Talk to an Expert

Fireside Chat: Paloma Truong, Head of Customer Experience – Algonomy Personalization Summit

Fireside Chat: Paloma Truong, Head of Customer Experience – Algonomy Personalization Summit

Share it on

Personalization lessons from Miinto: Prioritize customer experience, business goals will follow.

Welcome to this next session. My name is Thomas and I’m Director of Customer Success at Algonomy. In this session, you will learn some really hands on tips and tricks from Minto that have a really unique business model. And I’ve used permutation to solve for some of those stores challenges. And I will share some really great results with us and insights that you can take home some DNA really some results that are really dynamite. So use your pen and take notes and I’m super pleased to be here also with Paloma from into to share their story. Paloma is a true Rockstar that has built their team around customer experience, and has been also growing into from startup to now our really big player in the market. So a big welcome to Paloma, thank you for joining us today.

Thank you, Thomas. I’m Paloma and I’m Head of Customer Experience admin. So very, very happy to be here to share some insights with you guys. So today I’m going to run you through how we’ve been using personalization and we’re to be focused on customer experience across the entire customer journey to drive significant business impact. So I hook you up for that. Great, so we are Miinto and if you don’t know us yet We’re an online fashion marketplace operating in 30 markets. And we definitely one of the fastest growing marketplaces in Europe, we’re actually going through a very fast internalization process and with the six of the 13 markets that were just opened last year in the fall, and quite a few more in the pipeline coming up in the next few months, and the next few years as well. So we’re now reaching a gap of more than 2 million euros with, with actually the vast majority of which like, pretty much 75% coming from mobile. And we’re going through a very fast pace, with a growth rate of more than 50% year on year, we also welcoming every year more than 100 million visitors. And we are positioning ourselves in the LT premium to luxury segments, with a pretty high basket size of more than 200 euros overall, across our different markets. Yes, and what what’s the essence of what we do, I would say is, is basically growing fashion retailers, because as I mentioned, we are a marketplace. So we don’t have any stock, we actually work with more than 2000 of the best independent boutiques around Europe. And we sell their products on our platform. So if you, if you if you want to know a little bit more about the business model, I would say that the idea behind Miinto comes from the actually pretty sad reality that there is a lot of waste that is done in the fashion industry, you might know that 30% Of all the clothes that are produced are actually never sold and never used, which is really a very, very huge number. And the problem is a lot of the traditional ecommerce stores, they’re asking the brands to produce even more stores store stock, sorry, although there is a lot of stock already in the markets and already in the independent boutiques that are having a really hard time actually very often selling this stock. That brings me to basically what we offer our partners and that’s basically the possibility to get an additional source of revenue by getting their products online on Miinto and also advertised to a very, very large number of very large audience of international buyers. While at the same time being able to, I would say leverage the expertise that we have internally in terms of marketing in terms of E commerce in terms of you know Digital’s user experience, also into the supply chain and so on which things that they don’t necessarily are able to deal with themselves because they don’t have the structure for it. And on the on the other end what we offer customers is access to a very large assortment and also very diverse assortments due to the fact that we don’t have only one creational team but we actually have more than 2000 partners that all have their own style they all have their own assortment their own traditional team and that gives us a very, very deep and rich assortment. And as matter of fact we do have a very wide assortment and it is the widest assortment in Europe we have more than 800,000 unique skews across different markets and this is getting even the largest players in the market mostly position in the Luxury and Premium segments, but we do sell a lot of the what we call the local heroes meaning brands that are very popular in one markets and that the customers in these specific markets are very interested in is important to mention is that we don’t see like the we don’t see one shopping pattern we can see that our customers are not interested only in one type of products or when segment of products as a matter of fact the shopping patterns are very difficult to predict and they were very complex. And we can see that more than half of the of the customers for example that are buying a premium brands are also interested in products and not premium. So it really you know it is quite complex and it is very difficult for us to know exactly or to predict exactly what the customers are going to be interested in.

So I would say that that. That brings us to that brings quite a few challenges. The first one is really like the size of the assortment. As I mentioned we have a huge assortment. So what we’re thinking about is how do we make sure that our customers are finding what they came on Miinto for so what they’re looking for, in such a huge number of units use the second challenge that we that we have an which is free add to that is how do we make sure that internally we have the structure in place to offer a personalized experience, precise digital experience to every one of our customers, while also being, you know, mindful of resources, and not while hiring a million people. And the last challenge that we’re facing is related to the fact that we regenerate the vast majority of our revenue on mobile. And therefore, we, we have to deal with the fact that it is quite tricky to give a good and personalized experience on a tiny device, I would say the answer to these to these challenges is, is of course, very complex. And I think a lot of companies are, you know, or are looking and working on these challenges and how to address them. So I’m only going to talk about our own experience and how we’ve been dealing with it at Miinto. But the answer to these challenges for us has been to really focus fully on the customer experience, and really run it as a strategy across all our different channels of channels. So looking at a value proposition so that I already mentioned it, but what we offer to our customers, and what makes us really different from other players in the market is of course, the access to exclusive and popular products, but also at a great price. So I didn’t mention it before. But you know, we do have a lot of attractive offers. And it is very important for us to be competitive in the market. So to offer these products at prices that the customers are going to be interested in. But I would say that, you know, all these assortments wouldn’t like, would not never be able to generate such great performance and growth, if we if we were not able to offer personalized experience to our customers. And so this is what we do, we personalize the experience on the sides of who all the touch points that the customers have. So it’s not only on the food product recommendations, we do have, of course, different product recommendations, and the key touch points of the journey. So for example, as you can see in the video in the middle, right after customer places, product in their basket, they will get some nice recommendations on other products that we believe or we are the engine or the goals and beliefs they’re likely to like. But on top of these product foundations, we also personalize the experience on the product catalogue. So the product lists. So basically, when the user is visiting the product list, they will see the products in a different order than another user, because it is based on their purchasing and browsing history. And we actually also personalize the experience in terms of content. So basically the images that the customer see on the site. So if we’ve identified for example, that the user is a male, they will see different banners than if we’ve identified that the user is a female, that’s just one example, but based on you know, the data that we have about them and what we know about them, we will personalize the content that they will see on the site to make it as relevant as possible to them. So, we really use personalization across the entire websites to make the journey as relevant and personal, of course, as soon as possible.
So, I mean, I must say that, you know, it is very important to, to do customer profiling and to of course, use data and to know our customers, because we have to be aware of what who they are, what kind of motivations they have, what kind of pain points they have, we can have aspirations they have, of course, which type of products they interested in and so on. But, you know, having this knowledge is great, but the key challenge is how to how to use it, I would say and we you know, it is possible to personalize experiences and create some specific experiences manually if you have a limited number of markets or a limited number of customers, but it becomes much more difficult if you have a lot of markets, like we do. And in this case, you know, the manual approach is simply not possible anymore. And that’s why we are basically relying on technology to be able to scale personalization across the 30 markets that we have. And, you know, we have a pretty lean team, we actually only have two customer experience experts at Miinto that are spending maybe, you know, 15 to 20% of their time, managing personalization across a 14 sites. So it is definitely a pretty lean structure in terms of, of human resources. But we use technology of course to, to leverage human creativity. And I would say, give it some horsepower to scale personalization across the group.

Thank you, Paloma. This is really dynamite. I mean, this is super interesting. I know working myself with many customers over here. Many are discussing how to best organize internally with pronunciation. And, I mean, mean to then using pronunciation for not only product recommendations, but content and categories, and search really puts it to a challenge. And you running it for so many different sites and regions, with just two people and with so little time for each person. It’s just almost like a success story. I mean, what has been key to achieve yours? What are your thoughts for how to set up such a scalable approach internally?

Yeah, so I would say that, that’s where it all like I’m gonna me, of course, of course comes into play. Because it has been the key for us to, to be able to scale the experience so many markets with such limited resources. And again, like it would be impossible for us to achieve these results and to end to be able to cover so many markets and really personalize the experience across the entire website without, like going to me. So this is this has been, yeah, the key to one of the key to our success in this area for sure.

But looking at personalization, you know, I’ve been I’ve been talking about personalization on the websites. But I think it’s important to mention that we don’t only use personalization at this specific touch points, but we actually use it across the entire journey and the entire lifecycle. I would really like to run, like give you a little bit of insights into you know, what, what, what we’ve been playing around with in terms of personalization, because it all sounds, you know, very, very nice and easy. And, you know, like, I’ve only been sharing pretty good success stories so far. But the reality is that we’ve, we’ve actually been testing around the lots, and we’ve been experimenting, and you know, we had some wins, but we also had some failures. And I would say that’s part of, you know, that’s part of the building an experimentation, culture. So I think it is, it is always good to share a little bit of that with other, you know, other players in the market just to, to inspire, to inspire others to maybe go in that direction as well. And one of the first tests that, that I think is very, very interesting actually to share is a test that we’ve been doing on the browsing experience. So basically on the product catalogue or product lists. And here, we use a already mentioned, but we use Algonomy to personalize the experience. So basically to personalize to share our products, to sorry to just to share products that are personalized to that specific user. And we’ve been trying to play around quite a bit with that threshold. So to find the ideal spots of the ideal share of a product assortment that would be personalized to that specific customer. And the default setting is actually 25%. So meaning that 25% of the product that will be seen by the user would be personalized to them. And we’ve tried to we run several AP tests, and the first AP test was to bring this year from 25% to 50%. And as you can see, we saw actually a pretty good results like already a 5% uplift in the revenue per visit, which is you know, quite, quite significant. We were already pretty, pretty happy with that. Also increasing conversion rate and the in the average order value. So we were really happy with the result really excited with it. And we so we changed all the default setting from 25 to 50%. So meaning that handful of products would be personal to the users to the user and the other had food be you know, sideway bestsellers or other products that we think would be relevant for them. But then I thought a little bit later that I wanted to go, you know, a little bit like the extra mile and play around with it a little bit more. And so I launched a second AB test, where I increase the share person zoom from 50%, to 6065, and 70. So pretty high share of personalization, if you if you ask me, and at that stage, I was I was kind of skeptical because I thought, okay, it’s 50 is already a lot. And I don’t believe that we can go much higher without, you know, hurting experience. But it turned out that I mean, this is these are the results from one specific market, but still very interesting. But it turned out that for that market, 65% was the actually the sweet spots that that gave the highest uplift in the revenue per visits. And as you can see, as soon as we got to 70%, which is really like a, you know, pretty minor difference that at such, we could see an actual decline in the revenue per visits for the sessions. So, you know, that really taught me that there is a really fine line between being relevant and being invasive. And that it is basically impossible to guess, you need to test and you need to try different things and set up some AP tests, to be able to find that sweet spots. But there is a lot of the lottery gain in doing these experiments and doing this testing also across the different markets, because it’s not like you know, you can blindly apply the findings from one market to all the markets, you have to do it for each and every one of them. But of course, the technology itself makes it makes it kind of easy because it’s basically about you know, setting up a quick test where you switch the slider, and then you let it run and you will get the results.

Thank you Paloma, this is super interesting to listen to, I mean, seeing this results from just how good pronunciation performs. Well, we’ll just think that why not go to 100%. So it’s I mean, it’s really interesting to understand just having a pronunciation play based on the history of users and what they have been interested in historically, but also wanting to allow for some part of it to be undiscovered. Also, we’re going into the category to find something new that you might not have been purchasing previously or looking for previously. So having this perfect land days is super interesting and trying to find that sweet spot for you and for other retailers. But I’m thinking I mean, many retailers today are not in a stage where they are even have the tools to go from 25 to 50 or 65% polarization many of them are not processing anything on their categories. What would be your advice to them seeing these results?

Well, I would for sure advise them to, to get started with personalizing the sorting experience, because as you can see, you know, just changing some share presentation from 25 to 50. And then from 50 to 65, or even 70. I mean, it has brought us significant revenue uplift. So for us, I mean, I, I could couldn’t really imagine actually not having any personalization on the product sorting. Of course, we’re, we’re maybe a special case, because we have so many products, but I think any kind of online retailers would benefit from personalization and for making sure that that users are shown the products that are the most relevant for them. For me, there is absolutely no doubt about that as long as it’s done in the right way. But thanks so much for the question. Another test that I would like to share with you is, I mean, it’s not really one specific test, but it’s more like a series of experimentation that we’ve been doing. And that is on the product recommendations that that we have on the site. So we have different placements for the site where we use product recommendations to enrich the experience and make sure that our customers are also you know, recommended some other additional products that that they’re likely to be interested in. And what is what is quite, quite cool actually with the tool, I mean we are going to me is that we so we can we can use AB testing to find the right strategies for each placements, but we don’t have to find or to define specifically, which strategy we want to use for, for which placements because we can just define a group of strategy and then the tool is going to choose automatically which one is the most relevant for that space. to the user. So that’s really allows us to, you know, to be as relevant as possible and to fine tune the experience to each user specifically, which we wouldn’t be able to do if we, you know, if we had to define that, in that placement, we only show I don’t know, the latest beauty products or whatever. So it really gives us a level of fine tuning that that is, that is very useful for us specifically, again, with all the type of customers that we have, and the traffic that we have on the site as well. And, yeah, another touch points that I briefly mentioned earlier, but where we’ve been very activator, personalizing the experience is, is through automation. So email automation. So we’ve been building a lot of basically lifecycle, what we call lifecycle based automation, but basically automated emails that are sent to the customers based on different triggers. So meaning that only the customers that match these different triggers and the different criteria are going to receive these emails. And in this ways, in this way, these emails are personalized to these customer because they’re, they’re much more relevant than just normal manual emails that are sent to our entire email customer base. Getting to the to the success evaluation. You know, I’ve been talking a lot about what we’ve been doing and also the different tests that we’ve been running and kind of the culture of experimentation that we have in within the company. So I thought it would make sense to share with you some of the some of the benefits that we’ve been seeing from this focus on customer experience. And one of them has been the growth in retention among customers. So you can see on this graph that over time, we’ve been able to basically retain more customers and have them place a larger number of orders per year on average. And it’s that’s, you know, the growth has been for all customers, and especially for customers with email permissions, because of the personalized experience that we were able to offer them for their journey. And we could also see that very, very clearly in our customer lifetime value, which is basically like the average revenue per active customers within a 12 month period. And as you can see, we’ve, we’re actually very proud of this, of the way it looks. But we we’ve been really able to massively grow our revenue per active customers, thanks to two more to the full focus on the customer experience and to the fact that we’ve been very attentive at giving them a good experience and personalizing their experience. So they feel like it is relevant for them to come back and buy again, amen. So.
And I also have a small, you know, anecdote to share, which, which, which happened about two, three years ago, I believe, but basically, we had, at some point, we had an issue, unfortunately with on our site with, with the personalization models, and because of that we had to deactivate them for a limited period of time, I think was close to a week. And what we could see is, is a massive drop of close to 20%. In, in our daily revenue. And that’s when, in that period of time, it was only the top center and most popular, like the merchandise page pages and models that were basically at play, but none of the personalization, personalization models were working. So neither on the product sorting on the product recommendations, so and also on the content pages. So it was it was only running on most popular and yeah, what is selling the most on the websites? And yeah, we could see basically a 20% drop in revenue in that period of time. So that that allowed us like it was a bit rough, but it still allowed us to have an idea of what personalization is bringing in terms of revenue for our business.

That’s super interesting pillow, man. I mean, I think many retailers not doing the full platform professionals are anti entire site of search and content and products like you’re doing. I mean, it’s just interesting to understand that these top sellers are most popular products would be like almost a mimic of a merchandiser doing this herself for himself. So I mean, many customers and retailers today are still in the in the state of having merchandisers doing this and not personalizing everything. What would be your advice to them? And I mean, why is it so hard? To make that shift to go from Merchandising to personalizing and relying on the data.

Yeah, that’s, that’s a really good question to ask, but I cannot speak to, you know, for, for everyone else, but at Miinto, at least, I know that going back to only relying on merchandise pages would be complete novel, because we do know the value of personalization. And it would for sure, mean, key or declining revenue. And I think a lot of retailers, they, they simply not necessarily aware of the benefits of personalization. And they’re kind of, you know, maybe not that aware that they’re losing money without knowing it, or losing a lot of potential at least. And, and I think the problem is often that retailers don’t really know how to get started, it seems like a, you know, big project and, and they don’t know how to start, they also think maybe that they will need a lot of resources, a lot of experts, and then it’s going to be expensive, and so on. And the way I feel about it is that it is it is actually all about getting started and getting a foot in it. And then it is about taking one step at a time and one step after another and experimenting and trying to find the right recipes, but it doesn’t have to be huge machinery from day one. But for sure not using personalization of the of the experience is really missing out on a lot of revenue. That is that is pretty clear for me.

That is interesting. Thank you Paloma.
Great, and yeah, just some numbers that I would like to share with you. So these are gross merchandising volumes or revenue that that we’ve achieved over the last few years and that we’re targeting to achieve over the last few years as well. And as you can see, we have, yeah, very ambitious goals for 2021. And even more ambitious goals for 2022. And this is, of course, going to be through I mean, of course winning new customers. But we would never be able to, you know, to reach these goals and resist rows if we were not also focusing on like returning customers and making sure that our existing customer base is retargeted and given a great experience. So they’re they feel like I’m back on Miinto and continuing to be a loyal customers to us. So yeah, again, really a full focus on customer experience that has been showing some very good benefits. And that’s it’s continuing to show really nicely so far. So yeah, that brings us to the final slides of the of the free learnings. And yeah, it was a little bit hard to boil it down to, you know, just a few key takeaways. But I think these are the most important thing that’s I would like to share with you guys, and that I think, are important to keep in mind, at least on our own based on our own experience, of course. But the first one would be that targeting new customers is important for sure, but there is also a lot of value and a lot of revenue in, in getting existing customers back and driving customer retention through personalized experience. So there is really a lot of revenue to unlock, and it will be a huge loss to not to not do it. The second learning that that is also very important is that you know, it is very, or let’s say that technology is really empowering us to scale personalization and make sure that we can cover with very little, very limited resources, a very big number of markets. So it really is a huge asset and a huge tool that would be really a shame not to use nowadays. And ourselves. We’ve been seeing. I mean, we’ve been really, really relying on AI based technologies and just all different tools to help us personalize the experience and help us cover all these markets in the best possible way with really few resources as I mentioned earlier. And the last one is again that I feel like it is very much about just building a culture of experimentation. It is not about finding you know, there is no perfect recipe and every market is different and every company of course is different as well. It’s more about building that culture and being open to changes Being open to failure as well. And being ready to take one step at a time to build the perfect digital experience to your customers.

Thank you so much Paloma. It’s been a pleasure listening to you and sharing and learning from your success story. And big congratulations on the results as well. I look forward to the next few years.

Yes, same here too. Really, really looking forward to the next few years. And it was really a pleasure to share some insights with you here. So thank you for having me on the on the summit’s and while wishing you all the beautiful day.

Ready for the Next in Digital-First Strategies?

Learn how to use disruptive, AI-powered technologies to create frictionless,
hyper-personalized experiences that connected consumers expect today.

Connect with Us