April 9, 2025 • 30 mins
Join Zeke Camusio, CEO of Data Speaks, as he dives into the seven most critical marketing metrics that every brand must understand in 2024. In a landscape where misleading data from advertising platforms can derail your strategy, Zeke explains how his AI-powered analytics platform cuts through the noise, ensuring you invest in the right channels to drive real sales. Gain actionable insights to optimize your marketing efforts and fuel sustainable growth.
Listen on Podbean:
https://brainworkframework.podbean.com/
Connect with Zeke Camusio:
Company Website: https://dataspeaks.ai/
LinkedIn: https://www.linkedin.com/in/zekecamusio/
Connect with Chris Troka:
LinkedIn: https://www.linkedin.com/in/christopher-troka-3a093058/
Website: https://focused-biz.com/
Website: https://christroka.com/ #brainwork #framework #business #entrepreneurship #marketing #decodingdata
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
There used to be people that wouldgive you horse rides before cars.
Now you don't have that.
And it's just changed when you can'tfeel bad about it, but you just have
to understand that it's coming, whetheror not you like it, it's coming.
You're listening to BrainworkFramework, a business and marketing
podcast brought to you by focused-biz.
com.
Welcome back to another episodewith us today is the CEO of
(00:22):
Data Speaks, Zeke Camusio.
Data Speaks is an AI powered analyticsplatform that helps companies identify
what drives their sales and investin the right marketing strategies.
Zeke, so excited to have you here.
How are you doing?
Doing great.
Thank you for having me.
Absolutely.
We always like to ask our guests, tellus about your entrepreneurial journey.
What were you doing before?
And how did that lead youinto what you're doing today?
Yeah.
So I started when I was 15, I hadmy first business, you could say.
(00:46):
I had a little magazine and Isold advertising space in it
and pretty much did all of it.
Wrote all the articles and went tobusinesses and persuaded them to
advertise in the magazine even designsome of those little ads and stuff.
So that was kind of the first tasteof what it was like to work for
(01:07):
myself and find myself with maybea couple of hundred bucks but it
was more money that I'd ever had.
And the fact that I could just doit on my own, I was super excited.
So since then I've hadsix other businesses.
All of them pretty muchin the internet space.
My last one was a marketing agency thatI had from 2007 to 2015 and after it
(01:31):
got acquired, I kind of told myself.
For the second time in my life thatI was going to retire and I was like
retired for like a couple of monthsand I just couldn't do it anymore.
I just needed to do something productive.
So I was doing consulting for afew of my clients and I had this
Kind of plan to not work too much.
I was only working a couple of hours andI was happy with that and set my hourly
(01:56):
rate pretty high because I didn't wantto have too many clients and What I
noticed is that for every hour that I wasspending Providing insights to my clients.
I was spending four additional hourspreparing for those calls, So I thought
I was getting 500 bucks an hour But Iwas really getting 100 bucks an hour
because I was spending so much timedoing the prep work so I sat down with
(02:20):
a piece of paper and I was like, whatwould it look like if I could Do this
preparation in only 10 minutes and thatwas the inception of my current company.
Data speaks, so I built it for myself.
It's
an all in one analytics platform thatconnects to over 250 different data
sources and uses AI to scan millionsof data points daily to figure
(02:43):
out what works, what doesn't work.
Why?
What to do about it, so that allowedme to kind of check in right before my
calls, just see the alerts and soundlike I spent hours preparing and then
I realized, there's other peoplethat need this, so I started opening
it up to other companies and agenciesand that was about four years ago.
(03:05):
So that's what brought me here.
That is very excitingand quite the journey.
I love that you started sellingadvertising space and magazines but once
you get that taste of entrepreneurship,it's really hard to go back.
And even after building and scalingmultiple businesses and semi retiring
and coming out of retirement.
I think you realize that yourmind, the way that you work,
(03:26):
you just want to help people.
You're good at it and the problemthat you ended up solving was this
huge issue that you had for yourself,the four hours of prep work for a
one hour meeting definitely takesdown that hourly rate pretty quickly.
But to develop this software and asystem that puts that all together.
It's helping solve a lot ofproblems for other consultants,
(03:47):
coaches, and agencies as well.
So with everything that you'reworking with now, you've helped
with both e commerce brands, B2Bbrands, coaches, consultants.
How does the system work asfar as the the analytics?
Because that sounds so cool to take thesedata sources and kind of give you this
overview of what we're looking for.
How does this all work?
(04:08):
Yeah, so our technology is focusedon a aspect of marketing called
attribution and attribution essentiallyis how do you know what cost your
leads or your revenue, right?
So a very common scenario is you'readvertising on LinkedIn, Google, Facebook,
a number of different channels, you sendemails, you have referrals, you have
(04:31):
affiliates, you have influencers and thenat the end of the month, you have 100
leads, 100 million revenue doesn't matter.
There's an outcome and how do youfigure out how you reach that outcome
with the input signals that you have?
And why is that important?
Well, what are you goingto be investing in?
Maybe one of the things that you dohas a negative return on investment.
(04:55):
So you're losing money.
Another thing is, 10 X ROI, right?
So unless you have a way to aggregateall this data and and figure out how
much of your revenue or how many ofyour leads were contributed to by each
market activity that is impossible todecide what to invest more resources in.
(05:17):
So that's the key problem we solve andwe got really good at it and what we
found is that for most, in brands witha digital presence about 60 percent of
all their marketing is advertising spend.
So if you look at a profit and lossstatement, a significant fraction of
that is going to be your advertising.
So we essentially help you getthe most for every dollar that
(05:40):
you invest in advertising.
I love that.
And when you kind of take a step backand look at the buyer's journey, they
obviously see your business somewhereand then they interact with it and
maybe they consume some content.
What do you see as far as what theanalytics are showing how people are first
finding a business that buyers journey?
Does it tell a story there?
(06:01):
Yeah, so there are two different lensesthrough which you can see attribution.
One is called MTA or multi touchattribution and the way that's the
way most people do it in the waythat it's been traditionally done.
So let's say that you find a companyon TikTok and then you just go to
their website, signed up for theemails, get an email, get excited
(06:24):
about something but you don't buy it.
Come back on a different device a weeklater and just search for the company.
Just go to their site and buy it.
What's going to happen is you'regoing to have Google take a hundred
percent of the credit for that sale.
You're going to have your email softwarethat get a hundred percent of the credit.
You're going to have TikTok takea hundred percent of the credit.
So when you add it up, it would seem likeyou have three sales but you only got one.
(06:49):
So with a multi touch attribution.
The way it usually works isyou could say it's last touch.
So the last one gets 100 percent of theof the credit which doesn't make sense
because that wouldn't happen if youhadn't had the prior to touch points.
Or you could say the firstone but also arbitrary, right?
(07:10):
Same if you said, likeit's gonna be linear.
We're gonna divide it 33 percent to each.
Why?
How do you know that each onehad the same amount of impact?
So that was the problemthat I found a few years ago.
And what more than a problem to me,it was an opportunity, like the way
it was done wasn't right and I wasalso seeing the writing on the wall
(07:32):
that users demanded more privacy.
So there were ad blockers were beingincreasingly more popular and then
we have iOS 14, 15, 16, that everytime there's more and more user data
that is being blocked, so the way weused to do it as marketers was to put
a pixel or a tracking code on everywebsite and hope that that will work and
(07:55):
that started working worse and worse.
So what's the alternative toMTA or multi touch attribution?
It's what we coinedimpact based attribution.
So the impact based attributionis based on the actual impact that
every channel, every campaign has.
How do you measure that?
Well, Let's take a very simple test.
Let's say that you're investing10, 000 a month on Google ads.
(08:19):
What would happen if you turn that off?
How much do your sales, wouldyour sales decrease, right?
What would happen if you doubled that?
What would happen to your sales, right?
Like, would they increase by 20%, 30%?
So that's the real way to measure impact.
The problem with thatis that maybe you don't.
Want to double your budget, maybe youdon't want to turn off the campaigns
(08:42):
that bring you revenue, right?
So you have to do it in a way thatyou're minimizing the business.
The negative impact on your business butyou're maximizing the chances of that
measurement being as accurate as possible.
And that's the way we do it.
We talked about 10 differentmarketing channels, TikTok
Facebook, Google and so on.
Let's say that your marketis the United States.
(09:03):
So there's activity for each of those10 channels in each of the 50 states
and then you also have a number ofsales that you get in each state.
So our system increasesor decreases activity.
Let's say you increase your advertisingspend by 20 percent in Maryland.
Okay.
What happens to sales in Maryland?
(09:23):
Do they increase or do they stay the same?
And if they increase by how much?
So based on all that, we're able tomeasure the relative contribution of
each activity to the overall outcome.
So that's much more complex thanthat but that's the gist of it.
Wait, it gets more complex than that?
I'm already not to say it's over my headbut obviously, you know what you're doing.
(09:45):
This really goes deep into the technical,the analytical piece and structure of
how data works when it comes to data.
Was there something that was maybewe're looking at data in the wrong way
or we attribute success or impact oncertain data that is not correct that
you're seeing something different.
Yeah, I think that the key takeaway thatI got from working with data for the last
(10:10):
20 years is that it's not about the databut it's about what we do with the data.
So if the data is not actionable, forexample, you got a hundred visitors
last week and you got 120 this week.
It's like, so what?
Do I need to do somethingdifferent because of that?
I mean, you could be excited about that.
I'm not going to try to take that awayfrom you but in terms of figuring out
(10:31):
how to allocate the limited resourcesthat a company has, whether that's
time or money or focus like, that'sdefinitely the main thing, right?
Identifying out of the hundredpossible things that you could
do, what are the two or three thatwill move the needle the most?
And what are the actions thatyou need to take towards that?
(10:52):
So I think that there's a need to have abasic dashboard with some key metrics that
are important to you to keep track of howthings are going but you should always
be asking yourself, am I changing theway I do things based on the data I have?
And if not what are themetrics I should be looking at?
It seems very simple but it's usuallywhere there's a lack of implementation
(11:14):
in terms of figuring out what metricsmatter and what to do based on.
The story they tell you.
I really appreciate that you went moreinto the fact that data can tell you any
story that it wants but it matters basedon the action that you're going to take.
What does that data mean to me?
What am I going to do fromhearing that information?
(11:35):
And that's that's really important when itcomes to finding actionable insights from
from what you're learning and I hear allthe time as far as the difference between
analytics and reporting is analyticstells you what happened reporting.
You try to explain why it happened.
So understanding what data is tellingyou, the story that it's trying to
convey, the message is so important fortrying to grow and level your business.
(11:57):
What's going to havethe most impact for you.
A lot of our audience hereare actually in the B2B realm.
And one thing you talk aboutis how you can grow your B2B
company or brand in 2025.
What are your biggest takeaways?
What should be focused onfor a lot of these B2B brands.
Yeah, so I think that you really dependon where you are with your business but I
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think you have to start with What are allthe variables that you want to understand.
So for example, you could say
Where people come from.
That's one of them, right?
Like what channel they found youon, but that's not the only one,
our CEOs buying from you more thanCFOs or CMOs are ads with videos
working better than ads with images?
(12:41):
Is it the case that when you orsomebody in your team is in the
video, those videos were better thantestimonial videos, for example.
So All those are variables, right?
Like all of all those are questionsthat you have about what's working and
then you have to be very deliberatein terms of how you track that to get
the data to answer those questions.
(13:01):
So one of the things you could do isname your campaigns or ads in a way that
all video ads have medium equals video
so it's just Tagging things the rightway helps you find those patterns
because maybe you want to see theperformance of all your video content
versus text content across all platformsbut that's only possible if there's a
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common nominator for all media content.
So in terms of setting yourselfup in a way that you're going
to maximize the amount oflearning that's really important.
Figuring out what work questions.
Do I want to get answers to?
and how am I going to label thingsin a way that is going to help
me answer those questions?
(13:43):
Now, in terms of what works, itreally depends on the business
model is really hard to givelike a one size fits all answer
but what I found is, if you wantme to be LinkedIn, it's going to
be a great part of your success.
I love the new feature for newsletters.
LinkedIn is doing a reallygood job featuring people that
post a lot in quality content.
(14:04):
So shorts are being veryhelpful right now.
Um, what else?
I think that any kind of thoughtleadership, having your own Podcast,
your own webinars, doing having a blog.
I think that leveraging otherpeople's audiences is really key.
If you appear on a podcast thathas 5, 000 listeners, that's
(14:24):
usually 5, 000 people that youwouldn't have access to otherwise.
So I think that's huge.
The answer will really dependon who your target audience is.
I'm a big fan of prospecting., I learnedthis from a guy named Trevor Graves
that owns a mark marketing agency herein Portland, Oregon called Nemo Design.
And he was like a big inspirationfor me and he said that every year he
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sits down and he says, these are the20 clients I want to get this year.
Rather than having a shotgunapproach of like, I'll just
take whoever's like 20 clients.
I'm going to learn everything about them.
Who's on their team.
I'm going to follow everything they post.
I'm going to engage with them.
I'm going to take him out for lunch.
Anything but I really love that becauseeverything else we talked about prior
(15:11):
to that is like, big scale but not verypersonalized with this is the exact
opposite and we do that every year.
These are the 20 clientswe want to work with.
What can we do to get them, likeyou're not going to get all 20 of
them but if you do a good job definingwho your ideal client is, hopefully
you'll get at least five of them.
I love that.
That is so incredibly smart.
(15:32):
And I really agree with the quality overthe quantity when it comes to clients
really hone in on who you want to workwith your ideal client lists, those
companies learn everything about them.
The quality and the value that youprovide to them is going to show
you're building the trust towardstheir business and it's going to be
way more effective than just making ablanket advertising campaign or a video.
(15:52):
Again, many things can be effectivebut if you're really showing you want
to build a relationship, especiallyB2B that's so important to really
take that personalized approach.
And I loved hearing thatLinkedIn is the place to do it.
Here's what's working great.
I appreciate all that feedback.
Yeah.
I think the other thing is one of myfavorite quotes is strategy is not
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what we do is what we don't do and Ithink it's Peter Drucker and I think
every entrepreneur is guilty of this.
I've heard it called the shiny lightsyndrome where it's like intuitively,
it kind of makes sense, right?
Like if you do more things, you'll getmore clients but what we fail to realize
is the opportunity cost of if I'm goingto do 10 things, I'm not going to do
(16:35):
them as well as if I were to do two.
So I am much better off by identifyingwhich two are going to provide the lion's
share of the impact and how to kill itat those two and really do it better than
anybody else and it's really hard to doeven for me, this is my seventh business.
I struggle saying no to thingsbecause it's like, Hey, it's
(16:55):
another client, why not?
Let's do it.
You have to be mercilesswith that kind of stuff.
You had to say no to a lot ofthings that drain your time,
your resources and hyperfocus.
So I've been aware ofthis for many years.
I still I'm working on it,so easier said than done.
It's always a part of the journey.
We're always learning things,trying to improve, do better.
(17:16):
It's only human nature to kind of leantowards back what we're more comfortable
in the natural state of things butoverall, with everything you've
learned in business the past 20 years.
What is something that you would tell youryounger self if you could go back in time?
I don't think about that very often.
That's a really good question becauseI'm always thinking about the next
challenge and I don't go back.
(17:38):
I think that for me I used to haveso much anxiety over when you work
for an established company, youget a job and they tell you do
this and then this and this, kindof just follow directions, right?
When you have your own business,nobody has done it exactly
as you've done it before.
And there's no one size fits all formulaeven though there's so many experts are
(18:03):
out there that if you have this smoothiein the morning and wake up at 345 then
that's what it takes, Obviously, whoknows, first of all, even if they were
successful or not and even if they werenobody guarantees that if you just do
exactly what they did things are goingto turn out exactly the same for you.
So you really have to develop thisinternal compass and there's this concept
(18:28):
in economics, which is the expectedvalue, so you don't know before doing
a, B, or C, which one will provide thehighest value but you can try to like
estimate the expected value of each andyou have to be comfortable with the fact
that you really don't know before you doit, which is the best use of your time.
So I had a lot of anxiety over thatbecause it's like it generates a lot of
(18:50):
self doubt and I would spend so much timetrying to like make the right decisions
every time and there were a lot of failureand I think that just getting comfortable
with just taking everything as anexperiment is if I could go back in time,
that's what I would tell my younger self,that there's no direct path from A to B.
You just have to figure it out, do things,some are not going to work, no sweat,
(19:12):
just do the best calculation you have interms of how things are going to turn out.
And if that's incorrect, thencourse correct, then keep going.
That is some really great advicebecause I think we do beat ourselves
up a little bit and have thisfear and anxiety of the unknown.
We're trying something new.
We're all risk takers.
We're trying to take calculatedrisks to make short term
(19:33):
sacrifice for longer term gains.
I think that's what business is about.
To take that fear factor.
We learn a lot by messing up our mistakesand actually having hands on practice.
So I think that's so important to kindof take that fear element out of it.
So you can focus on trying, testing,make everything seem like an experiment.
I think that's so important.
(19:54):
With the AI that's built into yoursystem here, what in a general
sense with AI have you seen?
The changes in the last threeyears and where do you see it
going past 2025 here in in relationto your product and service?
Yeah.
So those are like two questions.
I'll answer the first one interms of like how we're using AI.
(20:15):
Think about it as.
What AI does really well is translatingEnglish to code and the code can do
whatever it needs to do and then itcan answer back in English, so I think
that's in the same way that you can trainan employee and say, Google ads expert.
I want you to look at.
These 20 things what viewers haveshown worst performance in last month.
(20:40):
What campaigns are outperformingother campaigns, so you could
create a list of things right?
And then do it in a way thatsequentially you look at a lot of things?
So I can ask those questions from thedata get the answers back and then
maybe you have 20 pages and thensummarize that and filter out all
the noise, so not everything thatreport is going to be important.
(21:03):
So out of all that human can havethe ability to scan all that and
say, well, what I'm seeing withthe business is this and this.
So that's what we're doing at data speaks
It's called data speaks becauseyou're able to like your data has
something to say but you have thatinterface to have that conversation.
So in terms of the second question, whichis like what's been happening with AI,
(21:26):
where AI is going I think it's goingto change the world much more than the
internet did and that's a lot to say.
And what I mean by that is thatwe've never had this ability to
have unlimited access to all theinformation in the world summarized in
real time or the ability to interactwith multiple systems and I can say.
(21:48):
Once I get that report, send that toPeter, the AI system knows who Peter
is, has the ability to connect tomy Gmail and send that email, right?
So it has not only access to abunch of data but also a bunch
of tools that can perform actionsbeyond just giving you a response.
So When I think about where AI is going,we have very powerful foundational
(22:10):
models, open AI, we have Claude, we havea number of them that essentially have
read the entire Internet, know how humanscommunicate can interpret your questions.
So maybe you're asking why mysales down in your in your data?
It's called revenue not sales buthe knows that revenue sales, right?
So that's really powerful, so thoseconditional models, I think, are
(22:32):
essentially the playground on whichvertical applications will be built.
And what I mean by that is they'retrained with general data.
They're not somebody who knows a littlebit of everything is not going to be as
good as any one thing as somebody who'san expert in that one thing, so if you
train somebody to be a data analyst, youfine tune that foundational model to do
(22:55):
exactly what you wanted to do and it'slike you are the way we have it set up.
For example, there's a concierge thattries to interpret your question.
There's the librarian who has access toall the databases to get the data that
you're looking for that can convert aquestion in English to a sequel query
to go get the data you're looking for abusiness analyst that can then summarize
(23:20):
the findings and then give it backto the concierge to check whether or
not that's what you were asking for.
If it's not, that goes back to the theother agent, so in the same way that
you can train people and do that youcan train agents and have documents
where you just describe what you wanteach one to do and every time somebody
makes a mistake, you do the exact samething you would do with an employee,
(23:40):
which is, by the way, when this happens.
Do this, right?
So you continue finetuning that kind of stuff.
So where I see the opportunityin AI is in picking one specific
problem and training in an agentthat already understands English.
You don't have to train an agentfor that because there's already
(24:03):
those foundational models.
But if you train that agent
to be able to do something that ahuman can do much better and faster.
I think that's where the opportunity is.
Absolutely.
I definitely agree.
It's going to have a ripple effect.
It's going to be disruptive.
It's going to be bigger than the Internetand I think many people perceive it where
Internet first came out, people aresaying it's never going to be a thing.
(24:23):
It's never going to be in homes.
It's not that important.
It's not going to be that disruptiveand suddenly we see a lot of jobs
changing and shifting becauseof the Internet and I think the
same will be said for AI as well.
It'd be fascinating to see howthis technology evolves, how we
use it to better our businesses.
There's a big benefit tohaving technology and software.
(24:44):
That can do things thathave never done before.
It's pretty incredible.
Yeah and I think that with any kindof revolution or substantial paradigm
shift in our way we do things, youcould be in one of two camps, you
could resist it or you can get onboard and you're not going to stop it
so the way I see it is, There used tobe people that would give you horse
(25:05):
rides before cars, like now you don'thave that and it's just changing and
you can't feel bad about it, you justhave to like understand that it's coming
whether or not you like it, it's coming.
And it could make your life a lot easierto get on board with this technology
and I think that what's unique aboutthis is that it will really lower.
It's a much more intuitive technologythan anything that I've seen before.
(25:28):
I think it's even with the Internet,if you want to take advantage of that
gold rush, you had to learn how tocode in a bunch of technologies and
maybe move to like Silicon Valley.
I think that this is something verydifferent in the sense that one business
idea that I had, I'll share this with youand whoever I am not going to pursue it.
Imagine like these experts like, TonyRobbins and all these people that have
(25:51):
built a huge following, how easy wouldit be to build a Tony Robbins AI?
He fitted all the blog posts, all thevideos, all the books he's ever written.
And now you're talking to Tony Robbins,well, the questions that you'd ask
Tony Robbins, most likely you getpretty much the same answer and you
don't have to be a genius to code thatand even AI can help you with that.
(26:13):
So I think there's still going to be aneed for coders for a lot of different
things but for certain things, youcould have AI Do a lot of that for you
and connect to a lot of tools for you.
And I think that is more aboutunderstanding that now you have this
technology that can pretty much outperformany human when it comes to indexing
(26:37):
unlimited amount of data and go intothe right shelf for the right book,
the right page and tell you exactlywhat you're looking for even if you
don't type the right keywords becauseyou could figure out what it is that
you're asking so with that in mind Ithink the opportunities are endless.
I literally have a business idea everyweek and there's only so much time.
(26:57):
I'm always considering how AI canhelp impact or improve this business
or solve this problem and I've hada similar thought to work with a
culture consultant to take their booksand blogs into a single agent just
like you're speaking to that person.
I think many other people have a similaridea and are wondering whether they
want to implement but the opportunitiesare out there for a lot of people, I
(27:18):
think in the same way that smartphonescame to be and now anyone with a camera
or a phone can become an influencer orcreate content, create value of some
sort and make a lot of money doing that.
I think the same willbe said for a lot of AI.
That's coming out thereand ready to be developed.
It's very exciting.
Yeah.
And I'll share my biggestfailure in business was I
(27:40):
started a line of a fashion line.
I'm originally from Argentina, so Ibrought handbags and backpacks, wallets
from Argentina, imported them to theU. S. And it were mostly for women.
There were people doing it, they weremaking money doing that was I got excited.
I didn't know anything about fashion,I dress in pretty casual clothes most
(28:02):
days so that told me a lot about likesolve problems that are your problems.
When your own customer, you're in avery unique position to understand.
What problems you have, what theideal solution would look like.
So I think that's a reallygood place to start.
Whatever business you're in right now,whether you're working for yourself
(28:22):
or you're an employee look at thechallenges that you currently have
that AI could potentially help with
and that's probably a verygood way to get started.
I love that.
For everyone looking forward togetting connected with Zeke here,
you can go to his website dataspeaks.
ai.
His LinkedIn and his ex profilewill be made available down in the
(28:43):
show notes and the description.
Zeke, we only have a few more minutes.
Just wanted to ask, what areyou most excited for for 2025?
Or this is just an open formatfloor for you to mention anything
that we haven't discussed already.
Sure.
So I feel very good about 2025.
I can't put my finger on it.
I just know that there are goodthings coming for data speaks.
(29:04):
I mentioned that I startedsomething that I needed.
So I built it along with a team ofdata scientists around me and it like
organically became something that brandsand agencies started using and that
transition was a little bit challengingbecause there's a big difference between,
we are a team of data scientists andwe use this really sophisticated tool
(29:28):
but then when we put it in the handsof some of our clients, we realized
that they were kind of strugglingwith the complexity of it so we had
to like simplify it substantially.
So we spent last year doing thatand we've been getting really good
feedback that it's so much easier.
That's what I'm excited about.
Making it more widely availablegrowing this year, there's a lot of
(29:49):
something that was already reallypowerful but you had to train yourself.
A lot in terms of howdo we use it properly?
And it was a huge learning curve for us,how to design something very easy to use.
So that's what I'm personally excitedabout but I think that in terms of
anybody who might be listening tothis and parting thoughts, I think
(30:13):
that everybody is struggling in a waythat people that are really successful
are on the same boat that everyidea started with the first sale.
So even if you have 10 sales orone sale, everybody started like
that so you don't doubt yourself,keep doing what you're doing, keep
learning and just don't give up.
I love it.
(30:33):
That's some great advice.
We appreciate you sharing all yourtips, tricks and your wisdom here, Zeke.
Thank you so much forbeing an incredible guest.
Congratulations on all your pastsuccess and looking forward to
what the future holds for you.
Thank you.
There used to be people that wouldgive you horse rides before cars.
Now you don't have that.
And it's just changed when you can'tfeel bad about it, but you just have
to understand that it's coming, whetheror not you like it, it's coming.
You're listening to BrainworkFramework, a business and marketing
podcast brought to you by focused-biz.
com.
Welcome back to another episodewith us today is the CEO of
(00:22):
Data Speaks, Zeke Camusio.
Data Speaks is an AI powered analyticsplatform that helps companies identify
what drives their sales and investin the right marketing strategies.
Zeke, so excited to have you here.
How are you doing?
Doing great.
Thank you for having me.
Absolutely.
We always like to ask our guests, tellus about your entrepreneurial journey.
What were you doing before?
And how did that lead youinto what you're doing today?
Yeah.
So I started when I was 15, I hadmy first business, you could say.
(00:46):
I had a little magazine and Isold advertising space in it
and pretty much did all of it.
Wrote all the articles and went tobusinesses and persuaded them to
advertise in the magazine even designsome of those little ads and stuff.
So that was kind of the first tasteof what it was like to work for
(01:07):
myself and find myself with maybea couple of hundred bucks but it
was more money that I'd ever had.
And the fact that I could just doit on my own, I was super excited.
So since then I've hadsix other businesses.
All of them pretty muchin the internet space.
My last one was a marketing agency thatI had from 2007 to 2015 and after it
(01:31):
got acquired, I kind of told myself.
For the second time in my life thatI was going to retire and I was like
retired for like a couple of monthsand I just couldn't do it anymore.
I just needed to do something productive.
So I was doing consulting for afew of my clients and I had this
Kind of plan to not work too much.
I was only working a couple of hours andI was happy with that and set my hourly
(01:56):
rate pretty high because I didn't wantto have too many clients and What I
noticed is that for every hour that I wasspending Providing insights to my clients.
I was spending four additional hourspreparing for those calls, So I thought
I was getting 500 bucks an hour But Iwas really getting 100 bucks an hour
because I was spending so much timedoing the prep work so I sat down with
(02:20):
a piece of paper and I was like, whatwould it look like if I could Do this
preparation in only 10 minutes and thatwas the inception of my current company.
Data speaks, so I built it for myself.
It's
an all in one analytics platform thatconnects to over 250 different data
sources and uses AI to scan millionsof data points daily to figure
(02:43):
out what works, what doesn't work.
Why?
What to do about it, so that allowedme to kind of check in right before my
calls, just see the alerts and soundlike I spent hours preparing and then
I realized, there's other peoplethat need this, so I started opening
it up to other companies and agenciesand that was about four years ago.
(03:05):
So that's what brought me here.
That is very excitingand quite the journey.
I love that you started sellingadvertising space and magazines but once
you get that taste of entrepreneurship,it's really hard to go back.
And even after building and scalingmultiple businesses and semi retiring
and coming out of retirement.
I think you realize that yourmind, the way that you work,
(03:26):
you just want to help people.
You're good at it and the problemthat you ended up solving was this
huge issue that you had for yourself,the four hours of prep work for a
one hour meeting definitely takesdown that hourly rate pretty quickly.
But to develop this software and asystem that puts that all together.
It's helping solve a lot ofproblems for other consultants,
(03:47):
coaches, and agencies as well.
So with everything that you'reworking with now, you've helped
with both e commerce brands, B2Bbrands, coaches, consultants.
How does the system work asfar as the the analytics?
Because that sounds so cool to take thesedata sources and kind of give you this
overview of what we're looking for.
How does this all work?
(04:08):
Yeah, so our technology is focusedon a aspect of marketing called
attribution and attribution essentiallyis how do you know what cost your
leads or your revenue, right?
So a very common scenario is you'readvertising on LinkedIn, Google, Facebook,
a number of different channels, you sendemails, you have referrals, you have
(04:31):
affiliates, you have influencers and thenat the end of the month, you have 100
leads, 100 million revenue doesn't matter.
There's an outcome and how do youfigure out how you reach that outcome
with the input signals that you have?
And why is that important?
Well, what are you goingto be investing in?
Maybe one of the things that you dohas a negative return on investment.
(04:55):
So you're losing money.
Another thing is, 10 X ROI, right?
So unless you have a way to aggregateall this data and and figure out how
much of your revenue or how many ofyour leads were contributed to by each
market activity that is impossible todecide what to invest more resources in.
(05:17):
So that's the key problem we solve andwe got really good at it and what we
found is that for most, in brands witha digital presence about 60 percent of
all their marketing is advertising spend.
So if you look at a profit and lossstatement, a significant fraction of
that is going to be your advertising.
So we essentially help you getthe most for every dollar that
(05:40):
you invest in advertising.
I love that.
And when you kind of take a step backand look at the buyer's journey, they
obviously see your business somewhereand then they interact with it and
maybe they consume some content.
What do you see as far as what theanalytics are showing how people are first
finding a business that buyers journey?
Does it tell a story there?
(06:01):
Yeah, so there are two different lensesthrough which you can see attribution.
One is called MTA or multi touchattribution and the way that's the
way most people do it in the waythat it's been traditionally done.
So let's say that you find a companyon TikTok and then you just go to
their website, signed up for theemails, get an email, get excited
(06:24):
about something but you don't buy it.
Come back on a different device a weeklater and just search for the company.
Just go to their site and buy it.
What's going to happen is you'regoing to have Google take a hundred
percent of the credit for that sale.
You're going to have your email softwarethat get a hundred percent of the credit.
You're going to have TikTok takea hundred percent of the credit.
So when you add it up, it would seem likeyou have three sales but you only got one.
(06:49):
So with a multi touch attribution.
The way it usually works isyou could say it's last touch.
So the last one gets 100 percent of theof the credit which doesn't make sense
because that wouldn't happen if youhadn't had the prior to touch points.
Or you could say the firstone but also arbitrary, right?
(07:10):
Same if you said, likeit's gonna be linear.
We're gonna divide it 33 percent to each.
Why?
How do you know that each onehad the same amount of impact?
So that was the problemthat I found a few years ago.
And what more than a problem to me,it was an opportunity, like the way
it was done wasn't right and I wasalso seeing the writing on the wall
(07:32):
that users demanded more privacy.
So there were ad blockers were beingincreasingly more popular and then
we have iOS 14, 15, 16, that everytime there's more and more user data
that is being blocked, so the way weused to do it as marketers was to put
a pixel or a tracking code on everywebsite and hope that that will work and
(07:55):
that started working worse and worse.
So what's the alternative toMTA or multi touch attribution?
It's what we coinedimpact based attribution.
So the impact based attributionis based on the actual impact that
every channel, every campaign has.
How do you measure that?
Well, Let's take a very simple test.
Let's say that you're investing10, 000 a month on Google ads.
(08:19):
What would happen if you turn that off?
How much do your sales, wouldyour sales decrease, right?
What would happen if you doubled that?
What would happen to your sales, right?
Like, would they increase by 20%, 30%?
So that's the real way to measure impact.
The problem with thatis that maybe you don't.
Want to double your budget, maybe youdon't want to turn off the campaigns
(08:42):
that bring you revenue, right?
So you have to do it in a way thatyou're minimizing the business.
The negative impact on your business butyou're maximizing the chances of that
measurement being as accurate as possible.
And that's the way we do it.
We talked about 10 differentmarketing channels, TikTok
Facebook, Google and so on.
Let's say that your marketis the United States.
(09:03):
So there's activity for each of those10 channels in each of the 50 states
and then you also have a number ofsales that you get in each state.
So our system increasesor decreases activity.
Let's say you increase your advertisingspend by 20 percent in Maryland.
Okay.
What happens to sales in Maryland?
(09:23):
Do they increase or do they stay the same?
And if they increase by how much?
So based on all that, we're able tomeasure the relative contribution of
each activity to the overall outcome.
So that's much more complex thanthat but that's the gist of it.
Wait, it gets more complex than that?
I'm already not to say it's over my headbut obviously, you know what you're doing.
(09:45):
This really goes deep into the technical,the analytical piece and structure of
how data works when it comes to data.
Was there something that was maybewe're looking at data in the wrong way
or we attribute success or impact oncertain data that is not correct that
you're seeing something different.
Yeah, I think that the key takeaway thatI got from working with data for the last
(10:10):
20 years is that it's not about the databut it's about what we do with the data.
So if the data is not actionable, forexample, you got a hundred visitors
last week and you got 120 this week.
It's like, so what?
Do I need to do somethingdifferent because of that?
I mean, you could be excited about that.
I'm not going to try to take that awayfrom you but in terms of figuring out
(10:31):
how to allocate the limited resourcesthat a company has, whether that's
time or money or focus like, that'sdefinitely the main thing, right?
Identifying out of the hundredpossible things that you could
do, what are the two or three thatwill move the needle the most?
And what are the actions thatyou need to take towards that?
(10:52):
So I think that there's a need to have abasic dashboard with some key metrics that
are important to you to keep track of howthings are going but you should always
be asking yourself, am I changing theway I do things based on the data I have?
And if not what are themetrics I should be looking at?
It seems very simple but it's usuallywhere there's a lack of implementation
(11:14):
in terms of figuring out what metricsmatter and what to do based on.
The story they tell you.
I really appreciate that you went moreinto the fact that data can tell you any
story that it wants but it matters basedon the action that you're going to take.
What does that data mean to me?
What am I going to do fromhearing that information?
(11:35):
And that's that's really important when itcomes to finding actionable insights from
from what you're learning and I hear allthe time as far as the difference between
analytics and reporting is analyticstells you what happened reporting.
You try to explain why it happened.
So understanding what data is tellingyou, the story that it's trying to
convey, the message is so important fortrying to grow and level your business.
(11:57):
What's going to havethe most impact for you.
A lot of our audience hereare actually in the B2B realm.
And one thing you talk aboutis how you can grow your B2B
company or brand in 2025.
What are your biggest takeaways?
What should be focused onfor a lot of these B2B brands.
Yeah, so I think that you really dependon where you are with your business but I
(12:19):
think you have to start with What are allthe variables that you want to understand.
So for example, you could say
Where people come from.
That's one of them, right?
Like what channel they found youon, but that's not the only one,
our CEOs buying from you more thanCFOs or CMOs are ads with videos
working better than ads with images?
(12:41):
Is it the case that when you orsomebody in your team is in the
video, those videos were better thantestimonial videos, for example.
So All those are variables, right?
Like all of all those are questionsthat you have about what's working and
then you have to be very deliberatein terms of how you track that to get
the data to answer those questions.
(13:01):
So one of the things you could do isname your campaigns or ads in a way that
all video ads have medium equals video
so it's just Tagging things the rightway helps you find those patterns
because maybe you want to see theperformance of all your video content
versus text content across all platformsbut that's only possible if there's a
(13:23):
common nominator for all media content.
So in terms of setting yourselfup in a way that you're going
to maximize the amount oflearning that's really important.
Figuring out what work questions.
Do I want to get answers to?
and how am I going to label thingsin a way that is going to help
me answer those questions?
(13:43):
Now, in terms of what works, itreally depends on the business
model is really hard to givelike a one size fits all answer
but what I found is, if you wantme to be LinkedIn, it's going to
be a great part of your success.
I love the new feature for newsletters.
LinkedIn is doing a reallygood job featuring people that
post a lot in quality content.
(14:04):
So shorts are being veryhelpful right now.
Um, what else?
I think that any kind of thoughtleadership, having your own Podcast,
your own webinars, doing having a blog.
I think that leveraging otherpeople's audiences is really key.
If you appear on a podcast thathas 5, 000 listeners, that's
(14:24):
usually 5, 000 people that youwouldn't have access to otherwise.
So I think that's huge.
The answer will really dependon who your target audience is.
I'm a big fan of prospecting., I learnedthis from a guy named Trevor Graves
that owns a mark marketing agency herein Portland, Oregon called Nemo Design.
And he was like a big inspirationfor me and he said that every year he
(14:48):
sits down and he says, these are the20 clients I want to get this year.
Rather than having a shotgunapproach of like, I'll just
take whoever's like 20 clients.
I'm going to learn everything about them.
Who's on their team.
I'm going to follow everything they post.
I'm going to engage with them.
I'm going to take him out for lunch.
Anything but I really love that becauseeverything else we talked about prior
(15:11):
to that is like, big scale but not verypersonalized with this is the exact
opposite and we do that every year.
These are the 20 clientswe want to work with.
What can we do to get them, likeyou're not going to get all 20 of
them but if you do a good job definingwho your ideal client is, hopefully
you'll get at least five of them.
I love that.
That is so incredibly smart.
(15:32):
And I really agree with the quality overthe quantity when it comes to clients
really hone in on who you want to workwith your ideal client lists, those
companies learn everything about them.
The quality and the value that youprovide to them is going to show
you're building the trust towardstheir business and it's going to be
way more effective than just making ablanket advertising campaign or a video.
(15:52):
Again, many things can be effectivebut if you're really showing you want
to build a relationship, especiallyB2B that's so important to really
take that personalized approach.
And I loved hearing thatLinkedIn is the place to do it.
Here's what's working great.
I appreciate all that feedback.
Yeah.
I think the other thing is one of myfavorite quotes is strategy is not
(16:13):
what we do is what we don't do and Ithink it's Peter Drucker and I think
every entrepreneur is guilty of this.
I've heard it called the shiny lightsyndrome where it's like intuitively,
it kind of makes sense, right?
Like if you do more things, you'll getmore clients but what we fail to realize
is the opportunity cost of if I'm goingto do 10 things, I'm not going to do
(16:35):
them as well as if I were to do two.
So I am much better off by identifyingwhich two are going to provide the lion's
share of the impact and how to kill itat those two and really do it better than
anybody else and it's really hard to doeven for me, this is my seventh business.
I struggle saying no to thingsbecause it's like, Hey, it's
(16:55):
another client, why not?
Let's do it.
You have to be mercilesswith that kind of stuff.
You had to say no to a lot ofthings that drain your time,
your resources and hyperfocus.
So I've been aware ofthis for many years.
I still I'm working on it,so easier said than done.
It's always a part of the journey.
We're always learning things,trying to improve, do better.
(17:16):
It's only human nature to kind of leantowards back what we're more comfortable
in the natural state of things butoverall, with everything you've
learned in business the past 20 years.
What is something that you would tell youryounger self if you could go back in time?
I don't think about that very often.
That's a really good question becauseI'm always thinking about the next
challenge and I don't go back.
(17:38):
I think that for me I used to haveso much anxiety over when you work
for an established company, youget a job and they tell you do
this and then this and this, kindof just follow directions, right?
When you have your own business,nobody has done it exactly
as you've done it before.
And there's no one size fits all formulaeven though there's so many experts are
(18:03):
out there that if you have this smoothiein the morning and wake up at 345 then
that's what it takes, Obviously, whoknows, first of all, even if they were
successful or not and even if they werenobody guarantees that if you just do
exactly what they did things are goingto turn out exactly the same for you.
So you really have to develop thisinternal compass and there's this concept
(18:28):
in economics, which is the expectedvalue, so you don't know before doing
a, B, or C, which one will provide thehighest value but you can try to like
estimate the expected value of each andyou have to be comfortable with the fact
that you really don't know before you doit, which is the best use of your time.
So I had a lot of anxiety over thatbecause it's like it generates a lot of
(18:50):
self doubt and I would spend so much timetrying to like make the right decisions
every time and there were a lot of failureand I think that just getting comfortable
with just taking everything as anexperiment is if I could go back in time,
that's what I would tell my younger self,that there's no direct path from A to B.
You just have to figure it out, do things,some are not going to work, no sweat,
(19:12):
just do the best calculation you have interms of how things are going to turn out.
And if that's incorrect, thencourse correct, then keep going.
That is some really great advicebecause I think we do beat ourselves
up a little bit and have thisfear and anxiety of the unknown.
We're trying something new.
We're all risk takers.
We're trying to take calculatedrisks to make short term
(19:33):
sacrifice for longer term gains.
I think that's what business is about.
To take that fear factor.
We learn a lot by messing up our mistakesand actually having hands on practice.
So I think that's so important to kindof take that fear element out of it.
So you can focus on trying, testing,make everything seem like an experiment.
I think that's so important.
(19:54):
With the AI that's built into yoursystem here, what in a general
sense with AI have you seen?
The changes in the last threeyears and where do you see it
going past 2025 here in in relationto your product and service?
Yeah.
So those are like two questions.
I'll answer the first one interms of like how we're using AI.
(20:15):
Think about it as.
What AI does really well is translatingEnglish to code and the code can do
whatever it needs to do and then itcan answer back in English, so I think
that's in the same way that you can trainan employee and say, Google ads expert.
I want you to look at.
These 20 things what viewers haveshown worst performance in last month.
(20:40):
What campaigns are outperformingother campaigns, so you could
create a list of things right?
And then do it in a way thatsequentially you look at a lot of things?
So I can ask those questions from thedata get the answers back and then
maybe you have 20 pages and thensummarize that and filter out all
the noise, so not everything thatreport is going to be important.
(21:03):
So out of all that human can havethe ability to scan all that and
say, well, what I'm seeing withthe business is this and this.
So that's what we're doing at data speaks
It's called data speaks becauseyou're able to like your data has
something to say but you have thatinterface to have that conversation.
So in terms of the second question, whichis like what's been happening with AI,
(21:26):
where AI is going I think it's goingto change the world much more than the
internet did and that's a lot to say.
And what I mean by that is thatwe've never had this ability to
have unlimited access to all theinformation in the world summarized in
real time or the ability to interactwith multiple systems and I can say.
(21:48):
Once I get that report, send that toPeter, the AI system knows who Peter
is, has the ability to connect tomy Gmail and send that email, right?
So it has not only access to abunch of data but also a bunch
of tools that can perform actionsbeyond just giving you a response.
So When I think about where AI is going,we have very powerful foundational
(22:10):
models, open AI, we have Claude, we havea number of them that essentially have
read the entire Internet, know how humanscommunicate can interpret your questions.
So maybe you're asking why mysales down in your in your data?
It's called revenue not sales buthe knows that revenue sales, right?
So that's really powerful, so thoseconditional models, I think, are
(22:32):
essentially the playground on whichvertical applications will be built.
And what I mean by that is they'retrained with general data.
They're not somebody who knows a littlebit of everything is not going to be as
good as any one thing as somebody who'san expert in that one thing, so if you
train somebody to be a data analyst, youfine tune that foundational model to do
(22:55):
exactly what you wanted to do and it'slike you are the way we have it set up.
For example, there's a concierge thattries to interpret your question.
There's the librarian who has access toall the databases to get the data that
you're looking for that can convert aquestion in English to a sequel query
to go get the data you're looking for abusiness analyst that can then summarize
(23:20):
the findings and then give it backto the concierge to check whether or
not that's what you were asking for.
If it's not, that goes back to the theother agent, so in the same way that
you can train people and do that youcan train agents and have documents
where you just describe what you wanteach one to do and every time somebody
makes a mistake, you do the exact samething you would do with an employee,
(23:40):
which is, by the way, when this happens.
Do this, right?
So you continue finetuning that kind of stuff.
So where I see the opportunityin AI is in picking one specific
problem and training in an agentthat already understands English.
You don't have to train an agentfor that because there's already
(24:03):
those foundational models.
But if you train that agent
to be able to do something that ahuman can do much better and faster.
I think that's where the opportunity is.
Absolutely.
I definitely agree.
It's going to have a ripple effect.
It's going to be disruptive.
It's going to be bigger than the Internetand I think many people perceive it where
Internet first came out, people aresaying it's never going to be a thing.
(24:23):
It's never going to be in homes.
It's not that important.
It's not going to be that disruptiveand suddenly we see a lot of jobs
changing and shifting becauseof the Internet and I think the
same will be said for AI as well.
It'd be fascinating to see howthis technology evolves, how we
use it to better our businesses.
There's a big benefit tohaving technology and software.
(24:44):
That can do things thathave never done before.
It's pretty incredible.
Yeah and I think that with any kindof revolution or substantial paradigm
shift in our way we do things, youcould be in one of two camps, you
could resist it or you can get onboard and you're not going to stop it
so the way I see it is, There used tobe people that would give you horse
(25:05):
rides before cars, like now you don'thave that and it's just changing and
you can't feel bad about it, you justhave to like understand that it's coming
whether or not you like it, it's coming.
And it could make your life a lot easierto get on board with this technology
and I think that what's unique aboutthis is that it will really lower.
It's a much more intuitive technologythan anything that I've seen before.
(25:28):
I think it's even with the Internet,if you want to take advantage of that
gold rush, you had to learn how tocode in a bunch of technologies and
maybe move to like Silicon Valley.
I think that this is something verydifferent in the sense that one business
idea that I had, I'll share this with youand whoever I am not going to pursue it.
Imagine like these experts like, TonyRobbins and all these people that have
(25:51):
built a huge following, how easy wouldit be to build a Tony Robbins AI?
He fitted all the blog posts, all thevideos, all the books he's ever written.
And now you're talking to Tony Robbins,well, the questions that you'd ask
Tony Robbins, most likely you getpretty much the same answer and you
don't have to be a genius to code thatand even AI can help you with that.
(26:13):
So I think there's still going to be aneed for coders for a lot of different
things but for certain things, youcould have AI Do a lot of that for you
and connect to a lot of tools for you.
And I think that is more aboutunderstanding that now you have this
technology that can pretty much outperformany human when it comes to indexing
(26:37):
unlimited amount of data and go intothe right shelf for the right book,
the right page and tell you exactlywhat you're looking for even if you
don't type the right keywords becauseyou could figure out what it is that
you're asking so with that in mind Ithink the opportunities are endless.
I literally have a business idea everyweek and there's only so much time.
(26:57):
I'm always considering how AI canhelp impact or improve this business
or solve this problem and I've hada similar thought to work with a
culture consultant to take their booksand blogs into a single agent just
like you're speaking to that person.
I think many other people have a similaridea and are wondering whether they
want to implement but the opportunitiesare out there for a lot of people, I
(27:18):
think in the same way that smartphonescame to be and now anyone with a camera
or a phone can become an influencer orcreate content, create value of some
sort and make a lot of money doing that.
I think the same willbe said for a lot of AI.
That's coming out thereand ready to be developed.
It's very exciting.
Yeah.
And I'll share my biggestfailure in business was I
(27:40):
started a line of a fashion line.
I'm originally from Argentina, so Ibrought handbags and backpacks, wallets
from Argentina, imported them to theU. S. And it were mostly for women.
There were people doing it, they weremaking money doing that was I got excited.
I didn't know anything about fashion,I dress in pretty casual clothes most
(28:02):
days so that told me a lot about likesolve problems that are your problems.
When your own customer, you're in avery unique position to understand.
What problems you have, what theideal solution would look like.
So I think that's a reallygood place to start.
Whatever business you're in right now,whether you're working for yourself
(28:22):
or you're an employee look at thechallenges that you currently have
that AI could potentially help with
and that's probably a verygood way to get started.
I love that.
For everyone looking forward togetting connected with Zeke here,
you can go to his website dataspeaks.
ai.
His LinkedIn and his ex profilewill be made available down in the
(28:43):
show notes and the description.
Zeke, we only have a few more minutes.
Just wanted to ask, what areyou most excited for for 2025?
Or this is just an open formatfloor for you to mention anything
that we haven't discussed already.
Sure.
So I feel very good about 2025.
I can't put my finger on it.
I just know that there are goodthings coming for data speaks.
(29:04):
I mentioned that I startedsomething that I needed.
So I built it along with a team ofdata scientists around me and it like
organically became something that brandsand agencies started using and that
transition was a little bit challengingbecause there's a big difference between,
we are a team of data scientists andwe use this really sophisticated tool
(29:28):
but then when we put it in the handsof some of our clients, we realized
that they were kind of strugglingwith the complexity of it so we had
to like simplify it substantially.
So we spent last year doing thatand we've been getting really good
feedback that it's so much easier.
That's what I'm excited about.
Making it more widely availablegrowing this year, there's a lot of
(29:49):
something that was already reallypowerful but you had to train yourself.
A lot in terms of howdo we use it properly?
And it was a huge learning curve for us,how to design something very easy to use.
So that's what I'm personally excitedabout but I think that in terms of
anybody who might be listening tothis and parting thoughts, I think
(30:13):
that everybody is struggling in a waythat people that are really successful
are on the same boat that everyidea started with the first sale.
So even if you have 10 sales orone sale, everybody started like
that so you don't doubt yourself,keep doing what you're doing, keep
learning and just don't give up.
I love it.
(30:33):
That's some great advice.
We appreciate you sharing all yourtips, tricks and your wisdom here, Zeke.
Thank you so much forbeing an incredible guest.
Congratulations on all your pastsuccess and looking forward to
what the future holds for you.
Thank you.
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