Aaron Conant  0:18  

Happy Thursday, everybody. My name is Aaron Conant, I'm the co founder Managing Director here at BWG Connect. We're a giant networking and knowledge sharing group with 1000s of brands who do exactly that we network and knowledge share together to stay on top of the newest trends, strategies, pain points, whatever it might be that shaping digital landscape, I spend the majority of my time just helping brands. And just connecting with them would love to connect with anybody on the line today. But just you know, having a conversation, what are the biggest things you're struggling with? And what are you trying to solve for him and the same things come up over and over again, we host an event like this. And so you know, a couple housekeeping items, we're starting three to four minutes after the hour. And we're going to wrap up with at least three to four minutes to go on the hour as well. Just give everybody a chance to get on to the next meeting without being late. The other thing is we want it to be as educational informational as possible. So at any point in time, if you have a question, drop it in the chat, drop it into q&a, or you can always email me Aaron Aaron@bwgconnect.com. And we'll tackle questions that way as well. When so now we kind of like kick off the conversation as a whole. What we've seen right now is a lot of people looking at different ways to grow the direct to consumer revenue. And a big hit on that is around returns. And so you know, what's really interesting as people has tried to tackle returns, there's just some innovative ways. So what if we can prevent them on the front end? And so we got some great friends, partner support is the network over at Returnalyze. We've done events with them in the past, and just have a lot of brands in that work, recommend them. And so it's going to be a great conversation. And Christine, I'll kick it over to you. First, you want to do a brief, brief intro on yourself and Returnalyze and we can keep it. Yeah,

Christine Bradford  2:08  

absolutely. Let me share my screen, I have a couple of slides I can share with you. As I'm speaking. I'll introduce myself, share a few things about returnalyze, and then I'll pass it over to Caroline. But thank you, everyone for joining us today. I know it takes a lot to take an hour out of your day. So we appreciate your time. My name is Christine Bradford. I'm with Returnalyze. And I'm really delighted to be speaking with you today. I want to thank Aaron and BWG for hosting this event today. And then also think Caroline Colavita, for joining the conversation with me. Our topic for today's Aaron mentioned is around how retailers such as yourselves can use their returns data to to not only reduce returns, but also increase the profitability. My slides I'm sorry, guys, where did my slides go? There we go. I'm like, why is it moving on me. Um, so how retailers can use their returns data not just to reduce the returns, but also increase your net profitability across the entire business, right. So Returnalyze is a returns analytics company, and we're focused on helping retailers take control of their returns. Returns is really a primary business signal that I think retailers often ignore. So imagine if you weren't ignoring that signal, and you were using that information to elevate your customer experience, gain critical visibility and insight into returns that can be prevented or avoided in the future. And also, in addition, increase efficiency and the bottom line across your entire business, right. So at Returnalyze, we really help you discern between a good return and an unwanted one or one that you can prevent in the future. To give you some examples between the two I'm going to use the Adrianna Papell business. So say the mother of the bride, she picks a dress, she loves the color, she loves the fit. And the bride says no. You have to return that dress. So I did that to my own mother who picked a color that was way too close to white and I said no can't wear that you're gonna have to return it mom. Or maybe she's picking you know, two sizes, right? She wants to get the fit, right? So she orders to she's gonna end up keeping the size that fits best and then returning the one that doesn't work for her. These are all returns that are naturally going to happen there. Okay? There's nothing wrong with these products right? Nothing's wrong. Nothing's impacting the customer. They're naturally going to happen. They you have a style though. That then is done. impacted by a manufacturing issue. And the gown is consistently delivered to customers with beads falling off. Right? So now you've got a product that the customer experience is being impacted because I'm I'm like, why are their beads coming off my gown? What's going on here, um, you know, Caroline's got a supplier issue, she's gotta go back, she's got to talk to the supplier and be like, Hey, what's going on here, and then you've got product shouldn't sitting on the shelf because it's damaged, and it's got defects. So if you were able to identify that issue, then you can get ahead of it, address it and avoid it from happening in the future. So at Returnalyze help you discern between your returns and really identify key business areas. What are the primary return reasons? What are the key opportunities across the business with the most recoverable revenue potential. So not only do we give you access to an intelligent dashboard, but we collaborate with you and work with you as an extension of your team. So what you'll hear today, from Caroline and I are going to be how Returnalyze partnered with Adrianna to help them reduce their returns, save on operational costs, and elevate the customer experience. I'm gonna stop sharing. If PowerPoint complies. And then Caroline, I can pass it over to you to introduce yourself and add anything else you want to add.

Caroline Colavita  6:27  

All right. Hi, I am Caroline Colavita. I'm the Vice President of eCommerce and digital marketing over here at Adrianna Papell and probably the happiest Returnalyze plan, we, we sell dresses and we still sell special occasion dresses specifically for weddings. So there is a lot of people looking for the perfect one dressed and they're going to be photographed all night long. So it has to be absolutely perfect. So as you can imagine, dresses have a high return rate Apparel has a higher return rate in certain categories. But then you layer in a special occasion event where you're the star of the show, and things seemed to really heightened in the returns area, we were very focused on the bottom line as most of you are and you know, instead of taking the cost cutting approach, we took the approach of let's focus on that sales. And let's attack this return rate where we can and really focus on the product and what we can do on our side from a digital aspect, which is really where Returnalyze has come in and been an epic partner.

Aaron Conant  7:34  

Here, if we jump into it, like questions that I get all the time around this space is, you know, maybe you can start by telling us a little bit around like, what is that analysis look like? What is the findings? What were those initial things? And we all know, high return rates are one thing. When you jump in, and you're like, hey, I think we can trick that. Because I think everybody on the line, it's like, yeah, you know what? So I've got four kids, right? We're ordering two sizes? Because the 14 year old might be in 1214. He might be in 1416? I don't quite know. But, you know, how do you spread that out? And what does that? What did that look like when you first jumped in? Because I think that's where we're at. People want to do their own little audit on the back end? That'd be awesome.

Christine Bradford  8:18  

Yeah, so we know one of the top reasons people return is due to size and fit. Right. So that is our low hanging fruit. That's where we start. So I think some of the initial things were able to identify for Adrianna was to quickly pinpoint and I areas and styles where overall maybe the style runs large or overall the style runs small, right? You all know that you're analyzing your data, you're looking at the returns, and you're thinking, Okay, what do I need to tell the customer so they get the right fit? Also, Adrianna had kind of this universal language of you know, if you're in between sizes just size up? Well, it doesn't work when you have different silhouettes, different body types, different fabrics, materials, all of that impact fit. And so we started with the eCommerce experiential findings, and letting Caroline know, you know, here's what's going on in the data in terms of styles that run large or small. And here are some best practices in terms of how you can provide the best information possible to your customers. So they're getting the right fit from the from the beginning, and not having to exchange and bracket and do multiple things. I'll pass it to Caroline to specifically share what we've implemented. I'm actually going to share my screen again and show you live on the site what we're able to do.

Caroline Colavita  9:44  

Yeah, so the so in part of our returns process, we've partnered with loop for returns and automation there. So we are partnering with Returnalyze updated the questions that we asked about why are you returning so the biggest thing that we have found initially what we just asked you was it too big or too small? With the big and small, we narrowed it down. If that's your choice, we're now asking specifically, where is it to base the bust isn't the waist isn't the hips. But what we've done now is we've created this funnel for alerts on, once the product hits certain returns threshold, if it is too big or too small, we're gonna put it right here on the product page right at where you select your size right before the CTA, and we're letting you know, in full transparency upfront, this style is gonna run big. So we made that decision pretty quickly last summer, and that we saw a really positive impact on the few styles that we did test. And this has now become almost a monthly cadence with Returnalyze and these alerts that we implement, and we can roll them out overnight. So that's been really, really a big help for us and a big help for the customer. We've also started to optimize some of our product descriptions to include a language that we've learned from the customers. If it's a soft dress, if it has please something to let them know why it might run bigger or smaller, depending on the fabric type, depending on the way that the Garmin is structured, which has really been helpful internal and to the customer. So it really helps us really full process along the way. In terms of the comment Christine made about the universal language, we actually ended up changing that to really let the customer know that we stand behind her if the dress if you're unsure, we've we've now recommended either set buying two sizes, but because of this one, particularly we we have put it right there in her face. Again, order size down, this one runs a little bit bigger, this isn't going to be your typical fit, or if your typical AP customer. This is where you arrange for this particular style. And then some of the other things that we have found is in terms of the fabric, we've now started to add what we're calling our stretch ometer. So this is a brand new thing that we're rolling out like as we speak, we have gone back to our design and merchandising team. And we've asked them, we had a whole stretch session in the office in our showroom, where we were pulling styles checking the stretch scale, they now have to put in a number between one and five. So not no stretch whatsoever, are very stretching, because we have found too that based on different body types, and the fabrication dresses are going to fit you differently, you could be a size four at every store. But depending on garment. So we've implemented this now and a handful of products will start rolling that out soon. And the goal is to have everything go forward, have our stretch ometer on this thing to let the customer know really in her face, how she should expect the government to fit when she gets it.

Christine Bradford  12:59  

Right, so I shared it up on the screen here you can see the stretch ometer. And then for this one, it doesn't have a clear indication of it running large or small. So as Caroline mentioned, we updated the language. So rather than just naturally sizing up, we're pushing the sampling behavior. So go ahead and try those two sizes on and keep the one that fits best. And we actually found that that increase the net revenue per order when she's trying on two sizes, because she's more than likely to end up keeping an item rather than just returning the one and saying it didn't fit or exchanging for something else and getting frustrated by the process. Something else that

Aaron Conant  13:41  

was good to see you in Crete? What did what went up the order value or profit?

Christine Bradford  13:46  

Yes, absolutely.

Caroline Colavita  13:48  

Our net revenue from those customers who bought so with the bracketing are now encouraging by two sizes. We want you to buy two sizes, we're encouraging you if you're in between and you're unsure, you don't know us, please buy them both and you aren't you're we have found through Returnalyze that she's more likely to keep one by ordering multiples than she is from ordering one size, hoping for the best and then returning.

Aaron Conant  14:14  

That's awesome. 

Caroline Colavita  14:16  

That was eye opening, 

Christine Bradford  14:18  

very eye opening.

Aaron Conant  14:20  

So encourage them to buy more than one

Caroline Colavita  14:23  

charge. So return something along the way. Right?

Christine Bradford  14:28  

The myth out there is I have to stop my customers from doing this because they're they're buying multiples. And that's not a good thing. When in fact what we're seeing is it's it's a positive thing because she's then more likely to keep something or we found, you know, in other industries and verticals. When she likes something, she's gonna buy multiples of the same color. And then she's going to keep the multiples in the same color. So again, it's beneficial to the business.

Aaron Conant  14:56  

Yeah. No, that's interesting, right? So a couple questions that roll in here. My industry is hard goods and housewares any learnings we can apply to my industry.

Christine Bradford  15:12  

In terms of, you know, this specific example with the bracketing, I'm not sure I don't have a hard example there. But certainly, there's a plethora of different PDP, experiential, best practices that we can apply across different verticals and industries. You know, today, we're speaking specifically about apparel and, and you know, but there's things you can do with shoes. So there's things you can do with houseware, to make sure that you're providing the best experience and the most information as possible. I'm sure, there's got to be some sampling insights in there as well, that can be applied. It also varies, you know, by by brand and retailer as well.

Aaron Conant  15:59  

So do like so they're doing a deep dive, and then around, Hey, why are people currently returning? What are their comments? Yeah, right. And then how do we get the most Oh, go ahead, jump in, please.

Caroline Colavita  16:10  

I was gonna say what we did find, actually, in terms of the bracketing while, while we found a lot of success in the sizes, there was one particular dress that was constantly being exchanged from one lighter color to a darker color. So we actually photographed them side by side and put more of like, this is pink, and this is rose gold. So we did find something there too, that there was some confusion almost within the color basis. So something could could potentially work when it comes to home goods. And that space when it comes to colors. If someone's unsure about textiles, or really where they're going to land in that area,

Christine Bradford  16:49  

or sizes to sometimes awful with sizes when I buy online. I'm like, oh, no, I thought this was going to be this big and it and it's not right. So if you're buying kitchenware or things like that, and I wouldn't know in terms of the sizing to get it right, and then maybe I want to buy multiples, to see if I want the bigger pan, the smaller pan the you know, whatever it might be. Awesome. Another

Aaron Conant  17:15  

question that comes in. And just a reminder, anybody if you have questions, drop them in the chat or the q&a, or you can email them to me as well. Tracy has one here, do you offer free returns in this situation? Or is the customer paying to send the extra size back.

Caroline Colavita  17:29  

So on the product page, we list that the return policy still applies, but for those customers who do reach out to us, and reach out to our customer service, we waive any return fees? You know, we're the ones encouraging this, were the ones encouraging you to buy multiples, I don't expect you to have to pay for it. So more often than not, they're reaching out asking for the refund. And I'm happy to do it if they're keeping the items.

Aaron Conant  17:55  

Right. Got it. So it's a case by case basis. But for Yeah, interesting. Awesome. All right, the next one. So Kate, since in question, and thanks, everybody for the great question. So then do you charge a restocking fee.

Caroline Colavita  18:12  

So we charge a flat 995 fee to return the item and we actually returned? We might sound a little counterproductive. We we changed our return policy earlier this year that it's a one time dine 95 fee for your first item essentially. And then we charge you $5 For each additional item as a restocking fee on return. So that was really to hinder the abusers. You know, we found some people quite literally would order 27 dresses and return 27 dresses. So that was really put in place to just stop the bad behavior. But we do have a restocking fee at the moment, man. Awesome.

Aaron Conant  19:00  

Have you ever so another question that comes in over email then and we can jump back to some returns here as well as do you ever offer credit instead of restocking fees? So instead of giving money, you know, instead of giving them their money back offering them credit instead and then waiving the restocking fee? Like how do you keep them as a customer, I think is a

Caroline Colavita  19:20  

1. So we do offer in the returns process you can get your refund, you can get a store credit and come back at your leisure will we waive the return fees. We also offer a shop now with a credit where we'll give you an additional I believe it's $20 if you make instead of refund or waiting for another purchase if you make another purchase right now this session will give you an additional credit to do so in a moment. Awesome.

Aaron Conant  19:50  

Next question that comes in is around bracketing. Can you tell us more about bracketing and how you and your team have been able to use what you've learned?

Christine Bradford  19:59  

Yeah, thinking, you know, it goes back to what we were saying earlier that we found it was more beneficial if she tried on the few sizes at home. So we were able to use language, you know, we've seen this across a few other retailers, and then they get stuck. And they're like, Well, how do I tell my customer to do this? Caroline's awesome because if she's willing to try things and test things with us, we're like, Hey, give this a shot, just just tell her in the copy. You know, if she feels like, she's in between sizes, instead of just telling her to size up, let's just push her to get, you know, both. And then she's been able to mitigate on the back end, right the the restocking fees or the return fees and and appease the customer the right that way. I mentioned it earlier, too, we used and Caroline, you know, said this as well. But through bracketing behaviors, we were able to identify that she was trying to also pick between light colors. So, you know, obviously, bridesmaid dresses, they come in a plethora of different shades and hues. And she was trying to figure out between these nude, you know, rosy gold colors and champagnes of Which one were the best ones. So the bracketing behavior helped us identify actually a problem that the imagery was not portraying the colors correctly. So then Caroline was like, why don't we just shoot them side by side and start showing the products side by side to be able to allow her to differentiate between the colors. So again, by understanding the behaviors, we are able to apply different types of tactics and test different things, to then ultimately reduce the returns increase the net revenue per order, as we mentioned earlier, and play around with with different strategies on on how to resolve the issue at hand.

Aaron Conant  22:00  

Awesome, if you also seen this another question that comes in around lifetime value of the customer, have you seen this impact that side as well, I'm thinking, you know, customer retention, customer satisfaction,

Caroline Colavita  22:13  

we were, we're just starting to see some increase in the retention, right, we started with Returnalyze, last summer, almost a year ago. But what we have found in our business particularly is the lead time for her second, and then consecutive purchases, starts at 180 days. So given that it's such a big purchase in her life, and that it's really a particular dress, but what we have actually started to do is working with the Returnalyze seem to talk about retention scores. So we just have recently started diving into, okay, if she buys product 123, she's more likely to come back and buy product for five, six. So now how do we target those for those specific groups first, and tackle those instead of trying to take a really larger approach to let's just get everyone to come back. We're really diving into product sets or product categories to talk to her about her second purchase and try to get her to come back sooner than the six month mark.

Aaron Conant  23:13  

I mean, it just makes sense, right? If you make it easier, and it works, because that's the most frustrating thing, right? I know there's getting the color right. But getting the fit, right is the most frustrating thing. And regardless of how easy returns are to do, they're, they're all around a pain. Yeah, right, you somehow have to get a return authorization form, you somehow have to get a package either drop it off, or somebody's gonna show up. It's you, Marian, I'll be leaving it on your front porch. It's it's all around a pain, if you can make it easy. That's what I was thinking in the back of my head, and you can identify who that is. But then also, you can identify those people that you made it really easy for they go in a different bucket. Right? Yeah. Completely different buckets. Awesome. Still, some great questions coming in here. So have you started gathering any customer feedback on these soft measurables? Like stretch, comfort, etc? Via customer reviews? And if so, are you showing those on the PDPs? And are they swaying customer behavior? So kind of a loaded question there? 

Caroline Colavita  24:23  

We just started putting that particular piece out there. So I don't think we're gonna see anything yet in terms of reviews until probably for another few weeks. But we'll be happy to follow up with that for sure. Because that is hot on my list. Okay, we just launched the stretch. We just launched more inclusive information on the product side. We'll we'll have measurements probably in the coming weeks.

Christine Bradford  24:50  

We're definitely using that data though to inform future product buys and assortment. So or just development right so we did find in the data Were the sleeves were not lined, they were, you know, it was itchy to the customer. And so that she was returning it because it was uncomfortable. So what then the product team was able to do was go ahead and line that sleeve, and make sure that that was resolved. Again, looking at different cuts. And using that information in terms of her preferences of how things are cut, or again, a flutter sleeve or a surplus, we can then inform product assortment. So it's not necessarily also to speaking to it on the site, but also using the data to then inform to improve your assortment for the future. So you may don't come across those types of returns or issues in the reviews in the returns. And you know, moving

Caroline Colavita  25:45  

forward. Yeah, we actually right example of the surplus we, we were seeing customer comments that it fit, but it didn't fit in the bus. And it was just something strange was going on. The return rates were high for that particular category, we ordered quite a few pieces from stock and multiple sizes, women in the office tried it on to the point where like right then and there while we were trying to monitor we could see it on ourselves on different bodies of different sizes, we changed the construction of the garment for that type of styling go forward, which we'll see come fall, just given the timeline on that. But we were able to action on that pretty immediately. And I actually made people office change. But it worked. And we figured out what the issue was and how we can remedy it go forward. So

Aaron Conant  26:34  

you're using it then Christine, if I pull that thread as well, and then you know Caroline, from your standpoint, you're using it for product design, revision. Yeah, future products are coming out. So then you can factor out hey, this material used on the inside, don't ever use it again.

Caroline Colavita  26:40  

Yeah, right. Yeah. Three dresses to Christine's point on the entry sleeve, we have three styles that have gone back into work into production, that they went back and double blind the sleeve with a softer mash. And that we've we've got that coming in in a couple months.

Christine Bradford  27:07  

I think you know, that's an area of the business that retailers don't think they can apply returns data for where we're trying to change that paradigm in that conversation in the space to say, you can absolutely use your returns data, even though it has high grossing sales. What are your net sales looking like? So you can say, Oh, well, it sells all day, but it has an 80% return rate? Did you really have high sales? So I'm the merchandising team at at Adrianna has been using our dashboard to look at the styles and understand what are the net sale performance and what are the return rates. So they can inform future buying decisions. So what the team has been able to do and I'll name a few and then let Caroline speak to some others but they removed the petite offering completely if it wasn't working for the business, the returns were too high, the you know, net sales were too low. So we just nixed it. We've done a lot of looking at what the product mix should be Adrianna Papell historically is is an occasion where it's a mother the bride item. But to get her to come back, she needs something else instead of that just one you know, once a year, maybe special occasion. So we talked about let's shift the product mix and start adding some daycation and getting more heavy and D occasions so then she either comes in on a you know an item she wants to wear to the office or on a date night and then moves over to an occasion or vice versa. And that speaks to the LTV that you're talking about to Aaron earlier. Oh Caroline, if you have more you want to add to it? 

Caroline Colavita  28:55  

Do you cover about one?

Aaron Conant  28:59  

No, that's awesome. And just reminder, as people have questions, keep dropping them in there. So this is the next question that comes in. So roughly the size of the company so I'm not sure you know how comfortable you are. We can share large,

Caroline Colavita  29:17  

let's call us Medium. Medium, in our eCommerce website is is a healthy size and we're in a medium space overall the company that we also are traditionally wholesale so you can find the palette, Macy's, Nordstrom, Bloomingdale's, Dillards, Amazon. So what we've actually started to do on that side is where we're not only looking at our DTC return rates and that sales, we're taking all company sales that we have access to and we're checking the return rates across the board. So we have taken you know, this conservative approach to income but layered in every any data point that we can get our hands on from all the omni channel, that anything that we have. And we just started working on that in the past few weeks finding areas of opportunity where Lacy's might be blowing out something that sales, we should add it to our assortment, or just benchmarking our return rates against everyone else. Is that a color issue from an image? Is it? Does Macy's have an issue? Do we have to replace their images? So we have started to learn within our larger approach for the company?

Aaron Conant  30:31  

I'm just thinking even from, you know, for those that are in brick and mortar as well, getting a heads up early on. So you think about that issue one, the last one you want to sell into a Macy's or Nordstrom? Right, you want to know that ahead of time in that material? And you can write it Yeah, because you don't want to take those technically, those returns back from Macy's as well.

Caroline Colavita  30:56  

Sadly, we're typically first to market so we're able to share these insights. So we actually have our company merchandising team just like out of Design and Merchandising on our bi weekly calls. So they're able to get out ahead of any sort of production issues like that as well. If Macy's doesn't have it yet, how do we mitigate that immediately, and make sure that back when we stopped, and we're trying to be much more proactive? In that approach?

Aaron Conant  31:19  

Awesome. Love it. So keep dropping questions. In the q&a or the chat, we'll keep getting them answered. What about the pricing side of things? Are you using it to do anything to guide you know, on the pricing, or pricing sensitivities and stuff like that, we are

Christine Bradford  31:38  

going off of what Caroline was saying. So we are using the you know, the retail data and the online data to understand, you know, because every retailer is pricing the products differently. So we're able to identify, you know, where Adrianna Papell may have been providing promotions too early and dropping prices too early, where it's working at the retail locations and calling that out. Or we were able to identify products that were performing really well at retail that they weren't pushing online. And so being able to do that, I'll also give another example that's blinded for another client of ours, where they're noticing they have now trained their clients, or their customers to be price sensitive. So she buys all our product. And then she's like, Oh, but I know that that sales going to happen tomorrow. And so then she returns everything and then buys everything again at the sale price. So you know, by understanding the returns behavior and being able to look at returns by price, via an omni channel view, by a customer level, then we can inform the business, hey, maybe you shouldn't be pushing this promotion at this time. Or maybe you're you're pushing too much of a promotion, where you shouldn't be because it's doing well it Macy's or Bloomingdale's or wherever.

Caroline Colavita  33:05  

The other thing that we've started to explore at price point is the actual ticket price. And the impact of you know, once you hit 285, you're gonna see the returns skyrocket. We're up to 79. And below, there's a little bit of a sweet spot. So we're now trying to figure out how do we take these products that they have high gross sales? Is there a price sensitivity at over $300 for example? And do we just make a different version of that at a lower price point that will end up sticking with the customer? So we've started examining the price tickets in specific price buckets and figuring out the lower return and high net sales within each of those.

Aaron Conant  33:50  

Are you also then working in like cross sell upsell?

Christine Bradford  33:53  

Yeah, so that was super fun finding where Adrianna has these, you know, the raps on a cold night you want to wrap yourself up or whatever it might be. So they were doing really well at retail, but we were really pushing them online. So what Caroline did was they added him to the checkout process as an upsell opportunity. So it increases your basket size, the return rate on them is super low. They sell a lot of them. And so you could do it at the checkout process, or we've made recommendations based on you know, again, of products with a high retention score to complete the look. A lot of retailers are doing that, right. So complete your look and you can push items that perform well have low returns, to go ahead and increase that basket size and upsell cross sell products.

Aaron Conant  34:56  

Awesome. Love it. Love it. Oh Um, are there. So another question comes in around being in stores as well and the omni channel view? You know, are you we talked a little bit about it, but are you able to then grab that data and ingest it in the program to? What does that? How do you look at the omni channel returns if we're in, in store, right? We're not just talking about marketplace we're talking about in store.

Christine Bradford  35:23  

Yeah, yeah. So the dashboard allows us to see, did they buy online return in store? Did they return, you know, buy in store return online? What does that look like? We know that returns online are higher than they are at retail. But it certainly helps. As we've given you guys, I think of several examples now of how you can use that information and the omni channel view to just improve right and increase your net sales, reduce returns, optimize? So absolutely, the system can see all of that. And I think that's where a lot of retailers get lost, because they're like, how do I marry my old point of sale system and my online data and put it all together and out return allies, we really help our retailers bring all that into one view, which is then helpful to the retailer.

Aaron Conant  36:17  

Yeah, that's, that's awesome. I'd love to hear your thoughts on that, too.

Caroline Colavita  36:23  

I mean, well, first, on the dashboard aspect, it is the easiest dashboard. And so user friendly, you know, they've certainly made it really, really accessible for us to in between our normal conversations are the insights that they provide on a bi weekly basis, we're able to go in in real time and pull anything that we need. But for us, especially with with an omni channel approach, we have been able to, look, we've looked at things blended, we've looked at things, you know, in store versus online, but having the the ability to discern, okay, if we're looking at our return rate compared to a Macy's return, right, what's happening with Macy's is all that happening, where it's online and online. What can we do to help them there, or if it's all happening in stores, we can then dig in and work with the Macy's team to figure that out. But being able to just quickly see what's happening and where it's happening has made him it's mostly on the time savings. And it allows us to action on it when otherwise we'd kind of be spinning in our chairs, just hypothesizing about what it could be.

Aaron Conant  37:28  

Awesome. And just reminder, keep dropping questions in the chat with q&a or email them to me, we'll we'll keep answering them. What about, like, are there other ways that you're using this data? So that I think one of the key things that I'm taking away is, you know, across the board right now, we have to think like next level, right, we're doing that as a paid media side, we're doing that on the paid search and social side. And now we're actually doing on the return side, where it's not just enough to just get returns, accept returns, and look at customer reviews is the blending across the board and then using it, you're saying like product design, you know, product updates, new product launch, like what are we doing as a whole to make sure we're getting the best possible product the first time around? But that kind of begets the question around like, operations supply chain. Do you see it affecting, you know, that side like earlier on is as well? Right? Kind of wondering, yeah, yeah. Anything there you can learn from returns data is I just think there's an there's probably three more spots that we're in pull, returns data and leverage. Yeah, I think

Caroline Colavita  38:38  

sort of, like Christine touched on very early on was for us specifically. Our beaded garments, for the most part are handmade, and they're hand beaded, and China, mostly Avandia. So what we've been able to do is take customer reviews, we measure all of the damage rates on our site, and we're able to take those particular products use and go immediately back to that factory and talk to them and talk to our team over there about any quality issues and how we can mitigate them upfront. And then what we've actually started to do was, while we are talking to the factories to be more proactive and talk through any issues that we bought over there, we implemented a damaged system in our warehouse where we now have someone who can fix any minor issues. They do the repairs right on site, we're able to save that stock, put it back in and resell it.

Christine Bradford  39:33  

You also changed your packaging Caroline. So that's been

Caroline Colavita  39:36  

our packaging, right? We actually checked her well.

Aaron Conant  39:39  

Another great one. Yeah,

Caroline Colavita  39:41  

it's a it's it will actually be delivered at the end of April. So we are we ship flatpacked and we found that there was some damage issues where the garments were getting dirty just from being on the conveyor belts and just being thrown around from FedEx. So we went back and we've changed our poly mailers to a much thicker bye bye It will be coming in two weeks. Yeah.

Aaron Conant  40:06  

If you see other stuff that you're seeing, like I, it's just amazing to me, that's that's what it is. Because, you know, a year ago, you know, people were thinking about this, but I don't think it was such an immediate need to kind of address all these different issues. And then even if they did, didn't realize, you know that in this solution, it can have a positive net impact, and so many different areas of the company. Anyways, besides customer satisfaction and lifetime value. Yeah, Christine, there are other areas that you see that have popped up like that as well.

Christine Bradford  40:43  

But yeah, that Mark is getting the marketing spend and the marketing strategies you don't think to use your returns data there. But you know, you want to shift your spend. Again, it's just like the assortment piece. When you're telling Google and paid search to promote certain products, don't promote the ones that just sell really well promote the ones that have high net sales that have low return rates, and shift, you know, your marketing spend to adjust to those products. So we can provide recommendations at the product level and at the customer level. And what Caroline has been able to do is, is take our recommendations and insights and just give it directly to her agency. And then they go in and they adjust for marketing spend, and make adjustments based on the recommendations that we're making from what we're seeing on the product side. And I think a lot of times people don't even think, Oh, my God, let me you know, let me take my data and apply it to my marketing or we had a really fun conversation the other day, we have this one Stiles giving us a lot of heartburn.

Caroline Colavita  41:59  

That's an understatement. Yeah.

Christine Bradford  42:02  

We've been trying to, you know, identify what the issue is, with this item, it has a lot of grossing sales, but again, a lot of high returns. So how do we optimize it? How do we improve upon it, and then we noticed, you know, the plus size version of it does really well. And so Caroline's, like, I'm just gonna push out in my email marketing, the plus version, and just sell more of that, because it's doing the best. And then let's just pull back on the Missy version. So again, just taking the returns data information and understanding what's working, what's not, and then applying it to your marketing Strategy.

Aaron Conant  42:44  

Know It, it's awesome, right? Especially a new product launch. Like everybody thinks you want to pump. But if you start getting the returns, yeah, stop the spend on it. Right, divert it someplace else, until you've got it figured out or updated. So

Christine Bradford  43:01  

Right. I mean, we send alerts to Caroline on a weekly basis, and it's all picking up those new items, um, that hit the, you know, the threshold where our algorithm is saying, if you don't do something, now, it's going to remain a high returned item. So then she can quickly take action. And then to your point, Erin, she can also move her spend, let me move my spin for now until I fix the problem with this product. And then I can put the focus back on to it once it's resolved. So you,

Aaron Conant  43:34  

you know, Christine from your side, you plug in on the back end of the website. That's next question that comes in. Are you SaaS based platform that plugs in?

Christine Bradford  43:47  

We can plug in Yeah, we, you know, we're SAS based, if there needs to be interaction, where we're feeding stuff back to the retailer and retailers feeding us data. Guess

Aaron Conant  44:01  

how long that question is? Just how long does it take to implement the return? Why solution

Christine Bradford  44:06  

on average is about four to six weeks. It's a quick implementation. We take all your disparate data systems actually, Adrianna I think was up in three weeks.

Caroline Colavita  44:18  

We were chatting three weeks. So it can be done. It can

Christine Bradford  44:21  

be done very quickly. Um, you know, we move as fast as you can move. We go ahead and collate and merge and manage all your data. You can give it to us how it, you know, comes out of all your different systems and it will handle

Caroline Colavita  44:36  

it for you. Yeah, yeah, we're guilty of a lot of data dumps and help. Just here, please help us and every single time they found something for us.

Aaron Conant  44:48  

If you're where does this fall in in your priorities? Because I think originally it's my original onset of this call. I would thought it would have been a little bit further down. But now seeing how many different parts of the organization it can actually feed data into. It's up about five notches.

Caroline Colavita  45:09  

But it's literally my number one priority. Right? Literally, number one, it and when I say number one priority for me, that is net sales. So whatever that means to increase net sales at the end of the day, that gross sales are great, but it's not what's hitting the bottom line. It's not what's driving the bottom line for me. And that's truly all I care about. So what we're eternalized has done has, we have seen a five point reduction in returns year over year, we've seen a significant increase not only in, in just the sales and what what's sticking, but all of the costs associated with returns and everything else along the way, everything increases from there, you know, you don't you you are not paying for the logistics back and forth, you're not paying for freight, you're not dealing with, you know, my grow as has to be based on some crazy arbitrary number, because the returns are so high, everything else has a positive impact as soon as you see those returns coming down.

Aaron Conant  46:05  

Other things that you thought would have come up today, but didn't. And I'm going to kick that same question over to Christine. 

Caroline Colavita  46:14  

No, I think we,

Aaron Conant  46:17  

we've done other questions hit a lot of of it was, yeah, a

Christine Bradford  46:21  

lot of them. I think, you know, some other things that we've done, and Caroline spoke to it, we've optimized the return policy, and we're testing that we've changed how we capture the return data. And we've tested that and we're adjusting that. We've worked together to send out additional surveys to question, you know, returning clients to get more data. We've been pretty scrappy, and really applied that returns information across the entire Adrianna business. And they're really, you know, the sky's the limit of what you can do. As long as you're, you're willing to be flexible and test and have an open mind and, and take that feedback and act. Sometimes it doesn't work. And we've had to, you know, make adjustments there too. But we really, you know, try to be an extension of the team that we're working with and truly be a partner. And I think we've covered quite a bit that we've been able to accomplish.

Caroline Colavita  47:21  

Yeah, we call Christine, our chief returns officer internally. So she's, as far as we're concerned. She's part of our team, the whole the whole personalized team, everyone. They've been such it's made such an impact for us.

Aaron Conant  47:33  

I think that was another point was like, Christine is noticing, like how much you knew about the business, which is really cool. She had a hands on piece at retail. That is That is awesome. I mean, I don't have any other questions that have come in. I always like to give people the gift of time back. But you know, both of you guys have been so awesome. Really appreciate, you know, you get your time today. More than happy to connect anybody on the call today with either Caroline or Christine asking for 100%. And Christine, you guys are just awesome friends supporters the network and look forward to having future conversations with both of you. But with that, I think we're going to wrap this one up. Thanks everybody for the great questions and dialing in. Hope everybody has a fantastic Thursday. Take care stay safe and look forward to having you at a future event. Already.