Episode Transcript
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Speaker 1 (00:13):
Hello and welcome back to the how to Get an
Analytics Job podcast.
So today we're doing somethingnew.
I don't think we've everactually done this before.
So I'm sitting here across fromone of my current students here
at Greensboro College and we'regoing to be talking about five
specific things.
So number one we're going to beintroducing him, kind of give
some background on you knowwhere he's at right now.
(00:35):
We're going to also be talkingabout his skills and experience.
We're going to be talking aboutthe job hunt, both kind of at a
high level, and then also whathe is going through as far as
you know what status he's atright now, what kind of
anxieties, what kind of worrieshe might have.
And then, finally, we're goingto do some mock interview
questions.
(00:55):
So, dejuan, welcome, how areyou feeling?
Speaker 2 (00:59):
I'm feeling great.
Thank you for having me.
Speaker 1 (01:02):
Yeah, so thank you so much.
I mean, this was kind of lastmoment.
We're actually studying thepodcast in class, so I don't
know if we can get any more metathan we are right now.
But it turns out that you havebeen doing content creation for
about a year, so sometimes Iactually just pull you up to the
front of the classroom and letyou kind of talk about what you
(01:23):
know, and then I'll fill in anyknowledge gaps.
So I guess, just quicklyintroduce yourself, like what's
your background, your currentgoals and kind of what are you
going through?
Right?
Speaker 2 (01:33):
now.
I am from Riverdale, Maryland.
I am currently a senior in atGreensboro College.
I major in businessadministration with a minor in
business analytics.
My goals are to just get a jobin my career, hopefully in
analytics, even if it's just anentry-level job.
(01:56):
Pass that life goals.
I'm a simple guy.
I just want to be able to paymy bills, do my hobbies and
hopefully spend time with myfamily.
If I have one, what?
Speaker 1 (02:08):
was the third one, my bad, just like.
So, I guess, the current status.
I guess I can kind of fill itin so you were rounding out the
last semester of your senioryear.
Yes, so now is when you need tokind of get your personal brand
tightened up.
We're getting on your LinkedInyour resume and then also
getting you prepped up.
We're getting on your LinkedIn,your resume and then also
getting you prepped up for theinterview process, because I
(02:29):
mean, literally, you just gotyour first interview set up, yes
, like within.
I mean we had class at, I think, one yesterday, so I mean this
is like in real time happening.
So I mean I guess let's kind ofstart with what skills and what
experience do you have?
Because I know that you're Ithink I looked at your LinkedIn
before this so you're about 10months in to like working a job
(02:53):
currently.
So I guess could you tell me alittle bit about that?
Speaker 2 (02:56):
My current job is at the Greensboro Board ABC stores.
There we just do usual salesassociate stuff, just talking to
customers.
We're recommending them drinks,helping them find drinks.
But we also we also have timeswhere they want us to push a
certain product or sales on acertain product.
Like if we get sales on likeallocated drinks which are
(03:20):
basically like if you're foranybody who drinks, it's bourbon
, it's buffalo, trace, eagle,rare wellers, blanton's, eh,
taylor, those kind of drinks wekind of when we get them, we put
them out.
We put them out fast.
A lot of people it's a hotseller because it's ready to get
.
Everybody wants somethingthat's scarce.
So yeah, we, we do that.
(03:42):
It's a lot of basic storemaintenance but when it comes to
that job I think it's veryundervalued.
Being a sales associate topeople who drink regularly, just
sometimes having to deal withpeople who sometimes come in and
they're not up to the standardof the store, they're not at
(04:04):
their best, and just having todeny them and seeing how they
can act when denied their drinks.
Okay, so you're kind of gettinginto like customer management a
little bit, maybe risk liability, like mitigating risk yeah
mitigating risk, just being ableto de-escalate situations,
being able to also just beingable to help people in general
(04:26):
help people who sometimes don'tknow they're asking for a gift
for their wife or their familyjust being able to help them.
But other than that I've done.
I'm currently doing theinternship with you which we are
studying this very podcast,looking at the audience curves
and the retention curves on thispodcast to help push content
and create.
Did we decide if we were goingwith the short clips?
(04:48):
I don't remember.
Speaker 1 (04:49):
I apologize.
Yeah, so we'll get into this alittle bit more, because this is
kind of what I guess to teasethe audience a little bit.
Like this is what we're goingto talk about.
As far as the mock interviewquestion, I'm going to ask you
like hey, I see that you, youknow, for three months at a
student practicum where you gotto work with real data.
Tell me about that, so we'llkind of get into that a little
(05:15):
bit more specific in the contextof a mock interview question.
But I guess okay, so that kindof gives a good breakdown of
your experience.
But as far as skills go, I meanone of the things we were
talking about, like when we werekind of diagnosing the podcast,
the last episode, we we pushedout, like we I mean I guess we
can get into it a little bit, sowe looked at the well, before
we even get into you know whatthe results were, what.
(05:38):
What data do we look at?
Speaker 2 (05:40):
we looked at audience retention curve and then we
looked at.
We also looked at audienceretention curve and then we
looked at.
We also looked at who iswatching the videos.
We looked at the views and theunique.
We also talked about uniqueviews versus just regular views.
Yeah, those are things that welooked at.
We also looked at where it was.
Where are people peaking in theretention curve?
(06:02):
Where are people peaking in theretention curve?
Speaker 1 (06:03):
So yeah, which I think is a really interesting
concept, especially for thosewho are listening, like you
probably don't think about, likethe analytics that are this
behind media consumption, butwhat is the audience retention
curve?
Speaker 2 (06:15):
The audience retention curve is basically how
long somebody is watching thevideo or how long they stay on
the video.
And basically, if I were, if itwas to be shown in a graph, it
would basically be like a line,and imagine at the top of that
line is when you first click onthe video, which is at a hundred
percent.
Speaker 1 (06:32):
Yeah, it's at a hundred.
Speaker 2 (06:33):
Yeah, your line can either stay at that rate or it
can slowly drop.
Speaker 1 (06:39):
Or it could rapidly drop.
Speaker 2 (06:40):
Yeah, it could rapidly drop as well, but with
that retention curve, if yourretention curve is steadily
constant throughout the video,your video everybody was able to
understand your video, watchyour video and they continued
watching it without feeling likethis video is talking about
something that I'm not lookingfor.
Speaker 1 (07:02):
So yeah, so the dips are when people you essentially
lose their interest.
They're switching off, or itcould be that they're fast
forwarding.
So what can we do with thatretention curve, Because there's
different ways to look at it,right?
So what you're talking about isthe aggregate view.
So that's everyone who viewedit.
We can look at it like that.
What can we do as far as theaggregation goes?
Speaker 2 (07:24):
We can look at it like that what can we do as far
as the aggregation goes?
We can look at it and see whereare we getting spikes, and then
we can go to that retentioncurve and we can look at the
spikes in the video and we cansay, okay, this is an
interesting topic from ourpodcast.
A lot of people came back andlooked at this and, like I, like
I when we were in class, we canjust take that portion, put it
(07:48):
into a short clip and if we bothlooked at it and was like I
feel like this is veryinformative, we can post that as
a short clip to have people whodidn't see the podcast still
gain a piece of informationabout what we're producing.
Speaker 1 (08:06):
Well, I guess what I was trying to kind of lead you
with a little bit with like theI guess the Socratic question
method, is we can change theaggregation so you were
describing it as the totalaudience If we change it to how
it relates to other videos,performances, that's where we
can see the spikes.
So what now we're doing isgoing back and looking at each
week's podcast episode andidentifying where those spikes
(08:28):
are, listening back to it,figuring out what the topics are
, and then we're using AI toclip the podcast as it relates
to those specific topics.
So, essentially, if we losesomebody early on in the episode
, we can post a short and thenretarget those people who
dropped it off.
So it's a way to.
(08:48):
It's essentially like anawareness campaign from a
marketing standpoint, which Ithink is really cool.
But okay, we're nerding out toohard on the details, I guess.
So this is kind of theexperience you've gained, which
I think is awesome, and it'sgreat that you can articulate it
pretty well, like you're ableto sit down and explain it.
I mean, part of it is becauseyou guys are doing the work.
(09:11):
I'm not spoon-feeding it to you.
I'm like here's the goal, youguys figure it out and then I'm
kind of here to play a supportrole and kind of manage the
project.
But tell me about the skillsthat you developed, because,
because we've we've beentogether for two semesters now.
Speaker 2 (09:28):
I've um.
The first was in Power BI.
That also helped me with theprevious internship and I could
get into that later.
If you'd like.
Um, that kind of getting betterat Excel, honing my skills at
Excel was something that yourclass helped me a lot with and
just overall data visualizationand project management.
Being able to even, like yousaid, cut up AI clips and also
(09:50):
go back in and make it evenbetter and make it even more
focused and more target audience, because sometimes AI can be
great in producing all thoseclips, but I still it's kind of
dumb yeah.
Yeah, in a weird way it's likehyper-competent, but also it
lacks any type of wisdom orjudgment yeah, so like sometimes
, like there are certain clipswhere it may say it's talking
(10:11):
about this topic, but if youwere a normal person watching it
, you wouldn't, you wouldn'teven make that connection.
Yeah, you wouldn't even makethe connection, and being able
just going back back in andbeing able to edit those and
being able to make sure thoseare reaching the right audience
or even speak on the rightsubject when relating to the
topic at hand.
Speaker 1 (10:29):
That's something that I've gained from this and I
guess let me ask you this Do youhave a way to show, let's say,
you show up into an interview inthe next few weeks.
Let's say it goes well withthis kind of phone screen that
you're about to go through, ifyou?
Speaker 2 (10:49):
were on like a Zoom call.
Do you have a way to kind ofshowcase the work that you've
done?
I would be able to showcase the.
In my previous internship,before I started with you, I did
data analysis for our collegefootball team where I took their
practice, penalties and errorsand I managed them, I organized
it, cleaned it up and put it inExcel and then transferred it
(11:10):
over into the data visualizationtool of Power BI and I made the
graphs and I made the linecharts for the comparison from
their in-game penalties andmistakes to their practice and I
was able to show the ratio andcomparison between those two
within those line graphs, whilealso showing the way my coach,
the way my supervisor, which wasthe coach, the way he wanted it
(11:34):
was.
He wanted to be able to see weekby week, the penalties and the
number of penalties, which isalso what I did.
So I was able to visualize thatwith a drop-down toolbar.
You can click on the week, eachgame week, and it will show you
the practice, penalties andmistakes and then the games.
And he said he just wanted tobe able to see where are we
(11:54):
overlapping, where are we havingtoo much of a problem in, and I
made that visible to himthrough Power BI, so that is
something that I can show topotential recruiters or
employers when they ask me toshow.
Speaker 1 (12:08):
Right, let me ask you this Did you have a test last
semester?
Speaker 2 (12:11):
Did I have a test?
No, no.
Speaker 1 (12:13):
I didn't.
Your test was your portfolio,so like and I did this with
intention because I mean, what'sa better story when you show up
for that interview of hey, Igot an A-plus on this test
versus?
Here are three projects I'veworked on.
I'd be happy to show you theuse case and show you the UI and
uncover some insights withinthis data that I analyzed, and
uncover some insights withinthis data that I analyzed.
(12:35):
I mean so like, whether yourealize it or not, I've been
slowly trying to help you prepfor the transition that's coming
.
What two months?
Speaker 2 (12:46):
two months away.
Speaker 1 (12:48):
Two months, I mean.
I guess that's kind of aperfect segue into.
The third topic that we wantedto cover was how's the job hunt
coming along?
Speaker 2 (12:58):
I mean your face.
Speaker 1 (12:59):
for those of you who are listening in audio, your
face is not looking superconfident, which is
understandable, because I meangoing from college to working is
a huge transition andespecially like we were kind of
talking like the market's alittle tough right now.
Speaker 2 (13:15):
It's not going well but, like we did say at talking,
like the market's a littletough right now it's not going
well.
But like we did say at thebeginning of the podcast, I did
get a text back for a Zoominterview with Crown Royal
Campaigns, so I have that Monday, so I hope that goes well.
But aside of that it has notbeen going well.
Speaker 1 (13:33):
Well, ok, is it not going well?
Or do you feel like maybe youneed to adjust your expectations
?
Like, let me ask you this howmany jobs have you applied for?
90.
90.
Okay, what is the timeline onthat?
The timeline as in like— Like ifyou applied for 90 jobs and
it's been two months, that'sprobably a bad sign, but if,
(14:01):
like, some of the jobs youapplied have been a matter of
weeks or maybe even a month likesometimes you don't hear a
callback for six weeks on a jobso I just want to kind of like
give you that zoomed outperspective on it.
Speaker 2 (14:07):
And I'm probably not used to that, probably because
of the jobs I've workedpreviously.
They usually hit you backwithin like a week or two, so
that's probably something I needto adjust to, but it's been
over the span of three months,okay.
So I've been getting somerejection emails later where
they've been moving on with adifferent applicant which is I'm
fine with.
Yeah, you're expected, yeah,that's natural.
(14:29):
I feel like at least you'relooking at my resume or somebody
or some type of system is so,at least it's being looked at.
I think that I'm not gettingdiscouraged.
Speaker 1 (14:44):
I think that eventually, Well, you just said
it wasn't going well.
Speaker 2 (14:50):
It's not going well, but I'm not surprised because of
one, not my experience, butjust I don't have that much of a
networking, as we spoke on inprevious classes.
I think I just need to build mynetwork more to be able to open
more doors than just coldapplying, as in when cold
applying, there could always besomebody who has more experience
(15:12):
, even at an entry-levelposition, than I do.
Speaker 1 (15:15):
So just opening my networks, which one of them is
you and another one can be thecamera guy, craig craig over
here our personal jamie yeah butyeah, I mean because I I've
invited you guys out because I Ihost, uh, a fairly regular
meetup and it's funny cause youguys were like six 6 PM on a
(15:37):
Wednesday, but now you'regetting it, while I was like
this is important becausethere's a whole hidden job
market out there, like whatyou're seeing on LinkedIn or in
D or whatever is.
It's the highest hurdle to jumpover.
Like it, these jobs are gettinghundreds of applicants, of
applicants, within the first 24hours.
(15:59):
So like you as a student whohaven't worked as an analyst
full-time yet, like that's, it'sa, it's a big challenge to get
up above that.
Now you can kind of play thenumbers game and just you know,
like I think I was saying, onestrategy is just get your
one-click apply set up, so every24 hours, every analytics or it
(16:21):
doesn't even have to beanalytics, it could be you want
to get into marketing, marketing, specialist jobs, any jobs that
are relevant for you, justevery 24 hours, posting and
being on top of that.
So you're at the top of thatlist.
I mean on top of that, soyou're at the top of that list.
But yeah, the kind of thehidden job market or like kind
of the back door into the job isto know somebody who is either
(16:42):
hiring or some know somebody whojust got asked hey, do you know
somebody who's looking for anentry level job?
Speaker 2 (16:50):
Yeah, yeah, and I feel like I get that door on top
of the cold applying.
I feel like I'll, I'll,eventually, I'll get somewhere
or I'm not.
I get that door on top of thecold applying.
I feel like I'll get somewhereor I'm not, and that's probably
why I'm not too anxious.
I know it'll take time and Idon't feel like I need to be in
as much of a rush as it'sperceived, so I just feel like,
as long as I just keep doingwhat I'm doing, I feel like my
(17:12):
resume is up to date, myLinkedIn profile is polished, I
feel like I've set myself up forthe opportunities at hand, so I
just have to keep knocking onthe door.
Speaker 1 (17:23):
Can you unpack that a little bit more?
So, when you say you feel goodabout your LinkedIn and your
resume, why do you feel that way?
Speaker 2 (17:29):
Because of some of it .
Most of it, I'm not going tosay.
Some of it.
Most of it was just having myresume looked over.
Yeah, and also by you and alsoby our careers and developments
Specialists yes, Karen Atwater,both of you looking at my resume
and then also just using theeverybody says keywords, making
(17:52):
sure it's actually related tothe jobs I'm applying for and
using the experience andactually accolades that I've
gained throughout my internshipsand my jobs in my profile.
So not just rambling on aboutduties but, like in my resume,
it says I boosted sales ofspecial order drinks by 15% at
(18:13):
my store, which is somethingthat's fantastic.
Speaker 1 (18:16):
Can we pause there and kind of dig into that a
little bit?
Yeah, so, like, what you'vedone is you've quantified the
work you've done, and I wouldsay the vast majority of people
are not doing that.
It's like they list out rolesand responsibilities.
They don't list out the impactthat they've had within a
business, so it, what do youthink that signals?
Speaker 2 (18:38):
I think that signals that I'm actually profitable or
helping the business make profit.
That's what I look at Well.
Speaker 1 (18:46):
I would say it signals that you have the right,
correct mindset, Like you arelooking at it from instead of
let me just be this person whodoes all these lists of tasks
you're actually thinkingcritical about it, Like you're
getting your job done, butyou're also thinking about ways
that you can potentiallyoptimize, or you know what are
(19:08):
the levers that you can pull tomake things go even better.
So like having that kind ofmindset ports over really well
to a full-time job.
So I think you're in reallygood shape there All right.
Speaker 2 (19:24):
So how's your LinkedIn?
I think my LinkedIn is is good.
I'll say good, I won't say myLinkedIn is great.
I think I need to kind of gointo more depth about the actual
skills that I've attained fromthe internships and the jobs
that I've worked.
Yeah, I just think that some ofthem are like kind of too broad
and then some of them aren'tlike really narrowed down.
(19:45):
Like for the one I did thesports analyst I did with my
football team.
I could say I did a projectmanagement Because, technically,
me uploading the data into,yeah, you managed it like they
gave you a directive and thenyou broke it down into steps and
you took all those steps.
Speaker 1 (20:06):
we go even further, like data governance.
You collected all the data,then you create, you put it into
a form that was actually cleanand able to be uploaded into a
BI tool, and then you took thatand you visualized it in a way
that the head coach couldinterpret and then they could go
back and rework their training,because you guys did crazy
(20:30):
training last semester, right.
Speaker 2 (20:33):
Yeah, in-season and out-of-season Right now, even
though I'm not on the team sinceI'm graduating, but right now
for spring ball, they do.
They do basically like uh,cardio runs five days a week,
lift three days a week, and thenthey have meetings and other
things throughout the week.
So this is like each week, thisand we're not even in season,
but I mean, so this is like eachweek.
Speaker 1 (20:56):
And we're not even in season.
But I mean speak to me a littlebit about how does the data
that you created help with thatwhole process.
Speaker 2 (21:02):
So it helps with it, as, when it comes to just the
coaches like basically teachingtheir positions, or the head
coach coaching his team overalland coaching his coaches, his
staff it's okay if our runningbacks fumbled the ball a lot.
Okay, as a head coach, I needto talk to my running backs
coach and see what we need tothink of something to help
(21:25):
reduce this, because turningover the ball is never a good
thing.
If we're getting a lot ofunsportsmanlike conduct,
penalties, which is basicallylike if a play is over and the
ref blows the play dead, one ofour players pushes somebody else
, that's unsportsmanlike, yeah,so why are we doing that?
(21:45):
That's us as a team.
We need to sit down as acoaching staff and address the
culture.
Speaker 1 (21:51):
Yeah, and address the culture of the team.
Speaker 2 (21:53):
Those are things that the head coach will now have to
think about, or now be likegoing into the next game.
Okay, we had two fumbles thisweek during practice.
We need to focus on ballsecurity, focus on not fumbling
the ball.
We need to do a lot of ballsecurity drills so that we can
help reduce this going into ourgame this Saturday.
Those are just ways that justme with a football background
(22:17):
know that these are things thata head coach would more than
likely say to his staff to helpreduce these mistakes that
they're making.
Speaker 1 (22:24):
Yeah, I mean, that's a really unique kind of setup in
that you are helping, kind ofyour manager in this situation,
or coach, coach and manager, Iguess Coach, well, but like the
coach is managing the team.
So I I'm like thinking about,like the title is coach,
functionally speaking.
(22:44):
They're managing all theplayers and you know, like how
things are going.
So you, you, you were playing arole in helping them optimize.
Yes, so I mean that's andhelping them optimize.
Yes, so I mean, that's prettycool and like, taking that
mindset, you could potentiallyport that over to an entry-level
job where you're, you know,proactively getting things done,
(23:06):
but then also thinking at ahigher level of like, how can we
optimize?
What can we do to improveoverall performance?
So that's awesome.
To improve overall performance,so that's awesome.
Okay, so, overall, with the jobhunt, how would you this is an
interesting question Out of ascale of 1 to 10, how do you
(23:27):
feel like it's going?
Because, bear in mind, like youjust got your first interview
and you have two months beforeyou graduate 'll give it.
Speaker 2 (23:40):
I'll give it a six.
A six, okay.
I'll give it a six just because, like you said, I got the
interview.
But also I feel like I feellike, even though it's not a lot
of analysts or entry-levelanalysts jobs that I'm looking
for, there are still potentialopportunities for me to get my
foot in the door, like you said,through marketing, being a
(24:00):
marketing specialist or eventhrough other business positions
.
So it's not like being ananalyst yes, I would like to be
an analyst at the end of mycareer, towards the back end,
but just getting my foot in thedoor.
There are a lot ofopportunities for me to just
enter the business world andstart my job in the business
world, and lot of opportunitiesfor me to just enter the
business world and start myright start my job in the
business and this was aconversation that we had um in
(24:22):
class what two or three weeksago of because every week, like
what?
Speaker 1 (24:27):
what?
I've worked into the capstonecourse this semester is a career
service component of it, of youneed to start applying early
and just kind of get your headin the game of it's going to be
a transition.
You know, once this semester isover it's not like you're going
to the next semester and it'scomfortable and it's You're kind
(24:48):
of going out into the greatunknown.
So understanding that that'srapidly approaching, like we've
started having you apply foranalyst jobs.
But I mean, I guess I was aboutto tell but like what has been
(25:09):
my advice as far as a quoteapplying for jobs?
Speaker 2 (25:13):
It's.
It's not the best way, but it'sit's like you said.
The way the routine you gave uswas, like you said, easy, apply
, refresh every day.
But your main advice was it'snot, it can work, it's just it
takes.
It can work, it's just it takes.
It's.
Speaker 1 (25:29):
It's a lot, it's a numbers game because, like I I
think back nine months ago and Iaccepted the role that I'm in
now, um, I think I applied to196 jobs and I got interviews
with five companies.
So I mean, that's what?
2.5 roughly speaking.
And this is somebody with eightyears of experience, an
undergrad in economics and mba,and you know like quite a few
(25:52):
quantified wins under my belt,um, and I'm not saying that to
like discourage you, but just tokind of give you like a hey,
this is, this is the state ofthe job market right now.
It's not great for analysts.
Speaker 2 (26:12):
That being said, what do we talk about as far as the
keywords that you're targeting?
Like you said being, well, thecategory analyst.
So, like you said being amarket, you could be a marketing
analyst, you could be a dataanalyst, you could also.
Speaker 1 (26:25):
I forgot what you said, so I guess the point that
I'm trying to make is that whenthe market is down, you may have
to be a little bit flexible onthe jobs that you target.
So instead of trying to get ananalyst job right out of the
gate, you may want to targetmarketing specialist jobs and
there's a lot more of those.
So maybe you get a marketingspecialist jobs, and there's a
(26:48):
lot more of those.
So maybe you get a marketingspecialist job, you would get
access to marketing data on somelevel.
Then you know you work that fora year, maybe two years, and
then keep applying for marketinganalyst jobs while you're doing
that and then you're a lot morecompetitive.
That second round, becauseyou're not completely fresh out
of college and you've workedwithin marketing.
(27:08):
So you have, you know, a trackrecord of understanding the
context in which the data isused.
And that's where the skills thatyou developed in my classroom
are going to kind of come backfull circle, because it's uh,
it's tough.
I mean I'm I'm like anxious foryou guys, because the market is
not very great right now, but Imean you're gonna land on your
(27:34):
feet like I.
Like I mean you proactivelyreached out to me what a year
before you got into my classroom, yes, so, like I mean you, like
, I have full confidence thatyou're gonna be able to land
something, and then, once youget in, you're gonna work really
hard, you're going to rack upsome wins, and it you're going
to be able to land something,and then, once you get in,
you're going to work really hard, you're going to rack up some
wins, and it's just going to bekind of like that.
First hurdle, though, is goingto be tough, but then, once
you're in, I think you're goingto do great.
(27:54):
All right, so do you have anyquestions for me?
So we've talked about theintroduction, your skills, your
experience, the job hunt.
Speaker 2 (28:07):
I mean your skills, your experience, the job hunt.
I mean any questions you wantto ask me about that.
I mean not really just becauseyou're also my teacher, so, like
you, kind of give me everythingthat you know about the job,
job hunt and the job huntingprocess as you've been through
it yourself.
Yeah, um, I don't.
Speaker 1 (28:21):
Yeah, I don't really have any questions about the job
hunt all right, so you're readyto jump into the mock interview
section?
Yes, because I don't think Iprepped.
I prepped you a little bit onthis, but I think this first
question you're kind of going inblind.
All right, let's get into scenehere.
Dejuan, thank you for coming tothis interview.
Can you tell me a little bitabout yourself?
Speaker 2 (28:45):
I am a senior at Greensboro College.
I'm a senior at GreensboroCollege with a major in business
administration with a minor inbusiness analytics.
I have taken two internshipsOne I'm still currently in in my
years at Greensboro College.
One was a sports analyst rolewhere I helped my football team,
(29:09):
through my head coaches, mysupervisor, collect data on
their penalty and game errors inpractice and in game and
relating those to help the teamhelp optimize and build better
overall performance for the team.
The second one that I am in isa student practicum where I
basically look at podcast dataand the analytics of a podcast
and monitor the retention curveand the audience curve to then
(29:32):
pull clips and shorts from thepodcast using AI to better push
publicity towards the podcast.
Speaker 1 (29:41):
Okay, that was pretty good.
Let me give you some feedbackso I would back up.
You got very specific, so liketell me about yourself.
I typically it's almost it'slike three points.
(30:10):
I mean you could break it downinto you know the past, the
present and the future, you know, or I mean you could break it
down.
It's tricky Cause you're it's,it's hard with you in that
usually when you're gettingasked that question about, tell
(30:31):
me about yourself, like you'veworked for a while, so that kind
of gives you something concreteto root down on.
But maybe let's, let's, let'sstick to that framework.
So like if you could give meone sentence about the past, one
sentence about the present andone sentence about the future
and maybe I need to do you thinkI need to give you a little bit
more context.
Speaker 2 (30:52):
Probably context on the past and the future Okay.
Speaker 1 (30:58):
So you could say something like I'm very
interested in.
I've always been interested indata and numbers and strategy,
so this is why I actuallymajored in business analytics
and then, once I got into mybusiness analytics minor classes
, I really enjoyed what I wasdoing, where I got to work with,
(31:18):
you know, huge data sets, I gotexposed to like real world
business use cases and I got tobuild out a portfolio which I'd
be happy to show you in thefuture.
What I would like to do is landan entry level marketing
analyst job where I get to workwith marketing data to help them
maximize their ROI so somethinglike like that.
(31:38):
To where your your initialresponse was very specific, to
where it's like the tell meabout yourself is just kind of
an icebreaker question.
You know, Like if I were to askyou, you know, give me a
breakdown of this specificproject, then you go into the
details.
Gotcha, you want to try itagain.
Speaker 2 (31:58):
Yeah, I'd like to try it.
Speaker 1 (31:59):
All right, I need to read it, all right.
So, duan, tell me a little bitabout yourself, so.
Speaker 2 (32:04):
I am a senior at Greensboro College with a major
in business administration and aminor in business analytics.
I got into business thebusiness major in general just
because ever since I was young Irealized that businesses not
going to say run the world, butwe rely on businesses a lot.
And what got me into theanalyst minor was always wanted
(32:29):
to help businesses grow, even ifit was just through looking at
their data sets.
I always felt like me findingthat one little tweak or that
one little thing that can help abusiness boost their profit,
even if it's by only 5%.
I feel like helping anybusiness grow.
That's great for me.
(32:49):
That's what I want to do.
I want to be able to helpbusinesses just grow in general.
It doesn't matter what it is.
And yes, I would like to.
Hopefully, if this was a realjob, I would like to land this
job position, hopefully at yourcompany, and I hope that your
company would be able to takethe risk on me in this
(33:10):
entry-level role, hopefully itbeing an analyst.
Speaker 1 (33:14):
Yeah Well, how did that feel versus the first one?
Speaker 2 (33:19):
I think the first one was I think it was just me
trying to push my what I've done, my experiences too fast, and I
think it's.
I think I just needed to givethem more about just me as a
person.
I felt like right, the firstpart.
I felt like the second part wasmore organic.
It didn't feel like I wasforcing it.
(33:39):
It kind of just felt like thisis this is why I'm here.
Like this, you're kind ofgetting a little why into why
well, it's almost like you tooka breath.
Speaker 1 (33:47):
You're like I'm connecting with you as a human
here at a hot, at a high level.
I I still feel like you.
You went on a little bit toomuch into the details, but it
was exceptionally better fromthe second take versus the first
take, so just kind of making itmore conversational.
Um, but then also too like you,have you ever heard of this
(34:11):
concept of like data granularityor or just granular in general?
So if you're out in the workingworld, there's layers of
management.
So the c-suite is interested ina specific level of detail,
middle management is interestedin a different level and then
the boots on the ground, kind ofindividual contributors, are
(34:33):
way into the weeds.
I think when you're having thatquestion about, tell me about
yourself, they're kind ofwanting that c-suite high level
view it's.
It's just it's breaking thenumber one, functionally
speaking, it's breaking the ice,but number two, it kind of
gives them some threads to pullon.
So, oh, you're interested inimproving ROI.
(34:56):
On marketing, tell me aboutthat.
Like what have you looked atbefore?
That kind of is a conversationstarter and you want them.
You can almost think of it likea dance, like you give them
kind of that high level view andthen you let them guide the
conversation through thequestions they ask.
Because what I've seen becauseI've been coaching people to
(35:17):
getting their first analyticsjob for like three or four years
and what you don't want to dois like a neil degrasse t Tyson
monologue.
We're not talking about themoon and the stars and going off
on this huge detail.
It's like answer the question.
I mean you want to give somedetail, but not not a ton, um,
(35:38):
and then if they ask you aboutit, then you drill down.
Does that make sense?
Yeah, does that make sense?
Yeah, all right, speaking onthe detail, the next question I
got for you is what experiencedo you have within analytics?
Speaker 2 (35:55):
So I have two which are internships that I've taken.
One was with my college throughtheir football team, where I
was a sports analyst managingtheir practice and game error
data.
The second was through acapstone class where I managed
podcast retention curves and AIdata.
Which one would you like tohear about first?
Speaker 1 (36:17):
Tell me about the podcast.
Speaker 2 (36:19):
So, within the podcast, we were managing a
podcast called how to Get anAnalytics Job.
We were managing a podcastcalled how to Get an Analytics
Job and within that podcast, ourprofessor would show us the
retention curve and basicallythe analytics behind the podcast
.
We would mainly look at theretention curve and the audience
groove and we would look atthat and we would determine what
(36:39):
parts of the podcast are theaudience looking at the most,
which parts are they going downon, which parts are they going
down on, which parts are theystaying constant with?
And what we surmised was thatwe would post clips on the parts
that the audience looked at themost.
So we would pull however longthe professor wanted it to be a
minute 30 seconds to a minuteand we will pull it.
(37:02):
We will let AI clip the wholepodcast and we will pull just.
We will let AI clip the wholepodcast and we will pull just.
We decided on two to threeclips Two to three good quality
clips that we felt were veryinformative and would garner
retention.
That's what we did.
Speaker 1 (37:18):
Okay, that's intriguing to me because our
company is.
We know about AI, but it'sstill this kind of vague thing.
Can you be a little bit moreexplicit about what AI tool did
you use and what was the usecase for that?
Speaker 2 (37:31):
So we used Raven, ravenside, riverside, we used
Riverside, we used Riverside,and basically what we did was
like I I said we would post thewhole podcast and we would.
We would put keywords, we wouldhave the AI look for keywords
throughout the podcast and theAI would clip those keywords.
(37:54):
If they felt like one of thekeywords matched up, they would
clip it.
Now the only downside to thatis sometimes the keywords in the
video itself would not align asin they would.
The topic at hand would notmatch what the title of the
video is.
So then we would have to goback in manually and then edit
(38:17):
it and make sure that this isactually a topic that somebody
would care about, or we wouldjust delete it overall just
because it wasn't relevant towhat we were looking for at the
time.
So with AI, it was great formass producing clips and helping
us cut down on the manual labor, but we still had to find that
(38:38):
fine line between the qualityover quantity aspect.
Speaker 1 (38:43):
Gotcha, Sorry, I'm just taking notes to kind of
like come back.
Okay, so did you see how thatconversation went?
So I asked you about and I'mnot a character, by the way, so
this is no longer interview.
John David, did you see how thatconversation went though?
I asked you about the projectand then you mentioned ai, and
(39:05):
then I made a note oh I, ai isimportant to us.
We know that we need to adaptto it, but we are not there yet.
So that gives you anopportunity to kind of go in and
just elaborate more, but youdon't want to throw all of the
detail out at all the time.
So did that kind of give youkind of a representation of how
(39:28):
those conversations can flowmore smoothly?
Speaker 2 (39:31):
Yes.
So kind of, even with that,with my answer to your question,
kind of cut back on how muchI'm giving into the project.
Speaker 1 (39:40):
Right, and maybe this is like way over analyzing this
, but it seems like you mightfeel not very confident and the
way that you're overcompensatingfor that lack of confidence is
by oversharing details.
I hope that's not like tooharsh a criticism.
Speaker 2 (39:59):
No, that's not true.
Speaker 1 (40:01):
So you're like trying to show, show, show, here's all
the things that I've done.
And then it's so much detailthat you kind of lose the force
for the trees.
And then it's like okay, hementioned 16 different things.
I don't know where to go fromhere because it's just kind of
overwhelming from aconversational Because, at the
end of the day, I mean, aninterview is a conversation and
(40:24):
you want to make sure that onlike a a personal level, you're
connecting with the other person.
You don't want to come off aslike a robot.
That's just like regurgitating.
You're not an AI, you're notjust going to go in and just
like oh, thank you for thequestion.
Blah, blah, blah, blah, blah,blah, blah, blah, blah, like and
(40:46):
just kind of spewing facts anddetails out, like.
But to give you some likeconcrete advice on how you
responded to that question about, like, tell me about your
experience and then, talkingabout the podcast you have.
We talked much about thestrategic versus tactical level.
We touched on it a little bitokay, explain, explain it to me
(41:09):
tactical is more like youactually drilling, you actually
going to tactical.
Strategic is like you planningit out, setting up the goals so
my feedback on how you answeredthat was that you completely
missed the strategic and jumpedstraight into the tactical.
So, like if if I were to answerthat question of hey, I see
(41:33):
that you did the studentpracticum Um, you, you worked on
a podcast.
Tell me about that, the.
The first sentence would besomething along the lines Well,
on a strategic level, we wantedto grow the scope of the podcast
.
So the way that we did this waswe came up with a way to create
an awareness campaign to expandour reach, and what's really
(41:54):
cool about that is we leveragedAI to go in and clip up the
podcast to the most interestingbits about it to scale out our
overall reach.
And then, you know, that's kindof it.
Right there, like then, thereare going to be questions like
really, how did you identifywhat were the most interesting
(42:16):
tidbits?
You could say that's a greatquestion.
Well, we went into the back endof YouTube and if you look under
the engagement tab, there's achart that gives you a view of
the retention, and then you canexplain the retention curve and
you can say well, what we didwith the last week's episode is
there were three peaks wherepeople were most interested.
(42:38):
We were then able to take thosetopics.
We went back and listened towhat we were talking about
during those peaks, fed itthrough that AI and then all of
a sudden, we were able togenerate 10 clips to retarget
the ideal audience for thispodcast.
So it's this is a little bithard to explain, and it's hard
(42:59):
because we're on a podcast too.
Like it adds like a whole otherlayer of, like almost
performance.
But is that?
Speaker 2 (43:08):
making sense.
Speaker 1 (43:08):
Like it makes sense do you want to try?
Do you want to try it one moretime?
We could try all right, we'lltry it one more time and then
we'll close out the podcast.
So you're you're almost through.
All right, duane, I see thatyou got the student practicum
where you worked with a podcastand you there's like analytics
behind it.
Can you tell me about that?
Speaker 2 (43:26):
so, within that podcast, our goal was.
We asked the teacher what hisgoal for his podcast was and he
said was to basically grow hispodcast and reach a target
audience.
So what we did was the planthat we came up with was to
basically take the mostinteresting parts of the podcast
, clip those and then run themthrough AI.
Speaker 1 (43:49):
Now, how we did that was See, I think you don't even
have to go into the detail, solike it's almost like you can
just kind of start high level,like what's the overall strategy
, you know what is the Almostlike the why, and then Does that
feel uncomfortable, just likesaying three sentences of an
(44:12):
answer.
I think so interesting why do?
You think that is?
Speaker 2 (44:16):
maybe it's probably me assuming that I feel like
they're already going to ask thequestion instead of just
letting them.
That's quite an assumption,though right yeah, it is, and I
think that just me not justletting the, letting it just
happen naturally yeah, I thinkthat's what I think.
Speaker 1 (44:32):
It's just me trying to lead it into my strengths
instead of just letting them askme about my well, it's funny
because, like I remember, amonth ago I asked you like, do
you want to do like a mockinterview?
You're like no, I got this, butnow you're in like the hot seat
.
It's like a little bit morestressful than you probably
anticipate it.
Right, yeah, which I mean thisis perfect timing because you
got when's your first interviewcoming up it is this monday bam,
(44:54):
you got.
You got one day to kind of sitwith this and kind of think with
it or think about like what we,what we talked about, but, um,
I mean we and we, we can go andlike run through some questions
if you want, with the audio andthe video off, just to help you
prep.
But all right, craig, thank youso much for recording us and
(45:16):
being the behind the scenes.
This has been great.
Speaker 2 (45:18):
Duann, thank you so much for your time.
Thank you, craig, and thank youThank both of you for having me
today.
Speaker 1 (45:24):
Awesome, all right, well, thank you so much for
tuning in.
I hope you guys enjoyed.
Hello and welcome back to the how to Get an
Analytics Job podcast.
So today we're doing somethingnew.
I don't think we've everactually done this before.
So I'm sitting here across fromone of my current students here
at Greensboro College and we'regoing to be talking about five
specific things.
So number one we're going to beintroducing him, kind of give
some background on you knowwhere he's at right now.
(00:35):
We're going to also be talkingabout his skills and experience.
We're going to be talking aboutthe job hunt, both kind of at a
high level, and then also whathe is going through as far as
you know what status he's atright now, what kind of
anxieties, what kind of worrieshe might have.
And then, finally, we're goingto do some mock interview
questions.
(00:55):
So, dejuan, welcome, how areyou feeling?
Speaker 2 (00:59):
I'm feeling great.
Thank you for having me.
Speaker 1 (01:02):
Yeah, so thank you so much.
I mean, this was kind of lastmoment.
We're actually studying thepodcast in class, so I don't
know if we can get any more metathan we are right now.
But it turns out that you havebeen doing content creation for
about a year, so sometimes Iactually just pull you up to the
front of the classroom and letyou kind of talk about what you
(01:23):
know, and then I'll fill in anyknowledge gaps.
So I guess, just quicklyintroduce yourself, like what's
your background, your currentgoals and kind of what are you
going through?
Right?
Speaker 2 (01:33):
now.
I am from Riverdale, Maryland.
I am currently a senior in atGreensboro College.
I major in businessadministration with a minor in
business analytics.
My goals are to just get a jobin my career, hopefully in
analytics, even if it's just anentry-level job.
(01:56):
Pass that life goals.
I'm a simple guy.
I just want to be able to paymy bills, do my hobbies and
hopefully spend time with myfamily.
If I have one, what?
Speaker 1 (02:08):
was the third one, my bad, just like.
So, I guess, the current status.
I guess I can kind of fill itin so you were rounding out the
last semester of your senioryear.
Yes, so now is when you need tokind of get your personal brand
tightened up.
We're getting on your LinkedInyour resume and then also
getting you prepped up.
We're getting on your LinkedIn,your resume and then also
getting you prepped up for theinterview process, because I
(02:29):
mean, literally, you just gotyour first interview set up, yes
, like within.
I mean we had class at, I think, one yesterday, so I mean this
is like in real time happening.
So I mean I guess let's kind ofstart with what skills and what
experience do you have?
Because I know that you're Ithink I looked at your LinkedIn
before this so you're about 10months in to like working a job
(02:53):
currently.
So I guess could you tell me alittle bit about that?
Speaker 2 (02:56):
My current job is at the Greensboro Board ABC stores.
There we just do usual salesassociate stuff, just talking to
customers.
We're recommending them drinks,helping them find drinks.
But we also we also have timeswhere they want us to push a
certain product or sales on acertain product.
Like if we get sales on likeallocated drinks which are
(03:20):
basically like if you're foranybody who drinks, it's bourbon
, it's buffalo, trace, eagle,rare wellers, blanton's, eh,
taylor, those kind of drinks wekind of when we get them, we put
them out.
We put them out fast.
A lot of people it's a hotseller because it's ready to get
.
Everybody wants somethingthat's scarce.
So yeah, we, we do that.
(03:42):
It's a lot of basic storemaintenance but when it comes to
that job I think it's veryundervalued.
Being a sales associate topeople who drink regularly, just
sometimes having to deal withpeople who sometimes come in and
they're not up to the standardof the store, they're not at
(04:04):
their best, and just having todeny them and seeing how they
can act when denied their drinks.
Okay, so you're kind of gettinginto like customer management a
little bit, maybe risk liability, like mitigating risk yeah
mitigating risk, just being ableto de-escalate situations,
being able to also just beingable to help people in general
(04:26):
help people who sometimes don'tknow they're asking for a gift
for their wife or their familyjust being able to help them.
But other than that I've done.
I'm currently doing theinternship with you which we are
studying this very podcast,looking at the audience curves
and the retention curves on thispodcast to help push content
and create.
Did we decide if we were goingwith the short clips?
(04:48):
I don't remember.
Speaker 1 (04:49):
I apologize.
Yeah, so we'll get into this alittle bit more, because this is
kind of what I guess to teasethe audience a little bit.
Like this is what we're goingto talk about.
As far as the mock interviewquestion, I'm going to ask you
like hey, I see that you, youknow, for three months at a
student practicum where you gotto work with real data.
Tell me about that, so we'llkind of get into that a little
(05:15):
bit more specific in the contextof a mock interview question.
But I guess okay, so that kindof gives a good breakdown of
your experience.
But as far as skills go, I meanone of the things we were
talking about, like when we werekind of diagnosing the podcast,
the last episode, we we pushedout, like we I mean I guess we
can get into it a little bit, sowe looked at the well, before
we even get into you know whatthe results were, what.
(05:38):
What data do we look at?
Speaker 2 (05:40):
we looked at audience retention curve and then we
looked at.
We also looked at audienceretention curve and then we
looked at.
We also looked at who iswatching the videos.
We looked at the views and theunique.
We also talked about uniqueviews versus just regular views.
Yeah, those are things that welooked at.
We also looked at where it was.
Where are people peaking in theretention curve?
(06:02):
Where are people peaking in theretention curve?
Speaker 1 (06:03):
So yeah, which I think is a really interesting
concept, especially for thosewho are listening, like you
probably don't think about, likethe analytics that are this
behind media consumption, butwhat is the audience retention
curve?
Speaker 2 (06:15):
The audience retention curve is basically how
long somebody is watching thevideo or how long they stay on
the video.
And basically, if I were, if itwas to be shown in a graph, it
would basically be like a line,and imagine at the top of that
line is when you first click onthe video, which is at a hundred
percent.
Speaker 1 (06:32):
Yeah, it's at a hundred.
Speaker 2 (06:33):
Yeah, your line can either stay at that rate or it
can slowly drop.
Speaker 1 (06:39):
Or it could rapidly drop.
Speaker 2 (06:40):
Yeah, it could rapidly drop as well, but with
that retention curve, if yourretention curve is steadily
constant throughout the video,your video everybody was able to
understand your video, watchyour video and they continued
watching it without feeling likethis video is talking about
something that I'm not lookingfor.
Speaker 1 (07:02):
So yeah, so the dips are when people you essentially
lose their interest.
They're switching off, or itcould be that they're fast
forwarding.
So what can we do with thatretention curve, Because there's
different ways to look at it,right?
So what you're talking about isthe aggregate view.
So that's everyone who viewedit.
We can look at it like that.
What can we do as far as theaggregation goes?
Speaker 2 (07:24):
We can look at it like that what can we do as far
as the aggregation goes?
We can look at it and see whereare we getting spikes, and then
we can go to that retentioncurve and we can look at the
spikes in the video and we cansay, okay, this is an
interesting topic from ourpodcast.
A lot of people came back andlooked at this and, like I, like
I when we were in class, we canjust take that portion, put it
(07:48):
into a short clip and if we bothlooked at it and was like I
feel like this is veryinformative, we can post that as
a short clip to have people whodidn't see the podcast still
gain a piece of informationabout what we're producing.
Speaker 1 (08:06):
Well, I guess what I was trying to kind of lead you
with a little bit with like theI guess the Socratic question
method, is we can change theaggregation so you were
describing it as the totalaudience If we change it to how
it relates to other videos,performances, that's where we
can see the spikes.
So what now we're doing isgoing back and looking at each
week's podcast episode andidentifying where those spikes
(08:28):
are, listening back to it,figuring out what the topics are
, and then we're using AI toclip the podcast as it relates
to those specific topics.
So, essentially, if we losesomebody early on in the episode
, we can post a short and thenretarget those people who
dropped it off.
So it's a way to.
(08:48):
It's essentially like anawareness campaign from a
marketing standpoint, which Ithink is really cool.
But okay, we're nerding out toohard on the details, I guess.
So this is kind of theexperience you've gained, which
I think is awesome, and it'sgreat that you can articulate it
pretty well, like you're ableto sit down and explain it.
I mean, part of it is becauseyou guys are doing the work.
(09:11):
I'm not spoon-feeding it to you.
I'm like here's the goal, youguys figure it out and then I'm
kind of here to play a supportrole and kind of manage the
project.
But tell me about the skillsthat you developed, because,
because we've we've beentogether for two semesters now.
Speaker 2 (09:28):
I've um.
The first was in Power BI.
That also helped me with theprevious internship and I could
get into that later.
If you'd like.
Um, that kind of getting betterat Excel, honing my skills at
Excel was something that yourclass helped me a lot with and
just overall data visualizationand project management.
Being able to even, like yousaid, cut up AI clips and also
(09:50):
go back in and make it evenbetter and make it even more
focused and more target audience, because sometimes AI can be
great in producing all thoseclips, but I still it's kind of
dumb yeah.
Yeah, in a weird way it's likehyper-competent, but also it
lacks any type of wisdom orjudgment yeah, so like sometimes
, like there are certain clipswhere it may say it's talking
(10:11):
about this topic, but if youwere a normal person watching it
, you wouldn't, you wouldn'teven make that connection.
Yeah, you wouldn't even makethe connection, and being able
just going back back in andbeing able to edit those and
being able to make sure thoseare reaching the right audience
or even speak on the rightsubject when relating to the
topic at hand.
Speaker 1 (10:29):
That's something that I've gained from this and I
guess let me ask you this Do youhave a way to show, let's say,
you show up into an interview inthe next few weeks.
Let's say it goes well withthis kind of phone screen that
you're about to go through, ifyou?
Speaker 2 (10:49):
were on like a Zoom call.
Do you have a way to kind ofshowcase the work that you've
done?
I would be able to showcase the.
In my previous internship,before I started with you, I did
data analysis for our collegefootball team where I took their
practice, penalties and errorsand I managed them, I organized
it, cleaned it up and put it inExcel and then transferred it
(11:10):
over into the data visualizationtool of Power BI and I made the
graphs and I made the linecharts for the comparison from
their in-game penalties andmistakes to their practice and I
was able to show the ratio andcomparison between those two
within those line graphs, whilealso showing the way my coach,
the way my supervisor, which wasthe coach, the way he wanted it
(11:34):
was.
He wanted to be able to see weekby week, the penalties and the
number of penalties, which isalso what I did.
So I was able to visualize thatwith a drop-down toolbar.
You can click on the week, eachgame week, and it will show you
the practice, penalties andmistakes and then the games.
And he said he just wanted tobe able to see where are we
(11:54):
overlapping, where are we havingtoo much of a problem in, and I
made that visible to himthrough Power BI, so that is
something that I can show topotential recruiters or
employers when they ask me toshow.
Speaker 1 (12:08):
Right, let me ask you this Did you have a test last
semester?
Speaker 2 (12:11):
Did I have a test?
No, no.
Speaker 1 (12:13):
I didn't.
Your test was your portfolio,so like and I did this with
intention because I mean, what'sa better story when you show up
for that interview of hey, Igot an A-plus on this test
versus?
Here are three projects I'veworked on.
I'd be happy to show you theuse case and show you the UI and
uncover some insights withinthis data that I analyzed, and
uncover some insights withinthis data that I analyzed.
(12:35):
I mean so like, whether yourealize it or not, I've been
slowly trying to help you prepfor the transition that's coming
.
What two months?
Speaker 2 (12:46):
two months away.
Speaker 1 (12:48):
Two months, I mean.
I guess that's kind of aperfect segue into.
The third topic that we wantedto cover was how's the job hunt
coming along?
Speaker 2 (12:58):
I mean your face.
Speaker 1 (12:59):
for those of you who are listening in audio, your
face is not looking superconfident, which is
understandable, because I meangoing from college to working is
a huge transition andespecially like we were kind of
talking like the market's alittle tough right now.
Speaker 2 (13:15):
It's not going well but, like we did say at talking,
like the market's a littletough right now it's not going
well.
But like we did say at thebeginning of the podcast, I did
get a text back for a Zoominterview with Crown Royal
Campaigns, so I have that Monday, so I hope that goes well.
But aside of that it has notbeen going well.
Speaker 1 (13:33):
Well, ok, is it not going well?
Or do you feel like maybe youneed to adjust your expectations
?
Like, let me ask you this howmany jobs have you applied for?
90.
90.
Okay, what is the timeline onthat?
The timeline as in like— Like ifyou applied for 90 jobs and
it's been two months, that'sprobably a bad sign, but if,
(14:01):
like, some of the jobs youapplied have been a matter of
weeks or maybe even a month likesometimes you don't hear a
callback for six weeks on a jobso I just want to kind of like
give you that zoomed outperspective on it.
Speaker 2 (14:07):
And I'm probably not used to that, probably because
of the jobs I've workedpreviously.
They usually hit you backwithin like a week or two, so
that's probably something I needto adjust to, but it's been
over the span of three months,okay.
So I've been getting somerejection emails later where
they've been moving on with adifferent applicant which is I'm
fine with.
Yeah, you're expected, yeah,that's natural.
(14:29):
I feel like at least you'relooking at my resume or somebody
or some type of system is so,at least it's being looked at.
I think that I'm not gettingdiscouraged.
Speaker 1 (14:44):
I think that eventually, Well, you just said
it wasn't going well.
Speaker 2 (14:50):
It's not going well, but I'm not surprised because of
one, not my experience, butjust I don't have that much of a
networking, as we spoke on inprevious classes.
I think I just need to build mynetwork more to be able to open
more doors than just coldapplying, as in when cold
applying, there could always besomebody who has more experience
(15:12):
, even at an entry-levelposition, than I do.
Speaker 1 (15:15):
So just opening my networks, which one of them is
you and another one can be thecamera guy, craig craig over
here our personal jamie yeah butyeah, I mean because I I've
invited you guys out because I Ihost, uh, a fairly regular
meetup and it's funny cause youguys were like six 6 PM on a
(15:37):
Wednesday, but now you'regetting it, while I was like
this is important becausethere's a whole hidden job
market out there, like whatyou're seeing on LinkedIn or in
D or whatever is.
It's the highest hurdle to jumpover.
Like it, these jobs are gettinghundreds of applicants, of
applicants, within the first 24hours.
(15:59):
So like you as a student whohaven't worked as an analyst
full-time yet, like that's, it'sa, it's a big challenge to get
up above that.
Now you can kind of play thenumbers game and just you know,
like I think I was saying, onestrategy is just get your
one-click apply set up, so every24 hours, every analytics or it
(16:21):
doesn't even have to beanalytics, it could be you want
to get into marketing, marketing, specialist jobs, any jobs that
are relevant for you, justevery 24 hours, posting and
being on top of that.
So you're at the top of thatlist.
I mean on top of that, soyou're at the top of that list.
But yeah, the kind of thehidden job market or like kind
of the back door into the job isto know somebody who is either
(16:42):
hiring or some know somebody whojust got asked hey, do you know
somebody who's looking for anentry level job?
Speaker 2 (16:50):
Yeah, yeah, and I feel like I get that door on top
of the cold applying.
I feel like I'll, I'll,eventually, I'll get somewhere
or I'm not.
I get that door on top of thecold applying.
I feel like I'll get somewhereor I'm not, and that's probably
why I'm not too anxious.
I know it'll take time and Idon't feel like I need to be in
as much of a rush as it'sperceived, so I just feel like,
as long as I just keep doingwhat I'm doing, I feel like my
(17:12):
resume is up to date, myLinkedIn profile is polished, I
feel like I've set myself up forthe opportunities at hand, so I
just have to keep knocking onthe door.
Speaker 1 (17:23):
Can you unpack that a little bit more?
So, when you say you feel goodabout your LinkedIn and your
resume, why do you feel that way?
Speaker 2 (17:29):
Because of some of it .
Most of it, I'm not going tosay.
Some of it.
Most of it was just having myresume looked over.
Yeah, and also by you and alsoby our careers and developments
Specialists yes, Karen Atwater,both of you looking at my resume
and then also just using theeverybody says keywords, making
(17:52):
sure it's actually related tothe jobs I'm applying for and
using the experience andactually accolades that I've
gained throughout my internshipsand my jobs in my profile.
So not just rambling on aboutduties but, like in my resume,
it says I boosted sales ofspecial order drinks by 15% at
(18:13):
my store, which is somethingthat's fantastic.
Speaker 1 (18:16):
Can we pause there and kind of dig into that a
little bit?
Yeah, so, like, what you'vedone is you've quantified the
work you've done, and I wouldsay the vast majority of people
are not doing that.
It's like they list out rolesand responsibilities.
They don't list out the impactthat they've had within a
business, so it, what do youthink that signals?
Speaker 2 (18:38):
I think that signals that I'm actually profitable or
helping the business make profit.
That's what I look at Well.
Speaker 1 (18:46):
I would say it signals that you have the right,
correct mindset, Like you arelooking at it from instead of
let me just be this person whodoes all these lists of tasks
you're actually thinkingcritical about it, Like you're
getting your job done, butyou're also thinking about ways
that you can potentiallyoptimize, or you know what are
(19:08):
the levers that you can pull tomake things go even better.
So like having that kind ofmindset ports over really well
to a full-time job.
So I think you're in reallygood shape there All right.
Speaker 2 (19:24):
So how's your LinkedIn?
I think my LinkedIn is is good.
I'll say good, I won't say myLinkedIn is great.
I think I need to kind of gointo more depth about the actual
skills that I've attained fromthe internships and the jobs
that I've worked.
Yeah, I just think that some ofthem are like kind of too broad
and then some of them aren'tlike really narrowed down.
(19:45):
Like for the one I did thesports analyst I did with my
football team.
I could say I did a projectmanagement Because, technically,
me uploading the data into,yeah, you managed it like they
gave you a directive and thenyou broke it down into steps and
you took all those steps.
Speaker 1 (20:06):
we go even further, like data governance.
You collected all the data,then you create, you put it into
a form that was actually cleanand able to be uploaded into a
BI tool, and then you took thatand you visualized it in a way
that the head coach couldinterpret and then they could go
back and rework their training,because you guys did crazy
(20:30):
training last semester, right.
Speaker 2 (20:33):
Yeah, in-season and out-of-season Right now, even
though I'm not on the team sinceI'm graduating, but right now
for spring ball, they do.
They do basically like uh,cardio runs five days a week,
lift three days a week, and thenthey have meetings and other
things throughout the week.
So this is like each week, thisand we're not even in season,
but I mean, so this is like eachweek.
Speaker 1 (20:56):
And we're not even in season.
But I mean speak to me a littlebit about how does the data
that you created help with thatwhole process.
Speaker 2 (21:02):
So it helps with it, as, when it comes to just the
coaches like basically teachingtheir positions, or the head
coach coaching his team overalland coaching his coaches, his
staff it's okay if our runningbacks fumbled the ball a lot.
Okay, as a head coach, I needto talk to my running backs
coach and see what we need tothink of something to help
(21:25):
reduce this, because turningover the ball is never a good
thing.
If we're getting a lot ofunsportsmanlike conduct,
penalties, which is basicallylike if a play is over and the
ref blows the play dead, one ofour players pushes somebody else
, that's unsportsmanlike, yeah,so why are we doing that?
(21:45):
That's us as a team.
We need to sit down as acoaching staff and address the
culture.
Speaker 1 (21:51):
Yeah, and address the culture of the team.
Speaker 2 (21:53):
Those are things that the head coach will now have to
think about, or now be likegoing into the next game.
Okay, we had two fumbles thisweek during practice.
We need to focus on ballsecurity, focus on not fumbling
the ball.
We need to do a lot of ballsecurity drills so that we can
help reduce this going into ourgame this Saturday.
Those are just ways that justme with a football background
(22:17):
know that these are things thata head coach would more than
likely say to his staff to helpreduce these mistakes that
they're making.
Speaker 1 (22:24):
Yeah, I mean, that's a really unique kind of setup in
that you are helping, kind ofyour manager in this situation,
or coach, coach and manager, Iguess Coach, well, but like the
coach is managing the team.
So I I'm like thinking about,like the title is coach,
functionally speaking.
(22:44):
They're managing all theplayers and you know, like how
things are going.
So you, you, you were playing arole in helping them optimize.
Yes, so I mean that's andhelping them optimize.
Yes, so I mean, that's prettycool and like, taking that
mindset, you could potentiallyport that over to an entry-level
job where you're, you know,proactively getting things done,
(23:06):
but then also thinking at ahigher level of like, how can we
optimize?
What can we do to improveoverall performance?
So that's awesome.
To improve overall performance,so that's awesome.
Okay, so, overall, with the jobhunt, how would you this is an
interesting question Out of ascale of 1 to 10, how do you
(23:27):
feel like it's going?
Because, bear in mind, like youjust got your first interview
and you have two months beforeyou graduate 'll give it.
Speaker 2 (23:40):
I'll give it a six.
A six, okay.
I'll give it a six just because, like you said, I got the
interview.
But also I feel like I feellike, even though it's not a lot
of analysts or entry-levelanalysts jobs that I'm looking
for, there are still potentialopportunities for me to get my
foot in the door, like you said,through marketing, being a
(24:00):
marketing specialist or eventhrough other business positions
.
So it's not like being ananalyst yes, I would like to be
an analyst at the end of mycareer, towards the back end,
but just getting my foot in thedoor.
There are a lot ofopportunities for me to just
enter the business world andstart my job in the business
world, and lot of opportunitiesfor me to just enter the
business world and start myright start my job in the
business and this was aconversation that we had um in
(24:22):
class what two or three weeksago of because every week, like
what?
Speaker 1 (24:27):
what?
I've worked into the capstonecourse this semester is a career
service component of it, of youneed to start applying early
and just kind of get your headin the game of it's going to be
a transition.
You know, once this semester isover it's not like you're going
to the next semester and it'scomfortable and it's You're kind
(24:48):
of going out into the greatunknown.
So understanding that that'srapidly approaching, like we've
started having you apply foranalyst jobs.
But I mean, I guess I was aboutto tell but like what has been
(25:09):
my advice as far as a quoteapplying for jobs?
Speaker 2 (25:13):
It's.
It's not the best way, but it'sit's like you said.
The way the routine you gave uswas, like you said, easy, apply
, refresh every day.
But your main advice was it'snot, it can work, it's just it
takes.
It can work, it's just it takes.
It's.
Speaker 1 (25:29):
It's a lot, it's a numbers game because, like I I
think back nine months ago and Iaccepted the role that I'm in
now, um, I think I applied to196 jobs and I got interviews
with five companies.
So I mean, that's what?
2.5 roughly speaking.
And this is somebody with eightyears of experience, an
undergrad in economics and mba,and you know like quite a few
(25:52):
quantified wins under my belt,um, and I'm not saying that to
like discourage you, but just tokind of give you like a hey,
this is, this is the state ofthe job market right now.
It's not great for analysts.
Speaker 2 (26:12):
That being said, what do we talk about as far as the
keywords that you're targeting?
Like you said being, well, thecategory analyst.
So, like you said being amarket, you could be a marketing
analyst, you could be a dataanalyst, you could also.
Speaker 1 (26:25):
I forgot what you said, so I guess the point that
I'm trying to make is that whenthe market is down, you may have
to be a little bit flexible onthe jobs that you target.
So instead of trying to get ananalyst job right out of the
gate, you may want to targetmarketing specialist jobs and
there's a lot more of those.
So maybe you get a marketingspecialist jobs, and there's a
(26:48):
lot more of those.
So maybe you get a marketingspecialist job, you would get
access to marketing data on somelevel.
Then you know you work that fora year, maybe two years, and
then keep applying for marketinganalyst jobs while you're doing
that and then you're a lot morecompetitive.
That second round, becauseyou're not completely fresh out
of college and you've workedwithin marketing.
(27:08):
So you have, you know, a trackrecord of understanding the
context in which the data isused.
And that's where the skills thatyou developed in my classroom
are going to kind of come backfull circle, because it's uh,
it's tough.
I mean I'm I'm like anxious foryou guys, because the market is
not very great right now, but Imean you're gonna land on your
(27:34):
feet like I.
Like I mean you proactivelyreached out to me what a year
before you got into my classroom, yes, so, like I mean you, like
, I have full confidence thatyou're gonna be able to land
something, and then, once youget in, you're gonna work really
hard, you're going to rack upsome wins, and it you're going
to be able to land something,and then, once you get in,
you're going to work really hard, you're going to rack up some
wins, and it's just going to bekind of like that.
First hurdle, though, is goingto be tough, but then, once
you're in, I think you're goingto do great.
(27:54):
All right, so do you have anyquestions for me?
So we've talked about theintroduction, your skills, your
experience, the job hunt.
Speaker 2 (28:07):
I mean your skills, your experience, the job hunt.
I mean any questions you wantto ask me about that.
I mean not really just becauseyou're also my teacher, so, like
you, kind of give me everythingthat you know about the job,
job hunt and the job huntingprocess as you've been through
it yourself.
Yeah, um, I don't.
Speaker 1 (28:21):
Yeah, I don't really have any questions about the job
hunt all right, so you're readyto jump into the mock interview
section?
Yes, because I don't think Iprepped.
I prepped you a little bit onthis, but I think this first
question you're kind of going inblind.
All right, let's get into scenehere.
Dejuan, thank you for coming tothis interview.
Can you tell me a little bitabout yourself?
Speaker 2 (28:45):
I am a senior at Greensboro College.
I'm a senior at GreensboroCollege with a major in business
administration with a minor inbusiness analytics.
I have taken two internshipsOne I'm still currently in in my
years at Greensboro College.
One was a sports analyst rolewhere I helped my football team,
(29:09):
through my head coaches, mysupervisor, collect data on
their penalty and game errors inpractice and in game and
relating those to help the teamhelp optimize and build better
overall performance for the team.
The second one that I am in isa student practicum where I
basically look at podcast dataand the analytics of a podcast
and monitor the retention curveand the audience curve to then
(29:32):
pull clips and shorts from thepodcast using AI to better push
publicity towards the podcast.
Speaker 1 (29:41):
Okay, that was pretty good.
Let me give you some feedbackso I would back up.
You got very specific, so liketell me about yourself.
I typically it's almost it'slike three points.
(30:10):
I mean you could break it downinto you know the past, the
present and the future, you know, or I mean you could break it
down.
It's tricky Cause you're it's,it's hard with you in that
usually when you're gettingasked that question about, tell
(30:31):
me about yourself, like you'veworked for a while, so that kind
of gives you something concreteto root down on.
But maybe let's, let's, let'sstick to that framework.
So like if you could give meone sentence about the past, one
sentence about the present andone sentence about the future
and maybe I need to do you thinkI need to give you a little bit
more context.
Speaker 2 (30:52):
Probably context on the past and the future Okay.
Speaker 1 (30:58):
So you could say something like I'm very
interested in.
I've always been interested indata and numbers and strategy,
so this is why I actuallymajored in business analytics
and then, once I got into mybusiness analytics minor classes
, I really enjoyed what I wasdoing, where I got to work with,
(31:18):
you know, huge data sets, I gotexposed to like real world
business use cases and I got tobuild out a portfolio which I'd
be happy to show you in thefuture.
What I would like to do is landan entry level marketing
analyst job where I get to workwith marketing data to help them
maximize their ROI so somethinglike like that.
(31:38):
To where your your initialresponse was very specific, to
where it's like the tell meabout yourself is just kind of
an icebreaker question.
You know, Like if I were to askyou, you know, give me a
breakdown of this specificproject, then you go into the
details.
Gotcha, you want to try itagain.
Speaker 2 (31:58):
Yeah, I'd like to try it.
Speaker 1 (31:59):
All right, I need to read it, all right.
So, duan, tell me a little bitabout yourself, so.
Speaker 2 (32:04):
I am a senior at Greensboro College with a major
in business administration and aminor in business analytics.
I got into business thebusiness major in general just
because ever since I was young Irealized that businesses not
going to say run the world, butwe rely on businesses a lot.
And what got me into theanalyst minor was always wanted
(32:29):
to help businesses grow, even ifit was just through looking at
their data sets.
I always felt like me findingthat one little tweak or that
one little thing that can help abusiness boost their profit,
even if it's by only 5%.
I feel like helping anybusiness grow.
That's great for me.
(32:49):
That's what I want to do.
I want to be able to helpbusinesses just grow in general.
It doesn't matter what it is.
And yes, I would like to.
Hopefully, if this was a realjob, I would like to land this
job position, hopefully at yourcompany, and I hope that your
company would be able to takethe risk on me in this
(33:10):
entry-level role, hopefully itbeing an analyst.
Speaker 1 (33:14):
Yeah Well, how did that feel versus the first one?
Speaker 2 (33:19):
I think the first one was I think it was just me
trying to push my what I've done, my experiences too fast, and I
think it's.
I think I just needed to givethem more about just me as a
person.
I felt like right, the firstpart.
I felt like the second part wasmore organic.
It didn't feel like I wasforcing it.
(33:39):
It kind of just felt like thisis this is why I'm here.
Like this, you're kind ofgetting a little why into why
well, it's almost like you tooka breath.
Speaker 1 (33:47):
You're like I'm connecting with you as a human
here at a hot, at a high level.
I I still feel like you.
You went on a little bit toomuch into the details, but it
was exceptionally better fromthe second take versus the first
take, so just kind of making itmore conversational.
Um, but then also too like you,have you ever heard of this
(34:11):
concept of like data granularityor or just granular in general?
So if you're out in the workingworld, there's layers of
management.
So the c-suite is interested ina specific level of detail,
middle management is interestedin a different level and then
the boots on the ground, kind ofindividual contributors, are
(34:33):
way into the weeds.
I think when you're having thatquestion about, tell me about
yourself, they're kind ofwanting that c-suite high level
view it's.
It's just it's breaking thenumber one, functionally
speaking, it's breaking the ice,but number two, it kind of
gives them some threads to pullon.
So, oh, you're interested inimproving ROI.
(34:56):
On marketing, tell me aboutthat.
Like what have you looked atbefore?
That kind of is a conversationstarter and you want them.
You can almost think of it likea dance, like you give them
kind of that high level view andthen you let them guide the
conversation through thequestions they ask.
Because what I've seen becauseI've been coaching people to
(35:17):
getting their first analyticsjob for like three or four years
and what you don't want to dois like a neil degrasse t Tyson
monologue.
We're not talking about themoon and the stars and going off
on this huge detail.
It's like answer the question.
I mean you want to give somedetail, but not not a ton, um,
(35:38):
and then if they ask you aboutit, then you drill down.
Does that make sense?
Yeah, does that make sense?
Yeah, all right, speaking onthe detail, the next question I
got for you is what experiencedo you have within analytics?
Speaker 2 (35:55):
So I have two which are internships that I've taken.
One was with my college throughtheir football team, where I
was a sports analyst managingtheir practice and game error
data.
The second was through acapstone class where I managed
podcast retention curves and AIdata.
Which one would you like tohear about first?
Speaker 1 (36:17):
Tell me about the podcast.
Speaker 2 (36:19):
So, within the podcast, we were managing a
podcast called how to Get anAnalytics Job.
We were managing a podcastcalled how to Get an Analytics
Job and within that podcast, ourprofessor would show us the
retention curve and basicallythe analytics behind the podcast
.
We would mainly look at theretention curve and the audience
groove and we would look atthat and we would determine what
(36:39):
parts of the podcast are theaudience looking at the most,
which parts are they going downon, which parts are they going
down on, which parts are theystaying constant with?
And what we surmised was thatwe would post clips on the parts
that the audience looked at themost.
So we would pull however longthe professor wanted it to be a
minute 30 seconds to a minuteand we will pull it.
(37:02):
We will let AI clip the wholepodcast and we will pull just.
We will let AI clip the wholepodcast and we will pull just.
We decided on two to threeclips Two to three good quality
clips that we felt were veryinformative and would garner
retention.
That's what we did.
Speaker 1 (37:18):
Okay, that's intriguing to me because our
company is.
We know about AI, but it'sstill this kind of vague thing.
Can you be a little bit moreexplicit about what AI tool did
you use and what was the usecase for that?
Speaker 2 (37:31):
So we used Raven, ravenside, riverside, we used
Riverside, we used Riverside,and basically what we did was
like I I said we would post thewhole podcast and we would.
We would put keywords, we wouldhave the AI look for keywords
throughout the podcast and theAI would clip those keywords.
(37:54):
If they felt like one of thekeywords matched up, they would
clip it.
Now the only downside to thatis sometimes the keywords in the
video itself would not align asin they would.
The topic at hand would notmatch what the title of the
video is.
So then we would have to goback in manually and then edit
(38:17):
it and make sure that this isactually a topic that somebody
would care about, or we wouldjust delete it overall just
because it wasn't relevant towhat we were looking for at the
time.
So with AI, it was great formass producing clips and helping
us cut down on the manual labor, but we still had to find that
(38:38):
fine line between the qualityover quantity aspect.
Speaker 1 (38:43):
Gotcha, Sorry, I'm just taking notes to kind of
like come back.
Okay, so did you see how thatconversation went?
So I asked you about and I'mnot a character, by the way, so
this is no longer interview.
John David, did you see how thatconversation went though?
I asked you about the projectand then you mentioned ai, and
(39:05):
then I made a note oh I, ai isimportant to us.
We know that we need to adaptto it, but we are not there yet.
So that gives you anopportunity to kind of go in and
just elaborate more, but youdon't want to throw all of the
detail out at all the time.
So did that kind of give youkind of a representation of how
(39:28):
those conversations can flowmore smoothly?
Speaker 2 (39:31):
Yes.
So kind of, even with that,with my answer to your question,
kind of cut back on how muchI'm giving into the project.
Speaker 1 (39:40):
Right, and maybe this is like way over analyzing this
, but it seems like you mightfeel not very confident and the
way that you're overcompensatingfor that lack of confidence is
by oversharing details.
I hope that's not like tooharsh a criticism.
Speaker 2 (39:59):
No, that's not true.
Speaker 1 (40:01):
So you're like trying to show, show, show, here's all
the things that I've done.
And then it's so much detailthat you kind of lose the force
for the trees.
And then it's like okay, hementioned 16 different things.
I don't know where to go fromhere because it's just kind of
overwhelming from aconversational Because, at the
end of the day, I mean, aninterview is a conversation and
(40:24):
you want to make sure that onlike a a personal level, you're
connecting with the other person.
You don't want to come off aslike a robot.
That's just like regurgitating.
You're not an AI, you're notjust going to go in and just
like oh, thank you for thequestion.
Blah, blah, blah, blah, blah,blah, blah, blah, blah, like and
(40:46):
just kind of spewing facts anddetails out, like.
But to give you some likeconcrete advice on how you
responded to that question about, like, tell me about your
experience and then, talkingabout the podcast you have.
We talked much about thestrategic versus tactical level.
We touched on it a little bitokay, explain, explain it to me
(41:09):
tactical is more like youactually drilling, you actually
going to tactical.
Strategic is like you planningit out, setting up the goals so
my feedback on how you answeredthat was that you completely
missed the strategic and jumpedstraight into the tactical.
So, like if if I were to answerthat question of hey, I see
(41:33):
that you did the studentpracticum Um, you, you worked on
a podcast.
Tell me about that, the.
The first sentence would besomething along the lines Well,
on a strategic level, we wantedto grow the scope of the podcast
.
So the way that we did this waswe came up with a way to create
an awareness campaign to expandour reach, and what's really
(41:54):
cool about that is we leveragedAI to go in and clip up the
podcast to the most interestingbits about it to scale out our
overall reach.
And then, you know, that's kindof it.
Right there, like then, thereare going to be questions like
really, how did you identifywhat were the most interesting
(42:16):
tidbits?
You could say that's a greatquestion.
Well, we went into the back endof YouTube and if you look under
the engagement tab, there's achart that gives you a view of
the retention, and then you canexplain the retention curve and
you can say well, what we didwith the last week's episode is
there were three peaks wherepeople were most interested.
(42:38):
We were then able to take thosetopics.
We went back and listened towhat we were talking about
during those peaks, fed itthrough that AI and then all of
a sudden, we were able togenerate 10 clips to retarget
the ideal audience for thispodcast.
So it's this is a little bithard to explain, and it's hard
(42:59):
because we're on a podcast too.
Like it adds like a whole otherlayer of, like almost
performance.
But is that?
Speaker 2 (43:08):
making sense.
Speaker 1 (43:08):
Like it makes sense do you want to try?
Do you want to try it one moretime?
We could try all right, we'lltry it one more time and then
we'll close out the podcast.
So you're you're almost through.
All right, duane, I see thatyou got the student practicum
where you worked with a podcastand you there's like analytics
behind it.
Can you tell me about that?
Speaker 2 (43:26):
so, within that podcast, our goal was.
We asked the teacher what hisgoal for his podcast was and he
said was to basically grow hispodcast and reach a target
audience.
So what we did was the planthat we came up with was to
basically take the mostinteresting parts of the podcast
, clip those and then run themthrough AI.
Speaker 1 (43:49):
Now, how we did that was See, I think you don't even
have to go into the detail, solike it's almost like you can
just kind of start high level,like what's the overall strategy
, you know what is the Almostlike the why, and then Does that
feel uncomfortable, just likesaying three sentences of an
(44:12):
answer.
I think so interesting why do?
You think that is?
Speaker 2 (44:16):
maybe it's probably me assuming that I feel like
they're already going to ask thequestion instead of just
letting them.
That's quite an assumption,though right yeah, it is, and I
think that just me not justletting the, letting it just
happen naturally yeah, I thinkthat's what I think.
Speaker 1 (44:32):
It's just me trying to lead it into my strengths
instead of just letting them askme about my well, it's funny
because, like I remember, amonth ago I asked you like, do
you want to do like a mockinterview?
You're like no, I got this, butnow you're in like the hot seat
.
It's like a little bit morestressful than you probably
anticipate it.
Right, yeah, which I mean thisis perfect timing because you
got when's your first interviewcoming up it is this monday bam,
(44:54):
you got.
You got one day to kind of sitwith this and kind of think with
it or think about like what we,what we talked about, but, um,
I mean we and we, we can go andlike run through some questions
if you want, with the audio andthe video off, just to help you
prep.
But all right, craig, thank youso much for recording us and
(45:16):
being the behind the scenes.
This has been great.
Speaker 2 (45:18):
Duann, thank you so much for your time.
Thank you, craig, and thank youThank both of you for having me
today.
Speaker 1 (45:24):
Awesome, all right, well, thank you so much for
tuning in.
I hope you guys enjoyed.
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