October 31, 2025 • 48 mins
Get ready to be guided through massive e-commerce growth with Lauren Nicole Muir, a digital commerce and product expert, who until recently was Head of Ecommerce at fashion brand Oh Polly.
Find out how she helped the brand grow during the pandemic. It's a story of bold engagement while embracing the zeitgeist, often on the spur of the moment.
The bold approach doesn't end there. Oh Polly recently stopped traffic on LinkedIn following its hugely creative use of video on the PLP, of all places. Who does that?
But Lauren doesn't only talk about the fabulous customer-facing front-end experience. She goes deep into the benefits of harnessing your product data correctly and how to use AI properly to make your back-end operations more effective and move the brand forward. Practical AI, instead of hyped AI.
At the heart of it all is a single message: ecommerce is only functional and fabulous when businesses adopt a truly collaborative and creative approach.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
This is Functional & Fabulous, the omnichannel podcast where we unbox tales of online retail and digital transformation.
In this episode, our guest takes an unconventional approach to ecommerce...
No one really should have been buying our stuff.
Ger asks a question for a 'friend'...
(00:21):
How do you sell glitzy dresses?
There is some bad language...
The other bit that she touched on really briefly was HS codes.
Yeah, dirty word.
There is some bad behaviour...
Maybe I should have checked in a little bit more on what I was actually allowed to do.
And there are some bad fashion choices...
Where's my fishtail dress, Goddammit?
(00:42):
This episode of Functional & Fabulous is brought to you with pride by StudioForty9, retail ecommerce experts, omnichannel growth consultants, and cut-through performance marketing specialists.
StudioForty9, where your digital retail success is built.
Hello and welcome to another episode of Functional & Fabulous.
(01:04):
If you've ever wondered what it looks like to take a fashion brand from one store on eBay to a £150 million global powerhouse, then you're going to love this one.
Lauren Nicole Muir joins us fresh from her five-year run at Oh Polly, where she helped steer one of the UK's fastest growing fashion brands through a complete ecommerce transformation.
From Magento to Shopify, from UK only to US-led, from manual merchandising to automated data-driven trading.
(01:31):
She's a part-marketer, part-technologist, part-trader, and somehow manages to make all three sound fun.
Based in Glasgow, Lauren has recently stepped back to work on research projects and to explore how brands can make ecommerce operations smarter, leaner, and a little more human.
Lauren, you're very welcome.
Thank you for the intro.
That was much better than I could have ever made up myself.
(01:52):
That was lovely.
You're very welcome, Lauren.
Let's start at the beginning.
Oh Polly went from selling on eBay to becoming a £150 million powerhouse.
When you look back at it, what do you think was the moment that the business truly leveled up?
So I got involved during the first COVID lockdown, which was quite weird.
(02:15):
And I always said for years, my first few years of working there, I'm like, I've never had a normal trading environment.
Like, I kind of wish I had been there before COVID and could have had something to compare it to.
But as I joined, the business had just launched a sister brand in activewear, which was just fantastic timing.
It's almost like they knew that there was going to be, like, a global pandemic where people maybe wouldn't want, like, glittery mini dresses and stuff for a little while.
(02:41):
So thankfully we launched Bo+Tee and I joined actually in digital marketing at the time.
That was my background.
I'd been agency-side for digital while I was at uni, graduated in the middle of COVID lockdown and started straight away at Oh Polly.
And I think my first couple of days and weeks there, I was like, this is, you know, this is crazy.
Like, we're in lockdown.
How do we respond to this crazy shift in demand, where people are not going out?
(03:05):
We don't know when we'll ever be able to go out again.
And it was really crazy.
But actually seeing what was at the time, a kind of skeleton team come together and work to be like, right, we're trying to sell something here for our big brand that is our named brand everyone knows and loves.
We're trying to sell something that no one needs right now.
How do we do that?
And how do we make it fun?
And we would have daily stand-ups and creative calls and stuff where we'd be like, what can we do today?
(03:30):
And it was just everyone from every different level of the business, every different part of the business would get involved in, like, whatever crazy ideas we could do to achieve growth in the most uncertain trading circumstances.
And we did, we had, like, 100 per cent year-on-year growth in a year where no one really should have been buying our stuff. Which was, it was pretty cool.
(03:51):
And I know that was testament to the kind of creativity of the teams that all came together and worked.
And also the business for knowing, like, we can pivot massively into activewear and things that people really did buy into at that point in time.
And I think, as we started to shift in and out of lockdowns and things were going up and down and stuff, I realised, like, oh look, we've got something pretty special here.
(04:12):
So yeah, massive, massive growth in a time when I don't think any of us really expected it.
That was pretty cool.
How do you sell glitzy dresses, glamour dresses during COVID, out of curiosity?
Interestingly, at the time I was actually doing, so I was in digital marketing, email, CRM, kind of all of our automated emails and, you know, marketing-related emails and launches and promos and stuff.
(04:36):
But also we didn't actually have, like, a core marketing function at that point in time.
So myself and one of the other guys who I worked with, and worked closely with our merchandising teams, I think that's where the trading side comes in for me, I love it.
We would decide what the Black Friday promos and stuff were going to be to say, do we, you know, it's COVID, everyone's locked up, like, no one's out, nothing's open.
Will we just do, like, a fun giveaway?
(04:58):
Will we do a fun promo?
Will we say, oh, for the next hour, you get 25 per cent off everything on the app, go or the first hundred people to do this, get this and made it this, like, kind of gamified a little bit.
And I was actually doing the social media at the time for Instagram, sorry, not Instagram, but Facebook and Twitter.
Which we at the time were quite big - like, during Love Island, and we would live-tweet during Love Island at night and stuff.
(05:24):
And one of my favourite things, I'd be sitting, like, watching the TV with my friends and my boyfriend, and I'd be, like, sitting on the brand's Twitter account, like, rapidly tweeting like, oh, okay, if, you know, if this person gets booted off tonight, we'll give away 20 free dresses.
You need to tell us who your favourite person is or - it's so different to what the Oh Polly brand is now.
But at the time we would do anything to get that engagement and get people excited and give people something.
(05:47):
Oh, you've been locked in the house for the last, like, four weeks, but we're going to do something fun.
And we would get crazy engagement on Twitter and I'd be sitting there...
I think there was, like, a Casa Amor one year and it was really crazy and there was loads of drama.
And I'm like, right, for every kiss in Casa Amor tonight, I'll give away a dress for someone who tweets us a picture of them in an Oh Polly dress or whatever.
And I probably should have, maybe I should have checked in a little bit more on, like, what I was actually allowed to do, because I was probably giving away more dresses than I potentially should.
(06:13):
But the community that we created and stuff was, like, insane.
The messages and stuff that we would get, like, the hype that we'd created, people would be tweeting me going, Oh Polly admin, like, I'm waiting for the next hour, like, for you to start live-tweeting Love Island.
I'm so excited.
And I would sit there, like, this wasn't ever meant to be my job or what I was meant to do, but it was so fun.
And we'd do giveaways and we'd be like, right, go on the website and find this hidden code and things like that and just get people excited and engaged.
(06:41):
And yeah, use promos to do what we needed to do at that point in time.
Now the brand's in a totally different position, much more kind of premium, definitely not as promo-led.
Because I changed the product offering a little bit
and probably we don't really do that kind of social engagement stuff that we did at the time.
But during COVID, during that environment, it was, like, amazing working for a brand that was so agile and so up for testing and trialing anything. Because we could have said any idea,
(07:08):
we could have been like, I think this would be really cool.
Like, will we try it? And we'd have got a yes.
Give it a go.
And if it works, it works.
If it doesn't, no harm done.
It's so fun.
It's interesting that you're talking, you're kind of contrasting, let's say that period with how the brand has grown, et cetera.
But I guess there's a good argument that could be made that the traces and the muscle memory is still there, because obviously we all know that Oh Polly melted the internet, at least the LinkedIn end of the internet, with your new approaches to product listing pages not so long ago.
(07:39):
So you guys are still very much agile and up for experimentation, I guess, right?
One hundred per cent.
It's always been something that's so fun.
And when I was lucky enough to kind of take over the e-comm function, I tried to instill in the team, like, there is no idea that is too crazy.
There is no idea that is not going to get some sort of response, nothing that we would absolutely never try.
(08:01):
Like, give it a go.
You know, raise ideas and give suggestions.
When I got a message one day, hey, we've went out to a beach in LA and shot all this content and actually the videos engage with each other and we don't want to just use them on social.
We want to try and use them on the website.
How do we do it?
How can we make it work?
We were like, interesting.
Never tried it before.
And actually, it was interesting to get the more technical and e-comm teams and the people involved in merchandising and the website to engage directly with the video creative and content teams to be like, right, this is how you would need to kind of shoot this.
(08:33):
This is the types of content.
So for example, to make something work on mobile and desktop.
Okay, what kind of videos do we want?
How do we want to do that?
Where would we merchandise it?
Merchandise position one and two, and getting that communication going.
And I ended up making like Canva animated presentations to show people what merchandising would look like.
And if it looks like this on mobile, this is what it looks like on desktop.
(08:54):
Are you happy to, you know, if we just test this on mobile to start with, and where the brand was 92 per cent mobile traffic, like we prioritised mobile 100 per cent. And working with them to go, oh, how do we optimise the video and make sure the video is, like, super-fast and the experience is great for the customer.
It was a really fun project and the response we got was, it was so fun and it validated that, like, you know, you just do something that's a bit different and it gets people talking and gets people thinking rather than just the standard,
(09:22):
let's get a launch up.
Let's pick the nicest image to put on the front.
Like, actually do something a bit different and get people talking and visiting the website and thinking about, oh, they're actually really cool.
And the amount that we invest in creative and content, it deserves to be spoken about and the teams behind it are fantastic.
So it was nice to see them get the recognition.
Yeah, it was such a kind of a... it tickled a funny bone, I think, in people, like, because it was so lovely.
(09:48):
It was so pleasurable to watch.
Obviously, you know, these are beautiful photographs on, you know, Santa Monica Pier and the clothes look great and the models look great.
And then there's this really lovely interaction between the images, you know, the ice cream bowl and the ice cream ball dropping into the, dropping from the sky. Or the bikes that are moving between each other.
(10:09):
You know, I think, I don't know, it's one of those times where it just landed so incredibly well.
You don't often see, like, innovation on the PLP.
On the PLP, no, not at all.
It's like, you'll see plenty on a product detail page.
And you'll see, but people don't really try new stuff on a PLP.
The PLP is just, like, really functional.
So to see something really beautiful on a PLP was probably why it broke LinkedIn.
(10:34):
But one of the things I think is really interesting, though, Lauren, is that, like, Oh Polly has, like, a vast amount of SKUs and it moves really, really quickly.
So, like, you've gone through your period of unbridled creativity during COVID.
And then you're in this period of growth now where people are starting to go out and people are starting to buy sparkly dresses again.
(11:00):
And it's transformed over that five-year period into this huge business.
But that must've come with, like, loads of operational challenges.
Like you mentioned there, you were skeleton staff during COVID.
And then into this period of spectacular growth and moving into an organisation that's doing a lot more.
(11:24):
So maybe it'd be good to talk a little bit about some of the things that were involved there.
And one of the things that, it's a very long-winded question, sorry.
But one of the conversations that we always have, and particularly with brand owners and retailers here in Ireland, is like, what is actually involved in, like, the operational admin of that many SKUs?
(11:47):
And like, how do you even deal with that?
Oh, it's funny because my background was marketing.
When I first started to get a bit more involved in, like, the technical side of things, it was probably more related to, like, product catalogues and things like that.
And we onboarded a couple of different pieces of tech onto Shopify, like Algolia and Nosto and, like, these kind of front-end solutions and stuff.
(12:10):
And at the time, I definitely, because I come from more of a digital background, definitely wasn't actually thinking about product data whatsoever.
I was thinking about the products, that they looked really cool and shiny and sexy on the front end.
And like, oh, they look really nice and I can sell them.
And I probably had a lack of appreciation for what goes on in the back end, in the back office, and how much you need to invest to make that run smoothly, especially when it comes to a time like Black Friday or something where we could, I mean, like, crazy days and crazy volumes of orders and stuff, to the point where we're having to have meetings.
(12:46):
Like, do we need to switch this off?
Because like, can we handle the volume of orders that are going through the warehouse or, you know, and that's the bit that excites me.
Like I enjoy it, but I don't actually think until probably the last two-ish years, two or three years, I really appreciated and understood, like, oh my God, there is so much that holds us up.
Like, it underpins all of the kind of sexy stuff that I'm trying to do on the front end.
(13:07):
And I've been lucky to work with an amazing technical team that we've built at Oh Polly over the past year, who are very much, like, operational.
They've all come from retail background, massive retail powerhouses.
And they really help us, like, help me understand things that potentially I should have known, and if I'd known maybe three, four years ago,
it would have been great to get those foundations in earlier in the stage of growth.
(13:30):
But I have this conversation all the time.
We grew at such a pace that there's things that, you know, when you hit that like nine-figure mark, you go, I wish I'd done this before because it's really complex now.
It's like a 7,000-strong catalogue.
But did we know a couple of years ago that it was going to go this crazy?
Like, would we have been aware of that?
Would we have, was that what we were prioritising, or were we just like, go, go, go, do whatever you can to get out of COVID, and growth?
(13:52):
So there's been a lot of challenges, I would say, in terms of really complex catalogue, really complex migrations.
Like, Gerard, you kind of mentioned this at the start.
Like, when I joined Oh Polly, we were on Magento 1.
The first year, and a bit of me working there, Oh Polly was migrating from Magento 1 to Magento 2.
(14:13):
We launched Bo+Tee on Shopify.
I was lucky enough to get the Bo+Tee brand as kind of my baby when I joined the business during that time.
And it was amazing stage of growth, but also one of the most amazing things was that it was on Shopify.
And I was so empowered and so enabled to do things quicker, faster.
We integrated tech seamlessly, quickly, sometimes without development, sometimes with development.
(14:35):
And when it was with development, it was still easier.
And we, I think about three months after we migrated Oh Polly to M2, switched everything to Shopify.
And in hindsight, you would look back and go, I wish we'd always been on Shopify, but you just don't know. Like, the world of tech evolves so quickly.
And there's so many new innovations and stuff like that, that I think it's hard to plan ahead.
People ask me, I got asked last year on a talk, what's your three-year roadmap?
(14:59):
And I was like, you're crazy.
I've got like a three-month roadmap at best.
Because things change so quickly, and trying to think where Oh Polly would be in three years' time, versus what tech would be available, versus what kind of work we have to do to get there and stuff.
I think it's quite difficult when things move at such pace.
Yeah, yeah.
I think about, like, one of the things we get asked quite a lot is where businesses want to future-proof their business from a tech point of view.
(15:25):
And it's almost impossible to answer.
It's like, how are you going to future-proof in tech?
You'd be lucky to make a good decision for the next two years.
And that's about, you know, like...
And so my answer to that question is always, well, what do you think you are definitely going to do in the next two years?
And then, will this piece of tech allow you to do that within the next two years, or not?
(15:45):
Because that's really the priority, you know.
Yeah, those were interesting times, that whole Magento and the Shopify and all the rest of it.
From, let's say, an operations point of view, you know, obviously from, with production for products and that side of things, what do you know now, do you think, about trading a catalogue with respect to, let's say, the product data that you need versus what, you know, what you didn't know, let's say, two or three years back?
(16:17):
I think, for me, from a kind of trading point of view, we probably, a couple of years ago, we were doing a lot of manual merchandising.
And if it wasn't manual, it was fairly manual and based off of, like, tags and stuff like that, which now I... again, going back to investing in technology, you know, would tell my team a million times over, and say the same to anyone, I wouldn't invest in any technology that involves manual workload.
(16:44):
There's no point in buying technology to me and spending,
I mean, at some, like, enterprise level, six figures, on technology where you're still going to have to sit and manipulate it and work really hard.
Like, please make the technology work harder for you.
So, for example, using AI,
I would no longer spend my money on a tool
that is not harnessing AI to some degree,
because if you're going to take on a year's contract
or a two-year contract
(17:06):
with something that can't take your product catalogue
and take all of that data
and use AI or something to enhance it
and make it better and to do some of the hard work for you,
then you're going to be left behind.
Because in a couple of years,
your competitors are all going to be
automating that manual workload,
letting AI do the hard stuff
and then focusing their actual skilled team members
(17:26):
on doing the stuff that's really exciting.
Going back to that, like, creativity and actually, like, thinking, and thinking what is going to make a big shift here?
Like, what's going to be something really cool and different?
I don't want my team sitting there going, oh, well, if someone, we know someone likes black dresses and we put them in a black dress segment, let's boost black dresses, that kind of stuff.
It needs to be like AI automatic personalisation,
(17:49):
make it quick and punchy and let it,
I'm not saying just let it sit and do its job,
keep monitoring it obviously
and testing and evolving and optimising,
but I would hate the thought of my team
having to sit there, like, doing all this manual workload
and sitting and setting,
using a search tool
where you have to sit and manually set synonyms
in the back end.
Like, if someone searches nightdress, they may also mean pyjamas, and get a tool that's really, really great,
(18:14):
uses AI, uses the most upcoming technology possible, has got a really cool roadmap that they're happy to share with you and tell you what's coming for the next year or two.
But also there is no point in buying that tool if your product data and what underpins it in the back end is awful because then you're going to go, oh, the AI doesn't work.
And it's like, well, actually, you didn't use any of the product attributes you're meant to use.
(18:36):
You didn't use metafields properly.
You're not enhancing all of your product data in the right way.
We were lucky, our team were really on the ball with the kind of front-end sexy-sided product data.
So all of our products have got every different possible attribute they could want.
We were pretty quick getting involved with native Shopify metafields and all these different things that we're now, we now know we're going to need AI and LLMs to be able to read nicely through Shopify to make ourselves discoverable.
(19:02):
So we're lucky that we did that.
I think the bit that I probably didn't appreciate quite as much, I got the front-end stuff.
I'm like, yeah, I need to know that the dress is like black, sleeveless, ruffled, all these things that make trading really cool on the front end.
But again, the bit that I didn't appreciate because my background was more marketing digital was the operational side of product data.
(19:23):
The stuff that actually... there is no point in me doing all this on the front end and giving everyone AI-personalised shopping experiences on site and doing all this digital transformation, if actually the HS codes are in a mess,
nothing's got a country of origin,
the fabric composition isn't there,
all of these things. Which someone who is not operational, or was never operational, doesn't really appreciate or understand.
(19:44):
So yeah, we had to go on a learning curve with product data massively and going through that, oh, we're getting to this really large SKU catalogue size and really growing up in scale and making all this money.
Do we need a PIM in making those kinds of decisions?
When you've got years of migrated product data, products that have been on eBay and Magento and Shopify and Airtable for years and stuff, and how do you harness that and make that make sense?
(20:11):
That was the bit that was actually, I'm like, oh, our product data's fine.
No one's product data is fine.
You need to do a lot of work on product data to make it classified as fine.
So yeah, those kind of operational bits are, they're the tough ones.
They're the really hard ones.
You can make sexy through Shopify and stuff, but the stuff outside of Shopify.
(20:32):
It's really, you know, there's definitely a kind of, so many different elements, like business elements come in.
There's this kind of concept of fortune favours the prepared, you know, there's elements like, you're lucky because you were kind of, you were almost thinking about it.
You didn't realise you were being lucky at the time, but you're lucky because you were being prepared and you were doing things like that.
(20:56):
But there's also then the point where you, you really have to make a decision and sometimes the decisions that are, the options that are available to you.
Let's say you mentioned a PIM, for example.
I presume you guys went through a bunch of PIMs or made some, maybe not correct decisions and then ended up on something that, that basically you eventually realised was, this is what we need as a minimum thing that will do what we need it to do and work from there.
(21:22):
You know, I guess that, is that kind of process that you go through?
Yeah.
You know, people keep telling us, you need a PIM.
You need a PIM.
You need to standardise product data.
You need to add some data governance, you know, and when you get a PIM, every other system will work better and they'll integrate better and everything.
And we were like, right, okay, it turns out we need a PIM.
But I think we went to go out and buy, like, an enterprise PIM and get that all on board, and then had the stark reality when we actually spoke to people who were very good at that kind of side of things.
(21:54):
At the time, there was literally, our tech team at Oh Polly, I think it was me doing all the kind of front end and development and Shopify side of things.
An IT guy and a consultant, like an external consultant, we didn't have a tech team.
So actually having, we had someone come in to kind of manage the tech team.
He was like, this, you know, this team's tiny, like we need help.
We need a PIM.
We need to buy all this technology.
We've got this huge roadmap of stuff we need to do.
(22:15):
And we very quickly realised, you know, we've got a lot of foundational things that we need to fix here,
product data being one of them, before we can go out and spend enterprise-level money on technology to fix the problem.
Like, at the time, like, if you put something low-quality into a machine, it's not going to churn out anything of any great quality, and sometimes I think we maybe thought we were putting a plaster over the problem by being like, oh yeah, we can just buy a PIM and everything will be fine.
(22:42):
And actually there was so much that needed to be solved before we could put data into a PIM, needed to do a huge data cleanse exercise.
And then it kind of turned out, actually, is that PIM what we need?
We had a business who was basically,
we were basically built on Airtable
and so much of the business was,
you know, powered through Airtable,
from marketing to operations
to influencers, collaborations,
(23:03):
product data, production planning,
everything was through Airtable
and the decision ended up
being to build our own PIM
through Airtable.
Which, I saw that come to life
a couple of months ago,
and it was fascinating.
Like, how much is possible through Airtable, which I always saw as being, like, a marketing planning system, because that's what I used it for, planning marketing campaigns.
(23:23):
And I'm like, how are we now powering everything from our factories from the minute a product becomes an idea in someone's head and may become a sample?
It goes through to factory teams
to put in all of the data
completely governed correctly,
and the exact correct types of data
flows through to the next person to say,
Okay, well these are the quantities we need,
and these are all the different
fabric options and colour options,
(23:44):
and the sizes and the stock units.
And okay, now we need a copywriter,
and then now we need e-comm to enrich it
and then by the time
it gets to me and my team,
I'm like, whoa,
this is, like, completely clean,
incredible product data
with automated HS codes
and all of these things
that at the time,
it was a huge investment,
a huge project for the tech team,
but it will change,
change the business.
(24:04):
It's just incredible.
I presume not only, because we have seen this sort of rollout, we'll say, and I guess it was the same in Oh Polly, like, it's not just the tech team, you know, there is change management that has to be dealt with throughout the business.
Can you reflect on that a bit?
Like, what was that like to have to, you know, work through all of those things?
I think that was probably the biggest challenge because people have, people have gotten used to what they do.
(24:30):
And I think sometimes until you disrupt that and say like, no, we need to make change here, people potentially don't see the issue in what they're doing.
We knew because we could feel the effect sometimes of some of the operational issues.
You know, the ops team coming to us saying, I've got all these things stuck at Customs, what's going on?
We're missing product data or whatever.
I could feel those kind of issues, but I think sometimes people further back in the production cycle, maybe at the buying stage or in the factory stage, don't ever feel those issues.
(24:58):
They do their bit and everyone kind of does their bits in silos.
And actually what the tech team had to do was map out the process start to finish.
Here is where you sit and here is how much you impact someone else.
And here's what happens if you put this data in incorrectly.
And because we're run on Airtable, for example, there was times where someone, like, 20 stages back in a process would make one change and it would break something on the front end of the website that I had implemented because it was all managed through Airtable and there was absolutely no governance.
(25:23):
And it would take someone from customer service coming to me saying, this product says it was restocking three weeks ago, but it's not due in for four weeks.
And I'm like, oh, like, that kind of thing.
There was so much, so many data things that we had to go back to the drawing board, really go to the business and the BAs and the PMs and the tech team at Oh Polly absolutely smashed this out of the park.
They ran workshops.
They had whiteboard sessions.
(25:44):
They sat there like, this is you, like, this is your impact.
This is what we're trying to achieve.
This is what I need from you.
You need to come on this journey with me.
And honestly, it seemed like a bigger thing.
I think such a huge thing at the time that I was like, we might have bitten off more than we can chew here.
We're never going to be able to change this business and do this change management and transformation.
And actually they did.
(26:05):
And when it went live and we're still, they're still in phase one of the PIM.
There's phase two rollout still to come, which will just be a game changer.
Some of the things that are in that, I'm like, how did we even think of this?
Like, but it's a big, big thing for the full business.
And I think also getting people to buy into a long-term project like that.
Everyone thinks, oh, you can get a PIM and put a PIM in and you're like, hmm, we need to build it, test it, there's hypercare, this is going to be nine to 12 months of doing this and rolling it out in a phased approach because we can't do a big bang approach to this.
(26:35):
It needs to be considered and there needs to be a rollout plan and a rollback plan and doing that properly, like, takes you into change management for a business that scaled and grew so quickly and such a, probably an unconventional way without a conventional tech team and things like that.
Then you bring that in and it's like, no, we need to do this properly.
It was a massive learning curve for me because I hadn't been involved in anything like that.
(26:57):
Now I speak to people all the time and I speak to other businesses and they're like, did you guys build that on Airtable?
We're thinking about building something on Airtable, and see a big shift into that low code, no code.
Yeah, it probably wasn't there a couple of years ago when I was screening massive PIMs to buy.
It sounds interesting that it wasn't actually the PIM that was needed, it's the product data.
It's the product data process and the governance around it before the PIM was not the solution.
(27:26):
It's the preparation for the PIM.
People in product 90 per cent of the time are not the problem but part of the solution, right?
It's the people in the process over the product.
We could have probably achieved a similar result with a couple of different products.
That buying the technology everyone sees as being the most important thing.
(27:48):
We need to buy the right bit of technology, but actually if you focus on the technology and don't think about the people in the process and actually do the right preparation, it would have failed.
It would have 100 per cent failed if they hadn't done that work around the people in process.
That is where it needed that level of engagement.
You could buy the best technology in the world, but if you don't engage the people properly, there's no chance.
(28:12):
And that's really common.
The technology is seen as the most important piece of the puzzle, but it's actually, sort out the rest and then pick the technology that fits best once it's sorted.
Yeah, somebody on the pointy end of that whole thing, I see it all the time.
ERPs, PIMs, you know, and even just the, let's say, standard key mistakes.
(28:36):
First is thinking that the technology is going to solve process problems or people problems that you already have.
The second one is, it's going to take six months.
The third one is big bang.
Oh, seeing as we're doing this, we may as well do this and this and this and we'll change our EPOs and, you know, everything else.
It's okay to think that way to a degree, as long as you don't keep on thinking that and then do the project that way.
(29:01):
I think, you know, everybody has to mature to come to the realisation that actually, you know, we got to sort out the people side of it, the process side of it.
What's the data?
You know, what do we need?
Where's the impact later on, et cetera, et cetera.
And then, okay, well, the tools that we have here in front of us, which of those are going to be able to help us move these things on?
(29:23):
So you put in all of this effort to sort out your product data, to bring people with you, to have your right data governance in there and then you've got your solution in.
Everything's wonderful.
What did that mean that you were then able to do?
And as a result of all of this effort, how did this then translate to, like, the fun stuff?
(29:47):
I think that's the bit that we've, as an e-comm team, had been, like, dreaming about for so long.
We kept getting told, we'll get this PIM and you won't have to like upload every product through a CSV anymore.
And you won't have to sit and do all this manual stuff.
Honestly, when I first started working with the e-comm team, and they won't mind me saying this because I said it to them when I first joined, I'm like, I sat in this tech product role for a couple of years before I moved fully into e-comm.
(30:14):
And from that, standing in my castle alone, like, working myself because I didn't have a team, didn't have anyone else doing front-end stuff with me, worked with external agencies and just sat as this kind of Matrix-fillery person, wasn't fully integrated into what the e-comm team were doing, even though we worked so closely.
And I got involved, I was like, I can't believe the manual processes and stuff that you guys are doing when you work with a tool as sharp as Shopify and as good as Shopify, still doing these manual CSVs to create products and using apps to do, you know, custom fields in the back end and uploading things.
(30:48):
And then we had multiple Shopify instances, different expansion stores, uploading CSVs into one, manipulating data in there, exporting them again, uploading them into another, you know, expansion store, exporting again, doing manual product price changes and stuff outside of that.
Like, I'm sitting going, oh, I need to, I need to do times 1.4, whatever for Euro and all, and manually doing all sorts of stuff.
(31:10):
And I'm like, my goodness.
And we started doing time series kind of trials of, like, okay, how long does it take you guys to create products?
What are you doing?
And why are you doing this?
And can we not automate pricing?
Can we, we ended up, we actually started using that AI pricing tool to help us with price changes and stuff that we'd previously have to sit and use Excel to decide.
Can we not automate that?
(31:31):
Can we not automatically sync products into Shopify from the PIM?
So now my team go through and would accept or decline product variant attributes and stuff based off of suggestions from the PIM.
So based on everything the PIM knows about that product, its length, its sleeve length, its neck shape, its colour, its fabric, its features.
Everything it will be, we think this should be the occasion metafield.
(31:54):
And we think that should be the category metafield.
And do you accept that?
And they go through and rather than manually typing out all of this stuff and putting it into a CSV and uploading it and all that, they just go, yes, yes, yes, yes, yes.
Because 99 per cent of the time it's correct.
They can go in and manipulate stuff if they want to.
But if almost all of that manual stuff is done for them just using logic, it's almost all done for them.
(32:14):
They get to go in and go, okay, sync live to all stores.
And then rather, they can then just go in and merchandise it, spend a bit of time merchandising it beautifully, not worrying about the price because they know the price is correct because they've checked it, the pricing was automated, they've went, yeah, pricing's cool.
They don't need to sit and go, did I multiply that correctly when I imported that price file?
That stuff and taking away the human error, did I put that HS code into that product correctly?
(32:38):
Was that the right HS code?
Was it the right tax code?
Was it the right, all of that stuff that people are, you know, will worry about and could have real impact.
We now, we've built and tested and tried this technology that can do it for us and we can go, yeah, cool.
Empower the teams to go, you can trust this, this can do half of the boring part of your job for you.
And then I can empower the team to spend a bit more time going,
go and do a bit of competitor research, go and figure out what's cool and what's going on just now.
(33:01):
Go and learn about Shopify.
Sit and play about with Shopify Flow.
Like, how can you automate rather than, I mean, again, not product-related but collection-related?
Everything was based off of tags, manual tagging.
Someone would tag something on Airtable, the team would have to export their table board, find the product handle, import the tags that way.
All that stuff and I'm like, but could we just automate that?
(33:23):
If that collection is always going to be full of dresses that are short, black and white and sparkly, let's make a Smart Collection, or let's make a Shopify Flow, or something to power that and getting them to think a little bit more about automation and efficiency and how do you make Shopify and how do you make your apps and stuff work harder for you.
Not everything needs to be hard.
(33:43):
Some things are hard, some things are hard, but not everything needs to be.
So take the boring, manual, repetitive tasks away and empower them to sit and go, I could use a tool to do this faster or I could do something really cool here, and if we do want to spend time and effort doing things, make it something that matters rather than something that a machine can do for you.
Absolutely.
And that is how you create an environment where you can end up with great video on the PLP.
(34:07):
Yes, exactly.
Spend time making sure that bicycle matches up to that bicycle.
Out of curiosity,
because it's an area
that I'm quite passionate about,
the trading side of things,
you know, so you came in as a marketer,
then you ended up doing
techie-type things
and I think you mentioned
(34:27):
that it's nearly, you know,
it's nearly the best,
I personally agree,
but it's kind of nearly the best way
to come at trading almost,
because you have to have
a commercial mindset
and a love for the customers
and an understanding
of what the customers want, et cetera.
But you also have to have the technical side of things to kind of, you know, like, the more hard reality - I've got X amount of stock left and I need to get rid of it, and what can I do in order to float that up somewhere?
(34:51):
Yeah, so how do you find the trading side of things?
Tell us a bit about that.
Yeah, I think trading when I started and when I moved from product to e-comm, that was the bit I was like, I don't really have trading background.
I've worked with good merchandisers and they've really helped me, but I can implement what the merchandisers want, but I didn't have that, what I thought was a trading mindset.
(35:14):
And I was like, I was a marketer for years, like, all I'm doing is marketing on the website, just seeing it as, like, onsite, onsite marketing, what I would have previously done through CRM campaigns and through, you know, Meta and Google and all these different things.
I can just do that on the website.
Like, I would always have put, you know, I'd be like, oh, I need the products that are converting really well, selling strongly, viral on social, like, the products that are getting loads of clicks and loads of engagement and beautiful imagery and stuff.
(35:40):
Let's prioritise them, make sure they've got good stock availability.
I would have done that probably in a slightly manual way for all of my CRM campaigns and email campaigns and stuff that I would send out and thinking about, you know, what ads and stuff I was going to put on different platforms and stuff.
I would have thought in that way, anyway.
And I was like, I've got tools here that I can implement, like Nosto, that I can put on a Shopify store.
(36:02):
I can feed it all that product data, and then I can just manipulate the algorithms to be like, okay, give me, when you're merchandising this page, I don't want to sit and pin...
And sometimes we did because there was times this product went crazy viral on social media or it's been seen on a celebrity or whatever,
let's pin that to the top so people see it.
But apart from that, I'm like, stuff with good availability that's got, you know, more than, it's got all the core sizes in stock.
(36:26):
And we did have to do a little bit of manipulation around stock availability because we might have, you know, might have 60 per cent of the stock pot available, but it's only in the very smallest and largest sizes and our core sizes and that size curve are out of stock.
So I had to say, you know, a product with good availability has these sizes in stock, or at least 60 per cent of sizes in stock, for example. It's converting well, it's getting loads of clicks, but maybe the clicks would be down a little bit versus conversion.
(36:52):
You'd have a really good click-and-conversion rate, and a product with really high clicks but not converting, probably not the best, but manipulate that algorithm and okay, a certain level of newness, like when was it launched?
I would rather probably show something that was launched in the last six weeks to 12 weeks based on seasonality rather than something that was launched maybe half a year ago, in a different season.
(37:15):
So I'll put newness up a little bit and manipulate those algorithms and even test them and automate as much as I could, because from a technical point of view and an efficiency point of view, that's what I want to do.
But use what traders and marketers and people who are commercially minded would know is the levers that we need to pull to sell the stock.
We ended up putting things in like seasonality.
(37:37):
So even if something had launched over a year ago, but it was a true summer product, we had good core availability of if it was converting really well.
We'd still push that because, o, it's a true Spring/Summer product,
let's boost that this season.
There were certain ones we would sit with the team on a Monday,
we'd get a trade report and we'd get reports in from buying of, like, what shapes and stuff are working well, what products are working well.
And we'd take insights from that every week and say, you know, we'd let the algorithms do their job.
(38:02):
We trust them.
We know that we've honed and tested these algorithms over the course of a couple of years we're working with this tool.
We know they work, but where can we then pull extra levers?
Midi dresses, for example, if we looked at our top 10 best-selling midi dresses, they were all square neckline.
So we're going, okay, let's boost products that have got the attribute square neckline within midi dresses and see if that boosted conversion rate of that category.
(38:24):
Lo and behold, it does.
What about maxi dresses?
Okay, the maxi dresses that have got the fishtail shape at the bottom, they do really well.
So boost fishtail within the maxi dress category.
But if someone's on a dresses category, for example, and they always shop mini dresses, let's demote maxi dresses and boost mini dresses a little bit and do those kind of slightly more manual tweaks, but things that, because we've got good product data...
(38:46):
Exactly.
Yeah, I was waiting for the product data punch at the end.
I was like, where's my fishtail dress, Goddammit?
We didn't put fishtail down.
Yeah, exactly.
But that kind of thing is like, that's where I think I was able to combine and go, okay, I know I've got a tool here that can do this, but that was important to me.
(39:08):
Like, have I got tools that can automate the workload?
Do they have, have we got the data flowing into the tool correctly?
Can we do what we want to do with it?
I would try and do as little manual stuff as possible.
Sometimes it's unavoidable and when you want to create the right experience, you have to sit and do it.
But we would tweak things on a kind of weekly basis, right?
Okay, that conversion rate of that categories went down a little bit.
Let's go in and make a tweak.
(39:29):
So we'd still do work on it.
We'd have merchandisers sitting there thinking, right?
Okay, it's getting a little bit, we're getting into transitional period here.
Let's boost brown, plum, purple, red, and remove any boosts that we had on butter yellow that was the colour of the season, because it's now going into autumn, and we'd do that kind of stuff.
But yeah, that was from me, the shift for me to be able to do trading and also balance trading with the kind of technical side of my job was having a team that were really commercially minded.
(39:56):
Really, I had people in my team who had done psychology and really understood consumer psychology, people who came from maybe more journalistic backgrounds and people who came from fashion backgrounds.
We would all come together, really brainstorm and go, okay, they'd be like, I want to do this and they'd come to me with the ideas.
I was never the one sitting there going, let's create an Office Dressing category.
I'm not thinking about that kind of side of trading.
(40:19):
They'd come to me with an idea like, it's Back to School season, let's do, like, On Campus, what people are wearing on campus when they're going back to uni and back to school, and let's do this collection and let's do a transitional collection.
I was never coming up with those ideas, but I'm like, okay, do you know how to do that in the best possible way?
Do you know how to do it in a fast way?
Do you know how to completely automate that to keep it manually, you know, keep it spinning and, like, remove workload from you or say, for example, I want to do, the team would come to me and say, I want to upsell more.
(40:46):
I'd say to them, right, we need to increase AOV.
We want to do more about upsells.
They'd be like, right, let's upsell this collection, let's upsell shoes, and let's upsell underwear.
They'd come to me with all these amazing trading ideas and I would do the kind of, okay, how do we implement that best through Shopify?
Will we use product metafields to put a complementary product on there and make sure that that product shows up on the PDP and the cart and the checkout?
(41:11):
How do we do checkout upsells best?
And that kind of thing, that was the bit I enjoyed was technically making it happen.
Yeah, I love that.
Very good.
Lauren, you're coming, you've come to the end of your run with Oh Polly.
What are you up to next?
I don't know.
I don't know.
I've got a couple of different opportunities I'm enjoying.
(41:34):
Yeah.
I am speaking to some really exciting brands about what they're doing, but also speaking to some agencies.
I think where I'm trying to position myself is, I've got brand-side knowledge, spending time at a high-growth brand that's scaled incredibly quickly, made some mistakes along the way, but also done some really cool stuff.
(41:56):
So hopefully I can help brands with potentially that stage of growth or want to reach that stage of growth and help them do things that I wish I had done, or wish I hadn't done, and help them with that, but also give that brand-side knowledge to tech partners.
I'm speaking to a couple of different SaaS companies and stuff just now about these amazing products that they're building, AI products and search-and-merge products and returns platforms and all these things, but giving them the, here's actually how you go to market and here's what brands want.
(42:26):
And if you were pitching me, this is what I would want to hear.
And these are the things that I actually care and consider.
And this is if I'm taking this to a board to get signed off, this is what you need to give me in helping with that side of things and trying to apply what I've learned over the past few years to consulting with other people.
That's where I'm at just now.
I'm going to dip my toes in a couple of different things.
(42:48):
That's brilliant.
It's got to be very, very excited to see where it goes, Lauren.
And we wish you all the best of luck with the next stage.
We missed so much, but we have to draw it to a conclusion, but I can't believe we even missed Oh Polly going into the US, for example.
We could have had, like, we could do, like, we could totally do, like, another hour on this.
(43:08):
But, like, the insight there was absolutely fantastic.
So I think anybody that's listened, like, if you didn't get, like, 10 take aways from that, then go back and listen again because there's at least 10 in there.
Absolutely.
Thanks so much, Lauren.
We'll talk to you soon.
Thanks, guys.
That was, that... Lauren feels like a person with the world at her feet.
(43:32):
I think, right now...
A lot of, loads and loads of experience.
Some incredible experience there.
A lot of hard-won experience, very obviously as well.
Obviously, still a lot of creativity, a lot of passion.
Yeah, but actually able to, like, do all of the things that people dream of, but understanding that you've got to build the basics first.
(43:53):
Yeah.
And this is the thing I found most interesting about that conversation with her, is that building that product architecture and having that quality of product data enables you to do so much.
It enables you to do it faster, more cost-effectively, and actually deliver a better customer experience.
And that's the bit that's most exciting about what she's talking about there.
(44:16):
And particularly now, like if you think about this in the age of AI, because we can't get away from it, actually having that level of product data in that good shape that you can then go and surface to whichever LLM is looking at it, can then enable that AI conversation.
(44:39):
Really exciting, but just goes to show the importance of putting a huge amount of effort.
And I'm sure there were, like, I'm sure it was horrific at some points, but getting all of that right, and then being able to utilise that to just make these great experiences for customers. Love it.
Yeah, it's an enormous competitive advantage.
(45:00):
You know, we were talking in other podcasts about, or other episodes about how the ability to identify what works well in a large collection of anything.
So we were talking about customers previously, but here we're talking about product.
If you want to know what's working and what's not working, you have to be able to classify, identify, categorise the product data that you have.
(45:22):
So being able to talk about things like, okay, if you, if we've got a square-necked midi dress that's doing well, we're going to promote square-necked midi dresses, requires you to know that these are square-necked midi dresses, which means that the product data has to be there in the first place in order to do it.
Otherwise you're flying blind.
And that needs to start at the factory.
Yeah.
Actually, it needs to start at an idea.
(45:44):
Start at the idea, probably.
Yeah, yeah.
Like what's going into it and then, yeah.
Yeah, there's a lot in there.
We didn't get to touch on a lot as well.
I suppose one of the advantages to a degree is that business Oh Polly does own the factories that it buys, that it uses.
So it's able to, it was able to implement this all throughout the chain.
(46:05):
There's no reason it shouldn't be implementable across most supply chains.
The other bit that she touched on really briefly was HS codes.
Yeah. Dirty word...
And they just make me want to cry because HS codes are so incredibly complicated for importation into the US.
With such an extremely delicate outcome in terms of, you know, you can go in, you can swing between going terribly wrong and not having a problem.
(46:34):
Yeah.
It's the difference between getting charged a couple of per cent as a tariff and 30 per cent plus, even higher.
So HS code accuracy can have a huge impact on, like, unit profitability.
Yeah.
So even something as small as that doesn't even impact merchandising, which is all the cool stuff that she was doing.
(46:56):
Yeah.
But also incredibly important because if you, you know, you can do all the cool stuff, you ship it off to America, then it gets slapped with a, effectively a penalty.
And then all of a sudden your business that was looking, your business case that then looked all, all profitable and handsome, suddenly looks all unprofitable and ugly...
I didn't know where I was going to go with that.
(47:17):
I was waiting for the outcome there now.
That was, that was wonderful.
I think we probably went way over time on the call itself.
We could have spoken to Lauren for so long.
We didn't even get on...
I think Lauren should come back.
Yeah, yeah.
Also missed, you know, did you know that Oh Polly started off, well, it started out on eBay as a charity set-up.
(47:37):
It was for a charity-funding, charitable activity in Cambodia.
Still donates a percentage of their profit every year to that.
Obviously it's moved along a lot since then, but you know, there's so many interesting stories there.
It's a great story, isn't it?
It's fantastic.
So yeah, I want to keep an eye on Oh Polly.
(47:58):
I want to keep an eye on what Lauren ends up doing, because I think it'll be wonderful.
Well, thanks very much, Gordon.
Thanks, Ger.
Take care.
You've been listening to Functional & Fabulous with Ger Keohane and Gordon Newman.
If you'd like to know more about the podcast, or about StudioForty9 and Omnichannel stories, please go to Functional & Fabulous. Our sound engineer was Elaine Smith, and the show was produced by Roger Overall.
This is Functional & Fabulous, the omnichannel podcast where we unbox tales of online retail and digital transformation.
In this episode, our guest takes an unconventional approach to ecommerce...
No one really should have been buying our stuff.
Ger asks a question for a 'friend'...
(00:21):
How do you sell glitzy dresses?
There is some bad language...
The other bit that she touched on really briefly was HS codes.
Yeah, dirty word.
There is some bad behaviour...
Maybe I should have checked in a little bit more on what I was actually allowed to do.
And there are some bad fashion choices...
Where's my fishtail dress, Goddammit?
(00:42):
This episode of Functional & Fabulous is brought to you with pride by StudioForty9, retail ecommerce experts, omnichannel growth consultants, and cut-through performance marketing specialists.
StudioForty9, where your digital retail success is built.
Hello and welcome to another episode of Functional & Fabulous.
(01:04):
If you've ever wondered what it looks like to take a fashion brand from one store on eBay to a £150 million global powerhouse, then you're going to love this one.
Lauren Nicole Muir joins us fresh from her five-year run at Oh Polly, where she helped steer one of the UK's fastest growing fashion brands through a complete ecommerce transformation.
From Magento to Shopify, from UK only to US-led, from manual merchandising to automated data-driven trading.
(01:31):
She's a part-marketer, part-technologist, part-trader, and somehow manages to make all three sound fun.
Based in Glasgow, Lauren has recently stepped back to work on research projects and to explore how brands can make ecommerce operations smarter, leaner, and a little more human.
Lauren, you're very welcome.
Thank you for the intro.
That was much better than I could have ever made up myself.
(01:52):
That was lovely.
You're very welcome, Lauren.
Let's start at the beginning.
Oh Polly went from selling on eBay to becoming a £150 million powerhouse.
When you look back at it, what do you think was the moment that the business truly leveled up?
So I got involved during the first COVID lockdown, which was quite weird.
(02:15):
And I always said for years, my first few years of working there, I'm like, I've never had a normal trading environment.
Like, I kind of wish I had been there before COVID and could have had something to compare it to.
But as I joined, the business had just launched a sister brand in activewear, which was just fantastic timing.
It's almost like they knew that there was going to be, like, a global pandemic where people maybe wouldn't want, like, glittery mini dresses and stuff for a little while.
(02:41):
So thankfully we launched Bo+Tee and I joined actually in digital marketing at the time.
That was my background.
I'd been agency-side for digital while I was at uni, graduated in the middle of COVID lockdown and started straight away at Oh Polly.
And I think my first couple of days and weeks there, I was like, this is, you know, this is crazy.
Like, we're in lockdown.
How do we respond to this crazy shift in demand, where people are not going out?
(03:05):
We don't know when we'll ever be able to go out again.
And it was really crazy.
But actually seeing what was at the time, a kind of skeleton team come together and work to be like, right, we're trying to sell something here for our big brand that is our named brand everyone knows and loves.
We're trying to sell something that no one needs right now.
How do we do that?
And how do we make it fun?
And we would have daily stand-ups and creative calls and stuff where we'd be like, what can we do today?
(03:30):
And it was just everyone from every different level of the business, every different part of the business would get involved in, like, whatever crazy ideas we could do to achieve growth in the most uncertain trading circumstances.
And we did, we had, like, 100 per cent year-on-year growth in a year where no one really should have been buying our stuff. Which was, it was pretty cool.
(03:51):
And I know that was testament to the kind of creativity of the teams that all came together and worked.
And also the business for knowing, like, we can pivot massively into activewear and things that people really did buy into at that point in time.
And I think, as we started to shift in and out of lockdowns and things were going up and down and stuff, I realised, like, oh look, we've got something pretty special here.
(04:12):
So yeah, massive, massive growth in a time when I don't think any of us really expected it.
That was pretty cool.
How do you sell glitzy dresses, glamour dresses during COVID, out of curiosity?
Interestingly, at the time I was actually doing, so I was in digital marketing, email, CRM, kind of all of our automated emails and, you know, marketing-related emails and launches and promos and stuff.
(04:36):
But also we didn't actually have, like, a core marketing function at that point in time.
So myself and one of the other guys who I worked with, and worked closely with our merchandising teams, I think that's where the trading side comes in for me, I love it.
We would decide what the Black Friday promos and stuff were going to be to say, do we, you know, it's COVID, everyone's locked up, like, no one's out, nothing's open.
Will we just do, like, a fun giveaway?
(04:58):
Will we do a fun promo?
Will we say, oh, for the next hour, you get 25 per cent off everything on the app, go or the first hundred people to do this, get this and made it this, like, kind of gamified a little bit.
And I was actually doing the social media at the time for Instagram, sorry, not Instagram, but Facebook and Twitter.
Which we at the time were quite big - like, during Love Island, and we would live-tweet during Love Island at night and stuff.
(05:24):
And one of my favourite things, I'd be sitting, like, watching the TV with my friends and my boyfriend, and I'd be, like, sitting on the brand's Twitter account, like, rapidly tweeting like, oh, okay, if, you know, if this person gets booted off tonight, we'll give away 20 free dresses.
You need to tell us who your favourite person is or - it's so different to what the Oh Polly brand is now.
But at the time we would do anything to get that engagement and get people excited and give people something.
(05:47):
Oh, you've been locked in the house for the last, like, four weeks, but we're going to do something fun.
And we would get crazy engagement on Twitter and I'd be sitting there...
I think there was, like, a Casa Amor one year and it was really crazy and there was loads of drama.
And I'm like, right, for every kiss in Casa Amor tonight, I'll give away a dress for someone who tweets us a picture of them in an Oh Polly dress or whatever.
And I probably should have, maybe I should have checked in a little bit more on, like, what I was actually allowed to do, because I was probably giving away more dresses than I potentially should.
(06:13):
But the community that we created and stuff was, like, insane.
The messages and stuff that we would get, like, the hype that we'd created, people would be tweeting me going, Oh Polly admin, like, I'm waiting for the next hour, like, for you to start live-tweeting Love Island.
I'm so excited.
And I would sit there, like, this wasn't ever meant to be my job or what I was meant to do, but it was so fun.
And we'd do giveaways and we'd be like, right, go on the website and find this hidden code and things like that and just get people excited and engaged.
(06:41):
And yeah, use promos to do what we needed to do at that point in time.
Now the brand's in a totally different position, much more kind of premium, definitely not as promo-led.
Because I changed the product offering a little bit
and probably we don't really do that kind of social engagement stuff that we did at the time.
But during COVID, during that environment, it was, like, amazing working for a brand that was so agile and so up for testing and trialing anything. Because we could have said any idea,
(07:08):
we could have been like, I think this would be really cool.
Like, will we try it? And we'd have got a yes.
Give it a go.
And if it works, it works.
If it doesn't, no harm done.
It's so fun.
It's interesting that you're talking, you're kind of contrasting, let's say that period with how the brand has grown, et cetera.
But I guess there's a good argument that could be made that the traces and the muscle memory is still there, because obviously we all know that Oh Polly melted the internet, at least the LinkedIn end of the internet, with your new approaches to product listing pages not so long ago.
(07:39):
So you guys are still very much agile and up for experimentation, I guess, right?
One hundred per cent.
It's always been something that's so fun.
And when I was lucky enough to kind of take over the e-comm function, I tried to instill in the team, like, there is no idea that is too crazy.
There is no idea that is not going to get some sort of response, nothing that we would absolutely never try.
(08:01):
Like, give it a go.
You know, raise ideas and give suggestions.
When I got a message one day, hey, we've went out to a beach in LA and shot all this content and actually the videos engage with each other and we don't want to just use them on social.
We want to try and use them on the website.
How do we do it?
How can we make it work?
We were like, interesting.
Never tried it before.
And actually, it was interesting to get the more technical and e-comm teams and the people involved in merchandising and the website to engage directly with the video creative and content teams to be like, right, this is how you would need to kind of shoot this.
(08:33):
This is the types of content.
So for example, to make something work on mobile and desktop.
Okay, what kind of videos do we want?
How do we want to do that?
Where would we merchandise it?
Merchandise position one and two, and getting that communication going.
And I ended up making like Canva animated presentations to show people what merchandising would look like.
And if it looks like this on mobile, this is what it looks like on desktop.
(08:54):
Are you happy to, you know, if we just test this on mobile to start with, and where the brand was 92 per cent mobile traffic, like we prioritised mobile 100 per cent. And working with them to go, oh, how do we optimise the video and make sure the video is, like, super-fast and the experience is great for the customer.
It was a really fun project and the response we got was, it was so fun and it validated that, like, you know, you just do something that's a bit different and it gets people talking and gets people thinking rather than just the standard,
(09:22):
let's get a launch up.
Let's pick the nicest image to put on the front.
Like, actually do something a bit different and get people talking and visiting the website and thinking about, oh, they're actually really cool.
And the amount that we invest in creative and content, it deserves to be spoken about and the teams behind it are fantastic.
So it was nice to see them get the recognition.
Yeah, it was such a kind of a... it tickled a funny bone, I think, in people, like, because it was so lovely.
(09:48):
It was so pleasurable to watch.
Obviously, you know, these are beautiful photographs on, you know, Santa Monica Pier and the clothes look great and the models look great.
And then there's this really lovely interaction between the images, you know, the ice cream bowl and the ice cream ball dropping into the, dropping from the sky. Or the bikes that are moving between each other.
(10:09):
You know, I think, I don't know, it's one of those times where it just landed so incredibly well.
You don't often see, like, innovation on the PLP.
On the PLP, no, not at all.
It's like, you'll see plenty on a product detail page.
And you'll see, but people don't really try new stuff on a PLP.
The PLP is just, like, really functional.
So to see something really beautiful on a PLP was probably why it broke LinkedIn.
(10:34):
But one of the things I think is really interesting, though, Lauren, is that, like, Oh Polly has, like, a vast amount of SKUs and it moves really, really quickly.
So, like, you've gone through your period of unbridled creativity during COVID.
And then you're in this period of growth now where people are starting to go out and people are starting to buy sparkly dresses again.
(11:00):
And it's transformed over that five-year period into this huge business.
But that must've come with, like, loads of operational challenges.
Like you mentioned there, you were skeleton staff during COVID.
And then into this period of spectacular growth and moving into an organisation that's doing a lot more.
(11:24):
So maybe it'd be good to talk a little bit about some of the things that were involved there.
And one of the things that, it's a very long-winded question, sorry.
But one of the conversations that we always have, and particularly with brand owners and retailers here in Ireland, is like, what is actually involved in, like, the operational admin of that many SKUs?
(11:47):
And like, how do you even deal with that?
Oh, it's funny because my background was marketing.
When I first started to get a bit more involved in, like, the technical side of things, it was probably more related to, like, product catalogues and things like that.
And we onboarded a couple of different pieces of tech onto Shopify, like Algolia and Nosto and, like, these kind of front-end solutions and stuff.
(12:10):
And at the time, I definitely, because I come from more of a digital background, definitely wasn't actually thinking about product data whatsoever.
I was thinking about the products, that they looked really cool and shiny and sexy on the front end.
And like, oh, they look really nice and I can sell them.
And I probably had a lack of appreciation for what goes on in the back end, in the back office, and how much you need to invest to make that run smoothly, especially when it comes to a time like Black Friday or something where we could, I mean, like, crazy days and crazy volumes of orders and stuff, to the point where we're having to have meetings.
(12:46):
Like, do we need to switch this off?
Because like, can we handle the volume of orders that are going through the warehouse or, you know, and that's the bit that excites me.
Like I enjoy it, but I don't actually think until probably the last two-ish years, two or three years, I really appreciated and understood, like, oh my God, there is so much that holds us up.
Like, it underpins all of the kind of sexy stuff that I'm trying to do on the front end.
(13:07):
And I've been lucky to work with an amazing technical team that we've built at Oh Polly over the past year, who are very much, like, operational.
They've all come from retail background, massive retail powerhouses.
And they really help us, like, help me understand things that potentially I should have known, and if I'd known maybe three, four years ago,
it would have been great to get those foundations in earlier in the stage of growth.
(13:30):
But I have this conversation all the time.
We grew at such a pace that there's things that, you know, when you hit that like nine-figure mark, you go, I wish I'd done this before because it's really complex now.
It's like a 7,000-strong catalogue.
But did we know a couple of years ago that it was going to go this crazy?
Like, would we have been aware of that?
Would we have, was that what we were prioritising, or were we just like, go, go, go, do whatever you can to get out of COVID, and growth?
(13:52):
So there's been a lot of challenges, I would say, in terms of really complex catalogue, really complex migrations.
Like, Gerard, you kind of mentioned this at the start.
Like, when I joined Oh Polly, we were on Magento 1.
The first year, and a bit of me working there, Oh Polly was migrating from Magento 1 to Magento 2.
(14:13):
We launched Bo+Tee on Shopify.
I was lucky enough to get the Bo+Tee brand as kind of my baby when I joined the business during that time.
And it was amazing stage of growth, but also one of the most amazing things was that it was on Shopify.
And I was so empowered and so enabled to do things quicker, faster.
We integrated tech seamlessly, quickly, sometimes without development, sometimes with development.
(14:35):
And when it was with development, it was still easier.
And we, I think about three months after we migrated Oh Polly to M2, switched everything to Shopify.
And in hindsight, you would look back and go, I wish we'd always been on Shopify, but you just don't know. Like, the world of tech evolves so quickly.
And there's so many new innovations and stuff like that, that I think it's hard to plan ahead.
People ask me, I got asked last year on a talk, what's your three-year roadmap?
(14:59):
And I was like, you're crazy.
I've got like a three-month roadmap at best.
Because things change so quickly, and trying to think where Oh Polly would be in three years' time, versus what tech would be available, versus what kind of work we have to do to get there and stuff.
I think it's quite difficult when things move at such pace.
Yeah, yeah.
I think about, like, one of the things we get asked quite a lot is where businesses want to future-proof their business from a tech point of view.
(15:25):
And it's almost impossible to answer.
It's like, how are you going to future-proof in tech?
You'd be lucky to make a good decision for the next two years.
And that's about, you know, like...
And so my answer to that question is always, well, what do you think you are definitely going to do in the next two years?
And then, will this piece of tech allow you to do that within the next two years, or not?
(15:45):
Because that's really the priority, you know.
Yeah, those were interesting times, that whole Magento and the Shopify and all the rest of it.
From, let's say, an operations point of view, you know, obviously from, with production for products and that side of things, what do you know now, do you think, about trading a catalogue with respect to, let's say, the product data that you need versus what, you know, what you didn't know, let's say, two or three years back?
(16:17):
I think, for me, from a kind of trading point of view, we probably, a couple of years ago, we were doing a lot of manual merchandising.
And if it wasn't manual, it was fairly manual and based off of, like, tags and stuff like that, which now I... again, going back to investing in technology, you know, would tell my team a million times over, and say the same to anyone, I wouldn't invest in any technology that involves manual workload.
(16:44):
There's no point in buying technology to me and spending,
I mean, at some, like, enterprise level, six figures, on technology where you're still going to have to sit and manipulate it and work really hard.
Like, please make the technology work harder for you.
So, for example, using AI,
I would no longer spend my money on a tool
that is not harnessing AI to some degree,
because if you're going to take on a year's contract
or a two-year contract
(17:06):
with something that can't take your product catalogue
and take all of that data
and use AI or something to enhance it
and make it better and to do some of the hard work for you,
then you're going to be left behind.
Because in a couple of years,
your competitors are all going to be
automating that manual workload,
letting AI do the hard stuff
and then focusing their actual skilled team members
(17:26):
on doing the stuff that's really exciting.
Going back to that, like, creativity and actually, like, thinking, and thinking what is going to make a big shift here?
Like, what's going to be something really cool and different?
I don't want my team sitting there going, oh, well, if someone, we know someone likes black dresses and we put them in a black dress segment, let's boost black dresses, that kind of stuff.
It needs to be like AI automatic personalisation,
(17:49):
make it quick and punchy and let it,
I'm not saying just let it sit and do its job,
keep monitoring it obviously
and testing and evolving and optimising,
but I would hate the thought of my team
having to sit there, like, doing all this manual workload
and sitting and setting,
using a search tool
where you have to sit and manually set synonyms
in the back end.
Like, if someone searches nightdress, they may also mean pyjamas, and get a tool that's really, really great,
(18:14):
uses AI, uses the most upcoming technology possible, has got a really cool roadmap that they're happy to share with you and tell you what's coming for the next year or two.
But also there is no point in buying that tool if your product data and what underpins it in the back end is awful because then you're going to go, oh, the AI doesn't work.
And it's like, well, actually, you didn't use any of the product attributes you're meant to use.
(18:36):
You didn't use metafields properly.
You're not enhancing all of your product data in the right way.
We were lucky, our team were really on the ball with the kind of front-end sexy-sided product data.
So all of our products have got every different possible attribute they could want.
We were pretty quick getting involved with native Shopify metafields and all these different things that we're now, we now know we're going to need AI and LLMs to be able to read nicely through Shopify to make ourselves discoverable.
(19:02):
So we're lucky that we did that.
I think the bit that I probably didn't appreciate quite as much, I got the front-end stuff.
I'm like, yeah, I need to know that the dress is like black, sleeveless, ruffled, all these things that make trading really cool on the front end.
But again, the bit that I didn't appreciate because my background was more marketing digital was the operational side of product data.
(19:23):
The stuff that actually... there is no point in me doing all this on the front end and giving everyone AI-personalised shopping experiences on site and doing all this digital transformation, if actually the HS codes are in a mess,
nothing's got a country of origin,
the fabric composition isn't there,
all of these things. Which someone who is not operational, or was never operational, doesn't really appreciate or understand.
(19:44):
So yeah, we had to go on a learning curve with product data massively and going through that, oh, we're getting to this really large SKU catalogue size and really growing up in scale and making all this money.
Do we need a PIM in making those kinds of decisions?
When you've got years of migrated product data, products that have been on eBay and Magento and Shopify and Airtable for years and stuff, and how do you harness that and make that make sense?
(20:11):
That was the bit that was actually, I'm like, oh, our product data's fine.
No one's product data is fine.
You need to do a lot of work on product data to make it classified as fine.
So yeah, those kind of operational bits are, they're the tough ones.
They're the really hard ones.
You can make sexy through Shopify and stuff, but the stuff outside of Shopify.
(20:32):
It's really, you know, there's definitely a kind of, so many different elements, like business elements come in.
There's this kind of concept of fortune favours the prepared, you know, there's elements like, you're lucky because you were kind of, you were almost thinking about it.
You didn't realise you were being lucky at the time, but you're lucky because you were being prepared and you were doing things like that.
(20:56):
But there's also then the point where you, you really have to make a decision and sometimes the decisions that are, the options that are available to you.
Let's say you mentioned a PIM, for example.
I presume you guys went through a bunch of PIMs or made some, maybe not correct decisions and then ended up on something that, that basically you eventually realised was, this is what we need as a minimum thing that will do what we need it to do and work from there.
(21:22):
You know, I guess that, is that kind of process that you go through?
Yeah.
You know, people keep telling us, you need a PIM.
You need a PIM.
You need to standardise product data.
You need to add some data governance, you know, and when you get a PIM, every other system will work better and they'll integrate better and everything.
And we were like, right, okay, it turns out we need a PIM.
But I think we went to go out and buy, like, an enterprise PIM and get that all on board, and then had the stark reality when we actually spoke to people who were very good at that kind of side of things.
(21:54):
At the time, there was literally, our tech team at Oh Polly, I think it was me doing all the kind of front end and development and Shopify side of things.
An IT guy and a consultant, like an external consultant, we didn't have a tech team.
So actually having, we had someone come in to kind of manage the tech team.
He was like, this, you know, this team's tiny, like we need help.
We need a PIM.
We need to buy all this technology.
We've got this huge roadmap of stuff we need to do.
(22:15):
And we very quickly realised, you know, we've got a lot of foundational things that we need to fix here,
product data being one of them, before we can go out and spend enterprise-level money on technology to fix the problem.
Like, at the time, like, if you put something low-quality into a machine, it's not going to churn out anything of any great quality, and sometimes I think we maybe thought we were putting a plaster over the problem by being like, oh yeah, we can just buy a PIM and everything will be fine.
(22:42):
And actually there was so much that needed to be solved before we could put data into a PIM, needed to do a huge data cleanse exercise.
And then it kind of turned out, actually, is that PIM what we need?
We had a business who was basically,
we were basically built on Airtable
and so much of the business was,
you know, powered through Airtable,
from marketing to operations
to influencers, collaborations,
(23:03):
product data, production planning,
everything was through Airtable
and the decision ended up
being to build our own PIM
through Airtable.
Which, I saw that come to life
a couple of months ago,
and it was fascinating.
Like, how much is possible through Airtable, which I always saw as being, like, a marketing planning system, because that's what I used it for, planning marketing campaigns.
(23:23):
And I'm like, how are we now powering everything from our factories from the minute a product becomes an idea in someone's head and may become a sample?
It goes through to factory teams
to put in all of the data
completely governed correctly,
and the exact correct types of data
flows through to the next person to say,
Okay, well these are the quantities we need,
and these are all the different
fabric options and colour options,
(23:44):
and the sizes and the stock units.
And okay, now we need a copywriter,
and then now we need e-comm to enrich it
and then by the time
it gets to me and my team,
I'm like, whoa,
this is, like, completely clean,
incredible product data
with automated HS codes
and all of these things
that at the time,
it was a huge investment,
a huge project for the tech team,
but it will change,
change the business.
(24:04):
It's just incredible.
I presume not only, because we have seen this sort of rollout, we'll say, and I guess it was the same in Oh Polly, like, it's not just the tech team, you know, there is change management that has to be dealt with throughout the business.
Can you reflect on that a bit?
Like, what was that like to have to, you know, work through all of those things?
I think that was probably the biggest challenge because people have, people have gotten used to what they do.
(24:30):
And I think sometimes until you disrupt that and say like, no, we need to make change here, people potentially don't see the issue in what they're doing.
We knew because we could feel the effect sometimes of some of the operational issues.
You know, the ops team coming to us saying, I've got all these things stuck at Customs, what's going on?
We're missing product data or whatever.
I could feel those kind of issues, but I think sometimes people further back in the production cycle, maybe at the buying stage or in the factory stage, don't ever feel those issues.
(24:58):
They do their bit and everyone kind of does their bits in silos.
And actually what the tech team had to do was map out the process start to finish.
Here is where you sit and here is how much you impact someone else.
And here's what happens if you put this data in incorrectly.
And because we're run on Airtable, for example, there was times where someone, like, 20 stages back in a process would make one change and it would break something on the front end of the website that I had implemented because it was all managed through Airtable and there was absolutely no governance.
(25:23):
And it would take someone from customer service coming to me saying, this product says it was restocking three weeks ago, but it's not due in for four weeks.
And I'm like, oh, like, that kind of thing.
There was so much, so many data things that we had to go back to the drawing board, really go to the business and the BAs and the PMs and the tech team at Oh Polly absolutely smashed this out of the park.
They ran workshops.
They had whiteboard sessions.
(25:44):
They sat there like, this is you, like, this is your impact.
This is what we're trying to achieve.
This is what I need from you.
You need to come on this journey with me.
And honestly, it seemed like a bigger thing.
I think such a huge thing at the time that I was like, we might have bitten off more than we can chew here.
We're never going to be able to change this business and do this change management and transformation.
And actually they did.
(26:05):
And when it went live and we're still, they're still in phase one of the PIM.
There's phase two rollout still to come, which will just be a game changer.
Some of the things that are in that, I'm like, how did we even think of this?
Like, but it's a big, big thing for the full business.
And I think also getting people to buy into a long-term project like that.
Everyone thinks, oh, you can get a PIM and put a PIM in and you're like, hmm, we need to build it, test it, there's hypercare, this is going to be nine to 12 months of doing this and rolling it out in a phased approach because we can't do a big bang approach to this.
(26:35):
It needs to be considered and there needs to be a rollout plan and a rollback plan and doing that properly, like, takes you into change management for a business that scaled and grew so quickly and such a, probably an unconventional way without a conventional tech team and things like that.
Then you bring that in and it's like, no, we need to do this properly.
It was a massive learning curve for me because I hadn't been involved in anything like that.
(26:57):
Now I speak to people all the time and I speak to other businesses and they're like, did you guys build that on Airtable?
We're thinking about building something on Airtable, and see a big shift into that low code, no code.
Yeah, it probably wasn't there a couple of years ago when I was screening massive PIMs to buy.
It sounds interesting that it wasn't actually the PIM that was needed, it's the product data.
It's the product data process and the governance around it before the PIM was not the solution.
(27:26):
It's the preparation for the PIM.
People in product 90 per cent of the time are not the problem but part of the solution, right?
It's the people in the process over the product.
We could have probably achieved a similar result with a couple of different products.
That buying the technology everyone sees as being the most important thing.
(27:48):
We need to buy the right bit of technology, but actually if you focus on the technology and don't think about the people in the process and actually do the right preparation, it would have failed.
It would have 100 per cent failed if they hadn't done that work around the people in process.
That is where it needed that level of engagement.
You could buy the best technology in the world, but if you don't engage the people properly, there's no chance.
(28:12):
And that's really common.
The technology is seen as the most important piece of the puzzle, but it's actually, sort out the rest and then pick the technology that fits best once it's sorted.
Yeah, somebody on the pointy end of that whole thing, I see it all the time.
ERPs, PIMs, you know, and even just the, let's say, standard key mistakes.
(28:36):
First is thinking that the technology is going to solve process problems or people problems that you already have.
The second one is, it's going to take six months.
The third one is big bang.
Oh, seeing as we're doing this, we may as well do this and this and this and we'll change our EPOs and, you know, everything else.
It's okay to think that way to a degree, as long as you don't keep on thinking that and then do the project that way.
(29:01):
I think, you know, everybody has to mature to come to the realisation that actually, you know, we got to sort out the people side of it, the process side of it.
What's the data?
You know, what do we need?
Where's the impact later on, et cetera, et cetera.
And then, okay, well, the tools that we have here in front of us, which of those are going to be able to help us move these things on?
(29:23):
So you put in all of this effort to sort out your product data, to bring people with you, to have your right data governance in there and then you've got your solution in.
Everything's wonderful.
What did that mean that you were then able to do?
And as a result of all of this effort, how did this then translate to, like, the fun stuff?
(29:47):
I think that's the bit that we've, as an e-comm team, had been, like, dreaming about for so long.
We kept getting told, we'll get this PIM and you won't have to like upload every product through a CSV anymore.
And you won't have to sit and do all this manual stuff.
Honestly, when I first started working with the e-comm team, and they won't mind me saying this because I said it to them when I first joined, I'm like, I sat in this tech product role for a couple of years before I moved fully into e-comm.
(30:14):
And from that, standing in my castle alone, like, working myself because I didn't have a team, didn't have anyone else doing front-end stuff with me, worked with external agencies and just sat as this kind of Matrix-fillery person, wasn't fully integrated into what the e-comm team were doing, even though we worked so closely.
And I got involved, I was like, I can't believe the manual processes and stuff that you guys are doing when you work with a tool as sharp as Shopify and as good as Shopify, still doing these manual CSVs to create products and using apps to do, you know, custom fields in the back end and uploading things.
(30:48):
And then we had multiple Shopify instances, different expansion stores, uploading CSVs into one, manipulating data in there, exporting them again, uploading them into another, you know, expansion store, exporting again, doing manual product price changes and stuff outside of that.
Like, I'm sitting going, oh, I need to, I need to do times 1.4, whatever for Euro and all, and manually doing all sorts of stuff.
(31:10):
And I'm like, my goodness.
And we started doing time series kind of trials of, like, okay, how long does it take you guys to create products?
What are you doing?
And why are you doing this?
And can we not automate pricing?
Can we, we ended up, we actually started using that AI pricing tool to help us with price changes and stuff that we'd previously have to sit and use Excel to decide.
Can we not automate that?
(31:31):
Can we not automatically sync products into Shopify from the PIM?
So now my team go through and would accept or decline product variant attributes and stuff based off of suggestions from the PIM.
So based on everything the PIM knows about that product, its length, its sleeve length, its neck shape, its colour, its fabric, its features.
Everything it will be, we think this should be the occasion metafield.
(31:54):
And we think that should be the category metafield.
And do you accept that?
And they go through and rather than manually typing out all of this stuff and putting it into a CSV and uploading it and all that, they just go, yes, yes, yes, yes, yes.
Because 99 per cent of the time it's correct.
They can go in and manipulate stuff if they want to.
But if almost all of that manual stuff is done for them just using logic, it's almost all done for them.
(32:14):
They get to go in and go, okay, sync live to all stores.
And then rather, they can then just go in and merchandise it, spend a bit of time merchandising it beautifully, not worrying about the price because they know the price is correct because they've checked it, the pricing was automated, they've went, yeah, pricing's cool.
They don't need to sit and go, did I multiply that correctly when I imported that price file?
That stuff and taking away the human error, did I put that HS code into that product correctly?
(32:38):
Was that the right HS code?
Was it the right tax code?
Was it the right, all of that stuff that people are, you know, will worry about and could have real impact.
We now, we've built and tested and tried this technology that can do it for us and we can go, yeah, cool.
Empower the teams to go, you can trust this, this can do half of the boring part of your job for you.
And then I can empower the team to spend a bit more time going,
go and do a bit of competitor research, go and figure out what's cool and what's going on just now.
(33:01):
Go and learn about Shopify.
Sit and play about with Shopify Flow.
Like, how can you automate rather than, I mean, again, not product-related but collection-related?
Everything was based off of tags, manual tagging.
Someone would tag something on Airtable, the team would have to export their table board, find the product handle, import the tags that way.
All that stuff and I'm like, but could we just automate that?
(33:23):
If that collection is always going to be full of dresses that are short, black and white and sparkly, let's make a Smart Collection, or let's make a Shopify Flow, or something to power that and getting them to think a little bit more about automation and efficiency and how do you make Shopify and how do you make your apps and stuff work harder for you.
Not everything needs to be hard.
(33:43):
Some things are hard, some things are hard, but not everything needs to be.
So take the boring, manual, repetitive tasks away and empower them to sit and go, I could use a tool to do this faster or I could do something really cool here, and if we do want to spend time and effort doing things, make it something that matters rather than something that a machine can do for you.
Absolutely.
And that is how you create an environment where you can end up with great video on the PLP.
(34:07):
Yes, exactly.
Spend time making sure that bicycle matches up to that bicycle.
Out of curiosity,
because it's an area
that I'm quite passionate about,
the trading side of things,
you know, so you came in as a marketer,
then you ended up doing
techie-type things
and I think you mentioned
(34:27):
that it's nearly, you know,
it's nearly the best,
I personally agree,
but it's kind of nearly the best way
to come at trading almost,
because you have to have
a commercial mindset
and a love for the customers
and an understanding
of what the customers want, et cetera.
But you also have to have the technical side of things to kind of, you know, like, the more hard reality - I've got X amount of stock left and I need to get rid of it, and what can I do in order to float that up somewhere?
(34:51):
Yeah, so how do you find the trading side of things?
Tell us a bit about that.
Yeah, I think trading when I started and when I moved from product to e-comm, that was the bit I was like, I don't really have trading background.
I've worked with good merchandisers and they've really helped me, but I can implement what the merchandisers want, but I didn't have that, what I thought was a trading mindset.
(35:14):
And I was like, I was a marketer for years, like, all I'm doing is marketing on the website, just seeing it as, like, onsite, onsite marketing, what I would have previously done through CRM campaigns and through, you know, Meta and Google and all these different things.
I can just do that on the website.
Like, I would always have put, you know, I'd be like, oh, I need the products that are converting really well, selling strongly, viral on social, like, the products that are getting loads of clicks and loads of engagement and beautiful imagery and stuff.
(35:40):
Let's prioritise them, make sure they've got good stock availability.
I would have done that probably in a slightly manual way for all of my CRM campaigns and email campaigns and stuff that I would send out and thinking about, you know, what ads and stuff I was going to put on different platforms and stuff.
I would have thought in that way, anyway.
And I was like, I've got tools here that I can implement, like Nosto, that I can put on a Shopify store.
(36:02):
I can feed it all that product data, and then I can just manipulate the algorithms to be like, okay, give me, when you're merchandising this page, I don't want to sit and pin...
And sometimes we did because there was times this product went crazy viral on social media or it's been seen on a celebrity or whatever,
let's pin that to the top so people see it.
But apart from that, I'm like, stuff with good availability that's got, you know, more than, it's got all the core sizes in stock.
(36:26):
And we did have to do a little bit of manipulation around stock availability because we might have, you know, might have 60 per cent of the stock pot available, but it's only in the very smallest and largest sizes and our core sizes and that size curve are out of stock.
So I had to say, you know, a product with good availability has these sizes in stock, or at least 60 per cent of sizes in stock, for example. It's converting well, it's getting loads of clicks, but maybe the clicks would be down a little bit versus conversion.
(36:52):
You'd have a really good click-and-conversion rate, and a product with really high clicks but not converting, probably not the best, but manipulate that algorithm and okay, a certain level of newness, like when was it launched?
I would rather probably show something that was launched in the last six weeks to 12 weeks based on seasonality rather than something that was launched maybe half a year ago, in a different season.
(37:15):
So I'll put newness up a little bit and manipulate those algorithms and even test them and automate as much as I could, because from a technical point of view and an efficiency point of view, that's what I want to do.
But use what traders and marketers and people who are commercially minded would know is the levers that we need to pull to sell the stock.
We ended up putting things in like seasonality.
(37:37):
So even if something had launched over a year ago, but it was a true summer product, we had good core availability of if it was converting really well.
We'd still push that because, o, it's a true Spring/Summer product,
let's boost that this season.
There were certain ones we would sit with the team on a Monday,
we'd get a trade report and we'd get reports in from buying of, like, what shapes and stuff are working well, what products are working well.
And we'd take insights from that every week and say, you know, we'd let the algorithms do their job.
(38:02):
We trust them.
We know that we've honed and tested these algorithms over the course of a couple of years we're working with this tool.
We know they work, but where can we then pull extra levers?
Midi dresses, for example, if we looked at our top 10 best-selling midi dresses, they were all square neckline.
So we're going, okay, let's boost products that have got the attribute square neckline within midi dresses and see if that boosted conversion rate of that category.
(38:24):
Lo and behold, it does.
What about maxi dresses?
Okay, the maxi dresses that have got the fishtail shape at the bottom, they do really well.
So boost fishtail within the maxi dress category.
But if someone's on a dresses category, for example, and they always shop mini dresses, let's demote maxi dresses and boost mini dresses a little bit and do those kind of slightly more manual tweaks, but things that, because we've got good product data...
(38:46):
Exactly.
Yeah, I was waiting for the product data punch at the end.
I was like, where's my fishtail dress, Goddammit?
We didn't put fishtail down.
Yeah, exactly.
But that kind of thing is like, that's where I think I was able to combine and go, okay, I know I've got a tool here that can do this, but that was important to me.
(39:08):
Like, have I got tools that can automate the workload?
Do they have, have we got the data flowing into the tool correctly?
Can we do what we want to do with it?
I would try and do as little manual stuff as possible.
Sometimes it's unavoidable and when you want to create the right experience, you have to sit and do it.
But we would tweak things on a kind of weekly basis, right?
Okay, that conversion rate of that categories went down a little bit.
Let's go in and make a tweak.
(39:29):
So we'd still do work on it.
We'd have merchandisers sitting there thinking, right?
Okay, it's getting a little bit, we're getting into transitional period here.
Let's boost brown, plum, purple, red, and remove any boosts that we had on butter yellow that was the colour of the season, because it's now going into autumn, and we'd do that kind of stuff.
But yeah, that was from me, the shift for me to be able to do trading and also balance trading with the kind of technical side of my job was having a team that were really commercially minded.
(39:56):
Really, I had people in my team who had done psychology and really understood consumer psychology, people who came from maybe more journalistic backgrounds and people who came from fashion backgrounds.
We would all come together, really brainstorm and go, okay, they'd be like, I want to do this and they'd come to me with the ideas.
I was never the one sitting there going, let's create an Office Dressing category.
I'm not thinking about that kind of side of trading.
(40:19):
They'd come to me with an idea like, it's Back to School season, let's do, like, On Campus, what people are wearing on campus when they're going back to uni and back to school, and let's do this collection and let's do a transitional collection.
I was never coming up with those ideas, but I'm like, okay, do you know how to do that in the best possible way?
Do you know how to do it in a fast way?
Do you know how to completely automate that to keep it manually, you know, keep it spinning and, like, remove workload from you or say, for example, I want to do, the team would come to me and say, I want to upsell more.
(40:46):
I'd say to them, right, we need to increase AOV.
We want to do more about upsells.
They'd be like, right, let's upsell this collection, let's upsell shoes, and let's upsell underwear.
They'd come to me with all these amazing trading ideas and I would do the kind of, okay, how do we implement that best through Shopify?
Will we use product metafields to put a complementary product on there and make sure that that product shows up on the PDP and the cart and the checkout?
(41:11):
How do we do checkout upsells best?
And that kind of thing, that was the bit I enjoyed was technically making it happen.
Yeah, I love that.
Very good.
Lauren, you're coming, you've come to the end of your run with Oh Polly.
What are you up to next?
I don't know.
I don't know.
I've got a couple of different opportunities I'm enjoying.
(41:34):
Yeah.
I am speaking to some really exciting brands about what they're doing, but also speaking to some agencies.
I think where I'm trying to position myself is, I've got brand-side knowledge, spending time at a high-growth brand that's scaled incredibly quickly, made some mistakes along the way, but also done some really cool stuff.
(41:56):
So hopefully I can help brands with potentially that stage of growth or want to reach that stage of growth and help them do things that I wish I had done, or wish I hadn't done, and help them with that, but also give that brand-side knowledge to tech partners.
I'm speaking to a couple of different SaaS companies and stuff just now about these amazing products that they're building, AI products and search-and-merge products and returns platforms and all these things, but giving them the, here's actually how you go to market and here's what brands want.
(42:26):
And if you were pitching me, this is what I would want to hear.
And these are the things that I actually care and consider.
And this is if I'm taking this to a board to get signed off, this is what you need to give me in helping with that side of things and trying to apply what I've learned over the past few years to consulting with other people.
That's where I'm at just now.
I'm going to dip my toes in a couple of different things.
(42:48):
That's brilliant.
It's got to be very, very excited to see where it goes, Lauren.
And we wish you all the best of luck with the next stage.
We missed so much, but we have to draw it to a conclusion, but I can't believe we even missed Oh Polly going into the US, for example.
We could have had, like, we could do, like, we could totally do, like, another hour on this.
(43:08):
But, like, the insight there was absolutely fantastic.
So I think anybody that's listened, like, if you didn't get, like, 10 take aways from that, then go back and listen again because there's at least 10 in there.
Absolutely.
Thanks so much, Lauren.
We'll talk to you soon.
Thanks, guys.
That was, that... Lauren feels like a person with the world at her feet.
(43:32):
I think, right now...
A lot of, loads and loads of experience.
Some incredible experience there.
A lot of hard-won experience, very obviously as well.
Obviously, still a lot of creativity, a lot of passion.
Yeah, but actually able to, like, do all of the things that people dream of, but understanding that you've got to build the basics first.
(43:53):
Yeah.
And this is the thing I found most interesting about that conversation with her, is that building that product architecture and having that quality of product data enables you to do so much.
It enables you to do it faster, more cost-effectively, and actually deliver a better customer experience.
And that's the bit that's most exciting about what she's talking about there.
(44:16):
And particularly now, like if you think about this in the age of AI, because we can't get away from it, actually having that level of product data in that good shape that you can then go and surface to whichever LLM is looking at it, can then enable that AI conversation.
(44:39):
Really exciting, but just goes to show the importance of putting a huge amount of effort.
And I'm sure there were, like, I'm sure it was horrific at some points, but getting all of that right, and then being able to utilise that to just make these great experiences for customers. Love it.
Yeah, it's an enormous competitive advantage.
(45:00):
You know, we were talking in other podcasts about, or other episodes about how the ability to identify what works well in a large collection of anything.
So we were talking about customers previously, but here we're talking about product.
If you want to know what's working and what's not working, you have to be able to classify, identify, categorise the product data that you have.
(45:22):
So being able to talk about things like, okay, if you, if we've got a square-necked midi dress that's doing well, we're going to promote square-necked midi dresses, requires you to know that these are square-necked midi dresses, which means that the product data has to be there in the first place in order to do it.
Otherwise you're flying blind.
And that needs to start at the factory.
Yeah.
Actually, it needs to start at an idea.
(45:44):
Start at the idea, probably.
Yeah, yeah.
Like what's going into it and then, yeah.
Yeah, there's a lot in there.
We didn't get to touch on a lot as well.
I suppose one of the advantages to a degree is that business Oh Polly does own the factories that it buys, that it uses.
So it's able to, it was able to implement this all throughout the chain.
(46:05):
There's no reason it shouldn't be implementable across most supply chains.
The other bit that she touched on really briefly was HS codes.
Yeah. Dirty word...
And they just make me want to cry because HS codes are so incredibly complicated for importation into the US.
With such an extremely delicate outcome in terms of, you know, you can go in, you can swing between going terribly wrong and not having a problem.
(46:34):
Yeah.
It's the difference between getting charged a couple of per cent as a tariff and 30 per cent plus, even higher.
So HS code accuracy can have a huge impact on, like, unit profitability.
Yeah.
So even something as small as that doesn't even impact merchandising, which is all the cool stuff that she was doing.
(46:56):
Yeah.
But also incredibly important because if you, you know, you can do all the cool stuff, you ship it off to America, then it gets slapped with a, effectively a penalty.
And then all of a sudden your business that was looking, your business case that then looked all, all profitable and handsome, suddenly looks all unprofitable and ugly...
I didn't know where I was going to go with that.
(47:17):
I was waiting for the outcome there now.
That was, that was wonderful.
I think we probably went way over time on the call itself.
We could have spoken to Lauren for so long.
We didn't even get on...
I think Lauren should come back.
Yeah, yeah.
Also missed, you know, did you know that Oh Polly started off, well, it started out on eBay as a charity set-up.
(47:37):
It was for a charity-funding, charitable activity in Cambodia.
Still donates a percentage of their profit every year to that.
Obviously it's moved along a lot since then, but you know, there's so many interesting stories there.
It's a great story, isn't it?
It's fantastic.
So yeah, I want to keep an eye on Oh Polly.
(47:58):
I want to keep an eye on what Lauren ends up doing, because I think it'll be wonderful.
Well, thanks very much, Gordon.
Thanks, Ger.
Take care.
You've been listening to Functional & Fabulous with Ger Keohane and Gordon Newman.
If you'd like to know more about the podcast, or about StudioForty9 and Omnichannel stories, please go to Functional & Fabulous. Our sound engineer was Elaine Smith, and the show was produced by Roger Overall.
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