Behind every fashion product, collection, or storefront, there’s an ambitious designer, buyer, merchandise planner, wholesale or e-commerce manager who has spent years arming themselves with a unique set of skills. And for every one of these fashion industry experts, there’s an inspiring career journey.
In Style Arcade’s Fashion Career Series, we leverage our passionate network to go beneath the glamour of fashion’s most sought-after roles—and take a seat with the people whose hard work and dedication are shaping the future of retail.
Meet Mareile Othus, whose 15 years of global retail industry experience led her to co-found and lead the online retail customer experience platform, Humii. Having previously held positions with The Iconic, where she was Chief Category Management Officer, Alquemie Group, Oroton, Zalando, and Hugo Boss, Mareile reveals fashion’s biggest data gaps, how AI is starting to reshape the customer experience, and what mystery shopping will rely on in the future.
From buyer, to category director, to co-founder and CEO of Humii. Tell us about your early career journey and what drew you to the fashion retail industry.
I can honestly say I ended up in fashion by coincidence.
Just before finishing university, a friend recommended a trainee program at one of Germany’s largest retailers, and that’s where it all started. From day one, I was hooked. Retail has this unique mix of pace, creativity, and commercial thinking that just pulls you in.
I very quickly gravitated towards eCommerce and ended up joining Zalando in its early days. It was an incredible time to be there; everything was about growth, experimentation, and figuring things out as we went.
A few years later, I got a call from Australia asking if I wanted to help build The Iconic. And I absolutely loved it.
How did co-founding Humii come about?
After more than 15 years in retail, mostly in eCommerce, there was always one thing that didn’t quite sit right with me. We spent a lot of time talking about customer experience, and rightly so, but when it came to measuring it, things got a bit… vague. We had our monthly NPS meetings, but no one could really explain why the score moved. What actually drove it? Where exactly were we winning or losing customers, and how are we comparing to our competitors?
At the same time, we all knew that experience, more than anything else, was becoming the real differentiator. Not just what you sell, but how it feels to shop with you.
At The Iconic, that was especially clear. Our assortment wasn’t wildly different from others in the market, so the experience had to be better. That’s what would set us apart. But there was still no clear answer to a very simple question: Who actually delivers the best online experience? And more importantly: why? That question stuck with me.
At some point, it just clicked. Retailers have been using mystery shoppers in stores forever to understand the real customer experience. So why weren’t we doing the same thing online? That idea became Humii.
What experiences in your career most shaped how you think about customer experience today?
That’s a great question. For me, it’s less one specific experience and more the accumulation of everyday ones. Customer experience isn’t something abstract; it’s something we all feel constantly, often without even realising it.
I’ve always been very sensitive to that. I’m a sucker for a great experience, but equally, one poor experience is often enough for me to walk away. Whether that’s a restaurant, a hotel, an employer, a coffee shop, or an online retailer. And I don’t think I’m alone in that.
What has really shaped my thinking is seeing how inconsistent experiences still are across industries. Retail has come a long way, but there are still clear gaps. The underlying issue is often the same: You can’t improve what you don’t truly understand.
Many brands are sitting on huge amounts of data but struggling to act on it. Where do you see the biggest gaps?
From my observation, the biggest gap sits in ownership. In many organisations, it’s not clear who truly owns the customer, who has the authority to act, and which metrics actually matter. You can have all the data in the world, but without clear ownership and accountability, it rarely translates into meaningful change.
Beyond that, there’s a disconnect between data and decision-making. Most teams are very good at reporting what’s happening, conversion rates, drop-offs, and NPS, but much less clear on what to do next. Data becomes descriptive, not directive.
Another major gap is context. Businesses often see the “what”, where customers are leaving or struggling, but not the “why”. Without understanding the actual experience behind the data, it’s difficult to prioritise the right actions or drive real impact.
And finally, data is often fragmented across teams. Marketing, product, CX, and operations are all looking at different signals, which makes it hard to build a consistent view of the customer journey. The result is that brands are data-rich, but insight-poor, and even more importantly, action-poor.
Data is often fragmented across teams... the result is that brands are data-rich, but insight-poor, and even more importantly, action-poor.
As more kinds of storefronts open up, customer experience is really the key differentiator between brands again. How is AI changing what a great brand interaction looks like in e-commerce?
Experience will always be the key differentiator, especially in categories where products are replaceable, and barriers to exit are low. Customers don’t complain, they simply leave.
AI is starting to reshape what a great experience looks like, primarily by making things faster, simpler, and more convenient. It helps customers find products quickly, answers questions in real time, and supports clearer expectation setting across the journey.
But in practice, we’re seeing that AI can just as easily introduce friction if it’s not executed well. Poorly implemented AI often creates confusion rather than clarity, and confusion erodes trust very quickly.
Trust is the key here. Customers don’t fully trust AI yet and still expect a human fallback when it matters. The strongest experiences today are not fully automated, but balanced, AI for speed and scale, human interaction for reassurance and resolution.
AI itself is not the differentiator. How it’s implemented within the experience is.
The strongest experiences today are not fully automated, but balanced, AI for speed and scale, human interaction for reassurance and resolution.
What are the most common CX friction points you see across fashion brands right now?
I love this question, especially as we’ve just released our 2026 Online CX report, which clearly outlines the biggest friction points in the journey, and more importantly, what actually drives abandonment and prevents customers from coming back.
When we look at the data, the biggest reasons customers don’t return, from an experience-related view, are a difficult returns process (17.2%), followed by slow refunds, poor communication, and difficulty reaching support. These are all moments where the brand breaks trust, often after the transaction is already complete.
At the same time, before checkout, we’re still seeing very fundamental friction points causing drop-off. The top reasons customers abandon are unclear shipping and delivery information (18.3%), customer support gaps (17.9%), and issues with navigation and search. Interestingly, customer support gaps were often driven by AI chatbots. Chatbot obstruction was not mentioned as a reason, but it is now very common. In general, negative feedback related to AI has increased by 70% from last year.
So if you zoom out, the pattern is actually very simple, and a bit uncomfortable:
- Before purchase, customers leave when things feel unclear or hard
- After purchase, they don’t come back when things feel slow, difficult, or unresolved
And none of this is particularly innovative. It’s very often about the execution of the basics.
That’s the part I find most interesting, and honestly, most concerning. Because these are all things retailers can control. But they often sit across different teams, different systems, and different owners…which is exactly why they persist.
How can brands get ahead of customer expectations rather than chasing them?
Most brands don’t need to get ahead of customer expectations; they need to consistently meet the ones that already exist.
Getting ahead starts with clear ownership. Someone needs to own the end-to-end experience, not just parts of it, and be accountable for how it performs across the entire journey.
The second piece is better metrics. Not just top-line indicators like NPS, but measures that actually show where and why customers are struggling.
And finally, it’s about understanding the real customer experience, not just the data. Most brands know what’s happening. Very few understand why.
How do you see the role of “mystery shopping” evolving in an AI-first world?
AI will absolutely change how we measure and simulate experiences, but not replace the need to live them.
What changes is what mystery shopping actually needs to evaluate. As AI becomes part of the journey itself, whether that's a chatbot handling a query badly, a recommendation engine missing the mark, or an automated return flow that just stops working, those interactions need assessing too. The only way to know how it actually feels when the AI gets it wrong is to go through it. In an AI-first world, mystery shopping becomes one of the few ways to audit the AI.
AI can’t replicate that full, end-to-end reality in a way that captures how it actually feels and is executed. And that’s the key point: Experience is not just functional, it’s emotional.
Experience is not just functional, it’s emotional.
What do you think the fashion retail experience could look like in 5 years?
In five years, fashion retail will look very different in how customers arrive, but not in what they expect.
Discovery will happen increasingly outside the website, driven by AI, social, and predictive journeys. Customers won’t browse endlessly; they’ll expect to be shown the right product instantly, often before they even land. Search becomes matching.
At the same time, emotional connection becomes more important. As more gets automated, brands need to work harder to feel human. Customers still need a reason to choose you, not just transact.
Speed is another shift. AI compresses timelines, good decisions scale faster, but bad ones do too. The edge will come from moving fast without losing discipline on the experience.
And one of the biggest unlocks will be post-purchase. AI is getting genuinely good at fit, sizing, and returns. If brands can increase confidence upfront and reduce returns, it changes the economics entirely.
So while the journey evolves, expectations don’t. Customers will still choose brands that feel simple, reliable, and human. The future isn’t more complex; it’s just far less forgiving.
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