Anya Cheng is an accomplished and award-winning Product Head with extensive experience in leading product initiatives for top technology, eCommerce, food-delivery, and retail organizations. As the Founder and CEO of Taelor, Anya specializes in creating product vision, strategy, and roadmaps while building and managing high-performing teams. Her expertise spans product management, design, development, go-to-market strategies, and monetization processes.
As a product management and marketing guru, helped build Meta (Facebook/Instagram) Shopping and worked on eBay’s emerging business and AI, Target’s (the 2nd largest retailer in the U.S.) mobile/table eCommerce app, and McDonald’s global food delivery business. Anya is adept at managing stakeholders and responding to industry trends in fast-paced, dynamic, and ambiguous environments.
Her achievements have earned her over 20 awards, including the Girls in Tech "40 Under 40" and the Webby Award for Best App of the Year. A TEDx Talk speaker, she also teaches at Northwestern University and brings a strong background in website and app product management, growth/product marketing, and analytics.
During the show we discussed:
- Inspiration behind starting Taelor and the growth journey.
- Challenges faced while scaling and how they were overcome.
- Technology driving business growth and efficiency.
- The role of data in decision-making.
- Expanding into new markets.
- Using AI to improve customer experience.
- Key tech trends businesses should adopt.
- AI's impact on streamlining operations.
- AI's potential beyond eCommerce.
- Lessons from working with global brands.
- How Taelor stands out in fashion rental through technology.
- Leading successful teams in fast-changing environments.
- Advice for aspiring tech and business leaders.
Resources:
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:02):
(Transcribed by TurboScribe.ai. Go Unlimited to remove this message.) Welcome to the Business Credit and Financing Show.
Each week, we talk about the growth strategies
that matter most to entrepreneurs.
Listen in as we discuss the secrets to
getting credit and money to start and grow
your business.
And enjoy as we talk with seasoned business
owners, coaches, and industry leaders on a variety
(00:22):
of topics from advertising and marketing to the
nuts and bolts of running a highly successful
business.
And now, to introduce the host of our
show, financial expert and award-winning author, Ty
Crandall.
Hello, thanks for joining us today.
I'm super excited you could be here.
So today, we have somebody who has just
killed it as an entrepreneur, and she's here
(00:43):
to give us really some lessons on the
intersection of kind of technology and then business
growth.
So we're actually gonna learn from a visionary
entrepreneur today, and with us is Enya Cheng.
Now, she is an accomplished and award-winning
product head with extensive experience in leading product
initiatives for top technology, e-commerce, food, delivery,
and retail organizations.
(01:04):
So actually, as the founder and CEO of
Taylor, Enya specializes in creating product vision, strategy,
and roadmaps while actually building and managing very
high-performance teams.
Now, her expertise scans product management, design, development,
go-to-market strategies, and monetization processes as
well.
And as a product manager and a marketing
guru, she has helped build Meta, which is
(01:25):
Facebook and obviously Instagram's platform, shopping, and worked
on eBay's emerging business and AI, targets the
second largest retailer in the world, by the
way, or in the U.S., by the
way, mobile, table, e-commerce app, and McDonald's
global food and delivery service.
So she is apt at managing stakeholders and
responding to industry trends in fast-growing, dynamic,
(01:46):
and ambitious environments as well.
But her achievements have earned her over 20
different awards, including the Girls in Tech 40
Under 40 and the Weebly Award for Best
App of the Year.
She's a TEDx Talk speaker.
She also teaches at Northwestern University and brings
a strong background in websites and app product
(02:07):
development, growth, product marketing, and analytics.
Hey, thanks for joining us today.
You've done so many great things.
Hi there, I'm Enya.
Yeah, I'm a startup founder now.
So I run a company called Taylor.
We use AI to pick perfect clothes for
busy men.
Excited to be here.
All right, well, let's talk a little bit
more about what you do.
I wanna talk a little bit more about
your history as well because you've done so
(02:27):
many cool things.
So what made you get started?
What helped you actually drive you to start
Taylor?
You know, when I was leading large teams
at Meta and eBay, you always feel a
little bit imposter syndrome, wanna look great.
So I tried some subscription boxes like Stitch
Fix, those like they will style you, but
they should be your clothes you have to
buy before you can wear.
(02:48):
It's just a styling service plus e-commerce.
And I didn't want to own that much
stuff.
Unlike you guys in Florida, we don't have
big closet here in San Francisco.
So I tried some rental companies, company like
Render Runway, were newly by Urban Outfitter, which
is a profitable unicorn just for years.
But all of these require me to browse
(03:09):
through thousands of garments and spend hours.
And there was an aha moment.
Wait, these fashion companies are designed for people
who are into fashion.
They are not designed for people who just
need to get ready for the days.
Hey shopping, hey laundry, socially active, such as
sales guy, recruiter, pastor, professor, single guy.
(03:30):
And they are kind of lazy in terms
of picking clothes, but definitely they are busy
in their own world.
And why there's no service like that?
And that's how Taylor is born.
So how does your system work here at
Taylor?
Yeah, so Taylor works like Netflix for outfits.
So for $100 per month, for example, you
get 10 clothes to wear.
(03:50):
You, our AI pick the perfect clothes, you
fill out a simple survey.
You can upload some of your picture.
If you want to get on 15 minutes
consultation call, you can with real professional stylist.
And then from there, our AI will get
over information and pick the clothes.
Our human stylist to make final decision, make
sure it's perfect, or complain to the AI,
(04:12):
say, you are wrong.
Then this is why.
And then we will send you the perfect
outfits, five items that you can mix and
match to a two to three outfits you
wear for a couple of weeks.
Once you're done, you can buy what you
love, or you put the dirty clothes back
to the return envelope, which is prepaid.
Drop in the post office in two days,
you get another shipment.
(04:32):
So no more shopping, no more laundry.
And if you're traveling even better, you don't
need to bring dirty clothes home, put into
the return envelope, give it to hotel lobby.
You go home without doing any laundry.
And people pay monthly fee.
And when they buy the clothes, it's also
deep discount because it's pre-owned, even though
it still looks like new.
And our garment gets sold after renting within
(04:54):
three times.
So it still looks very new, but you
get discounts right away because it's pre-owned.
Nice.
So when you started this, give me, and
you touched upon this a little, when you
looked at the industry as a whole, and
you saw the problem, what is the biggest
problem you think this solution solves?
In fact, on the other side, we actually
saw one of the most important problem in
(05:16):
the world, which is 30% of clothes
go directly from factory to landfill.
10% of carbon emission in the world
were from fast fashion alone.
So it's a huge inventory waste problem in
the fashion world.
And guys usually tend to buy the same
thing again and again.
So if you were just not through rental
(05:38):
model, then those guys would never try something
new.
Open your closet, last 10 years, you only
know five brands and you have been wearing
the same brand again and again.
It's not because you like to be the
same, no one pick stuff for you, you
don't want to re-GQ, you don't know
what looks good, and you don't want to
make a decision right away, even if someone
pick for you, when you open the box,
(05:58):
you don't know if this is worth to
buy, you don't know if you should compare
the price, you don't know if you feel
comfortable after you're wearing it, right?
So it's just, there's no simple solution before
Gen AI that we allow those lazy man
are able to try something new.
And then so in a supply side, there's
(06:20):
tons of brands globally, or even in the
US, because a guy buy the same thing
again and again, so they never be able
to reach a new customer.
So even for amazing brand, high quality brands,
the only way they do it is spend
lots of money in marketing in order to
get attentions, versus those high quality brand actually
(06:41):
invest in the quality are not able to
get the customer.
So by using the circular fashion, lazy economy,
sharing economy and AI, we are able to
bridge the two sides and make sure that
the garment can find great customers and also
get the feedback from the customer while customer
can discover something new, while also looks great
every day.
(07:01):
So going from working for very large companies
to working for yourself, what are some of
the unexpected challenges that you faced along the
way of launching there?
I think so for being a startup founder,
many of you guys might be able to
relate, it's really about trusting yourself.
Give you a story, when I was to
start a company, we went on a startup
(07:22):
competition.
And I thought the best way to practice
a competition would be finding four more judges
and do the mock practice.
So I did, I found 42 of them.
I practiced with every one of them and
my pitch was perfect.
So when I went on the competition, after
the pitch, the judges asked me a question.
(07:43):
After I heard the question, I stunned.
I wasn't able to answer, not because I
didn't know the answer, was because in my
head, I didn't believe that I can answer.
Oh, I was thinking, oh yeah, this question,
practice judge number 37 asked me about this.
And then he also told me his point
of view, which I put in the appendix
number 26.
(08:03):
And the answer was, it's almost like students.
Sometimes when we do the open book exam,
I teach in Northwestern University and students, when
you have open book exam, and many of
them would just spend all the time trying
to find the answer from the book.
And then suddenly the time goes, time is
up.
They realize they haven't write down anything.
But in fact, when they read the question
(08:24):
carefully and think about it, they actually know
the answer, but they just didn't believe that
they can answer.
Of course I lost in the competition, but
it was learning that I realized that, you
know, I actually know a lot.
Who like startup founder, who think about the
problem 24 seven for a couple of years.
Right, so just trusting yourself, there's something really,
(08:47):
really hard being a startup founder, but it's
going to pay off.
How are you using technology to be able
to kind of streamline and enhance your growth
now?
Yeah, so in this business, it wasn't feasible
before GNI, because in order to serve those
lazy man or busy man, you actually before
(09:07):
you need humans and professional stylist and bring
you to a department store and shopping around,
they call personal shopper.
And you probably heard about that in Hollywood,
those celebrity will have their personal shopper and
they will spend a day with them and
pick clothes out for them.
And then on top of the hourly rate
(09:27):
to the stylist, you also have to buy
lots of clothes and which spend thousands of
dollars and go home.
You have to do a laundry and ironings
and all stuff.
So it wasn't feasible before GNI, because for
you need to look at customer's personal size
and information, their previous hard items, their previous
photos, the photo they are inspired by and
(09:50):
the weather of location, their schedule in the
next two weeks and many more.
So with AI, these all can be done
in three seconds.
And what's most powerful in GNI is you
do, you can use large language model like
OpenAI, for example, but you are only defensible
if you have your own unique data.
(10:11):
In our example that we have customer's true
preference, which is not impacted by the purchase
price.
What do you mean?
Means when you go on e-commerce store
or Amazon or any e-commerce store, you
buy something or not, it's not because you
like it, it's not.
It's because how much is it?
So if it's something really cheap, even though
(10:32):
you don't like it, you might still buy
it.
But in our model, because it's subscriptions and
rental, so people pay a monthly fee, so
we know the true preference, just like how
you decide what to watch on Netflix.
You pay a monthly fee, so then when
you pick the show, is that you really
do like it.
We also have like professional stylus data.
We also know the true quality after watches,
(10:54):
et cetera.
We have a lot of proprietary data and
technology.
And we combine these, put it on top
of a large language model so that it's
defensible.
But every time larger language model grow, we
also grow, but we are always one step
ahead.
You mentioned a little bit about data.
What role does data play that you're seeing
(11:16):
in the product itself?
And how are you using data right now
to make better business decisions?
Yeah, so back to the decision on the
AI side, when AI peak close, it does
require a lot of data.
So besides the data I mentioned, for example,
AI only know the past.
AI doesn't know the future.
So model, we work with 300 brands.
(11:38):
Those fashion brands are already designing something two
years from today in the future.
So we know it's information from the future.
Or for example, when our customers tell us
their personal information, because they need to make
sure our outfit fit well with their occasions.
Oh, next Tuesday, I have interview with Google.
(11:58):
Then those informations are those proprietary information we
have.
So we use those to help make sure
that our AI algorithm will fit in the
best clothes for the customer.
And in terms of decision-making, for example,
we also use it for deciding on our
pricing, dynamic pricing.
Given that it's rental, it's like airport car,
after renting a few times, the price will
(12:21):
drop.
So then someone will buy it.
So then they can have the money to
buy another new car.
So we use it for dynamic pricing.
Or we use a lot of customer information
to decide what kind of brand should we
acquire, should we buy, because we are membership.
So we know customer before we source any
inventory, which is very different from e-commerce.
(12:41):
You are hoping someone will buy the stuff
that I put in the warehouse, right?
So we already know the customer's profile.
So we source items specifically for Thai, for
example.
Like, oh, we know Thai is a podcast
host.
So we better to be this type of
outfits in Florida.
So I think this will be perfect for
your everyday wear.
So lots of information being used in decisions.
(13:02):
Well, what should I be wearing as a
podcast host?
I guess that's a good question.
I think that would be a question for
the professional stylist in AI.
I would love to show you.
I would love to see that.
What do you do to expand?
How do you look at this with expanding
into new markets?
I'm interested in your business.
Like, are you expanding through the United States?
(13:23):
Are you looking at expanding around the world?
Like, what is your strategy for expansion?
Yeah, so one thing is that within the
U.S. it's definitely a category expansion.
What we found was while men's wear rental
company and women's rental company, sounds like only
one word different, but it's actually fundamentally totally
different business.
(13:44):
Because in a woman's rental business, they solve
the problem that women want to wear different
things every day.
In our business, our guys are here to
save time.
So if you think of this, if you
have a personal stylist or personal assistant, if
your assistant can only order lunch for you,
your assistant isn't good enough, right?
So, but if your assistant can do many
(14:05):
things, recording the podcast, cutting the podcast, promoting
the podcast, also order lunches and also help
you to put input on business strategies, it's
a great assistant.
The same thing, our customer expect us to
more than renting clothes.
They ask us, where do I get my
hair cut?
Okay, Valentine's Day gift.
It's a Valentine's Day outfit is ready.
What should I buy for Valentine's Day gift?
(14:25):
Oh, this outfit is perfect.
How about shoes?
What shoes should I buy?
How about belt?
How about accessory?
How about hats?
How about sunglasses?
What are other things that I should pair
together so I look really good for this
meeting so I can close the deal?
So we found that our customer are treating
us more like a assistant, more like their
black car service.
(14:46):
Therefore, how we are expanding is actually a
category.
We are adding additional item, additional like belt,
accessories that we are not renting as a
complete outfit to help our customer to save
time.
Or for example, in Valentine's Day, we now
partner with company like Armour and one of
the largest women's rental company.
(15:07):
So guys can buy gift card from Armour
for the Valentine's Day where we do what
I found out was jewelry companies, Olivia Yao.
And so guys can buy jewelries or partner
with like flower companies room.
So then the customers can buy flowers so
to save them time.
So category expansion to help enhance the value
(15:27):
profits one.
And now a quick break to hear from
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We also found that a lot of company
are really, really value our technology.
For example, one of the largest fashion company
in the world, they are actually wanna using
(16:10):
our AI to put on the e-commerce
website globally.
So then the customer can ask, what should
I buy and use our AI to train
their store associate.
So a store associate can do a better
job in pairing outfit for their customers.
I love what you do.
It just removes so much stress from us
as guys.
You just literally stress me out.
You're like, sunglasses, shirts.
(16:31):
I'm like, oh my gosh, belt.
I'm like, this is like so stressful to
even think about.
So I love the fact that you solved
that problem.
What are you seeing?
Obviously you're creating the trend in an industry.
So what do you see with technology that
we should be aware of that's happening with
technology right now, developing trends, not just in
your industry, but other industries as well?
(16:51):
What kind of technology that the industry-
Yeah, I mean, like what are the most
exciting technology trends that you're like, oh, I'm
really excited this is happening.
And like you said, like you're dealing with
clothing brands that are looking years in the
future, developing things, right?
So like, what are you seeing that some
of those exciting trends that are happening in
the technology now that we should all be
kind of on the lookout for?
(17:12):
Yeah, I think no doubt everybody know like
the gen AI is going to dominate next
20 years.
But specifically, I think you have to think
about how you use gen AI and how
you architecture your AI.
Today, building AI is a lot easier than
before.
Now with even college grade in couple months,
(17:35):
you will have your own AI.
It's almost like building a website nowadays compared
to 20 years ago.
So it's a lot, lot easier.
And your data, even though you could be
a traditional company, manufacturers or just a small
fintech company or what, but whatever your unique
know-how or unique processes or unique data,
these are all gold nowadays.
(17:57):
And because in last decade, it's all about
algorithm, right?
The Google's box, the black box, whatever you
put it in, right?
Foundability, then you come out with the search
engine optimization, it was all about algorithm.
But the era of algorithm is dead, is
dead.
Why?
Because now everybody use large language models algorithm.
(18:21):
So everybody has those algorithm.
Before only Google has the algorithm, right?
So now everybody has the algorithm.
What matter is what you put into the
algorithm, the data is the goal.
So I think it's really important that you
think about when you are structuring your AI,
for example, architecturally, it can get very expensive
that you use LLM so much.
(18:42):
So maybe you should, in our case, for
example, we structure in a way that if
you think of those LLM are workers, we
are building tools for the workers.
So there's a module that we use our
proprietary data and technology, which is allow LLM
will do better jobs.
So then we don't have to constantly using
(19:02):
LLM, which will be cheaper, while also we
are always better than LLM because it's a
tool for the LLM.
So LLM is better than we are better,
but we are always one step ahead because
we are using additional tool to help the
LLM doing better jobs.
So I think nowadays, it's definitely generally about
how you structure your architecture and how you
(19:24):
are using your proprietary data so you can
be even one step ahead of those companies.
How important do you think the data piece
is to being able to really grow and
scale and even make your company work more
money?
It's extremely important, but it also depends on
what you want to do with the data.
(19:45):
So for example, people, we have eight different
AI agents in the company and people ask
me like, oh, you just, for styling alone,
you have eight agents, like why?
Oh, because different agent is responsible for different
thing.
For example, you have top compared to your
bottom.
You have inside clothes compared to outfits of
(20:06):
the outside for outerwear.
You have human, like customer have to match
to certain item.
The item have to match to an outfit
and pay it back to the customers.
Or when your customer coming in, they are
new customer, I don't know much information about
the customer.
I have to find a customer who looks
like Tai for your locations.
(20:27):
Or new item coming in, we will use
AI to create all those attribute.
For example, one attribute is a color and
in the color is yellow or greens and
reds.
And so we use a lot of those
information so then we can make sure the
styling is perfect.
But end of day, it's about what problem
you want to solve.
(20:47):
So for example, Amazon, they at one point
they want to solve a problem.
They want to help their drivers to can
be easier to get their packages without opening,
turning on or off the lights.
So what they have done is they implement
the AI and AI should be able to
detect the driver and turn it on the
light when the driver is in the truck.
(21:08):
However, AI only see the customer driver when
there's daytime.
So when doing the daytime, the AI will
see the driver, it will turn on the
light, which is not needed because it's daytime.
And at nighttime, the AI couldn't see the
driver so the AI didn't turn on the
light, which is needed.
So end of day is about what problem
are you really solving and why your data
(21:29):
can help you to solve the problem better.
You talked a little bit about team.
How do you do this?
Because I find that team members don't like
change.
Well, some of them don't.
As entrepreneurs, we love change, but then our
team members, some of them just get stressed.
So what are you doing?
How do you build?
You're in a very successful, high-performing team.
So what are some lessons that you found
(21:50):
to build and lead a successful team in
a fast-changing environment like you're in?
Yeah, I think it's never easy.
In my experience, when I was working for
McDonald's, for example, they actually hire people who
are super cutting-edge, from very cutting-edge
companies.
And when I was there, they don't even
(22:11):
have Google Analytics.
And the stuff on the roadmap is like
drones will deliver food to you.
It was almost 10 years ago.
So as you can imagine, then after a
couple of years of the innovations teams, we
sometimes joke as an innovation theater, because you're
always like, it looks amazing on the paper
(22:31):
show.
There's a show on the theater, and then
you never get implemented.
So I think change management is about changing
small.
It's about constantly getting feedback.
And it's back to just like Agile, right?
So when we were doing Agile in technology
development, if you are trying to build a
car, you shouldn't be building four-wheel and
a window.
(22:51):
And after six months, you got a car,
and then you realize everyone work from home
and you don't need a car.
Ideally, you build a bicycle, no one buy
it.
You ask, why is it too slow?
They say, no, because I work from home.
Then you save all of your time later
on building the car, right?
So it's about change management.
It's about changing frequently.
It's about how can you get something that's
(23:12):
tangible so people can get your feedback, really
quickly feedback.
And then how can you iterate it really
quickly?
The same thing for business like Stitch Fix,
for example.
We asked the former president, hey, you are
known for styling service.
Why not you use AI?
AI has been there for a decade.
Yes, general AI is new, but AI itself
has been there for a decade.
(23:33):
And he said the same thing.
He said, it's change management.
It was really hard because stylists feel like
they will lose their job.
So no one want to implement that.
Unfortunately, AI stylists does need stylists to train
the AI.
So then give the knowledge to the AI.
So stylists didn't willing to do so.
And oppositely here in Taylor, what we do
is we have stylists to be the mother
(23:56):
of AI.
Hey, this is your baby.
You are, it's going to create a mini
you as a stylist.
And it's your baby that you created something
to help your job easier.
And it's our stylist's job to create those
AI agent alongside, of course, with our AI
machine learning engineer.
I love this.
What other advice would you give to other
(24:18):
aspiring leaders like you that are in the
technology and fast-growing business space?
Yeah, I think solving problem is still very,
like most important, right?
So for example, when I was working for
Target, we found there was a issue, which
is people going to the store and they
forget one thing.
(24:38):
So my colleague, a different team, they decide
to launch a new feature called the store
like GPS.
You can put down your shopping list, milk
and eggs and chocolates.
And then you go to store and you
shop there and then you will become a
store GPS, turn right, turn left.
You will never forget one thing.
They launch a feature, it was extremely difficult
(24:59):
because every store that they are is very
different.
The skill is different, constantly changing.
They still pull it off and make it
happen.
But after they launch a feature, nobody use
it.
Why?
If you think of Target mom, those mom
are going to a store to get lost.
They like to get away from their family
and annoying kids, right?
It's their time to be shopping around, wandering
(25:21):
around.
And yes, they might forget about one thing
or sometime, but they have been going to
the same store for the last 10 years.
They might get lost, but they don't need
an in-store GPS.
That's a fun part of being in a
Target versus just go and shop something on
Amazon or something in Walmart, right?
So like, are you really solving a problem
or are you solving a problem that is
(25:42):
going to take away from your value propositions
and actually drive away from your audience?
So the same thing in our business, we
realize that we are offering while men's rental
company and women's rental company only have one
word different.
But women's rental company is about women want
to wear a different thing, while in our
model is we save time for our customer.
(26:04):
So fundamentally, very, very different business, different user
experience, different assortment strategy, different financial strategy.
So end of day, it's like, what problem
are you solving and what's your superpower to
solve that?
All husbands wish their wives had that Target
GPS.
It would save a lot.
Exactly, exactly.
(26:26):
So what's this tailor?
Like what makes you different than anybody else
even attempting to do what you do so
well?
I think fundamentally, we are helping people who
are not into fashion to be confident and
get ready for their day.
We want the confidence and the readiness to
be effortless and inclusive, right?
(26:46):
So if you think of this, we partner
with schools.
So why only rich kids should look great,
right?
Why the engineer who go to MBA school
cannot be a really professional and confident businessman?
We partner with corporates like law firms.
The law firms say, you know, we feel
that some of our employees are old school.
(27:07):
And of course, very sensitive to talk about
old school.
Well, what?
So how about they want to use our
service to help more like branding side.
Hey, everybody try something new, starting with your
outfits.
And you will look great and you will
close a deal with your client and you
feel great for your job.
You save time as well.
Or we partner with accounting firm, they offer
(27:29):
to their new hires.
So as a new hire employee, you're always
nervous, right?
First three months, okay, who should I talk
to?
How's best use of my time?
Will they like me?
And if they don't like me for the
first three months, oh no, you will be
bad in the next two years, right?
So help them feel ready for their day.
Or we also partner with dating sites.
(27:52):
So a lot of single guy, you know,
dating is very stressful, right?
So figure out how to look like for
your date night.
Oh my God, it's a lot of worry.
And they don't even have the mind space
to think about how to talk already, have
not to mention you have to think about
how to wear.
So I think our goal is really to
help everyone feel ready for their week.
(28:12):
And that's like why I start a company.
I felt impossible syndrome when I was working
for big tech company as a woman leader,
woman minorities on the team.
And I hope that no one need to
do that.
On the other hand, my co-founder, she
is a sustainability, like really passionate about this.
So she felt like why there's so much
(28:33):
fashion ways in the world?
Why not?
There's a better way to distribute those products
and help them to find a great customer
and also get feedback.
Very many of them, they keep producing junk
because they don't know they sell to big
distributor who sell to small distributor and eventually
get to a customer hand.
So never get the feedback back.
So then that's why they keep producing junk
(28:53):
that people don't want.
So how can we bridge that together?
I love it.
Where can everybody go to be able to
learn more about what you do?
Yeah, so it's taylor.style, T-A-E
-L-O-R-S-T-Y-L-E.
And Valentine's Day is around the corner.
So if you wanna try the Valentine's Day
(29:13):
gift and you can use just businessgift10, coupon
code businessgift10 to get 10% of gift
card, or you can get business30 to get
30% of subscription that you can try
for yourself right away.
I love it.
Thank you for coming out with us today.
Thank you so much.
This is Anya Chen at taylor.style. Thank
you.
So listen, as Anya said, Valentine's Day is
(29:34):
coming up and you probably haven't bought me
a gift yet.
Let's start there.
So in order to be able to do
that, I love this.
If you just go to taylor.style, and
by the way, it's T-A-E-L
-O-R.style, you're gonna love it.
I mean, just by looking and seeing what's
on the site, you'll already go, wow, like
this is way more style than I have.
I already know I'm completely inappropriate dress for
(29:56):
a podcast.
By one quick look at her.
(Transcribed by TurboScribe.ai. Go Unlimited to remove this message.) Welcome to the Business Credit and Financing Show.
Each week, we talk about the growth strategies
that matter most to entrepreneurs.
Listen in as we discuss the secrets to
getting credit and money to start and grow
your business.
And enjoy as we talk with seasoned business
owners, coaches, and industry leaders on a variety
(00:22):
of topics from advertising and marketing to the
nuts and bolts of running a highly successful
business.
And now, to introduce the host of our
show, financial expert and award-winning author, Ty
Crandall.
Hello, thanks for joining us today.
I'm super excited you could be here.
So today, we have somebody who has just
killed it as an entrepreneur, and she's here
(00:43):
to give us really some lessons on the
intersection of kind of technology and then business
growth.
So we're actually gonna learn from a visionary
entrepreneur today, and with us is Enya Cheng.
Now, she is an accomplished and award-winning
product head with extensive experience in leading product
initiatives for top technology, e-commerce, food, delivery,
and retail organizations.
(01:04):
So actually, as the founder and CEO of
Taylor, Enya specializes in creating product vision, strategy,
and roadmaps while actually building and managing very
high-performance teams.
Now, her expertise scans product management, design, development,
go-to-market strategies, and monetization processes as
well.
And as a product manager and a marketing
guru, she has helped build Meta, which is
(01:25):
Facebook and obviously Instagram's platform, shopping, and worked
on eBay's emerging business and AI, targets the
second largest retailer in the world, by the
way, or in the U.S., by the
way, mobile, table, e-commerce app, and McDonald's
global food and delivery service.
So she is apt at managing stakeholders and
responding to industry trends in fast-growing, dynamic,
(01:46):
and ambitious environments as well.
But her achievements have earned her over 20
different awards, including the Girls in Tech 40
Under 40 and the Weebly Award for Best
App of the Year.
She's a TEDx Talk speaker.
She also teaches at Northwestern University and brings
a strong background in websites and app product
(02:07):
development, growth, product marketing, and analytics.
Hey, thanks for joining us today.
You've done so many great things.
Hi there, I'm Enya.
Yeah, I'm a startup founder now.
So I run a company called Taylor.
We use AI to pick perfect clothes for
busy men.
Excited to be here.
All right, well, let's talk a little bit
more about what you do.
I wanna talk a little bit more about
your history as well because you've done so
(02:27):
many cool things.
So what made you get started?
What helped you actually drive you to start
Taylor?
You know, when I was leading large teams
at Meta and eBay, you always feel a
little bit imposter syndrome, wanna look great.
So I tried some subscription boxes like Stitch
Fix, those like they will style you, but
they should be your clothes you have to
buy before you can wear.
(02:48):
It's just a styling service plus e-commerce.
And I didn't want to own that much
stuff.
Unlike you guys in Florida, we don't have
big closet here in San Francisco.
So I tried some rental companies, company like
Render Runway, were newly by Urban Outfitter, which
is a profitable unicorn just for years.
But all of these require me to browse
(03:09):
through thousands of garments and spend hours.
And there was an aha moment.
Wait, these fashion companies are designed for people
who are into fashion.
They are not designed for people who just
need to get ready for the days.
Hey shopping, hey laundry, socially active, such as
sales guy, recruiter, pastor, professor, single guy.
(03:30):
And they are kind of lazy in terms
of picking clothes, but definitely they are busy
in their own world.
And why there's no service like that?
And that's how Taylor is born.
So how does your system work here at
Taylor?
Yeah, so Taylor works like Netflix for outfits.
So for $100 per month, for example, you
get 10 clothes to wear.
(03:50):
You, our AI pick the perfect clothes, you
fill out a simple survey.
You can upload some of your picture.
If you want to get on 15 minutes
consultation call, you can with real professional stylist.
And then from there, our AI will get
over information and pick the clothes.
Our human stylist to make final decision, make
sure it's perfect, or complain to the AI,
(04:12):
say, you are wrong.
Then this is why.
And then we will send you the perfect
outfits, five items that you can mix and
match to a two to three outfits you
wear for a couple of weeks.
Once you're done, you can buy what you
love, or you put the dirty clothes back
to the return envelope, which is prepaid.
Drop in the post office in two days,
you get another shipment.
(04:32):
So no more shopping, no more laundry.
And if you're traveling even better, you don't
need to bring dirty clothes home, put into
the return envelope, give it to hotel lobby.
You go home without doing any laundry.
And people pay monthly fee.
And when they buy the clothes, it's also
deep discount because it's pre-owned, even though
it still looks like new.
And our garment gets sold after renting within
(04:54):
three times.
So it still looks very new, but you
get discounts right away because it's pre-owned.
Nice.
So when you started this, give me, and
you touched upon this a little, when you
looked at the industry as a whole, and
you saw the problem, what is the biggest
problem you think this solution solves?
In fact, on the other side, we actually
saw one of the most important problem in
(05:16):
the world, which is 30% of clothes
go directly from factory to landfill.
10% of carbon emission in the world
were from fast fashion alone.
So it's a huge inventory waste problem in
the fashion world.
And guys usually tend to buy the same
thing again and again.
So if you were just not through rental
(05:38):
model, then those guys would never try something
new.
Open your closet, last 10 years, you only
know five brands and you have been wearing
the same brand again and again.
It's not because you like to be the
same, no one pick stuff for you, you
don't want to re-GQ, you don't know
what looks good, and you don't want to
make a decision right away, even if someone
pick for you, when you open the box,
(05:58):
you don't know if this is worth to
buy, you don't know if you should compare
the price, you don't know if you feel
comfortable after you're wearing it, right?
So it's just, there's no simple solution before
Gen AI that we allow those lazy man
are able to try something new.
And then so in a supply side, there's
(06:20):
tons of brands globally, or even in the
US, because a guy buy the same thing
again and again, so they never be able
to reach a new customer.
So even for amazing brand, high quality brands,
the only way they do it is spend
lots of money in marketing in order to
get attentions, versus those high quality brand actually
(06:41):
invest in the quality are not able to
get the customer.
So by using the circular fashion, lazy economy,
sharing economy and AI, we are able to
bridge the two sides and make sure that
the garment can find great customers and also
get the feedback from the customer while customer
can discover something new, while also looks great
every day.
(07:01):
So going from working for very large companies
to working for yourself, what are some of
the unexpected challenges that you faced along the
way of launching there?
I think so for being a startup founder,
many of you guys might be able to
relate, it's really about trusting yourself.
Give you a story, when I was to
start a company, we went on a startup
(07:22):
competition.
And I thought the best way to practice
a competition would be finding four more judges
and do the mock practice.
So I did, I found 42 of them.
I practiced with every one of them and
my pitch was perfect.
So when I went on the competition, after
the pitch, the judges asked me a question.
(07:43):
After I heard the question, I stunned.
I wasn't able to answer, not because I
didn't know the answer, was because in my
head, I didn't believe that I can answer.
Oh, I was thinking, oh yeah, this question,
practice judge number 37 asked me about this.
And then he also told me his point
of view, which I put in the appendix
number 26.
(08:03):
And the answer was, it's almost like students.
Sometimes when we do the open book exam,
I teach in Northwestern University and students, when
you have open book exam, and many of
them would just spend all the time trying
to find the answer from the book.
And then suddenly the time goes, time is
up.
They realize they haven't write down anything.
But in fact, when they read the question
(08:24):
carefully and think about it, they actually know
the answer, but they just didn't believe that
they can answer.
Of course I lost in the competition, but
it was learning that I realized that, you
know, I actually know a lot.
Who like startup founder, who think about the
problem 24 seven for a couple of years.
Right, so just trusting yourself, there's something really,
(08:47):
really hard being a startup founder, but it's
going to pay off.
How are you using technology to be able
to kind of streamline and enhance your growth
now?
Yeah, so in this business, it wasn't feasible
before GNI, because in order to serve those
lazy man or busy man, you actually before
(09:07):
you need humans and professional stylist and bring
you to a department store and shopping around,
they call personal shopper.
And you probably heard about that in Hollywood,
those celebrity will have their personal shopper and
they will spend a day with them and
pick clothes out for them.
And then on top of the hourly rate
(09:27):
to the stylist, you also have to buy
lots of clothes and which spend thousands of
dollars and go home.
You have to do a laundry and ironings
and all stuff.
So it wasn't feasible before GNI, because for
you need to look at customer's personal size
and information, their previous hard items, their previous
photos, the photo they are inspired by and
(09:50):
the weather of location, their schedule in the
next two weeks and many more.
So with AI, these all can be done
in three seconds.
And what's most powerful in GNI is you
do, you can use large language model like
OpenAI, for example, but you are only defensible
if you have your own unique data.
(10:11):
In our example that we have customer's true
preference, which is not impacted by the purchase
price.
What do you mean?
Means when you go on e-commerce store
or Amazon or any e-commerce store, you
buy something or not, it's not because you
like it, it's not.
It's because how much is it?
So if it's something really cheap, even though
(10:32):
you don't like it, you might still buy
it.
But in our model, because it's subscriptions and
rental, so people pay a monthly fee, so
we know the true preference, just like how
you decide what to watch on Netflix.
You pay a monthly fee, so then when
you pick the show, is that you really
do like it.
We also have like professional stylus data.
We also know the true quality after watches,
(10:54):
et cetera.
We have a lot of proprietary data and
technology.
And we combine these, put it on top
of a large language model so that it's
defensible.
But every time larger language model grow, we
also grow, but we are always one step
ahead.
You mentioned a little bit about data.
What role does data play that you're seeing
(11:16):
in the product itself?
And how are you using data right now
to make better business decisions?
Yeah, so back to the decision on the
AI side, when AI peak close, it does
require a lot of data.
So besides the data I mentioned, for example,
AI only know the past.
AI doesn't know the future.
So model, we work with 300 brands.
(11:38):
Those fashion brands are already designing something two
years from today in the future.
So we know it's information from the future.
Or for example, when our customers tell us
their personal information, because they need to make
sure our outfit fit well with their occasions.
Oh, next Tuesday, I have interview with Google.
(11:58):
Then those informations are those proprietary information we
have.
So we use those to help make sure
that our AI algorithm will fit in the
best clothes for the customer.
And in terms of decision-making, for example,
we also use it for deciding on our
pricing, dynamic pricing.
Given that it's rental, it's like airport car,
after renting a few times, the price will
(12:21):
drop.
So then someone will buy it.
So then they can have the money to
buy another new car.
So we use it for dynamic pricing.
Or we use a lot of customer information
to decide what kind of brand should we
acquire, should we buy, because we are membership.
So we know customer before we source any
inventory, which is very different from e-commerce.
(12:41):
You are hoping someone will buy the stuff
that I put in the warehouse, right?
So we already know the customer's profile.
So we source items specifically for Thai, for
example.
Like, oh, we know Thai is a podcast
host.
So we better to be this type of
outfits in Florida.
So I think this will be perfect for
your everyday wear.
So lots of information being used in decisions.
(13:02):
Well, what should I be wearing as a
podcast host?
I guess that's a good question.
I think that would be a question for
the professional stylist in AI.
I would love to show you.
I would love to see that.
What do you do to expand?
How do you look at this with expanding
into new markets?
I'm interested in your business.
Like, are you expanding through the United States?
(13:23):
Are you looking at expanding around the world?
Like, what is your strategy for expansion?
Yeah, so one thing is that within the
U.S. it's definitely a category expansion.
What we found was while men's wear rental
company and women's rental company, sounds like only
one word different, but it's actually fundamentally totally
different business.
(13:44):
Because in a woman's rental business, they solve
the problem that women want to wear different
things every day.
In our business, our guys are here to
save time.
So if you think of this, if you
have a personal stylist or personal assistant, if
your assistant can only order lunch for you,
your assistant isn't good enough, right?
So, but if your assistant can do many
(14:05):
things, recording the podcast, cutting the podcast, promoting
the podcast, also order lunches and also help
you to put input on business strategies, it's
a great assistant.
The same thing, our customer expect us to
more than renting clothes.
They ask us, where do I get my
hair cut?
Okay, Valentine's Day gift.
It's a Valentine's Day outfit is ready.
What should I buy for Valentine's Day gift?
(14:25):
Oh, this outfit is perfect.
How about shoes?
What shoes should I buy?
How about belt?
How about accessory?
How about hats?
How about sunglasses?
What are other things that I should pair
together so I look really good for this
meeting so I can close the deal?
So we found that our customer are treating
us more like a assistant, more like their
black car service.
(14:46):
Therefore, how we are expanding is actually a
category.
We are adding additional item, additional like belt,
accessories that we are not renting as a
complete outfit to help our customer to save
time.
Or for example, in Valentine's Day, we now
partner with company like Armour and one of
the largest women's rental company.
(15:07):
So guys can buy gift card from Armour
for the Valentine's Day where we do what
I found out was jewelry companies, Olivia Yao.
And so guys can buy jewelries or partner
with like flower companies room.
So then the customers can buy flowers so
to save them time.
So category expansion to help enhance the value
(15:27):
profits one.
And now a quick break to hear from
our sponsor.
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We also found that a lot of company
are really, really value our technology.
For example, one of the largest fashion company
in the world, they are actually wanna using
(16:10):
our AI to put on the e-commerce
website globally.
So then the customer can ask, what should
I buy and use our AI to train
their store associate.
So a store associate can do a better
job in pairing outfit for their customers.
I love what you do.
It just removes so much stress from us
as guys.
You just literally stress me out.
You're like, sunglasses, shirts.
(16:31):
I'm like, oh my gosh, belt.
I'm like, this is like so stressful to
even think about.
So I love the fact that you solved
that problem.
What are you seeing?
Obviously you're creating the trend in an industry.
So what do you see with technology that
we should be aware of that's happening with
technology right now, developing trends, not just in
your industry, but other industries as well?
(16:51):
What kind of technology that the industry-
Yeah, I mean, like what are the most
exciting technology trends that you're like, oh, I'm
really excited this is happening.
And like you said, like you're dealing with
clothing brands that are looking years in the
future, developing things, right?
So like, what are you seeing that some
of those exciting trends that are happening in
the technology now that we should all be
kind of on the lookout for?
(17:12):
Yeah, I think no doubt everybody know like
the gen AI is going to dominate next
20 years.
But specifically, I think you have to think
about how you use gen AI and how
you architecture your AI.
Today, building AI is a lot easier than
before.
Now with even college grade in couple months,
(17:35):
you will have your own AI.
It's almost like building a website nowadays compared
to 20 years ago.
So it's a lot, lot easier.
And your data, even though you could be
a traditional company, manufacturers or just a small
fintech company or what, but whatever your unique
know-how or unique processes or unique data,
these are all gold nowadays.
(17:57):
And because in last decade, it's all about
algorithm, right?
The Google's box, the black box, whatever you
put it in, right?
Foundability, then you come out with the search
engine optimization, it was all about algorithm.
But the era of algorithm is dead, is
dead.
Why?
Because now everybody use large language models algorithm.
(18:21):
So everybody has those algorithm.
Before only Google has the algorithm, right?
So now everybody has the algorithm.
What matter is what you put into the
algorithm, the data is the goal.
So I think it's really important that you
think about when you are structuring your AI,
for example, architecturally, it can get very expensive
that you use LLM so much.
(18:42):
So maybe you should, in our case, for
example, we structure in a way that if
you think of those LLM are workers, we
are building tools for the workers.
So there's a module that we use our
proprietary data and technology, which is allow LLM
will do better jobs.
So then we don't have to constantly using
(19:02):
LLM, which will be cheaper, while also we
are always better than LLM because it's a
tool for the LLM.
So LLM is better than we are better,
but we are always one step ahead because
we are using additional tool to help the
LLM doing better jobs.
So I think nowadays, it's definitely generally about
how you structure your architecture and how you
(19:24):
are using your proprietary data so you can
be even one step ahead of those companies.
How important do you think the data piece
is to being able to really grow and
scale and even make your company work more
money?
It's extremely important, but it also depends on
what you want to do with the data.
(19:45):
So for example, people, we have eight different
AI agents in the company and people ask
me like, oh, you just, for styling alone,
you have eight agents, like why?
Oh, because different agent is responsible for different
thing.
For example, you have top compared to your
bottom.
You have inside clothes compared to outfits of
(20:06):
the outside for outerwear.
You have human, like customer have to match
to certain item.
The item have to match to an outfit
and pay it back to the customers.
Or when your customer coming in, they are
new customer, I don't know much information about
the customer.
I have to find a customer who looks
like Tai for your locations.
(20:27):
Or new item coming in, we will use
AI to create all those attribute.
For example, one attribute is a color and
in the color is yellow or greens and
reds.
And so we use a lot of those
information so then we can make sure the
styling is perfect.
But end of day, it's about what problem
you want to solve.
(20:47):
So for example, Amazon, they at one point
they want to solve a problem.
They want to help their drivers to can
be easier to get their packages without opening,
turning on or off the lights.
So what they have done is they implement
the AI and AI should be able to
detect the driver and turn it on the
light when the driver is in the truck.
(21:08):
However, AI only see the customer driver when
there's daytime.
So when doing the daytime, the AI will
see the driver, it will turn on the
light, which is not needed because it's daytime.
And at nighttime, the AI couldn't see the
driver so the AI didn't turn on the
light, which is needed.
So end of day is about what problem
are you really solving and why your data
(21:29):
can help you to solve the problem better.
You talked a little bit about team.
How do you do this?
Because I find that team members don't like
change.
Well, some of them don't.
As entrepreneurs, we love change, but then our
team members, some of them just get stressed.
So what are you doing?
How do you build?
You're in a very successful, high-performing team.
So what are some lessons that you found
(21:50):
to build and lead a successful team in
a fast-changing environment like you're in?
Yeah, I think it's never easy.
In my experience, when I was working for
McDonald's, for example, they actually hire people who
are super cutting-edge, from very cutting-edge
companies.
And when I was there, they don't even
(22:11):
have Google Analytics.
And the stuff on the roadmap is like
drones will deliver food to you.
It was almost 10 years ago.
So as you can imagine, then after a
couple of years of the innovations teams, we
sometimes joke as an innovation theater, because you're
always like, it looks amazing on the paper
(22:31):
show.
There's a show on the theater, and then
you never get implemented.
So I think change management is about changing
small.
It's about constantly getting feedback.
And it's back to just like Agile, right?
So when we were doing Agile in technology
development, if you are trying to build a
car, you shouldn't be building four-wheel and
a window.
(22:51):
And after six months, you got a car,
and then you realize everyone work from home
and you don't need a car.
Ideally, you build a bicycle, no one buy
it.
You ask, why is it too slow?
They say, no, because I work from home.
Then you save all of your time later
on building the car, right?
So it's about change management.
It's about changing frequently.
It's about how can you get something that's
(23:12):
tangible so people can get your feedback, really
quickly feedback.
And then how can you iterate it really
quickly?
The same thing for business like Stitch Fix,
for example.
We asked the former president, hey, you are
known for styling service.
Why not you use AI?
AI has been there for a decade.
Yes, general AI is new, but AI itself
has been there for a decade.
(23:33):
And he said the same thing.
He said, it's change management.
It was really hard because stylists feel like
they will lose their job.
So no one want to implement that.
Unfortunately, AI stylists does need stylists to train
the AI.
So then give the knowledge to the AI.
So stylists didn't willing to do so.
And oppositely here in Taylor, what we do
is we have stylists to be the mother
(23:56):
of AI.
Hey, this is your baby.
You are, it's going to create a mini
you as a stylist.
And it's your baby that you created something
to help your job easier.
And it's our stylist's job to create those
AI agent alongside, of course, with our AI
machine learning engineer.
I love this.
What other advice would you give to other
(24:18):
aspiring leaders like you that are in the
technology and fast-growing business space?
Yeah, I think solving problem is still very,
like most important, right?
So for example, when I was working for
Target, we found there was a issue, which
is people going to the store and they
forget one thing.
(24:38):
So my colleague, a different team, they decide
to launch a new feature called the store
like GPS.
You can put down your shopping list, milk
and eggs and chocolates.
And then you go to store and you
shop there and then you will become a
store GPS, turn right, turn left.
You will never forget one thing.
They launch a feature, it was extremely difficult
(24:59):
because every store that they are is very
different.
The skill is different, constantly changing.
They still pull it off and make it
happen.
But after they launch a feature, nobody use
it.
Why?
If you think of Target mom, those mom
are going to a store to get lost.
They like to get away from their family
and annoying kids, right?
It's their time to be shopping around, wandering
(25:21):
around.
And yes, they might forget about one thing
or sometime, but they have been going to
the same store for the last 10 years.
They might get lost, but they don't need
an in-store GPS.
That's a fun part of being in a
Target versus just go and shop something on
Amazon or something in Walmart, right?
So like, are you really solving a problem
or are you solving a problem that is
(25:42):
going to take away from your value propositions
and actually drive away from your audience?
So the same thing in our business, we
realize that we are offering while men's rental
company and women's rental company only have one
word different.
But women's rental company is about women want
to wear a different thing, while in our
model is we save time for our customer.
(26:04):
So fundamentally, very, very different business, different user
experience, different assortment strategy, different financial strategy.
So end of day, it's like, what problem
are you solving and what's your superpower to
solve that?
All husbands wish their wives had that Target
GPS.
It would save a lot.
Exactly, exactly.
(26:26):
So what's this tailor?
Like what makes you different than anybody else
even attempting to do what you do so
well?
I think fundamentally, we are helping people who
are not into fashion to be confident and
get ready for their day.
We want the confidence and the readiness to
be effortless and inclusive, right?
(26:46):
So if you think of this, we partner
with schools.
So why only rich kids should look great,
right?
Why the engineer who go to MBA school
cannot be a really professional and confident businessman?
We partner with corporates like law firms.
The law firms say, you know, we feel
that some of our employees are old school.
(27:07):
And of course, very sensitive to talk about
old school.
Well, what?
So how about they want to use our
service to help more like branding side.
Hey, everybody try something new, starting with your
outfits.
And you will look great and you will
close a deal with your client and you
feel great for your job.
You save time as well.
Or we partner with accounting firm, they offer
(27:29):
to their new hires.
So as a new hire employee, you're always
nervous, right?
First three months, okay, who should I talk
to?
How's best use of my time?
Will they like me?
And if they don't like me for the
first three months, oh no, you will be
bad in the next two years, right?
So help them feel ready for their day.
Or we also partner with dating sites.
(27:52):
So a lot of single guy, you know,
dating is very stressful, right?
So figure out how to look like for
your date night.
Oh my God, it's a lot of worry.
And they don't even have the mind space
to think about how to talk already, have
not to mention you have to think about
how to wear.
So I think our goal is really to
help everyone feel ready for their week.
(28:12):
And that's like why I start a company.
I felt impossible syndrome when I was working
for big tech company as a woman leader,
woman minorities on the team.
And I hope that no one need to
do that.
On the other hand, my co-founder, she
is a sustainability, like really passionate about this.
So she felt like why there's so much
(28:33):
fashion ways in the world?
Why not?
There's a better way to distribute those products
and help them to find a great customer
and also get feedback.
Very many of them, they keep producing junk
because they don't know they sell to big
distributor who sell to small distributor and eventually
get to a customer hand.
So never get the feedback back.
So then that's why they keep producing junk
(28:53):
that people don't want.
So how can we bridge that together?
I love it.
Where can everybody go to be able to
learn more about what you do?
Yeah, so it's taylor.style, T-A-E
-L-O-R-S-T-Y-L-E.
And Valentine's Day is around the corner.
So if you wanna try the Valentine's Day
(29:13):
gift and you can use just businessgift10, coupon
code businessgift10 to get 10% of gift
card, or you can get business30 to get
30% of subscription that you can try
for yourself right away.
I love it.
Thank you for coming out with us today.
Thank you so much.
This is Anya Chen at taylor.style. Thank
you.
So listen, as Anya said, Valentine's Day is
(29:34):
coming up and you probably haven't bought me
a gift yet.
Let's start there.
So in order to be able to do
that, I love this.
If you just go to taylor.style, and
by the way, it's T-A-E-L
-O-R.style, you're gonna love it.
I mean, just by looking and seeing what's
on the site, you'll already go, wow, like
this is way more style than I have.
I already know I'm completely inappropriate dress for
(29:56):
a podcast.
By one quick look at her.
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