How can you improve a product’s global experience? With Mauricio Monico from Wish

Hello and welcome to Building Globally: Lessons in Enterprise Product Growth, the podcast which asks, how do enterprise products grow? And which just occasionally asks, does testing have anything to do with it? We'll be talking to people working in product in some of the most exciting businesses in the world in software. We are Global App Testing.

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Hello and welcome to Building Globally: Lessons in Enterprise Product Growth, the podcast which looks at how software businesses can deliver more Miles, higher revenues, extra subscriptions when they are around the world. I am your host, Adam, and this is our very first episode. We've got a very exciting series lined up. We are Global App Testing. We're a crowd testing organization that helps enterprise product businesses understand their product experiences around the world. And we're very fortunate to be joined today by Mauricio Monaco. Mauricio has held strategic product positions in some of the world's most famous global product businesses. We're going to get into that in a bit, but today Mauricio is the Chief Product Officer at Wish, which, if you're not familiar, is discovery shopping for things that you love on a budget. Mauricio spent the last few years steering the ship and seeing the business forge a new global product strategy. Hello, Mauricio. How are you doing today?

Hey, Adam, thanks for having me here. It's a pleasure to be here. I have worked with Global App Testing for so long now that it feels like home.

So Mauricio, so just very, very quickly for people who might not be aware of you, your context is that you were at Meta 2015 to '16. You were at Google 2016 to '21, so group product manager at Google, international product growth manager at Meta, and then now you are the chief product officer at Wish. Do you want to just kind of give us the kind of headlines of what those experiences were like?

So I think that the best way to kind of look into this is that like for the majority of my career, I spent my time on marketplaces and some of those marketplaces like international growth was a key component, but I also did growth both at Google and Facebook. On Facebook,— and Wish, of course, like on a little bit of a different way that I'm going to explain in a second. Meta was very much in the beginning of its international growth from a product perspective. Like we got the chance to kind of see the early days of it. Google was also doing very similar things, but in a very different way because Google had done already the very specialized countries they were trying to basically scale. And Wish is one of those places that It was born international, like it was focused on cross-border trading. By the time I joined, they were selling into 140 countries and it was more of a need of consolidating and focusing. So very different types of experiences.

So you're Chief Product Officer at Wish. How's that different from being a product manager in such a big organization, right? You're sort of the guy in charge now.

Do you prefer that? So let me put it like this. When the organization is properly structured and the product manager has empowerment over the areas that they own, the feeling that they're gonna have, which is, which is their ability to turn that wheel and the bus moves in the direction that you wanna move, is very similar to the feeling you're gonna have when you own an organization. You actually manage and you can turn that wheel for sure. The difference here is really gonna be, are you truly empowered? Which is what you actually get, no questions asked, when you are the CPO for an organization. But the fulfillment that you get from that is very, very similar. Obviously, yes, there were several circumstances in my career that that feeling was 100% there. There was a very good clarity of what is it that I owned, how I wanted to manage, how I wanted to drive. It's just a given when you actually had a product. Obviously, you're still working with your counterparts on engineering and influencing finance, which is actually a really big portion of this when you're leading product overall. Like the focus you have to have on the finance part of the house is much higher than when you actually are an individual contributor. Or even just a lead.

I suppose that product management in general is not a department you can run as an island, right? It's got to be integrated into the business in order to work at all. 100%. So you started at Wish in 2021. So can you paint us a bit of a picture of Wish in 2021?

So like you said, Wish is discovery shopping for things you love on a budget. It's like gadgets for your kitchen, or tool that you're using for a hobby you have, or jewelry that is fantastic looking for very low prices. And you discover those products, you align that with the budget's interests you have. It had existed since 2010. It grew quite a bit during COVID It had a huge brand recognition, but it had also bad brand recognition because when you looked and you thought about Wish, you thought about low quality products, things that you thought you're going to get, but you got something else. There was a huge meme of the internet, which is Every time you saw something fail, something having low quality, they'll say this is the wish version of something. So when I joined, like my main work was how do we transform this marketplace and something that people can take the value that they were taking, because there was a lot of people taking value out of it, but also be reliable, ensuring that what you're getting is what you thought you're getting and that the surprises are mostly pleasant rather than unpleasant. That's the ecosystem we're trying to kind of fix.

So why does somebody end up on the Wish sites in the first place?

Wish was actually founded by a Google engineer that worked on the ads team. He basically created a completely new way of advertising products and influenced both Google and Facebook to create a new ad format, which is like product display ads nowadays. And if there is one thing that Wish did extremely well, was how to drive efficiency of those advertisements on both of those platforms. So the vast majority of people that showed up at Wish, they showed up at Wish because they were searching for something on Google or because they're browsing Facebook and they saw an advertisement for a product that intrigued them.

And so that's the product. And can you kind of give us a sense of what are like the dynamics for success in that market? Do you think what's actually important within that product in order to drive whatever it is the most important commercial outcome for Wish?

This question is a heavy question because it really depends where you are on the stage of your organization. Are you in the beginning and trying to grow? Are you trying to scale right now in a profitable way? But in general, there's a few things that actually are important for a marketplace like Wish. One is how you're attracting traffic and does that traffic acquisition channel has the right return on investment for you, has the right ROAS for you., right? Because remember, we're talking about reasonably low-priced items. And yes, people have to build a basket in order to maximize their savings, but it's pretty reasonable low basket size. So finding that channel, be it Facebook advertisement, be it Google, be it SEO, whatever you can make it like. And on those days, like the social influencers and so on and so forth, which do happen to work for certain types of categories. But getting that channel right is job number one. Job number two is that once you get people to land, you have to remember that people are not necessarily there, they're there for an interest, a hobby. They're mildly interested on that very first product that they clicked on. So based on the information you have from them, how do you engage them? And we see this tremendously on Wish, like people explore hundreds of products before they add something to cart. Like the kind of products they see, the videos that they see on our site, are very, very engaging from the perspective of you, of us being able to align those products to the interests you have. So creating that model that allows me to do exactly that, which is like showing the right recommendations, using immediate signals, how long you stayed on that product, the clicks, the add to carts, the views to kind of show the next set of products that even more engaging to you is job number 2. And then obviously like job number 3 is deliver on your promise so that people come back.

And can you give us a bit of a picture of the business of Wish in 2021 when you joined?

So when I joined in 2021, it was basically going through this phase of huge growth, got to the IPO, then COVID lane was kind of ending up like every other company. The e-commerce growth that was there was not sustainable. Plus, combined with the fact that like our retention was terrible at that point, right? Exactly for the reasons that I just mentioned around quality, keeping our promises, and so on and so forth. We were about, I think, 130, 140 countries at that point. The biggest geos that we had were North America, US and Canada, and Europe. At one point, Japan was huge for us. At one point, Brazil was huge for us. But by the time I joined, Europe and North America were the biggest sectors. We had, I can't remember exactly, but somewhere between 1,200 and 1,500 employees at that point.

And you're at this moment where you've gone through the IPO, you've got a huge boost from the pandemic in terms of people using e-commerce to buy things who would be normal physical retail buyers. And was Wish at this point braced for the fact that that growth was likely to end?

Did leadership understand that? So it did. And we had a huge call, which is like, how do we continue to grow much more sustainably than we have before? And part of this is that is ensuring that we have the right retention so that as we grow, that we just don't continue burning cash, but we actually start getting to a point in which we're becoming operationally profitable. There was a huge recognition that we grew a little too fast in terms of people, in terms of geos, in terms of everything, right? In terms of number of merchants. And we needed to add some control to that whole process. Meaning, what does it actually mean to be ready for country? What does it actually mean to have a validated merchant? What is quality of a merchant? And we went through this process of actually looking into each one of those big rocks and trying to figure out what to do with them, when to pull back, when to double down and be able to focus.

And so at that moment, so you come into post, you've mentioned you were thinking about the actual quality of Wish. You had indicators that maybe Wish wasn't as good quality as it could have been. You're in all these countries. What do you do? What's the kind of course of action that you took?

So when I joined, there were a few things that became very clear. Like, so first of all, we had zero control or very little control of what are the merchants that are actually trading on the platform. So we created a variety of different things. Like the first thing was what we call Wish Seller Standards, which basically promotes high standard merchants and demotes low standard merchants. Then we closed the marketplace for new merchants and made it an invitation-only model. And the reason for that is because there was a variety of different things we needed to go fix in terms of being able to properly validate it and properly ensure quality. The second thing, which is kind of a little more geo-related is we looked into the countries that we, that we were supporting and we looked into like, what are some of them that actually had either grown before, but 100% collapsed or never really took off and understood what are the costs that we had in each one of those. You have to decide your ad strategy for that country. You have to spend in terms of ads, and there is always a minimum spend that you can have for it to be practical, for it to be effective. So we looked into a variety of different geos as well to try and figure out which geos was actually performing and we had a chance to perform versus the ones that we are just spending but not actually taking any value out of it.

Can you think of a time during that period where there was like a particular decision point that you or that the business found difficult and where you had to kind of chew over a couple of different commercial and product routes that you could have taken?

All of those decisions were in hindsight 100% clear and they don't feel difficult, but at the time they were not as easy, right? Like for example, like the decision of actually exiting more than half of the countries that we're serving was a very difficult decision back in the days because we're trying to, obviously like one of the metrics that we're trying to grow is gross merchandising value, GMV. And when you exit countries, no matter how much they are contributing, obviously that's going to have a negative impact on GMD. So getting to the understanding of like, what are the countries that we want to focus on and doubling down? And what are the ones that we want to exit because they're not performing or moving to the right direction? Makes logical sense. But for the overall organization, it was a not as easy to understand step to take because the tradition in, in the Silicon Valley is always, well, just invest more and get those countries to the place that you want them to be rather than exiting. But we needed to kind of almost regroup and attack rather than trying and spreading our army as we had been.

And strategically clear, but maybe tactically and operationally difficult. That it's the details that are the really difficult thing in terms of the decisions and the processes you had to go for. Did you have success criteria?

So this is one of those, it's not the kind of stuff that you experiment with and you're, you're not testing what happens when that happens. Like it's more of a stepping stone towards something else. You had success criteria of actually, obviously might introduce things that you didn't expect. But our success criteria was actually exiting with minimum merchant disruption and within the GMV loss that we expected to have so that we can reallocate those resources, those people, that mindset towards the regions that we wanted to grow.

So how has the strategic landscape for Wish changed then?

I guess the best way to answer this is that when I joined, Wish was pretty much playing by itself. Like it was on the world of discovery shopping, cross-border trading, very low price for things you want, not the things you need. If you knew what to search for, you could find something similar that you could find on Wish. And our focus is like, we have done some damage to ourselves through the lack of, you know, marketplace health that we had. Let's focus on that. It took us a year, but in a year we were in a state in which like our refund rates went down dramatically. Our customer NPS was, had moves that were extremely high from negative numbers to very high positive numbers. Our retention was definitely increased and we're ready to kind of grow. But when you open a hole in the markets, which we kind of did, like, cause we proved that there was demand for that and we proved that we didn't execute 100% correctly in the very beginning. We're trying to improve that. There were some people that saw the opportunity and came in. So a year later, you see different competitors coming into this ecosystem.

So do you think then that Wish nowadays, I guess the term that's in my head, I don't know whether I'm applying this correctly or not, would be red ocean versus blue ocean, right?

That's a really good question. And you're right, like just finishing the competition, like Shopee kind of went into Latin America. You get Temu that's going to a bunch of other regions that we have in exactly the same model. And then you get to this point of like, if you're in this red ocean, as you put it, what is your strategic vision to be able to compete? And the budget side is something that becomes, hey, you need to be within the budget boundaries. But if your entire strategy is to compete on price, you're going to lose because then it's a matter of like who has the most money to lose the most until they gain the market. If you're purely talking like Wish in the very beginning introduced this discovery shopping that was revolutionary. A bunch of new players come in with exactly the same type of discovery shopping and they're building their models to become as good as, and they're sourcing from similar merchants. So they have similar products. So the question now is, is understanding your customers and what are they looking for and how do you serve them better in a way that's differentiated? And what we have been understanding is that like, hey, most people are coming because they have a passion, they have a hobby, they have something they love. And the way that we have traditionally served them is show them a bunch of products and see what, which ones they interact with and then start learning from that and showing more products that represent connections between those products.. But now we're bringing it in front and center and saying, not only are we going to recommend you the product, but we're going to help you understand which products you're selecting, why you're selecting, which ones go together.

This sounds like a huge database. And is that not an AI thing now? Or are you describing different ways of structuring AI recommendation algorithms?

Wish started as a product recommendation engine, which is AI driven, not LLM AI, which is what everybody is actually talking about today., but it's an AI model behind the scenes, 100%. And improving the AI model, improving the ability to take more signals and understanding and more entities as well. By the entities, I mean, for us, a product was an entity, like the list of products you're trying to buy. Now, a desire of a specific function, for example, I want to improve my espresso puck. I want to bake French bread. Those are entities for us too that connects products that helps you recommend and drive the content. And by the way, some of that content can be generated through LLM. Some of that content can be generated through influencers. Some of that content can be generated by merchants, but connecting that content to the user and their interest is what we're trying to drive towards. A mix of traditional AI and LLM for the content side of the house.

How much of the success of Wish in terms of like the things on your in-tray that are important for the product in order for you to grow, how much of that do you chalk up to the traditional AI? We need better recommendations. It's something that we've had like a lot of emphasis on across different products.

So I think they own that you can drive some improvements. The business will likely not exist without that. That's number one. But number two, we have more than 10 years of existence. That model has improved over multiple times. We're in the process of making yet another improvement to that, but you don't double or triple anymore. You make improvements to that. It becomes a little bit better, a little bit more certain, or a little more exploratory. There are certain levers you can actually move. Like, do you want to just narrow in? You want to help the user explore? At what types do you actually help them explore? At what times do you help them just select? You can make improvements to that, but after a certain amount of time, you can improve them, but they're not what's going to make this like 50% bigger, 50% smaller.

It becomes much more marginal at that point. In terms of recommendation algorithms and building something that is really, you know, successful and better for customers, recommends things that they're more likely to use.

Are there things that you've learned? I think there's two, actually. Number one is, especially on e-commerce, it's not just the machine. There is so many things that changes that one of the things that we recognize is that the, what we call category managers, like the knowledge of somebody that's expert in a specific category and knowing how to introduce new products, knowing how to basically override the machine is super important. And we have learned our lesson on that one, and we have seen the improvements that it drives when you have the mix of machine plus human. That's number one. Number two is also be very intentional about what you're trying to do. There was a time that everybody's answer is like, the AI is going to solve it. We're going to use AI on this. It's not the right approach. It may be the right approach when you're talking about a set of products that you're going to make an infinite feed on that you're going to show tremendous amount of products on. But let's say you clicked on that product. And when you click on that product, you have a new opportunity. The user is into a new mindset. You're already seeing that product. What are the types of recommendations and what are the intentions that you have? How many items do they have on cart? Are they close to a certain amount that's ready that you want to drive them to check out? Are they still exploring? Which kind of recommendations do you build on this? That understanding of, and that intentionality of which kind of recommendations and which behavior you want to drive the user towards for the specific state that they are in is key. And also testing it, like what we have learned is. It's not just one recommendation. It's like we provide a variety of them and we allow the system to prioritize which recommendations have worked better and rank them over time.

One of the most important relationships you will have will be with the chief marketing officer, I guess, because a lot of what you're describing is stuff that could be interpreted as product or marketing, depending on the kind of business that you're in. Would you mind just talking a little bit about that relationship?

It's definitely one of the key relationships you have in a product organization. If you think about the relationship we have, we have to discuss what are the kind of things we're doing that are brand oriented that's going to actually help with the brand marketing side of the house and how you are sending the right tone, passing the right values, and what are the products that you expose that are going to allow you to do this. That is work related into if you're doing integrations with Meta, with Google, and so on and so forth, what is our ability to send the right set of products, create the right automations on that feed of products. That allows marketing to do what they can do best and we improve ROI on those ads. Once you get somebody to click on anything and they're landing on Wish, we need to kind of merge what is the product intention and the product role at that point. And what is it that we're trying to drive from a marketing behavior? Like when you actually have a new user, you have returning users. What are the kind of messages? What are the kind of incentives? What are the kind of experiences? What are the kind of exploratory behavior from that user on the land on that page? That was so much so that when we hired our head of marketing, We actually created a completely new landing page just for that, because we used to just land people into the product description page.

So final question. So we're going to ask this to every interviewee, and I'm going to just preface this by saying, don't say Steve Jobs or Paul Graham. I would love for it to be somebody real, but which person in product management would you most like to take out to lunch? And also, what kind of lunch would you want to go for with them?

That's a difficult question. The reason it's a difficult question is that I think that there's a lot of people I admire in the product world. You're going to find a bunch of them that have had experience consulting. You have people that I have worked with that honestly nobody knows but the people that you have worked with that are extremely empowered to kind of do user discovery and understand how to solve people's problems. I don't know if I had one person, but like it's a combination Fantastic.

Well, thank you so much for talking to us, Mauricio. Yeah, it's been a really interesting conversation and I wish all the best.

Obviously, we'll continue working together to drive those outcomes. Same here, man.

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