Welcome to today’s episode, we are discussing online marketplace advertising with Regina Ye, Co-Founder & CEO of Topsort. We’ll explore the challenges and strategies for running effective ad campaigns, the shift towards first-party data, and methods for improving ad spend efficiency.
About Regina Ye
Regina, is a Gen-Z entrepreneur and former small vendor. In college, she founded the beauty ecommerce brand, Zirui, and spent many tireless nights trying to understand Facebook and Amazon Ads. Today, her sights are set on demystifying the advertising industry for all.
Resources
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Transcript
Greg Kihlstrom:
Today we’re going to talk about online marketplace advertising with Regina Yeh, co-founder and CEO of TopSort. We’re going to explore the challenges and strategies for running effective ad campaigns, the shift towards first party data, and methods for improving ad spend efficiency. Regina, welcome to the show. Thank you.
Regina Ye: Thanks for having me.
Greg Kihlstrom: Yeah, looking forward to talking with you. Why don’t we get started with you telling us a little bit about your journey to co-founding TopSort and what kind of inspired you to focus on advertising technologies for online marketplaces?
Regina Ye: Yeah, for sure. So I studied computer science in school and then I actually took this class called Entrepreneurship and as a fun little experiment to see if I could push an idea of just an idea and see if I can turn it into something more real beyond an idea. And then that’s how my first business ever, Zarae, got started in school. And it’s a travel case where I had a, as a Shopify store. And at the same time, I had some wholesale distribution channel set up. And the thing that was the hardest for me to figure out in the journey of setting up that business and selling the product is that online advertising, performance-based marketing. It was very difficult for me to learn and it was quite confusing to navigate all these different platforms and pay-per-click campaigns. So I saw this very sharp contrast between what you experience as a brand in the wholesale and retail world. which is lots of volume, very little data and zero ways to really influence the sell through rate at the time. And on the other side, I also had DTC business where I was moving inventory via Amazon ads and Meta ads and Google as the usual suspects. And it was very interesting to me how the options that are essentially you only have three options, three companies that would take the performance based marketing budget and For me, I had this really strong feeling back then that it would be great if it’s a level playing field between wholesale and DTC model. So you’re not really dealing with rising CAC with only three providers. But I could actually have a way to really gain more visibility and influence the pace of selling with the wholesale channels and retailers as well. what got me the most excited this time around when the three of us, Michael, Francisco, and I were discussing the idea of Talsord.
Greg Kihlstrom: Great, great, so yeah, let’s dive in here then. And I think you touched on some of the challenges here, but I’d like to dive a little deeper. And just start by talking about challenges of ad campaigns on online marketplaces, kind of the inspiration for you to start Top Sword in the first place. So online marketplaces are increasingly relying on ad revenue from sponsored listings. What are the main challenges that retailers face in getting better returns on their ad spends?
Regina Ye: Yeah, I think it’s always a bit of feels counter nature to a lot of retailers. their core business and probably the first five to 10 years of their business, really sometimes more, we’re all used to build a business that is very robust in retail and in having happy first-party providers and third-party sellers and happy consumers. That’s a different flow of revenue than now all of a sudden going to the suppliers who used to pay and say, Hey, can you guys pay us? And then. get this advertising revenue. So the first thing we see is that it’s a brand new world. Retailers need to really learn a different set of muscles. And when you start thinking in that wavelength, you start to get into a lot of concerns around How do you do it in a way where it doesn’t jeopardize your organic business? There’s no cannibalization where you’re making more from ads, sure, but you’re really having a decline in actual revenue and your consumers are not so happy with all the ads that are all over the website. And then the other thing is that, which is why we actually think there’s very big difference between having an ad that’s identity based and sort of spammy and feels like an interruption to the shopping experience versus the ones that are actually the right content appearing in the right time. The other thing is this sort of, can you really make it very inclusive when a retailer introduces an ad program? Because it’s very sort of easy and common to go directly to your top GMV brands, to go to the brands that have very deep marketing pockets that will just buy all the ad inventory out there. If you’re a grocery brand, you probably talk to the Unilever, you talk to Pepsi, Coca-Cola. And how about the mid-tier brands and the long tail brands? Can they also gain some benefits from the retailer having this ad ecosystem launched and seeing data and seeing results from it. Because we also believe that having this diversity in brands that participate in a retailer’s ads really drive a lot of the value in the end. So I think these are two examples of some of the challenges that a retailer will have to face when they start this business.
Greg Kihlstrom: Yeah. And I, I want to talk to you a little bit more about how Top Sort helps some of those retailers solve, solve some of these challenges. But first, you, you mentioned something, you know, kind of the, there’s spammy ads and there’s more beneficial ads. Do you mind just kind of explaining like what, maybe an example of, you know, what, what would be the, the good version of the ad versus the spammy in the, in that example?
Regina Ye: Yeah, for sure. So I think probably everyone, you or me have experienced that you’re perhaps even buying a gift for someone else or buying a pair of shoes online. And for the next few days and weeks, you just can’t seem to get away from that pair of shoes or that brand’s images and marketing materials anywhere you go on the internet, right? And it can just be Like I am literally looking up a blog post about a cookie recipe. I see an ad that’s about this pair of shoes I saw three days ago. Or I’m on social media seeing my friend’s birthday party and I’m seeing completely irrelevant content that is just following me around because of my actions in the past. So that’s really identity based, right? That’s about who you are as a person. And it’s trying to find out and trying to guess what you would like to see and retarget the user across all these different platforms. It’s a very different experience to say that this brand is showing me better pair of shoes when I’m looking at, when I’m searching for a pair of shoes on a website, let’s say it’s, I don’t know, Poshmark, right? Where I’m looking for a pair of shoes and I’m getting, different types of shoes and different recommendations. And there’s one that doesn’t add that gets more prominent positioning and images. So that’s a very different experience where it doesn’t feel invasive and it’s appearing in the right moment to the right audience and actually converts better and doesn’t hurt all the parties involved in terms of metrics or just the viewing experience. And so that would be an example.
Greg Kihlstrom: Yeah, yeah, that’s that’s great. Yeah, I always I always think of the example of like, buying a car, you know, you’re you’re doing a little shopping, and you know, you don’t buy a car every 30 days or something like that. And so you know, you buy a car, and then you see ads for cars for like, six months afterwards. And sometimes you maybe regret your choice, three months later or something like that. But you’re kind of stuck with it regardless. So yeah, thanks for providing that example. So to to talk then about how to help help retailers kind of overcome some of these challenges and standing out in a crowded marketplace. You know, what what effective strategies or tools does TopSort provide?
Regina Ye: Yeah, I think for retailers, a lot of them are constantly gauging how far into the innovation spectrum they should go. Right. And it’s very oftentimes a lot of them carry a really rich history. So then they’re really weighing the risk of innovation as well. At the same time, a lot of them are facing this new wave of retailers and we’re seeing where there are vertical e-commerce and vertical marketplaces that are taking over some of the traditional models such as, do you buy it on Wayfair? Do you buy it on Home Depot or HomeGoods? And the other thing is that A lot of the general retailers really do view the, let’s say Amazon or in Latin America, sometimes MercadoLibre, like some of these names as the benchmark for what they would see transformed next version of their business should be. And Top Store, essentially, we like to say where Amazon ads democratize in an API. And what we do is we really think it’s about providing a very good experience that is easy for retailers to adopt, to experiment in, to really make the decision for themselves to say, okay, this works for us. It captures the nuances of what we’re asking for here as this retailer with this very particular mission and demographic. versus saying that it doesn’t really work or we would like to customize and keep it this way versus the other. So having that flexibility is very important. And then the other thing is that retail, it really operates at a very long cycle sometimes. A lot of retailers do five-year plannings and their development roadmap is always very full. For us to be able to give a set of local libraries and tools so they can really plug and play and experiment and find out for themselves very quickly without having too much investment or very hard to pivot would be another way of how I think Top Store helps.
Greg Kihlstrom: I want to switch topics a little bit to just the importance of first-party data and clean rooms. And certainly with Google’s relatively recent news on you know, they kept kicking the can down the road as far as third-party cookies go, and finally made an announcement that it’s the cookiepocalypse, or whatever you want to call it, is kind of off. But at the same time, first-party data and first-party data strategies, I believe, are still as important as ever. I wanted to talk with you a little bit about this part. And, you know, many others agree, you know, there’s still a shift towards first-party data. How does TopSort look at this as far as your commerce and media-focused cleanroom? And what are the benefits for marketers from a privacy standpoint in this first-party data approach that you’re taking?
Regina Ye: Yeah. One is that we believe a lot more in having a multi-party collaboration. So instead of having today, a lot of the existing clean room set up and attribution models are very focused on pure exchange of data. And it’s a one-to-one ratio. So you’re not really having more than two parties involved in the build of this clean room. And what we think the future of clean room for especially a retail media use case is really having more than just two parties involved between a brand and a retailer, but also at the same time, perhaps you would have, for example, loyalty program laying on top of that and making it a little bit less about the user and more about behavior based on a product or based on things that you already given explicit consent and sharing instead of a very static two pools of data exchanging. And then the other things that I think today, what we hear from retailers sometimes is that the data, the clean room solutions out there don’t quite answer the last step, which is attribution. How do you know? Sure, you have two pools of data, but what’s the final answer? What ultimately happened? It ends at a purchase. So tracing back that sort of journey without being singling out, without singling out a user, one individual user, which gets to a privacy level concern. I think that’s kind of the very nuanced balance that is challenging for whoever’s building this retail media cleanroom product. And that’s exactly what we’re focused on solving.
Greg Kihlstrom: Yeah. And so just we’ve talked a little bit about data cleanrooms on this show, but for those that didn’t catch that, and maybe need a little terminology check. Do you mind just at a high level explaining, you know, what exactly do we mean when we, you know, we’re talking about a clean room?
Regina Ye: Yeah, for sure. So data clean room on the very surface level explanation would be that it allows multiple parties, multiple companies to exchange data, sometimes sensitive data in a very controlled and clean environment where neither party has full control over the data and it’s sort of in a separate third-party controlled environment.
Greg Kihlstrom: Great, great. Yeah, thanks for that. And so another thing to talk through maintaining zero visibility into privacy data, you know, how does this impact effectiveness and trustworthy of marketing campaigns?
Regina Ye: So that’s a big wrestle, I would say, like, it feels like a wrestling match we’ve been having sometimes with, um, a lot of our customers or existing customers, future customers, and sort of like also trying to convince them because you’re really talking to a generation of marketers that grew up and studied marketing based on it’s all about audience targeting. And we believe and we’ve seen with our own data is that you don’t really need audience targeting as the most fundamental layer to make a retail media business work. In fact, that’s kind of the beauty of it. I think that’s why there’s so much interest behind it and people sort of view it as an alternative that’s on the rise to give them more data autonomy back, to give them more first party data back and more control over their monetization, over having to work through those big giants. So what we’ve seen is that you don’t necessarily need audience data to create the best results or you can go pretty far without it. So sometimes having the knowledge of your Greg, you’re looking for a t-shirt on this clothing retailer and in this very moment in getting really good at running that decision in that moment in real time gets you very far. And what we see is actually audience data and targeting become something that is more of a product-based identity. So it’s not individualistic. It’s more about the cohort of people who added this shirt to car but did not end up purchasing. So that’s still more product-based identity and new to brand, right, these attributes. And then the other thing is that you can always layer on top. So it’s more of an optimization layer. a way to boost already good results to be even better than something that you have to have as a must have in the beginning. And then we’ve seen that sometimes keeping it, especially in an auction dynamic, keeping it very broad does create really good competitive unit economics in terms of the ad results than having the segmentation being done really early on.
Greg Kihlstrom: So then from the marketer or advertisers perspective, agreed, they’ve probably been trained to think about you know, kind of segmentation first, does that mean they think about the product and product benefits first? Or like, what’s the what’s kind of the order of the thinking as far as the ad goes, then?
Regina Ye: Yeah. The other thing that’s happening, that’s been happening in the background is kind of a luxury that we take for granted sometimes these days is that search is very good. The retailers and e-commerce search are very good. They all have really good organic relevance. So then it’s not saying that we’re completely flying blind, but it’s more so that if you are add infrastructure, retail media infrastructure, you don’t have to necessarily have a separate relevance engine and replicate search and create this parallel search, but it can be already using and trusting the existing environment as the first step and then add all these optimization on top.
Greg Kihlstrom: Okay. Got it. Yeah. So the last topic I wanted to talk about with you is, you know, just in, I think it’s a good, a good way to, to, wrap up here is talking about, you know, return on ad spend. And, you know, we’ve been talking about a lot about ways to optimize and, and, and things. So wanted to really dive into return on ad spend here. And so, you know, in terms of, of doing so on platforms like Amazon, you know, what insights do you find the most crucial for advertisers to understand about their campaigns?
Regina Ye: Yeah, this has changed a lot and it keeps changing, but we’ve seen that from a lot of the marketers I speak with these days, everybody is trusting the auto bidding algorithm more and more, especially the smaller players and the ones that I actually was talking to a marketing director that spends 7 million a year on Amazon promoting a brand that’s definitely top three in the category and saying that we pretty much just do 90% of our campaigns on auto-bidding. So I think that’s a big trend is that using AI and trusting the automatic bidder and seeing results coming from that. When you have really good auto-bidding, it does work and it takes away a lot of the mental load from marketers in terms of managing the ad ops. And you get to free up more space to think about growth hacking experiments, creative ideas, and those are some trends that we’ve seen.
Greg Kihlstrom: Yeah, yeah. Are there specific metrics that marketers tend to, I would say, overvalue or, I mean, even undervalue if there’s some of those as well? But how should they adjust their focus to better measure and understand their return on ad spend?
Regina Ye: Yeah, I think return on ad spend is pretty key as an indicator, especially in more bottom of the funnel campaigns. However, it’s still important to take into consideration the scale and know if you’re calling the race too quickly. So we’ve seen brands start looking at the ROAS when they’ve only spent, let’s say $200 and have sold two products. It really doesn’t matter. Even if you have a 2X ROAS at a $10,000 scale versus having an 8X ROAS at a $500 scale, it’s completely different. So the scale still matters and how long you can keep up those results for really matter as well. And we’ve seen that getting mixed. And I think it’s also very interesting. this sort of idea of trade marketing versus brand marketing and how to replicate that and connect those two in the retail media world, where retail media has been kind of considered more bottom of the funnel, ROAS-centric. And lately, the rhetoric has been, maybe it’s not just about the ROAS, but we’ve seen that from the actual brands that are investing into these campaigns, they still very much care about ROAS. So then for those bigger brands that have the appetite to buy more in the retail media world, how do you provide the equivalence of a Super Bowl ad for them to buy in the retail media space at scale and also still be able to measure the result in the metrics they want, like share voice or even ROAS? right, and then demonstrate the value there. I think that’s where it’s becoming more clear and more transparent, but there’s still a long way to go.
Greg Kihlstrom: Yeah, yeah. Well, really appreciate you joining today. And you know, before we wrap up here, I wanted to ask you a couple things, just looking out some future trends, certainly you’re keeping an eye on on what’s going on in online marketplaces and advertising, you know, what major trends are you seeing that are going to shape the future of advertising in marketplaces?
Regina Ye: Yeah, this is a really big one, but I can share what I have seen. And we’ve seen this sort of, I don’t know if we call it the third 3.0 or because I don’t think it’s even 2.0 anymore, where this sort of Recently, we’ve seen a lot of retailers are not really thinking about do we invest in retail media or not? And this is the question they would ask like three years ago. But now it’s a lot about we’ve tried it. We know it works. We’ve seen great results. And yet we hit all these bottlenecks and we have a lot of pain points around what we have today. What is the next phase of it look like? And that’s a big one we’ve seen. The other one is this sort of omni channel approach where People start to look at retail media more holistically and not just thinking about their onsite monetization as one piece, two different formats between display and listings, and they can live in different platforms. And then the other thing is like, okay, what about my offsite investment into all these different DSPs and networks? And then there’s the in-store part where there are happening a lot of experiments and place there. So how do you connect the data? How do you combine a very fragmented? set of tools into a place where there’s more connectivity, where you see that the results start to make sense. Because even though maybe Coca-Cola’s budget is going to five different places, it still ends up being like one user journey for the consumer. And the other thing is that, what are the companies that will need to come together and work together? Because I think it’s really too broad for any one company to tackle. and sort of the tools that are able to really bring more simplicity and bring more clarity to this very confusing, like increasing list of tools that the retailers are using. It becomes a very long list and like a lot of features and it gets very nuanced. So that’s where I think it’s interesting is that we’re seeing that sort of evolution happen.
Greg Kihlstrom: Yeah, yeah. Well, and so, you know, to prepare for all of these changes, you know, there’s certainly, as you said, there’s a lot to keep tabs on and to be aware of, you know, what’s a piece of advice that you’d have for a company to remain competitive and maximize advertising effectiveness in the months and even years ahead?
Regina Ye: I’m not sure if I’m qualified to give some advice, but I would say, like, talk to your customers, care about your customers more than your competitors. It’s all about what the customers want at the end. And we always believe customers are the solution. They’re never the problem.
