping businesses succeed.
And also, I don't claim that Iknow all the answers.
I'm learning all the fly, everyday something new.
That's why it's important tostay on the front line and
(30:36):
actually do the work beforetrying to help others.
I think that's important to beon the front lines, learn it,
front lines, learn it.
And I can share moreperspective regarding, like, why
is important and why isrelevant to human being as a
(30:58):
users.
But like, that can be probablyalready long answer for this.
But yeah, long story short.
I refined the vision, I refinedmy POV and perspective and I'm
gonna uh, let's say uh,accelerate the content
production for my newsletter.
And uh, it is.
(31:19):
It is free, by the way.
There will be some uh paidpremium content moving forward,
but for now it's free.
Speaker 1 (31:27):
Anyone can subscribe, read and and I also uh
developing the whole uh strategyacross different channels to to
share the ideas through visuals, infographics and many other
things yes, I love the way youtalk about that and really
position it in the marketplace,talga, it is much needed
education that, as you said,most people have never had
(31:49):
access to this.
So, talga, that's why you arelooking at your latest
subscriber.
I'm so excited to continuegetting your genius and
listeners.
We're going to drop that linkin just a minute, but before we
do, talgat, I have to ask youfor your number one best piece
of advice.
Knowing that we're beinglistened to by both
entrepreneurs and entrepreneursat all different stages of their
own growth journeys, andknowing that you are not only a
(32:10):
subject matter yourself and thethings we've talked about today,
but you're also one of us.
You're also a fellowentrepreneur.
So, with that hat on, what isthat one piece of advice that
you want to leave our listenerswith today?
Speaker 2 (32:22):
If it comes to entrepreneurs.
I would say it took me sometime to understand this.
It's not related to advertising, just overall, overall that I
spent a lot of time researching,analyzing, analysis, paralysis
and then strategizing.
I think that I spent too muchtime on that part.
(32:43):
And only simple thing I learnedthat I think almost everyone
who's already started they'reready, you're ready to go and
the best way to learn is toactually execute and on the fly
you understand and you actuallyabsorb information faster and
better when you start doing it,because you can do the two
(33:07):
scenarios.
One is like you're preparingfor a, like lunch, and you can
spend years, but iteratively,incrementally.
Or one at a time when you'redoing step by step, you learn on
the fly.
This learning uh, stick in themind deeper and then you
actually develop new neuronconnections related to this.
(33:29):
So I think I'm also a proponentof not only intellectual
approach but spiritual approach.
So when you're doing somethingand you knew and you also
emotionally experienced thislike new experience that
transforms you when you'regetting better at it.
If I make a simple analogy, youcan read about riding the bike
(33:55):
like years, but the only way tolearn you have to actually start
biking, falling down, learning,iterating, and only with this
you develop this new emotionalconnection, new emotional
learning, a new neuralconnection.
Develop this new emotionalconnection, new emotional
learning, a new neuralconnection when you then, over
over time, you can do it on onyour brain already, tackle this
(34:17):
and put it in background and youcan do it without even thinking
.
I think that's that skills,same as the writing back applied
to any part of the business.
So I'll say this and maybe I'llwatch it in future to myself
again that like reminding myselfagain uh, just start doing it,
learning on the actual practice,and and when you're doing this,
(34:39):
then you uncover all thechallenges which you didn't know
exist before.
Speaker 1 (34:44):
Yes, talgat, I love that advice.
I've always loved that analogyand, to your point, it's not
just advice that we get to hearonce and we'll remember forever.
We have to keep coming back toit because it is an iterative
process and I think that fits inso perfectly with all the
things that we talked about heretoday.
So, talgat, I know that I'mexcited to be on your newsletter
.
I can imagine that a lot oflisteners are excited to
(35:06):
continue getting this insiderknowledge and strategies and
tactics as far as reducing ourad waste and increasing our ad
spend that turns into ROI.
So drop those links on us.
Where should listeners go fromhere?
Speaker 2 (35:23):
Incrementalitynet.
It's a newsletter on Substack.
I just connected my customdomain Incrementalitynet that's
the name of my newsletter.
A lot of fun things to come, alot of exciting things to come.
And I'm planning to do not onlynewsletter.
There will be the video content, there will be the educational
series, webinars and maybe someeven private coaching for the
(35:47):
decision makers how toaccelerate faster in that
knowledge.
Speaker 1 (35:52):
Yes, listeners, you already know the drill.
We're making it as easy aspossible for you to find that
link down below in the shownotes Super easy to remember
incrementalitynet.
But you can click right onthrough from the show notes, no
matter where it is that you'retuning into today's episode.
We're also linking to Talgat'spersonal LinkedIn.
So if you want to reach out tohim, continue the conversation,
(36:15):
get his insider knowledge foryour business's benefit.
Reach out to him.
It's always great to havebrilliant people in your network
.
So, talgat, on behalf of myselfand all the listeners worldwide
, thanks so much for coming onthe show today.
Speaker 2 (36:22):
Thank you for having me, it was super fun.
Speaker 1 (36:25):
Hey, it's Brian here, and thanks for tuning in to yet
another episode of theentrepreneur to entrepreneur
podcast.
If you haven't checked us outonline, there's so much good
stuff there.
Check out the show's websiteand all the show notes that we
talked about in today's episodeat thewantrepreneurshowcom, and
I just want to give a shout outto our amazing guests.
There's a reason why we are adfree and have produced so many
(36:47):
incredible episodes five days aweek for you, and it's because
our guests step up to the plate.
These are not sponsoredepisodes.
These are not infomercials.
Our guests help us cover thecosts of our productions.
They so deeply believe in thepower of getting their message
out in front of you, awesomeentrepreneurs and entrepreneurs,
that they contribute to help usmake these productions possible
(37:10):
.
So thank you to not onlytoday's guests, but all of our
guests in general, and I justwant to invite you check out our
website because you can send usa voicemail there.
We also have live chat.
If you want to interactdirectly with me, go to
thewantrepreneurshowcom.
Initiate a live chat.
It's for real me, and I'mexcited because I'll see you, as
always every Monday, wednesday,friday, saturday and Sunday
(37:34):
here on the entrepreneur toentrepreneur podcast.
Hey, what is up?
Welcome to this episode of theWantrepreneur to Entrepreneur
podcast.
As always, I'm your host, brianLoFermento, and if there's one
thing that we can all unite onthat we do not like it is wasted
dollars.
None of us like to waste moneywhen it comes to ad campaigns
marketing.
None of us want that.
We want our ad dollars to makeus money, not cost us money, and
(00:22):
that's why I'm so excited tointroduce you to today's guest
and fellow entrepreneur, talgatMusin.
Talgat is a marketing scientistwith over a decade of experience
in ad tech.
It feels like we're getting alittle behind the scenes glimpse
into this world today, becausehe has had roles at Google,
amazon and TikTok.
He's helped leading techcompanies optimize over $300
(00:44):
million in marketing spend andhas a deep understanding of
incrementality testing andcausal inference.
Talga is now applying hisexpertise as an entrepreneur,
guiding marketers to achieveclarity and confidence in their
marketing investments throughIncrementality Insider, which he
puts out an incrediblenewsletter every single week.
(01:05):
I love the work that he does.
He's also putting out greatcontent on LinkedIn.
There's so much that we'regonna learn from him, but what I
really appreciate about hismission in business and in his
life is he wants to rescue onebillion with a B one billion
dollars in wasted ad spend.
So this is something that we'llall get to learn from, because
it's important as our businessesgrow.
(01:27):
So I'm excited about this one.
I'm not going to say anythingelse.
Let's dive straight into myinterview with Talgat Musin.
All right, talgat, I am so veryexcited that you're here with
us today.
First things first.
Welcome to the show, thank you,thank you.
Speaker 2 (01:43):
I'm excited as well.
Speaker 1 (01:44):
Heck.
Yes, we are going to learn alot of very important things
from you today, but before weget there, take us beyond the
bio.
Who's Talga?
How did you start doing allthese cool things?
Speaker 2 (01:56):
I'll start from the very beginning that I have an
economist education.
I spent some time in marketingand back in 2015, I immigrated
to the US and by some randomchance event, I landed at Google
as a contractor, worked thereas a year and a half and then
converted to a full-time role.
(02:18):
So I didn't know that I liked ituntil I tried.
So I landed to the role of themarketing experiments and I was
helping internally to developprogram experimentation and do
the GTM strategies, and overtime, I was involved in a
(02:38):
client-facing role where I washelping advertisers understand
the causality of the ads sounderstanding what truly works
and what's actually drivingimpact and that leads to the
whole career of the causalmeasurement and incrementality.
That's pretty much it andwithin the, let's say, after
(03:00):
working at big tech companiesacross Google, amazon and TikTok
, I finally came to the pointwhere I actually like to do it
on my own and then just lastyear, in in may, I started my
own thing and it's still.
It's still in the process ofdevelopment, but I see the
(03:23):
feedback from the market.
There's high demand for thisknowledge, there's opportunity
to create value by minimizingthe spend, and there's so much
that can be done in that area.
That's why I'm very excited tospread the knowledge and also
(03:44):
educate interested marketeers.
Speaker 1 (03:48):
Yeah, I love that overview, Talgat.
It's such a cool background,because what really stands out
to me is the fact that asentrepreneurs, as business
owners, we all understand theconcept of spending ad dollars
and putting together marketingcampaigns, but the verb that you
use is experiment.
You talk so much about adexperimentation and all of the
more scientific approach toadvertising.
(04:09):
Talk to us about that, becauseprobably most people don't view
it as experimentation.
Speaker 2 (04:16):
Yeah, depending on the view it.
So experimentation we allexperiment in our life, we do
some stuff.
We all experiment in our life.
We do some stuff, we observeand we try new things and we see
how it's changing the outcomeor not.
So in case of the digitaladvertising, there's like long
(04:37):
history.
My personal take on this therewas been relatively on par speed
between academia and businessback in the days when it started
(04:58):
with radio, then television,the print and different media
formats where people get exposedto ads and then, as a result,
buying product and services orbeing aware of the brand or the
different objective for themarketing campaigns of the brand
or the different objective forthe marketing campaigns.
Then what happens?
With the rapid acceleration oftechnology, specifically the
cell phones?
The adoption was so fast thatacademia, I think, lagged behind
(05:20):
in terms of the understandingand applying the scientific
approach, meaning that intoday's world, in the
multi-device, multi-dimensional,multi-network where we live,
it's really hard to understandwhat's actually driving impact.
And the only way to do itnowadays with this complex world
(05:43):
, is to run experiment andunderstand the causal factor.
Because there is a phrase Idon't really like that one, but
I think everybody is saying overand over that correlation
doesn't mean causation.
So, yes, that's the reality, alot of things correlated, and
(06:11):
the problem also thatadvertising platforms trying to,
they're doing the really greatjob, driving the business and
creating the value, but in thesame time, there is a limited
credit, performance credit whichall advertising platforms
claiming to drive.
So and there's a simple realitythat if you take all those
dashboards across all the mediaplatforms you have, for example,
let's say like you have sevenmedia channels, and then they
(06:33):
all claim some level ofattribution, if you take all
those numbers and combine themtogether, it's not going to
match to your sales, it's goingto exceed your sales.
So there is a problem of doublecounting, there's a problem of
inflating metrics, there's likemany issues so and sophisticated
advertisers nowadays they awareand know that.
That's why they they arerunning this uh causal
(06:56):
experiments to understand whatactually driving impact.
And also there is a kind ofnext layer of complexity that uh
that can be primary cause,there can be a fractional cause,
some, some channels can beamplifiers, some, some channels
can be uh just cannibalizing onthe other.
Speaker 1 (07:13):
So that's that's very complex uh web of causes and
and synergies and and then uhnegative effects across channels
yeah, tal, hearing you talkabout these things, it's
probably the first time thatmost listeners are being told
about these and it really feelslike it's from behind the scenes
, because we only see that endresult.
(07:33):
We only ever see the Facebookads platform or the Google ads
platform, and we hope to makesense of all the buttons that we
can click, but there's so muchdata analysis happening in real
time behind the scenes that wedon't understand.
So take us into some of thosecomplexities and, of course,
hopefully make it a little bitsimpler for us, because a lot of
people probably have neverheard that term of
(07:54):
incrementality testing.
You've given us a little bit ofan intro into causal inference,
but walk us through.
What are these mechanisms?
Why do you pay attention tothese when it comes to helping
to rescue those wasted addollars?
Speaker 2 (08:09):
I think the magnitude of problem depends on the
complexity of the media mix andalso spend levels.
And if you're a small businessowner and you're implementing
some spend across Google, maybeMeta, it's not going to be a big
deal for you.
The wasted portion can be verytiny.
(08:33):
But over time I think when yougrow the brand and you start
leveraging more and morechannels, the complexity and the
potential waste proportionexponentially increase.
So it's more applicable for thebigger businesses.
But also I would say thatcertain medium-sized businesses
(08:54):
can benefit from knowing this,particularly those who are doing
well in organic meaning thatthey do their social game really
well.
They do, uh storytelling, thereis some uh good brand dna and
and they drive organic traffic.
And on top of that, you know,to amplify the use paid media.
(09:16):
This is where uh things getwonky, uh, where uh advertising
it's a good ad, it's a goodmechanism for business.
Don't get me wrong, I loveadvertising, I love industry, I
see it as an oil to move economymachine faster, but everything
(09:36):
within the limits ofunderstanding what really works.
And then, when things getbigger, budget get bigger and
then spend get higher, thingsget really complex.
So I think that's a verycomplex topic.
If to try to simplify it, butI'll try.
(09:58):
I'll try to make it some simpleanalogies.
One of the analogies I think Iused several times with a client
at Help that if you take asport team professional sport
(10:19):
team and the attribution problemis similar to how coach
evaluate the players, if youonly reward the player who
actually scoring the points,then that's like what actually
happening across the board.
(10:39):
It's called last clickattribution, where the last
interaction with the ad, withthe last channel who interacted
with the user before theconversion sale, getting all the
credit.
Same if coach only creditingthe, let's say, quarterback and
then ignore all othercontribution of other players,
like defense and then somecombination of passes, then
(11:06):
there will be the problem.
So I think similar logic canapply here and one of the let's
say what will be theincrementality testing of this
particular team and the impactof certain, let's say, defense
players are not visible.
But let's do the incrementalitytests In the next game.
(11:28):
Let's remove the biggestcontributor to defense and see
how it goes.
So it doesn't matter how manyit's going to change the whole
game because it's all relativeto each other and there are so
many uh combinations of the gameand how many uh points you get
and how many uh you lose.
(11:49):
So, uh, that's actuallyanswering the question like, oh,
uh, actually, uh, it's not onlyabout the, the one who lost the
touch, the ball and scored thegoal, or got the guy the point,
but it's all it teamwork, andthere's a combination of factors
.
Yeah, this is one of the way Ican talk more, but this is one
of the metaphor I can use.
Speaker 1 (12:11):
It's such a good analogy, talga, I'll tell you,
and especially as a sports fan,a lot of sports analysts want to
say, oh, if you remove the bestplayer from this team, they're
going to miss out on those 20goals that he scores every
season.
But to your point, no, there'sso many different variables and
factors at play that otherthings will fill in that missing
gap, and so it might not be asstraightforward.
(12:31):
Of course it's not.
It's such a complex world.
I want to ask you about this,though, because a lot of people
will be hearing you talk aboutexperimentation and I'm sure you
hear this with companies andleaders, business leaders that
you advise with which is Talgat.
I don't have the budget toexperiment.
It sounds like I'm going tohave to use ad dollars in order
to get these answers, because Ihave to run these ads in order
(12:52):
to get the data back.
How do you navigate themthrough that?
It sounds to me like you have avery experimentation mindset
and you understand that that'swhat's going to bring the
positive ROI.
How much of our budget shouldwe just view as experimentation?
Speaker 2 (13:09):
I would say that in the case of advertising is not
always like this particularexample you described.
That's for the new channel,when you're trying to understand
how it works and there's a newspend like allocating new
dollars towards this channel.
But that also comes intoassumption that you already know
how.
Let's say you have already likethree, four main channels
(13:32):
Google, meta, some others youalready know exactly how much
they're contributing.
So if you're alreadyadvertising, you already have
the budget per se for theexperiment, because there is a
way, there's different way to doit.
You can turn off the ads andsee what all the impact.
There's different experimentdesigns, but idea that you need
(13:55):
to understand the incrementalcontribution of each channel
relative to the mix.
So, and if you have a big spendacross, let's say if it's more
than two channels, then youprobably need to understand
what's happening there.
Then, after you answer thosequestions, you have okay, now I
know true contribution of myGoogle channel and meta channel.
(14:17):
And there is one technique whenyou can actually, after you
done the study, you canoperationalize that learning to
the business to make it actuallyactionable.
You, let's say, you usemultipliers, so you see that
Google reporting dashboardclaiming this number of
conversion and then meta thisnumber and if you're able to
(14:42):
test each of them and you knowwhat true incremental
contribution of each channel,you can come up with
multi-privacy.
Most of the times it's afraction, let's say, out of
hundreds of reported conversions.
Through scientific experimentsI proved that it's only 60 are
(15:02):
incremental to this channel.
So attribution most of thetimes is inflated, not always
some channels under-attributing,but mostly they're
over-attributing.
And for the next channel youalso within relative to the mix.
Again, that's a problem thatyou cannot view them in a silos
Because the way how they worktogether it's like relative to
(15:22):
each other and you don't live insilos.
You treat the user acrossdifferent ad platforms.
It's usually same user.
You just bombard them with themessages, if you're able to
reach them.
Then you get those multipliersassigning to your channels and
then, okay, now I see myincremental contribution of each
(15:43):
channel, this and like, let'ssay, this multiplier, and then
you get a sense okay, now if Ispend more on this channel, I
should expect, uh, truecontribution of this much.
Then you solve so your baseline, how all this works.
Now you explore new channels.
Then, if you uh, for example,you're able to understand what's
(16:06):
true contribution of these twochannels and then you're able to
understand what's truecontribution of these two
channels.
And then you're able tooptimize budgets, meaning that
reducing the spend to a certaindegree didn't hurt your sales at
all because it's notincremental.
So now you're freed up andadditional budgets you can
allocate to a different newchannel which you never used
(16:26):
before.
Then, of course, you'restarting slowly with
experimenting and seeing how itworks, and that's iterative
process.
The more you channels utilize,the more you spend.
You continuously should beexperimenting and understanding
what was a true impact.
Speaker 1 (16:43):
Yeah, what I really appreciate about that overview,
talgad, is that a lot of people,when it comes to advertising,
they obsess about thoseadvertising analytics.
But it sounds to me like youbring that comprehensive
business approach to it ofsaying, hey, let's look across
your entire marketing mix, ofcourse, let's look at your
business analytics and let'sfigure out what's working and
what we should ramp up.
I really appreciate thatapproach that you're sharing
(17:06):
with us here today.
What I want to ask is justthinking about a business owner
who has advertised on many ofthese platforms that we're
talking about.
I always thought and hoped andbelieved that these ad platforms
, they also want me to succeed.
Of course, they have their ownengines and algorithms that are
happening behind the scenes inreal time in order to maximize
(17:28):
my return on investment as well,of course, as best as they can,
because you've already talkedabout a lot of the attribution
stuff that happens behind thescenes.
But is that the case?
Can we, as business owners,count on the fact that these
algorithms are also helping usin getting our message and our
campaigns in front of the rightaudience?
Or should we still retain thataccountability and ownership and
(17:50):
self-responsibility on our ownside and say, hey, it's us that
has to drive these changes, theiterative processes that you've
talked about.
Speaker 2 (17:59):
Yeah, good question, so very nuanced one.
I'll say this In the capitalistworld, every organization have
one objective maximizeshareholder value.
So, knowing that objective andmotivation, you should act and
then make a decision.
(18:22):
Knowing that.
So ad platforms like they, ofcourse want the business to
succeed, but in the same timethey need to provide the return
on investment and every quarterwhen they report the wall street
, which is affect the shareprice.
(18:42):
So, and that leads to the pointwhere objective is to keeping
the balance between helpingbusinesses grow but also getting
the return.
So, knowing that, I wouldn'tcount on the ad platform that it
(19:03):
will help certain business,particularly the ad platforms,
optimize for the maximizingrevenue and that distribution
can be different depending onhow the different segments of
businesses look like on the adplatform.
And logic that apply to that isthe use internal metric called
(19:28):
ARPU, which is average revenueper RPA sorry, average revenue
per advertiser, and for thatmetric, everything optimized
towards that.
So of course there is alsodifferent variables regarding
algorithm, the changes toalgorithm and and overall
advertising is very beneficialfor business, but I I would say
(19:50):
always experiment, always keepaccountable platforms and
representative platforms,because anything in life,
everything moderation.
So if you lose control, then uhthings like can get uh south
(20:12):
not in your, in your favor yeah,it's true.
Speaker 1 (20:15):
I love the way that you talk about that because it
is so important.
There are so many things thatwe can look at, that we can
control, that we can tweakinside all of our ad campaigns,
which is why I do.
I want to put you on the spotand ask you about a few of the
metrics that you pay attentionto, because I'll out myself, I'm
a data, a marketing scientist,like you, talgat, and so
typically I keep it a little bitsimple and I just look at click
(20:38):
through rate, cost per click.
I pay attention to, to thosetwo metrics, among others, of
course, and I'm always lookingat conversion rate and
percentage on the backend.
But where does your mind gowhen you look at an ad campaign?
What are some of those KPIsthat you look at?
Speaker 2 (20:55):
If I myself run the campaign, I will not be too
obsessed with the I'll call itsurface level metrics, those
CTRs and other things.
There's many variablesimpacting it.
There's internal auction.
There is also seasonality.
There's your category you'replaying with, like how tough is
(21:18):
the competition?
Because most of the ad platformauction-based and, depending on
the bids, there is a certainlike battles happening on
different level of the bits.
So I will say that platformmetrics are directional.
(21:39):
I think the most important thingto pay attention to is actual
sales, like not the reportedsales, but your CRM data, your
actual sales and understandingthat there is a lack effect
happening when it comes toadvertising Like sometimes it's
not realized this fast.
(22:01):
And also the trend nowadaysadvertising platform become very
sophisticated, platform becomevery sophisticated and it takes
some learning periods tooptimize, to know what, what
your ideal customer profile andfor you as a business or agency,
who helping you to targetspecific audience profile.
So over time, algorithm learnand I think important step to do
(22:27):
if there is a possibility toreport back your conversion, to
upload it or have a pixel inplace so that way algorithm will
know better when the conversionhappening, it will optimize for
it and then perform better.
But from the reporting side,that's like a service level
reporting From the business side.
Business side again, keeping inmind that this is all
(22:49):
attributed, it's not caused, soyou can imply causality, but uh,
that's require experimentation.
So there is no simple answer tothis.
It's depending on platform.
I would say that, uh, just uh,take it easy on the surface
(23:16):
level metrics and lookholistically and see how your
sales and conversion fluctuatesand also, of course, check
carefully what's being reportedand what actually happened.
Speaker 1 (23:24):
Yeah, I love that realistic and pragmatic view to
it, because you call those outas surface level metrics and I
think it's important for all ofus, as business owners, to
really come back to the fact andit's obviously a core part of
your mission is we are spendingad dollars to make sales and
make that revenue back.
So the fact that to you Talgayou went straight there when I
asked you the question that isultimately the most important
(23:46):
metric.
So I really appreciate that Iwanna.
That is ultimately the mostimportant metric, so I really
appreciate that I want to askyou this question because it, of
course, is coming up in all ofour conversations this year and
you and I are talking in thefirst half of 2025.
And AI everybody's using it,Everybody's wanting to get
better at it.
How's AI factoring into all ofthis?
I would imagine that it helpswhen it comes to making sense of
the data.
It can help with regards tosome of the experiments that
(24:07):
we're running.
Speaker 2 (24:13):
But of the data, it can help with regards to some of
the experiments that we'rerunning, but what's your view of
where we are with AI and how itcan best suit us where we are
right now, and what's that viewfor the future?
In which context?
As a business owner or as anadvertising platform?
Speaker 1 (24:22):
I would say for the business owners.
Speaker 2 (24:25):
Okay, business owners , I think there's a huge unlock
of productivity.
I use AI every day.
You can 10x your learning speedusing AI.
I think you can view it as youralways-on advisor.
And when it comes toadvertising, there have been
(24:47):
some bottlenecks in terms of theproduction, creating the
visuals, creating the creativeassets.
That's also speeding up theprocess.
But when it comes to measurement, I don't see, at least in the
short and midterm, ai helping tomake it better.
Make it better, maybe in somecases it's, it's making it worse
(25:13):
because mostly it's acorrelation driven and uh, it
can.
It can inflate those alreadyinflated metric even further.
And uh, and also another thingthat, with the agents and other
things happening, that there'llbe a rise of the bots, uh, which
affecting the advertisingdollars, because it's already
big portion of the bots, whichaffecting the advertising
dollars because it's already abig portion of the activity.
(25:33):
It's not the humans, it's thebots and they're able to click
your ads and waste your dollars.
So that's, I think, alsoimportant to know and understand
when it comes to budgetoptimization, important to know
and understand when it comes tobudget optimization.
But, again, from theproductivity standpoint and for
(25:53):
the business owners, it's a huge, huge productivity booster.
It helped to scale.
It helped to scale globallybecause of the like.
Let's say, using AI selling yourproduct.
Services across the board ifthere's no logistical issues.
Services across the board ifthere's no logistical issues
globally across differentlanguages.
(26:14):
So I see that AI it's anamplifier of the humans'
activity as electricity.
Back in the days Not my words,it's already been used, but I
think back in the day, every biginnovation, back in the day,
every big innovation there havebeen early adoptions and there
have also been opponents to it.
(26:34):
But I think it's easier toconnect dots backwards.
So, of course, electricitymakes sense, but back in the day
, there has been also a hardtime to adopt it.
Same with AI, hard time toadopt it.
Same with ai.
(26:55):
I think it's just like a.
There is no threat to uhbusinesses from ai itself.
It's just like business who,amplifying ai, do better than
than those who don't.
Speaker 1 (27:02):
That's my theory really well said, talgan.
I love hearing the way that youtalk about this stuff, because
there's so much noise out thereabout AI and how we can be using
it, how we should be using it,but I love that practical
approach to it that you bring inreal life considerations.
Like you've said a few times inour conversation today, it's a
complex world and, even thinkingabout AI agents, we've all seen
(27:23):
the power of agents going towebsites, doing research.
I didn't even think about thefact that, of course, those
agents are clicking ads in orderto gain that data and that
research.
So really useful to hear yourthoughts there.
I want to ask you aboutIncrementality Insider, the
newsletter that you announcedlast year and that you've been
running, and that's a core partof your mission in order to
(27:43):
teach people and really exposepeople to the fact that, hey,
this is how you can reduce yourwasted ad dollars.
Speaker 2 (27:54):
Talk to us about Incrementality Insider and what
people look forward to seeing inthere.
So since I started, there wasone very, let's say, high level
vision and after some time Ispend most of the time nowadays
with the actual working on thefront lines consulting, helping
advertisers to elevate themeasurement on the capacity as a
(28:19):
consultant.
So in overtime I was able tohone and clarify what I'm trying
to do.
Of course, missions stay thesame, but now I get the clarity
how I actually can helpadvertisers and marketeers or
whoever interested in this topic, that I'm going to make a focus
on education and education howdoes things work, how it can
(28:44):
help, how businesses can benefitfrom knowing this.
And uh, there's the two issuesI observed like.
First one, that uh, there's anot a lot, but uh, I'll say like
a some uh critical mass ofprofessionals who who know how
to do this, who have thisspecific subject matter
(29:07):
knowledge, but most of them,like 99%, working for big tech,
very attractive salaries and,let's say, like golden handcuffs
, and that knowledge is gatedinside.
It's also benefiting theplatforms.
Of course, there's a certainlevel of advertisers.
Where they reach certain levelsspent, they get access to this
(29:29):
knowledge and expertise, where Iwas a part of it, helping
advertisers to succeed, but onopen market there is a very
limited thought, leadership andsharing the knowledge.
And second one, that area byitself it's relatively new and
still developing because I think, as I mentioned previously, the
(29:54):
lack of academia behind it, soa lot of professionals learning
on the fly and this knowledgeonly now become to getting
synthesized and then coming tosome sort of broader industry
bodies were being explored.
(30:15):
So it's a very exciting topicoverall, but there are so many
gaps that exist and my missionis to address those gaps,
helping businesses succeed.
And also, I don't claim that Iknow all the answers.
I'm learning all the fly, everyday something new.
That's why it's important tostay on the front line and
(30:36):
actually do the work beforetrying to help others.
I think that's important to beon the front lines, learn it,
front lines, learn it.
And I can share moreperspective regarding, like, why
is important and why isrelevant to human being as a
(30:58):
users.
But like, that can be probablyalready long answer for this.
But yeah, long story short.
I refined the vision, I refinedmy POV and perspective and I'm
gonna uh, let's say uh,accelerate the content
production for my newsletter.
And uh, it is.
(31:19):
It is free, by the way.
There will be some uh paidpremium content moving forward,
but for now it's free.
Speaker 1 (31:27):
Anyone can subscribe, read and and I also uh
developing the whole uh strategyacross different channels to to
share the ideas through visuals, infographics and many other
things yes, I love the way youtalk about that and really
position it in the marketplace,talga, it is much needed
education that, as you said,most people have never had
(31:49):
access to this.
So, talga, that's why you arelooking at your latest
subscriber.
I'm so excited to continuegetting your genius and
listeners.
We're going to drop that linkin just a minute, but before we
do, talgat, I have to ask youfor your number one best piece
of advice.
Knowing that we're beinglistened to by both
entrepreneurs and entrepreneursat all different stages of their
own growth journeys, andknowing that you are not only a
(32:10):
subject matter yourself and thethings we've talked about today,
but you're also one of us.
You're also a fellowentrepreneur.
So, with that hat on, what isthat one piece of advice that
you want to leave our listenerswith today?
Speaker 2 (32:22):
If it comes to entrepreneurs.
I would say it took me sometime to understand this.
It's not related to advertising, just overall, overall that I
spent a lot of time researching,analyzing, analysis, paralysis
and then strategizing.
I think that I spent too muchtime on that part.
(32:43):
And only simple thing I learnedthat I think almost everyone
who's already started they'reready, you're ready to go and
the best way to learn is toactually execute and on the fly
you understand and you actuallyabsorb information faster and
better when you start doing it,because you can do the two
(33:07):
scenarios.
One is like you're preparingfor a, like lunch, and you can
spend years, but iteratively,incrementally.
Or one at a time when you'redoing step by step, you learn on
the fly.
This learning uh, stick in themind deeper and then you
actually develop new neuronconnections related to this.
(33:29):
So I think I'm also a proponentof not only intellectual
approach but spiritual approach.
So when you're doing somethingand you knew and you also
emotionally experienced thislike new experience that
transforms you when you'regetting better at it.
If I make a simple analogy, youcan read about riding the bike
(33:55):
like years, but the only way tolearn you have to actually start
biking, falling down, learning,iterating, and only with this
you develop this new emotionalconnection, new emotional
learning, a new neuralconnection.
Develop this new emotionalconnection, new emotional
learning, a new neuralconnection when you then, over
over time, you can do it on onyour brain already, tackle this
(34:17):
and put it in background and youcan do it without even thinking
.
I think that's that skills,same as the writing back applied
to any part of the business.
So I'll say this and maybe I'llwatch it in future to myself
again that like reminding myselfagain uh, just start doing it,
learning on the actual practice,and and when you're doing this,
(34:39):
then you uncover all thechallenges which you didn't know
exist before.
Speaker 1 (34:44):
Yes, talgat, I love that advice.
I've always loved that analogyand, to your point, it's not
just advice that we get to hearonce and we'll remember forever.
We have to keep coming back toit because it is an iterative
process and I think that fits inso perfectly with all the
things that we talked about heretoday.
So, talgat, I know that I'mexcited to be on your newsletter
.
I can imagine that a lot oflisteners are excited to
(35:06):
continue getting this insiderknowledge and strategies and
tactics as far as reducing ourad waste and increasing our ad
spend that turns into ROI.
So drop those links on us.
Where should listeners go fromhere?
Speaker 2 (35:23):
Incrementalitynet.
It's a newsletter on Substack.
I just connected my customdomain Incrementalitynet that's
the name of my newsletter.
A lot of fun things to come, alot of exciting things to come.
And I'm planning to do not onlynewsletter.
There will be the video content, there will be the educational
series, webinars and maybe someeven private coaching for the
(35:47):
decision makers how toaccelerate faster in that
knowledge.
Speaker 1 (35:52):
Yes, listeners, you already know the drill.
We're making it as easy aspossible for you to find that
link down below in the shownotes Super easy to remember
incrementalitynet.
But you can click right onthrough from the show notes, no
matter where it is that you'retuning into today's episode.
We're also linking to Talgat'spersonal LinkedIn.
So if you want to reach out tohim, continue the conversation,
(36:15):
get his insider knowledge foryour business's benefit.
Reach out to him.
It's always great to havebrilliant people in your network
.
So, talgat, on behalf of myselfand all the listeners worldwide
, thanks so much for coming onthe show today.
Speaker 2 (36:22):
Thank you for having me, it was super fun.
Speaker 1 (36:25):
Hey, it's Brian here, and thanks for tuning in to yet
another episode of theentrepreneur to entrepreneur
podcast.
If you haven't checked us outonline, there's so much good
stuff there.
Check out the show's websiteand all the show notes that we
talked about in today's episodeat thewantrepreneurshowcom, and
I just want to give a shout outto our amazing guests.
There's a reason why we are adfree and have produced so many
(36:47):
incredible episodes five days aweek for you, and it's because
our guests step up to the plate.
These are not sponsoredepisodes.
These are not infomercials.
Our guests help us cover thecosts of our productions.
They so deeply believe in thepower of getting their message
out in front of you, awesomeentrepreneurs and entrepreneurs,
that they contribute to help usmake these productions possible
(37:10):
.
So thank you to not onlytoday's guests, but all of our
guests in general, and I justwant to invite you check out our
website because you can send usa voicemail there.
We also have live chat.
If you want to interactdirectly with me, go to
thewantrepreneurshowcom.
Initiate a live chat.
It's for real me, and I'mexcited because I'll see you, as
always every Monday, wednesday,friday, saturday and Sunday
(37:34):
here on the entrepreneur toentrepreneur podcast.
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