Growing Ecommerce – The Retail Growth Podcast

Zalando is Banning Shoppers: Are Returns Killing YOUR Profits?

• Smarter Ecommerce • Season 4 • Episode 13

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This controversial episode is tackling the messy side of shopping! Hosts Mike Ryan and Christian Scharmueller dive straight into the news that Zalando is tightening its return policy, issuing warnings and even year-long bans for shoppers with "disproportionately high return volumes". 

With fashion return rates soaring (sometimes 30-70%!), they break down why retailers are finally getting serious about profitability and why relying solely on order value is a massive, costly mistake for your advertising campaigns.

But don't panic! We offer the smart, proactive solution: leveraging off-channel first-party data. 

Mike and Chris explain how you can integrate return rate data into your campaigns using tools like Conversions with Cart Data and even Google’s Product Return Rate Predictor. Plus: Mike and Chris take a look at how Google is leading the pack with virtual try-on technology to stop returns before they even happen. 

Finally, the boys tackle the all-important Black Friday strategy, discussing the dilution of the sales event and Google's new "triple peak week" thesis: Surging Sunday, Black Friday, and Cyber Sunday.


Links mentioned in this episode:

https://smarter-ecommerce.com/en/smec-market-observer/
https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/virtual-try-on-api
https://github.com/google-marketing-solutions/product-return-predictor


About smec (Smarter Ecommerce):

At smec - Smarter Ecommerce, we specialize in transforming business goals into optimized ad campaigns. With over 16 years of experience in Google & Microsoft Ads, our intelligent software and expert services help retailers achieve superior results.

We're committed to giving you the tools and insights needed to stay ahead in the ever-evolving world of digital advertising.

Make sure to follow smec - Smarter Ecommerce for more performance marketing insights:

SPEAKER_01:

Mike. Chris. How are you doing? Good. Hold on. We have one step before that. The intro. The intro. Hold on. Here we go. Welcome to Growing E-Commerce. I'm your host, Mike Ryan. And with me? Chris. Again. Hey, Chris. This is episode 13 of our co-hosting. I'm proud of ourselves. Yeah, lucky number 13. Yes. Let's see. Let's see. Exactly. And before we get started, Chris, I have a question for you. Did you watch Dumb Money? Not yet. Okay. Not yet.

SPEAKER_00:

But it's on my watch list. All right. Have you watched Marching Call? No. Okay. You should do that.

SPEAKER_01:

It's on my watch list. Yeah, I was telling Chris that I was actually born in the same city as Rory and Kitty and then went to the same college as Roaring Kitty. So we knew each other briefly before the millions. The big question is have you participated in any way, shape, or form? I mean, the this is one of my very personal. It's very personal, Chris, because actually we were we were building our cellar and garage at exactly that time. And out of money, probably because everything and zero capital anyway. So I I completely missed out on this entirely. And now it's one of the biggest. New opportunities. One can only help. But I will watch it. All right. Promise. I really think it's kind of an inspiring story. But yeah. So we've got a couple topics on the agenda today. Let me lead in to the first one here. Um just last night at home, Stefi was saying that she's waiting on kind of an overdue return money from Zolando. Um did you shop at Zolando? You are the fan of that?

SPEAKER_00:

No, but but shout out to my wife. I love you. She is, she is, and I will talk about the news you you're breaking now.

SPEAKER_01:

Yeah, sure. So this is these two things are unrelated, but I I had to warn Steffi that there's some there is some news from Zolando. Um they are tightening up their return policies. And yeah, I mean, uh basically in a nutshell, they're working to identify what they consider disproportionately high return v volumes. And I don't know what those thresholds are. I don't think they're transparent about it. And it could, of course, be relative to your overall order volume or whatever, it might be personalized.

SPEAKER_00:

But so there are no specifics yet.

SPEAKER_01:

Not that I've seen. No. But the what they'll do if they if they think that you have too high return volume, then first they'll give you an email warning. So check your Zelando emails. And it might not just be a coupon or whatever. And then they might temporarily shut down your ability to place new orders. And if they're really not happy with you, they'll ban you for a year. They'll shut down your account for a year.

SPEAKER_00:

Okay. Yeah. We talked about that, right? Happy wife, happy life. Imagine, imagine your wife is not allowed to order Salando anymore. Yeah, I don't know.

SPEAKER_01:

I mean, what is what is what is normal shopping behavior and what is not short normal shopping behavior?

SPEAKER_00:

Um This is a big question. That that's why I would would love to get the specifics on it. I mean, just yesterday we had a big quarterly business review with one of one of our biggest clients, and return rates were a big topic. The return rates of this client were very, very low, uh significantly below 6%. Um so I think they're doing a great job there. But it was again a massive question: how how can we use, how can we deal with this data in order to understand, okay, which which which products are actually very prone to be returned? And how can we use this data again to optimize our our our paid paid search um uh campaigns? So I think this is a is a very, very important topic for every retailer. Yeah. As far as I know, especially when you talk about the big retailers, I haven't heard anything remotely close to what Solando is doing right now.

SPEAKER_01:

Or have you have you heard any other retailers going that down this this um I think I think Amazon uh for a while has had an abuse detection policy in there or something, but I I can't remember what the penalties are for that. I mean, yeah, this question about what is a good return rate anyway, or low or high, I mean it varies a lot per category. Of course, it's gonna be higher in fashion, whether you should touch on size variants, color variants, et cetera. And I I think there are actions you can take both on yeah, the advertising side. If you have a product with a high average return rate, do you want to promote it as aggressively? Also, is there stuff that you could do on your landing page side? That's definitely where a lot of investments are being made right now, too, with AI, especially. But like virtual try-on technology.

SPEAKER_00:

Talk about that in a minute. Yeah. I mean, one one one thing I and look, I mean, this is of course a small sample, but you can read read a lot of uh studies about that. One thing which uh makes Salando and and I think in general, buying especially fashion online so appealing to a lot of people is because you you can just order whatever you want and there is this possibility of return, right? You you you have your private wardrobe at home because you that for me the big question is you know how restrictive will Salando be? Because I think it's a big part of the value proposition, especially against offline shopping. So I I I would love to get some specifics on it. I think it's a very, very slippery rope.

SPEAKER_01:

Yeah, I agree. Because, you know, yeah, Stefan will buy stuff in multiple sizes and colors of the stuff. Absolutely. And some of that stuff is going back 100%, but it's done with the best of intentions. Sure. There's also, you know, meanwhile, there's like Instagram influencers and TikTokers, and they're they're buying stuff, wearing it once for a TikTok or for Instagram reel or whatever, and then they send it back. That's clearly abuse. Yeah. But um some of it needs to be baked into pricing. Yes. And you know, Zelando and their press release, I mean, no judgment on them, but they talk about how this is unfair to other customers because it's tying up inventory. I think there's truth to that. It's not e environmentally sustainable. I think there's truth to that too. Unnecessary freight movements, that it's disruptive to their processes and partners, but I mean, it's also, let's face it, it's about profitability. That's true. And the the word profitability, our profitability, was not mentioned there. And I mean, I don't know why they need to talk about everything else besides their profitability.

SPEAKER_00:

Everyone knows that's that's the name of the game. I mean, just just to give context, I mean, and I I don't know specific specific data for Solana, but fashion industry, I think it's quite normal to to look at return rates between 30 and 70 percent, bearing varying from, of course, I I guess categories. There will be even products which are massive outliers. Uh but imagine that, right? I mean, this this this of course is a massive driver for profitability. And for me, it's again, I mean, look, this is one action you can take as a as a retailer. Solano does it now, and let let's see how restrictive they are. And I think there will be some impact, I assume, on on demand. Probably it will be the right impact because it's demand you maybe don't even want to have in the first place. Yeah. But for me, the bigger, bigger question is, and we have been talking about this, I think, in one of our episodes before, the return rates are one of the first-party data which is probably probably mostly impacting, potentially impacting your profitability. Let's say in Google Search, Microsoft Search, whatever you do. And my question again now is what is your take on it? First party data such as return rates. How adopted is this idea that I'm from a retailer perspective, that I'm really actively thinking about, okay, what first-party data do I have and how to activate it in my, let's say, PMEX campaigns, standard shopping campaigns, whatever it is. Because return rates are available, I assume, right? On the retailer side.

SPEAKER_01:

Yeah, yeah. I mean, for sure, an average return rate is not the hardest data to calculate. It's super important. Like this is again, I I talk all the time that people hear first-party data, they think of remarketing less audiences and stuff like that. And there's so much more than just your your user data and it's your product data as well. So a return rate, it's that's off-channel data. Google doesn't know about this. And it's it's actually decisive because they're bidding on on the the order value. Yes. And you can then send an adjusted order value later on. But the question is, how soon do you send that value over? And just to give you an example, though, like yeah, years ago, I I wrote an article about this back in 2018 or something about someone who was segmenting their products and scoring them on the basis of the yeah. I can remember yes, I know. They they had margin brackets and return rate brackets, and they were looking at the intersection of these two and creating buckets. And I mean Creative. Yeah. And certainly in 2018 I was very high.

SPEAKER_00:

Highly advanced retailer. Yeah.

SPEAKER_01:

But so this data has been around forever. It's been possible to integrate forever. And the question is, will people do it?

SPEAKER_00:

When will people do it? I think again, I mean that that that might be the learning, ladies and gents. I mean, if you want to go down this route to really I don't know, potentially ban people with high return rates. I think yes. I mean, why not? I think the way smarter way would be to to more or less anticipate it, right? And to to to acquire clients or to to push products where you know, on average, I can deal with with these return rates. I think it's a way more proactive and smarter way to say.

SPEAKER_01:

Exactly. Uh I'm just I'm gonna dive into two quickly into two different options here as well. I mean, one thing, and in in the Google universe, you can use what's called conversions with cart data. It's a small little snippet of code that you add onto your standard track. It's big. Exactly. It's big. This unlocks your clicked versus bought data, like the the lead item, which is what received the advertising click, and then what was actually in order. And this can help bring these kinds of effects into your campaign data next to performance, next to everything, so that you can start to look at this. It's down at the item level. You can look at it at the brand level, the the category level, you can look at it at custom labels too. So you can intersect that with if you have margin custom labels or whatever in there. Yeah. This is all possible. Another thing that I'd call out is that Google, I haven't used this, but they have in their Google Marketing Solutions GitHub repository. They have this package that they call what is it even called? It's called Return Rate Predictor. Product return rate predictor. Yeah. Pre-straight forward. It's good. Not all of these little so I think I I've said this maybe on here too before. I say it a lot. I think some of the coolest things being built by Google are not in Google Ads. It's in their Google Marketing Solutions GitHub. And some of them have very intransparent names. This one's very descriptive. But basically they took their, they have a crystal value lifetime, a lifetime value L T V predictor model that they created, and they've modified that. So what they do is they predict your your value after returns, your conversion value after returns for every transaction. So I mean, as I was saying before, like you can have two customers, A and B, and A comes in at 150 bucks and B comes in at 120 bucks. It looks like A is the biggest. Yes. But adjusted for return rates, if customer A returned 80% of their value and customer B didn't, then things look really different. And the algorithm didn't have a chance to learn on that. Even if you you send in modified values after, you need to be as quick as possible and given your return window, and that's that's maybe not possible. So what this does is it predicts the value, and then you can import the predicted modified value that makes it.

SPEAKER_00:

Super smart. I would definitely certainly have a look at it. It's worth testing. For sure. Again, return rate is I think it's what one of one of the huge dark courses. Everyone knows how big the impact of return rates is on your profit. Yeah. But again, yeah, with so many retailers, I just don't see this strategy. What do I do with with first party data? This is my big shout-out to every online retailer listening to us. Look at your first party data and activate it. Build strategies around it. I mean, the prediction of this return rates on basically a client level. If this really works, what Google promises right now, I mean, it's it's certainly worth a try. We should have a look at this as well, Mike. Maybe we can we can test it with some clients.

SPEAKER_01:

Yeah. I mean, that's those are things we're talking about that you can do on the advertising side, like which looking at return rates, integrating into your campaigns, into product scoring, et cetera, using things like click versus bot data, just really a few extra lines of code, or trying out tools like the product return predictor. On the landing page side, there's a whole other dimension, especially in fashion right now, and that is virtual try ons. So what's going on there? I haven't well, I haven't used a virtual tryon before. You need a I've used some AR features in the past few years, and they were often pretty underwhelming. Yeah, they were. So uh you know, AR was being really hyped, but I think generative AI is a much better way of solving these things. And that's what this kind of stuff does. So yeah, I mean, we're talking about Zolando earlier. They're they have a huge data science team. In the US, there's a company called Stitch Fix. They were kind of a pandemic darling. I think they're not doing quite as well right now at the moment, but they're trying to find their legs, and they also have a huge data science team. And one thing that they're working on is virtual try-on. Yeah. So basically you upload an image of yourself, and then they can use generative AI to show you what these clothes will look like. And they they're like a subscription company where you get boxes of outfits, like personalized outfits arrive in the mail for you. You don't even have to do the shopping. So that but it you see that with independent companies like them, but also the platforms are tackling this too, of course.

SPEAKER_00:

And it's a great technology because I assume I mean I think there are certainly frog patterns to be detected. I mean, TikTok has, you know, rocked a new shirt one time and then send it back. But I literally think a lot of people, you know, go for a a broad, broad basket because they just don't know, right? You have this picture online, but you just don't. This technology, I think, is a very smart way to reduce you know return rates in a positive way, right? It's positively positively loaded from a client perspective. And I think it's it would be a way better way than the okay, if you have a lot of return rates, you might be banned for a year, you know, talk to Lander again. I think this technology, I haven't tried it out. I mean, who who is who is from your perspective, who is who is leading, leading, leading the pack right now? Uh is it Amazon? What what for for me without a a doubt, it's Google.

SPEAKER_01:

Amazon has virtual try-on, but it's just for shoes and eyewear. So those are pretty limited and yeah, kind of the easy stuff, I would sort of say. Of course, super important categories anyway for return rates. But Google is definitely leading on fashion with full body try-on. It's coming to Google Shopping. Um, it's coming to the a standalone app as well. They also have things like using AI to generate 3D spins so you can generate, like you can upload basically the standard uh feed pictures that you have, and then they're able to figure out what this thing looks like from all views, so people can rotate it and have a better look at it, then try on stuff virtually. They even have a virtual try-on API, which is yeah. I think this is very exciting. It's gonna be allowing retailers to use Google's technology on their own. That's massive. Yeah. So that will use that's basically in Vertex AI, which is their it's their AI tool inside of Google Cloud, and it uses their Image N model.

SPEAKER_00:

Return rates a big topic. And uh I think a lot of ways to tackle it. I think message to our listeners. I mean return rates, probably they look at it anyway. Yeah. Big question is what do you do about it, right? And there are different ways to tackle it. Technology on your website, activating first party data, looking at this return rate predictor from Google. There are there are ways to tackle this. And it's a massive profitability driver, right? For sure.

SPEAKER_01:

It's it's i if it's something that's hurting your company right now, I think the message is that there are options to get. So definitely.

SPEAKER_00:

Let's end on this positive note. There are solutions out there. Exactly. Not for every topic, but for this one.

SPEAKER_01:

Making headway. And some of it's thanks to AI. So, you know, for to AI haters, which I I can never decide which I am.

SPEAKER_00:

That look, I mean, I didn't want to bring it up, but to the listeners, we had our debate, right? Is is there an AI bubble? And not an argument. Why there isn't. It's it's working. Just kidding. But AI helps you. For sure. For sure. There are definitely use cases. Let's move on. What about I mean, what about your your shopping behavior going into the the peak season? Uh talking about online retail, Black Friday, holiday season. Yeah, yeah. Well you change your buying baby?

SPEAKER_01:

Me? Or your wife? Yeah, yeah. For sure. I mean, we're absolutely deal seekers. Um sorry, but the prices almost always like it's definitely one of our number one criteria for sure. Fair enough. I mean, not always. I just bought I just bought out of pure sentiment this US I Spy series. Do you know these from Walter Wick? They're these beautiful books, and it's ice spy Christmas. Massively overpriced? Massively overpriced because the availability here in Europe is just very limited. But I I need my kids to have it this Christmas, and I bought it.

SPEAKER_00:

I became also a very price-sensitive person, but certainly not when when it's even remotely related to my kids.

SPEAKER_01:

Yeah, exactly. The price elasticity is totally different. With kids and pets usually.

SPEAKER_00:

Yeah, exactly, exactly. But all jokes aside, what's because there's there's some interesting perspective directly coming directly from Google on on this peak season.

SPEAKER_01:

Yeah. I mean, well, one thing that we were talking a couple episodes ago about like conversion lag, and and I think we talked in the episode about how there's seasonality to this. So the October blues, that is October is a tough transition month. Yeah. Exactly, because people start deferring their purchases already. This demand gets pulled up and people are waiting for the deals to for this to unleash. On the other hand, something weird that's going on is that Black Friday as a focal sales event has somehow become diluted. It's gone from Black Friday to BFCM to Black Friday week to Black Friday month. Maybe we'll have a Black Friday year at one point. Imagine that, Mike. We'll just wait till Black Friday decade. We're just getting started, Chris. Black Friday century. Lifespans are getting longer, Chris. Sales sales windows need to match this. Well, what 1000%.

SPEAKER_00:

By the way, on a serious note now. Also based on the data, when when I had my master class, I think it was at the D-Mexico, I talked about the the the question is is Black Friday still massively impacting Q4 for the online retailers? Yeah. And although we see some so we were not talking about the Black Friday levels, let's say during pandemic or or pre-pandemic. Yeah. So it's definitely there there is some some I would say cooldown to be yeah, observed with regards to Black Friday, but it's still by far the biggest Friday in this whole in the whole year, right? So Black Friday is still big. Yeah. But Google, there's there are other days which are as big as Black Friday.

SPEAKER_01:

Exactly. They have a new thesis this year, let's call it. They're calling it the triple peak week. Sounds great.

SPEAKER_00:

The the marketers at Google. Yeah, they are good. I'm I'm always wondering now, I mean, there's no AI in it, there's no performance in it. Just call it triple week. Can we call it peak triple max week? Max week performance week.

SPEAKER_01:

But what what is it about? Yeah, their their thesis is that besides black like Black Friday is one of those three peaks, but the other two are what they call surging Sunday, and that's the Sunday before and then Cyber Sunday, which is the Sunday immediately following. Um so you might have heard of Cyber Monday, of course, but they're saying that actually it's all about surging Sunday, Black Friday, and Cyber Sunday. And which makes sense. Yeah. How do you think feel like you think that Sunday is just a logical shopping date for consumers?

SPEAKER_00:

It's a lo look, I mean, the the big thing, the big caveat caveat, honestly, is I mean, Google is talking about demand, right? So they look at these three days as as super, super strong days from a demand perspective.

SPEAKER_01:

They even say that for just for context, uh, Surging Sunday has 107% of the demand.

SPEAKER_00:

Of the demand of Black Friday. So it's bigger than Black Friday. Yeah. Based on demand. My question now to Google would be what does demand mean, right? And again, this is I think very much connected to to the to the conversion topic. Because the question is the demand on Sunday, let's say the sun before Black Friday. But I assume when Google is talking about demand, I think it's just search volume. I think so too. And it's certainly not not based on conversions, conversion rate, and so forth. However, it might still be a very important day, right? To to from a strategic perspective, to really be there when people just start their their research for the Black Friday conversions. So I think it makes a lot of sense. Big question would be what does Kubu mean with the marked?

SPEAKER_01:

Yeah. That's that's my question too. I would love to see if they have like some further materials about it. I think it's probably search volume two. And the the tricky thing here is that that's actually maybe the peak of latent demand. Like that that demand it's given. There's people are searching, they're researching. But in that case, it's probably about moving a step up funnel, talking about like demand gen campaigns, your meta activity as well. These are the things that are gonna support search lift and support conversion volume down the line.

SPEAKER_00:

It it perfectly feeds into the the episode we had when we talked about the the October blues or the the lead up to this peak season. I think it's just wrong to look at at this isolated data, what conversions happen during that time. Because a lot of conversions don't happen during that time. But if you look at the right conversion data, which is conversion by time, you will find out that these days are might be very, very important to you. I think it's the the worst thing an online retailer could do is to just think about okay, I'm I'm ready for for this Black Friday week. And and and the weeks before I'm I'm just, I don't know, maybe even be defensive with my ad spends. I think this this is the worst thing you can do because the demand is happening, right? Yeah, and you have to be there. This data supports our thesis, yeah, which might be obvious anyway. But I think it's very interesting. Yeah, for sure. My question we will certainly do some Black Friday or peak season review anyway. We should talk about that in one of our episodes.

SPEAKER_01:

Yeah, that's right. I have not, I'll be I will be doing some research in advance of Black Friday about last year, the past years, so I think we can share that here. We're also we have a free tool on the website called Market Observer. It's SMEC Market Observer. And you just you log in with an email address and then you can see a different uh like yeah, I don't want to say benchmark CPC values, but things like CPC, click-through rate and stuff like that. Um and I'm working right now on an overhaul of that. We're gonna be adding like a competition monitor and some other stuff, and all this stuff will be available in time. And it's a hell of a tool.

SPEAKER_00:

Yeah. And it's free. I mean, it's crazy.

SPEAKER_01:

It's free.

SPEAKER_00:

It's free. No, no, look, I mean, not really.

SPEAKER_01:

Well, it's a c nothing's free. It's the cost of your email.

SPEAKER_00:

Exactly. We want your email. No, but really, this this dispensary outdated just to remind the the listeners, we have billions and billions of data points, right? I mean, there's there's it it's there are advantages being a big player in this this this paid search universe. Yeah. And one of the advantages that we have this overview, and I'm really looking forward to this overall. I would really encourage everyone to to look at this market observer tool. It's it's really great. It gives you perspective on your own data. So mate, time flies. Yeah.

SPEAKER_01:

Shout out accomplished.

SPEAKER_00:

Yeah, I think yes, shout-out accomplished. Yeah. At least one shout-out per episode. That's my new goal. No, I'm I'm I'm I'm I'm not kidding. It's it's really a great tool.

SPEAKER_01:

Yeah, definitely. So yeah, I think I think that's gonna do it for today. So thanks everyone for tuning in. Do you want to do the outro, Chris?

SPEAKER_00:

Or man, I I would love to, but there's just no way I can do it as as charming as you. So, man, the floor is yours.

SPEAKER_01:

I I think I'm known for being awkward rather than charming. I'm not sure. I love the gringe. I love the gringe, but maybe a handshake first. Absolutely. Let's go. All right. This has been another episode of Growing E-Commerce brought to you by Smarter E-Commerce, also known as SMEC. To learn more, you can visit smarter ecommerce.com, and we have great free resources there, like our market observer, some free scripts and tools, our blog, all kinds of stuff. So head on over and uh thanks for listening. We'll catch you next time.

SPEAKER_00:

All the best, guys. All right.