Returns Myth-Busters: Best Kept Secrets to Reduce Returns and Improve Profitability

Jul 12, 2023 3:00 PM4:00 PM EST

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Key Discussion Takeaways

Historically, product returns have had a negative stigma in the retail landscape. Most retailers believe that they impede profitability and compromise the customer experience. Yet returns are indispensable data sources brands can harness to optimize multiple business facets. What are the most widespread myths about returns, and how can you use these data sets to lower your rates?

Retailers who rarely analyze returns data lack an adequate understanding of the process and assume their return rates are low and limited to specific categories. Instead, customers can return almost any product, initiating opportunities to reduce return rates. For instance, if you discourage bracketing — ordering multiple variations of the same item — you may incentivize more frequent returns and cannibalize sales. By allowing customers to assess and select ideal products, you can encourage authentic feedback and leverage the data to improve PDPs, marketing campaigns, and shopper experiences. 

In this virtual event, Christine Bradford and John Bowman of Returnalyze join Tiffany Serbus-Gustaveson to dispel common myths about the returns process. Together, they explain how to mitigate return policy misuse, optimize return reasons, and reduce overall returns.

Here’s a glimpse of what you’ll learn:

  • What is bracketing, and how can it boost revenue? 
  • How to optimize return reasons 
  • Insights for leveraging returns data to enhance retail strategies 
  • Debunking myths about returns on luxury items, footwear, and apparel
  • The importance of identifying return rates and data
  • How retailers can mitigate return policy misuse
  • Advice for reducing returns and improving customer experiences
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Event Partners


Returnalyze is a returns analytics company on a mission to help retailers take control of their returns. Returnalyze's Intelligent Dashboard provides critical visibility which elevates customer experience, reduces operational overhead and adds significant savings to the bottom line. The dashboard empowers retailers, showing them why their customers are returning items, what product or supplier issues exist, and what actions can be taken to reduce, prevent and predict returns.

Connect with Returnalyze

Guest Speakers

Christine Bradford LinkedIn

VP of Customer Success at Returnalyze

Christine Bradford is the VP of Customer Success at Returnalyze, which helps businesses reduce returns and operational expenses while improving the customer experience and loyalty. As an experienced client services leader and strategist, she helps brands achieve business goals and drives improvement by transforming complex obstacles into tangible and profitable solutions. Before Returnalyze, Christine was the Senior Client Account Director at Epsilon.

Tiffany Serbus-Gustaveson LinkedIn

Senior Digital Strategist at BWG Connect

BWG Connect provides executive strategy & networking sessions that help brands from any industry with their overall business planning and execution. BWG has built an exclusive network of 125,000+ senior professionals and hosts over 2,000 virtual and in-person networking events on an annual basis.

John Bowman LinkedIn

Chief Analytics Officer at Returnalyze

John Bowman is Chief Analytics Officer of Returnalyze, a company at the forefront of product returns analytics. He leads development of an AI-powered platform that uncovers the causes of product returns, recommends actions, and measures results. John's 15 year career in data and analytics spans all aspects of the data lifecycle. Before Returnalyze, John led marketing optimization for Grainger, a top-10 B2B ecommerce website. He holds a PhD in mathematics from the University of Wisconsin-Madison.

Event Moderator

Christine Bradford LinkedIn

VP of Customer Success at Returnalyze

Christine Bradford is the VP of Customer Success at Returnalyze, which helps businesses reduce returns and operational expenses while improving the customer experience and loyalty. As an experienced client services leader and strategist, she helps brands achieve business goals and drives improvement by transforming complex obstacles into tangible and profitable solutions. Before Returnalyze, Christine was the Senior Client Account Director at Epsilon.

Tiffany Serbus-Gustaveson LinkedIn

Senior Digital Strategist at BWG Connect

BWG Connect provides executive strategy & networking sessions that help brands from any industry with their overall business planning and execution. BWG has built an exclusive network of 125,000+ senior professionals and hosts over 2,000 virtual and in-person networking events on an annual basis.

John Bowman LinkedIn

Chief Analytics Officer at Returnalyze

John Bowman is Chief Analytics Officer of Returnalyze, a company at the forefront of product returns analytics. He leads development of an AI-powered platform that uncovers the causes of product returns, recommends actions, and measures results. John's 15 year career in data and analytics spans all aspects of the data lifecycle. Before Returnalyze, John led marketing optimization for Grainger, a top-10 B2B ecommerce website. He holds a PhD in mathematics from the University of Wisconsin-Madison.

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Tiffany Serbus-Gustaveson

Senior Digital Strategist at BWG Connect

BWG Connect provides executive strategy & networking sessions that help brands from any industry with their overall business planning and execution.

Senior Digital Strategist Tiffany Serbus-Gustaveson runs the group & connects with dozens of brand executives every week, always for free.

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Discussion Transcription

Tiffany Serbus-Gustaveson 0:18

Happy Wednesday everybody. I am Tiffany Serbus-Gustaveson, a digital strategist with BWG Connect and we are a networking knowledge sharing group we stay on top of the latest trends challenges whatever is shaping the digital landscape we want to know and talk about it. We are attracted to do at least 500 of these virtual events this year due to the increase in demand better understand everything in the digital space, we'll also be doing at least 100 in-person small format dinner. So if you happen to live in a tier one city, feel free to shoot us an email, we'd love to send you an invite, the dinners are typically 15 to 20 people having specific discussion around a certain digital topic. And as always a fantastic time, we'd love to have you join. We spend the majority of our time talking to brands and so we stay on top of the latest trends and challenges within the market. We'd love to have a conversation with you feel free to drop me a line at And we can get some time on the calendar is from those conversations we generate the topic ideas we know that people want to learn about and it's also where we gain our resident experts such as eternalized, who's with us today. Anybody that we asked to teach the collective team has come highly recommended from multiple brands. So if you're ever in need of anything within the digital space, please don't hesitate to reach out to me I have a shortlist of the best of the best service providers and be happy to provide that information to you. Also note if you have any hiring needs, we do partner with a talent agency Hawkeye Search, which is formerly BWG Talent that we can put you in contact with as well. A few helps housekeeping items, we started about four minutes after the hour. So rest assured, we will wrap up at least five to 10 minutes before the end of the hour to give you ample time to get to your next destination. And most importantly, we want this to be fun, educational, conversational. So please put in those question comments into the chat, the q&a bar or if you feel more comfortable, you can email me at And we will be sure to get to them. So with that, let's roll and start the returns. Mythbusters is the best kept secrets to reduce returns and improve your profitability. The team at eternalized have been awesome friends and partners in the network. So I'm going to kick it off to our panelists. If you can give a brief introduction and yourself that would be lovely. And then we can dive into the information. Thank you.

John Bowman 2:30

All right. My name is John Bowman. I'm the chief analytics officer Returnalyze. Our we love returns data. Very excited about it very excited to talk to you today. And yeah, I mean, this, this is kind of capping off a number of years that I've spent in the data and analytics space and retail. And, yeah, again, I mean, very, very fun topic today.

Tiffany Serbus-Gustaveson 2:59

Thank you.

Christine Bradford 3:01

Hi, everyone. Welcome. My name is Christine Bradford. And I'm the VP of Customer Success here at Returnalyze. I have also worked in the data space for a long time within digital marketing and now returns worked with a lot of retailers throughout my tenure. Also love for Dana, and so very excited to to have this conversation with

Tiffany Serbus-Gustaveson 3:23

you today. Beautiful. Well, Christine, let's dive into the presentation. And then we'll get to the fun Mythbusters part if that's alright with you guys.

Christine Bradford 3:32

Yeah, absolutely. So just a couple of slides to take you guys through just so you understand who we are and what we do. I do want to thank BWG for hosting us again, as Tiffany mentioned, we've been great partners for some time. And this event is one that we love to do. So without further ado, I'm just gonna dive in Returnalyze a returns analytics company. We're on a mission to help our retailers to control their returns. We help you by looking at your returns data across your entire business and help you to elevate your customer experience, gain critical visibility and insight into your data and then ultimately increase efficiency and the bottom line. How do we do that? We look at your returns. And we're able to decipher between the good returns and the bad returns, right? A good return actually might be a bracketing experience that we're going to talk about where I'm ordering multiples, and I ended up keeping multiples because I liked the item and I want to keep it in multiple colors. And I'm going to return maybe the couple of things that didn't work out for me in size or that one color I didn't like but I kept to others. So in that case, it's okay to have some returns. Then there's you know, the bad returns the ones that you can prevent or avoid, such as perhaps understanding if something's running large or small and has a size or fit problem and you can do have a better job at educating your customer. Or maybe there's an operations issue going on, where wrong items are being shipped or, and things are missed, you know, impacting your, your first time buyers, and you're gonna want to know about that so you can get ahead of it and and fix that from happening. So what we do is we're able to discern between all the different types of returns, and how they impact your business. So that you can go ahead and take action and resolve these from happening in the future. We don't just give you access to our dashboard, we have a customer success team that I had up and that we partner with you, right, so we meet with you on a regular basis. And we talk to you about the insights that the dashboard are uncovering. And we also help you debunk these myths. So a lot of times what ends up happening is we start a relationship with a retailer and they come in with some preconceived notions of things. And that's what we're going to cover today, what we've seen in the industry, of what we've seen across many different verticals and retailers, and what the data is showing us. And as a result of that, we partner with you, and we provide you with best practices, recommendations of actions that you can take to help resolve the issues. And then we go ahead and we measure the impact of the actions that you've taken, um, so that we can perpetually optimize and continue to improve upon your business. So once we've done all of that, we're able to, you know, see a 15 to 20% reduction or return rate, we can save you an operational costs, and elevate the customer experience and, and what retailer doesn't want to achieve all of that, right.

Tiffany Serbus-Gustaveson 6:40

Awesome. Thank you so much for the overview of right. So this is the fun part. And I am no Adam Savage, who hosts the real Mythbusters. But I will do my best here. So I'm going to put in the myth into the chat. And I also say it as well. But for reference, it will be in the chat if you guys want to look at it as we go, because we have quite a few to get through. And like Christine said, these are preconceived notions that they've heard in the industry, and so they are going to debunk them accordingly. So Myth number one, bracketing is bad for my business.

John Bowman 7:15

Hey, I will take that one. First, we ought to define what we mean by bracketing. So bracketing would be ordering multiples of an item, perhaps with the intent to keep only one, right. So you might order multiple sizes. To try to find the right size, you might order multiple colors, because you're not quite sure what color is going to work. Sometimes this is called home wardrobing. Now, we hear from a lot of retailers, that they have an impression this is a bad behavior. We want to prevent customers from bracketing, we want to help them to choose that one item that's right for them. But when we dig into the data, we often find that that's not the case, we often find that bracketing is beneficial. And you can kind of see this if you think about the percentage of customers who are likely to keep an item, right? So if if I order an item, and it's not the right size, then maybe I go back and exchange it for another size. Or maybe I just send it back and I've decided to buy something else. Whereas if I've ordered to and I find the right size, often I'm more likely to keep that size that works for me. So we see this quite often where actually, there's an impression that both sides, bracketing is bad, I don't want my customers buy buying multiple sizes or, or even color bracketing is bad. But when we look at the data, and we actually look at the percentage of items that are kept, or even beyond that, look at the net revenue of those purchases, we're finding that on average bracketing is really good, right? And but it's important to understand in sort of a detailed, granular way, right, because there could be certain segments of the business where it's not working as well, and somewhere where it's working quite well. Now, I will say, you know, we've had a variety of a variety of sort of actions taken based on bracketing data, right. So, we have one retailer that had sort of a low bracketing rate and a lot of exchange due to size a lot of size and fit issues, and they were actually able to promote bracketing on their sight, we saw a measurable increase significant increase in the bracketing rate, we went from 8%, bracketing to 10%, bracketing and that came with a improvement in the percentage of customers who are keeping the items and and in that revenue, right. Um, on the on the flip side, we had another another customer who, who actually was was trying to actively discourage bracketing so they were putting a message on their cart page Right saying that, hey, you know, if it looks like you have multiple sizes of this item, we really recommend this would be the right one for you based on what we know, right. So trying to encourage the customers to just choose the single item, we were actually able to show them that that was that was not not profitable for them that, that it would actually be better to just let the customers do what they wanted to do and, and buy those multiple sizes. So those are just a couple of examples of of how bracketing can even be good. And certainly, knowing your customers bracketing behavior is very valuable.

Christine Bradford 10:34

I think to just to add to that, people come in, and they think that customers are only bracketing on size. What we've also found is that customers actually bracket more for color, and size ends up being secondary to that. So customers typically know what their size might be. And they just really liked the item. And they want to try it in different colors. And then what ends up happening is they keep the multiple colors. And a lot of retailers are kind of shocked to identify that because they're like, I just thought people were doing it to try on different sizes, and they didn't realize it could be helpful to them. Because actually, I might end up keeping multiple colors instead.

Tiffany Serbus-Gustaveson 11:13

super interesting. Wow. And I don't feel so guilty about bracketing because I am guilty of it. I've always had like the background of me being an eCommerce for over a decade. I'm like, Oh,

John Bowman 11:25

we have a question. The question is, how do you quantify bracketing? So I, I like to look at it on sort of a per per item level, right? So if I have a if I have an item in a unique item ID right. So a style ID within an order, right? Is that style being purchased? With other variations? Right? So it's being purchased with with other sizes? Or colors of the same style? Or is it just a single? Is it just being being purchased alone? So I look at that kind of percentage, right? Of of those of those styles, right? How many are being purchased or with variations versus how many are purchased alone? Okay, Myth number

Tiffany Serbus-Gustaveson 12:10

two customers don't follow the return process and or give accurate return reasons. Yep.

Christine Bradford 12:18

So I'll go ahead and take this one. You know, we hear this all the time, how do we trust our return reasons, customers are just selecting the first one at the top, just to get through the process. Maybe they're telling me what I want to hear. So yes, it's possible, the customer is just trying to go through the process. But what we've actually found is that if you have the right return reasons, customers are willing to be honest with their feedback. And there's a lot of tools out there that that can help you optimize the returns process that can also let you adjust your return reasons. So as a value add, we certainly support retailers in optimizing their return reasons to make sure that we're capturing the right set of data. And we found what works best is actually to have primary and secondary reasons. Because even if something runs small or large, maybe in the case of footwear, right, maybe it's narrow and not running short, or maybe it's running long or wide. And it's good to have that additional information when you're trying to digest the data and look at the issues. Also having the flexibility allows us to kind of test and play with ideas. So for example, we had a shoe retailer that launched a new style. And you know, they were curious to see if something might be going on with the toolbox. So they actually added it as a new return reason. So then we could see is it the the shape of the toolbox that was causing the problem versus the very generic, smaller, large? Or we have another retailer that specializes in the occasion industry? And they were like, I think it's not really the customer buying our product. I think it's the bride that is telling the customer? No, I don't want you to keep that dress. So we tried it, we added a return reason that said Brian did not approve. And the resounding response to that was just amazing to see what type of styles were not resonating with the bride and what was getting returned. The other best practices is there's tools out there that lets you randomize the return reasons. So the top ones not always the one being shown every single time you can start to move them around and shift them. And then something else that we do here at Returnalyze is we don't just look at the return reason. So we're not going to just look at the return reason and say yep, this run small we're calling it we look at many different dimensions and many different product attributes. So we're going to also look at the customer behavior. So it goes back to that sampling conversation. What is she doing? Is she trying multiple sides? uses and is 80% of the time keeping the smaller one. And the return reason says too large, okay, then we can start to introduce okay, this item actually does run perhaps large. Let's now also look at exchange behavior. So if someone's not sampling and they're exchanging, are they doing the same thing? Are we seeing an 80% return rate or exchange rate, where you know, they're going down in size. So we look at exchanges, we look at sampling, we then look at the different product attributes to say, okay, something going on with with the material or a supplier or whatever it might be. And then we can also bring in ratings and reviews. So what is the star rating on the product? And then what are the key words in the reviews or even in the open ended return reason box, we've been able to do a lot of analysis with this because we also find that customers are funny, don't give a product a five star rating. And then they'll they'll completely have negative remarks to say in the text and vice versa. Maybe they give it a bad rate star rating, but then say, I love this product. But this was my issue with it. So identifying those key words. And doing that syntax analysis also helps us corroborate the return reasons in some of the other data points that we're looking at. The

Tiffany Serbus-Gustaveson 16:23

bride Scylla example is amazing. By the way, it's a great one, right? It's so great to that you can like change it. So is that always the first option is always there. Because again, guilty. All right, question comments, put them into the chat. Myth number three, we're going to move on. So Myth number three returns have a negative impact on all my customers.

John Bowman 16:49

This is a good one. And this is one that I think coming in, I assumed, right? I assumed that, hey, if if I have a return, I'm less likely to buy again, maybe from from a brand. But what we're finding again and again, in the data is this is not necessarily true, right? There are many cases where having a return could lead to more engagement with the brand if it's if it's a relatively easy return process. And I've seen this so much that I would almost say that if what you're seeing is that your customers who return are less likely to shop the brand, you really need to look at your return process, right? I think shoppers now understand that they may have to make a return that returns are sort of a normal part of doing online shopping. And it's only when that is sort of a bad return experience that then they're having a negative impression of the brand or, you know, possibly they if they have to return multiple times in the same item or something extreme like that. So returns not necessarily bad. I, but I will say you know that, of course, they're a cost to the business. Right? Of course, as a brand. I don't, I want to eliminate those unnecessary returns. So that's where, you know, we talked about many different, many different options to do that. Right. I also I think, will say one thing that we're finding is that, that sometimes there are customers who just simply have a higher return rate than other customers, right? Some, some customers are, you know, either they're, they're more picky or they they're just buying more items, right with the intention to return some of them. So we really, when we see that right, we really have to ask the question, right? Are these customers profitable? Are these customers I want to market to? In some cases, they are right? In some cases, they're your most loyal, most valuable customers, but in some cases, they're not. So we sort of have to make that determination.

Tiffany Serbus-Gustaveson 18:56

seen anything to add before we go to miss board? 

Christine Bradford 19:00

No, I think John has that covered. 

Tiffany Serbus-Gustaveson 19:02

Awesome. Questions, comments, put them in the chat, we're moving on. Myth number four. returns are a logistics problem only. So

Christine Bradford 19:14

I love this topic. Actually, last BWG event, we did cover this entire topic. So I'll try to synthesize this one down. But happy to talk about it at length with anybody else who's interested. So returns can really inform your entire business. We're not just talking about logistics or operations or just looking at your eCommerce experience. We can really look at all of your data and then inform all aspects of an organization so we can help the eCommerce team optimize the PDP pages, make sure that the size guides are accurate imageries consistent descriptions are correct. We actually had a conversation this morning about how do we educate customers better about how they layer products when we're talking about outerwear? And how do we show that like an most outer layer is supposed to fit a little bit more large, because you want to have the ability to layer within, what does that look like? The stretch odometer is huge these days in terms of showing stretch on jeans, or on a specific material, or we've even transcended that over to shoes, and then it can go over to non apparel items such as mattress firmness, and being able to show that on the scale, so that the customer knows in my buying or super firm mattress or something in the middle. From there, we can go over into the merchandising, buying planning department, a lot of merchandisers these days plan their assortment by by looking at gross sales alone, when really if you start to look at returns and how they are a part of your business and your buying process, then you can start looking at net sales and understand okay, did I really sell through the items? Or did I have a high return rate and therefore maybe it's not a good idea to do buy from this vendor again, for this type of product again, or this product with this specific product attributes not working for me? Or perhaps is it going back to the supplier or the vendor and negotiating on allowances? Hey, guess what, when we negotiated our buy with you, you said you would only have 5% of returns, but I'm actually getting 10% back which is double than that. So then it allows you to improve upon your contract negotiations. We can also inform the omni channel. So if you've got direct to consumer, and then you've got brick and mortar stores, and you also sell to wholesalers, we can inform all of that and look at the bigger picture. I have a story that super recent where a client found out that their store associates were just letting final sale items to be returned clearance items that weren't supposed to be returned returned. And they started working with their store associates to be able to cut back on that and they're already starting to see the savings from that. Or perhaps there's items that don't do well online that you want in store and vice versa. They're killing it in the store and you're not even giving them the right presents on your website. And they should be maybe it's an item that can be up sold or cross sell as somebody's going to their cart. And that's going to include increase your basket size, and ao V so you know, we can inform that as well. And then last, I think you know, another area that we can talk about is marketing and marketing spend optimizing your marketing spend by looking at returns, and items returned, optimizing your marketing materials in terms of acquisition efforts pushing her from a first purchase to a second purchase. And using returns data to make sure that you're putting your best products forward in your in those marketing efforts. I didn't even mention, you know, the fact that we can inform operations and logistics? And are things leaving the warehouse on time. Are there pick pack issues, QA issues? You know, do you have multiple carriers do you use a national carrier like a UPS and then regional carriers to help you out on the East Coast and West Coast and maybe you have a challenge with one of those. So really, when you think about it returns does impact all of the different departments within an organization. And we can certainly help inform all those different areas. So we can help increase net profitability not just in one department, but across all departments.

Tiffany Serbus-Gustaveson 23:53

Love it. Great examples, especially the negotiations with allowances. Wow, that's powerful. Questions, comments, put them in, we're about halfway through. Moving on to number five myth, luxury items. occasionwear are rentals and I can't prevent them from happening.

John Bowman 24:15

So here the idea is, I'm sure our audience has thought about this right? Is my customer buying that designer gown, wearing it out for the night and then returning it? Of course we don't want that to happen. Right? That would be a violation of the return policy and certainly not beneficial to the brand. And, you know, this is an interesting one because it's actually it's a little bit difficult to tell from the data if this is happening. We have a couple of signals that maybe it doesn't happen quite as often as we might assume. For example, we work with a large law every retailer, and they have been implementing measures to make this more difficult, especially on their, their luxury gowns. And what they're finding is that it were really, it's not sort of moving the return rates significantly, right. So I I'm not sure that it's that it's a big problem, right, that's happening. I actually think for those for those items, fit is a much bigger issue. And a lot of those items are being sent back to to do to fit. I also think, you know, that you can sort of look at the profitability of customers who return right. And, you know, in many cases, as I think I was saying earlier, like your customers are returning the most are also pretty loyal customers, right? So so you assume that if they're buying and keeping other items, they're probably not engaging in the kind of this kind of rental behavior. So, you know, I think PD, Christine has already called some of this out, but Right, but what we really want to try to address with returns, like what are the core drivers, it doesn't seem to be rental, but there's a lot of, there's a lot of return activity due to fit, there's a lot of return activity due to sort of not understanding the item or having the item not match what's expected in terms of the image that's on the website. So we really want to focus on addressing the core issue the root cause and improving those PDPs giving the customer better information so that they can make a good decision.

Tiffany Serbus-Gustaveson 26:35

An example Alright, number six, the myth only footwear and apparel have a returns problem. Yeah, so

Christine Bradford 26:45

obviously, you know, that is probably where it's the largest problem is in footwear and apparel and, and, you know, this the sweet spot, but that's not true. Obviously, everybody, regardless of what you're selling out there is going to see some sort of returns. So we we do work with retailers that are not within the apparel and footwear space, I have some really fun stories to share from those areas. We have a client that works in sundries and household items, they do have some you know, apparel and footwear, but they also do large furniture and they're kind of a mix right? We were able to identify the fact that Dawn dish soap was getting delivered damaged. And that it must have either been like spilling out or you know, something was happening in the packaging process and a large number of customers were getting a damaged you know, they came back to us and they were like, we didn't even think to look at this product. You know, and after taking a look we're identifying that there's there was an error in the way we package this and so that's why it's going out and it's getting damaged in transit. I mentioned mattresses earlier, you know, certainly that it's a tough sell online, making sure that the mattress is the right firmness for you. It meets your needs and so making sure that that PDPs up to snuff understanding perhaps is it a specific type of material within the mattress that's causing the returns or you know, this specific retailer found out that it you know, mattresses were preferential to specific regions. So New Englanders prefer a firmer mattress and they returned soft mattresses. So they found that data to be super useful as they started to look at opening brick and mortars they didn't want to you know stock up inventory with soft mattresses in that region if New England is more prone to buying a firmer mattress. We've seen everything from you know car headlights, people purchasing car headlights on Amazon and Amazon's compatibility guide with different vehicle making models you know being incorrect and as a result of that headlights are coming back and they're you know, and they're not so it's certainly not just apparel and footwear. If you know you're selling it we can definitely identify what's going on with the returns and the product attributes certainly provide a lot of insight into what John mentioned as the core you know the primary drivers behind your returns problem

Tiffany Serbus-Gustaveson 29:38

New England who knew go no, you guys must have like the the best like cocktail party attendees because you have like these random like stats in your brain of like what like how was that learned something new every day. Beautiful. Alright, myth number seven. Remember question comments, put them into the chat. My return rate is low. So

John Bowman 30:00

I can't reduce it. Right. Well, so this is an interesting one out. I, I think I would have to ask, right, someone is asking me this question, right? Or making a statement? Well, how do you know? Right? How do you know that you ever return a low return rate for the specific type of item that you're selling? Right. And, you know, one thing that we love to do is bring data to the table, across a wide range of clients in an industry to truly benchmark and understand, you know, what's a good return rate? The other question I would have is, is the return rate uniformly low on all your items, right? And we invariably find that it's not right there, there are always outliers, right? You'll always have, even if you have a category that has fairly low returns, like, I'm trying to think of one, perfume is one that tends have low returns, there's always going to be the one right that that's, for whatever reason, it's just not doing well with the customer, and they're sending it back. Right. And you definitely want to know that. Also, there are there, they're out, there are outliers based on the product itself, right. And but there's also outliers based on your operation. And since your operation is always in flux, right, you could have Miss ships that suddenly begin to occur because someone put an item in the wrong bin in the warehouse, you could have damage that suddenly occurs because you switch to care, you switch your freight carrier, and now they're not packaging it properly, right, you could suddenly begin to have shipping delays. And we find again and again that when customers are delayed in getting the item, they're more likely to return it. So I would say, even if you feel your return rate is low, there, there's likely a lot of opportunity to improve it. Not only that, but the data that you get about your returns even even on a relatively low return category, that data is going to help you to improve your customer experience, you'll have more satisfied more loyal customers, because you have deeply understood the reasons behind those returns.

Tiffany Serbus-Gustaveson 32:17

Since moving on to number eight, question comments, put them into the chat. Myth eight, I cannot act on returns as inventory is transient and or the sales volume is low.

Christine Bradford 32:32

Store. So fast fashion is huge these days. And a lot of retailers only buy, you know, a couple 1000 units of something, once they sell through it. They're done. So who cares, right? How can you help me? Actually, you know, we're able to using models, take a look at any new products as they launch on the site until you very quickly within 1015 items returned if it's projected to maintain a higher return rate for the life that it's on your website. So then you can be proactive, rather than reactive and say, Well, I couldn't do anything because it's now sold out. We can pick up on it very fast. So you can make adjustments, whether it be on the website in the operations process. But also it can inform your future assortment too. So as we continue to collect the data and understand what's happening, we can look at, again the product attributes, we can look at the categories that you're offering, and start to optimize your assortment or talk about how you can continue to improve about the the mix that you're offering, right. So even though you may only be buying 100 here and 100 there and 100 Here, let's optimize that and make sure that you are picking the right mix. And that we're calling things out super, super early. We have a lot of clients that are small volume, you know that we can certainly inform Limited Edition styles, we can inform, you know, special seasonal items. And then they have their carryover, right. And sometimes even looking at the returns data and comparing the two also provides a lot of insight to understand how does the core perform against some of the more transient, seasonal limited edition and how do we continue to optimize on that.

John Bowman 34:33

I almost think that data is more important when you have a low volume because you really want to get every bit of learning that you can out of out of those items when you launch a new set of items. Right.

Tiffany Serbus-Gustaveson 34:45

Absolutely. Great point. All right, number nine myth. Customers can read reviews to figure out their size so they don't need a size guide.

John Bowman 35:00

All right, well, I guess I'll say first that reviews are a source of sizing guidance, right. And we see this with a number of clients that those when you go to the PDP, you'll see, you'll see a recommendation, which says others have found this item True to Size or others have found this item runs large. And that would be based on a review data that they've processed. Certain vendors will do this. And then they they've put that recommendation there. Now, our recommendation would not be to rely solely on that. Because in many cases, your reviews are a pretty small sample. And your reviews are not necessarily representative of everyone who bought the item. We think it's very important to look at return data. So people will actually sent the item back, what are they saying? And also to look at things like bracketing and exchanges, et cetera, right. So we don't want to only look at reviews, especially when the volume is low. But that is an important data source that when it's combined with the others can be can give you really helpful guidance.

Tiffany Serbus-Gustaveson 36:17

All right, we are in our final two here. So number 10, the myth, everyone follows my return policy.

Christine Bradford 36:30

So you know, one thing I think we can provide great visibility into is understanding what percentage of your customers are following the policy versus what percentage or not, we do see a you know, about roughly 80% of returns do happen on time? You know, with the tail trailing? It depends on the on the retailer. But I think what's interesting, right, and I mentioned it a little bit before is what's happening with the rest of the customers? And are they returning things after the the return policy window that you can resell? Or are they coming back with things that have been worn, or final sale or damaged at this point. And so now you're going to not only accept it after the return policy, but you're going to have to consume the cost of shipping receiving and the goods of that item. So we've been able to help identify, you know, for certain retailers where you know, what they could recoup if they stopped allowing customers to return items after the return policy that were damages or defects and then say, maybe we recommend that they don't get a refund in the store credit, or something a little bit different, right. I mentioned the final sale example earlier. So we helped the retailer identify that customers are still returning final sale items. And it was a large portion of customers after the return policy as well. So we've been working with that real tailor to understand okay, is it the online portal that is glitching and not allowing, you know, is allowing a return that shouldn't happen? Or is it again, that store associate, and they have to do a better job in the brick and mortar to not allow those from happening. It also speaks to what John said earlier in terms of your your customers, right. So this is another data point, when we start to look at the profitability of your customer, are they also policy of the users. So if they're chronic return, or they're not profitable, and they're also going to abuse your policy, maybe they're not customers, you want to continue to market to or keep, or maybe when they try to return the next time you want to adjust your policy with them. So you know, certainly another data point that we can, we can help make those decisions.

John Bowman 38:58

I want to point out too, that we're in an environment where a lot of brands are becoming more strict on the return policy. So we're seeing more brands starting to charge for returns, even Amazon charging for returns in certain situations. So this may be a good time for brands to really have a start to enforce the policies that they have and be look at whether in certain cases they ought to be having an even more restrictive policy or a policy, where are they? The customer can bear more of the cost of the return.

Christine Bradford 39:31

Yeah, I mean, I think Nordstrom is a huge example of that. And this is all public knowledge. But you know, they used to let customers return anything at any time, no matter if it was used worn or whatever. And I'm a loyal Nordstrom member so I I know this happened. They've changed their policy. It's now there's a window of time that I have to go return my items. They can no longer be worn. And so they're they're certainly cut Getting back into John's point right now a lot of retailers are getting tighter with their policies, starting to charge for returns, etc.

Tiffany Serbus-Gustaveson 40:08

Yeah, that's such a great takeaway is like the time is now especially when you have Amazon, who is now retracting and starting to charge for those. And they really set that precedence of return anything anytime. We'll take care of you. It's really the time is now it's a great opportunity. Excellent. All right, we are in the final myth, questions, comments, put them into the chat in myth number 11. I have a dashboard and a team already analyzing returns. So there's no value in considering additional returns or analytic support

John Bowman 40:43

of the Smith? Well, first, I think what I would want to say, in this situation is the fact that you have a dashboard, where you can see returns data, and you have someone actually looking at that dashboard on a regular basis who's focused on reducing returns, that is amazing, that is better than easily 50% of the clients that we see, right, so if you're in that situation where you have that in place, that's, that's very positive. But I will say that there, there are many ways that having a partner to help you reduce and reduce your returns and improve your customer experience can be beneficial, right? Just just to pull one out of out of our clients, you know, there there are, it's difficult to pull the data together, in in the right way. And sometimes having someone else just look at the data and go through the exercise of merging that data together and understanding it. That in itself is valuable. Many times with clients, when we do that exercise, we uncover problems even in their internal systems. We had a client who, for example, wasn't properly crediting refunds when someone makes a return. So that's, you know, as as a brand, you know, there's value in just having someone look at that someone else look at that data, second set of eyes to uncover those types of issues. I also think, you know, we talked a little bit about benchmarking there, there can be a ton of value in working with a partner who has visibility into multiple brands, multiple clients, across an industry, right, helps you understand sort of, what are what is working in that industry, what is not working? Where do you stack up in various categories? Right? Is my, you know, 80% return rate on designer gowns? Is that good? Or is that bad? Can it be better, right? Those are the types of things that a partner can help you with. And, you know, I also think that there's, you know, a dashboard is great, but there, there are other capabilities, other analytical capabilities, that are really valuable when they're used along with a dashboard. One of those that we love that we provide is, is Automated Insights. So it's so you go in the dashboard, but you don't have to dig right, you have the insights automatically surface for you. So the most relevant, the most actionable, the most valuable, insights are right there for you to see and take action on. That's very helpful. Also, predictive capabilities. That's something that I think, at times, brands don't have access to right, to be able to understand well, what are the factors that are likely to lead to a return? What types of customers are returning? What types of products or even even what's the connection between the customer and the product, right? Customers of this type, when they're buying products of this type? What's their return rate, right, that we, we can get very specific with, with those recommendations using using predictive models. And then, another another area that we've seen some brands struggle is is understanding texts data, right? So you can get a mountain of text data from your customers. If you have a lot of customer reviews, if you're allowing customers to provide free text responses and their return reasons. That is extremely valuable data because you're having someone who is literally just telling you what they think what their experience was. But if you don't have something in place to systematically digest and sift through that data, it's going to be very difficult to act on it. So that's another place where we, we've, we think that there's value in having a returns analytics partner.

Christine Bradford 44:49

I'd also like to add I think a lot of what we hear too is I know what the category level my returns look like. I know at the brand level what my returns look like, but always or just show them at the SKU level, what the returns look like. And it's because of this size, or this issue, or these colors, and your assortment, this season just tanked and didn't work well, and maybe you don't want to do this canary yellow shoe again, you know, that's when they start to go, there's no way I could have been able to drill down to this level, or if I did, it would take me hours, and hours to go ahead and get there. You know, so the efficiency part of it, too, is also a value add in terms of being able to pull together the information quickly, and get down very quickly. Also, the looking at things across products and customers. So the engagement of your customers with your products and your categories. And vice versa can easily be, you know, seen within the dashboard. And I think, you know, customers will come to us and they say, I know everything there is to know about my products being returned, but I have no idea what's going on with my customers. So then we can also show them and say, Okay, here's how your customers break down, here's how returns are impacting them. And then here are the types of products they're buying and returning. And here's how we optimize, to make sure that you're acquiring the right customers and retaining them.

John Bowman 46:24

You can think about a partner as an accelerator, right? The your returns analytics partner they're taking, they're taking something that you're already doing, but they're allowing you to move faster, they're they're offloading some of that, that work that would, would perhaps right, take a take a long time for your internal team, if you have, you know, as many brands that we work with, you know, you have 10s of 1000s of products, that can be very difficult. So there's, there's help out there.

Tiffany Serbus-Gustaveson 46:54

Awesome. And with the brands that you're working with, who are the ones that are optimizing, and using a solution, like which analyzed to its fullest potential? Who are the stakeholders that are involved in the system? What teams are collaborating and working in that system day in and day out?

Christine Bradford 47:14

Yeah, so I think that goes back to the other myth, right? We talked about where it's not just one team. So it can be anyone from the eCommerce, digital marketing owner, to the merchandising team, the marketing, you know, lead the head of operations and logistics. Sometimes we have CFOs in there, you know, looking at it and understanding what's coming in what's going out and working on forecasting. So really, I think, you know, we have a lot of different stakeholders that are that are in there, and finding value from the tool.

Tiffany Serbus-Gustaveson 47:58

product development, product development.

Christine Bradford 48:01

Thank you. So yeah, left went out. Development for sure. It can inform those retailers that Do you know, produce their own items and can inform product development or, you know, pride themselves on product development? Absolutely. They can be in there to understand what's going on with their products so they can improve them for the next season or the next last run or whatever it might be.

Tiffany Serbus-Gustaveson 48:25

What a great solution to holistically bring an organization together and break down silos just because of having the data there that can help everybody. As you know, we get more of this omni channel mentality and business strategy moving forward. So very cool. Well, John, Christine, it was such a pleasure. The minutes were super fun, fun to debunk. You know, again, I'm not Adam Savage, but I don't think I'm gonna go watch Mythbusters after this. Thank you all for attending today. Greatly appreciate it. We definitely encourage follow up conversations, but the Returnalyze team and we'd love to have a conversation with you. That's how we get the content for our future webinars and in person events. So with that it is a wrap for seeing John, take care. Thank you so much for all the information and hope everybody has a lovely week. Thanks, Tiffany. Yes, thanks so much, everyone.

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