In this episode, Amit Aggarwal (Principal, Elevation Capital) speaks with Shaurya Gupta and Divyansh Ameta (Co-Founders, Wishlink) on their journey of building Wishlink, a platform enabling creator-led commerce through personalized storefronts.
The duo, along with Chandan Yadav, started Wishlink in 2022 with a keen insight: influencers and content creators, despite owning prime internet real estate (user attention) and being a key source of consumer influence, were failing to capture their fair share of value. Recognizing that over 55% of social media users engage with brands and discover products through these platforms, they saw an opportunity to optimize this process and make it mutually beneficial for consumers, brands, and creators. Thus, Wishlink was born.
By developing a sophisticated tech stack, Wishlink drives transparent and measurable attribution for brands, thus enabling creators to generate consistent, meaningful income. Their efforts have culminated in fantastic growth, with the company recently doubling its monthly GMV to Rs 10 crores in just two months, working with 600+ content creators and 200+ brands. By leveraging technology across the value chain, Wishlink is revolutionizing creator-led commerce, especially in the context of India’s booming $70B+ e-commerce market, predicted to grow 2-3X in the next five years.
Join us as Shaurya and Divyansh discuss Wishlink's genesis, its unique problem-solving approach, and their dreams of rewriting the playbook for e-commerce. They delve into their data-driven product development, the experiences and insights shaping their operations, experiments to achieve PMF, and the impact of Wishlink on the rapidly growing creator economy. This enlightening conversation also explores the challenges faced by Shaurya and Divyansh, the lessons learned, and the tremendous potential of creator-led commerce in the digital age.
Amit Aggarwal, Principal, Elevation Capital: Welcome to the Day One podcast, a new series where we focus on the stories and journeys of companies and founders that Elevation is partnering with. I'm Amit, and I focus on consumer tech investments at Elevation. Today my guests are Shaurya and Divyansh, the founders of Wishlink and building a very exciting platform to drive creator commerce. Before we dive in, let me give a quick intro to Wishlink. Wishlink today allows creators to create custom storefronts. They partner with brands at the backend. This allows creators to launch e-commerce websites which they can share with followers on their existing social platforms and drive sales. Alright, guys, before we dive into the details, can you briefly tell me what Wishlink does? What is Wishlink about?
Divyansh Ameta, Co-Founder, Wishlink: First, thank you so much, Amit, for having us here. I'll give you an idea, and you know a lot of it, but I'll take you through how we got here. So we first started looking at social media and what was happening on social media from a user lens. Not creator lens, not brand lens. We started looking at what was happening with users, and the first insight that we got was that more and more users are discovering new products and new brands on social media via creator content, other people, their friends, and family that they follow. So they were discovering new products, but after discovery, the journey from discovery to purchase was completely broken. So what happened was I, as a user, let's say I'm watching a reel; I really like a shirt that a person is wearing, but what do I do next? So what they were doing was they were commenting, asking for product details, asking for product links from the creators. Secondly, a lot of users were clicking screenshots and searching for that image on Google Lens or, let's say, Myntra image search or Amazon image search. So that was the first behavior that we saw. Users were discovering products on Instagram and YouTube, but they could not find those exact products on different purchase destinations.
Secondly, we started digging deep into it and talking to many creators about what was happening with them. Three insights majorly. The first was that creators monetize only via brand collaboration. So brand collaborations are the major source of monetization for all creators, and only the top 1-2% of creators get access to brand collaborations. Second was the brand collaborations that they do. It's very inorganic content, and every creator I talked to did not like doing brand collaborations, but because it gives them money, they used to do that. Third, there was still a lot of organic content that creators were creating for which their audience followed them, for which they got the most views and engagement. They were making product recommendations in all that organic content but not making anything out of it. Their followers were looking at that content and then making purchases, but they were not looking at it. So we thought there was an opportunity to create an alternate monetization model for creators here. The third thing then we started talking to brands, where all the dots connected wherein we spoke to brands. The first thing was they are looking at Influencers as a branding channel, as a top-of-the-funnel awareness channel wherein they work with Influencers, get videos out, and do branding with them. But firstly, it was very manual and very ops-heavy. Second, they were unable to measure the exact ROI out of those branding campaigns, and another thing was the performance channels where brands get a lot of users, which are Meta and Google. They were getting saturated and very costly for those brands. So brands were also looking at a lot of other channels to get users and drive sales. That is where all the dots connected, and we figured we could create a solution to solve these specific pain points for all these stakeholders. And that's when we started with Wishlink.
Amit: And the follow-up question in my head is, how did you build conviction that it was big enough to solve? Like clearly, things were broken. I think you walked us through them. Some things can be done better. Was it big enough? I think a lot goes back to saying, "Look, is this influencer marketing, do an area, be an agency? How did you build conviction? Or look, this is sizable. There's a large pool that can attack, and I'm assuming you wanted to go after a large one, so how did you build comfort?
Shaurya Gupta, Co-Founder, Wishlink: So the initial thesis was, and it was based on a couple of observations in the market,One of them was that users now need curation because, on e-commerce platforms, there are 150 to 200 million unique SKUs that are listed. There are about 80,000 or so purchase destinations online now,So users want some bit of curation about which product matches their needs, which product would look well on them, et cetera,So there was this one trend that we had started observing and tying back to what Divyansh said,We saw this curation happening on social media platforms via the creators. The second observation was that the way e-commerce is currently built, that playbook was written 30 years back, right, in the 1990s, by Amazon. And that playbook is still applicable as of date. Now, that playbook is suited for intent-based shopping, where you know what you want to buy, you can search for a particular product and then buy it, but it doesn't allow any serendipitous commerce,It doesn't allow you to discover products. So those were the two macro trends we saw to build conviction on this market's size. So some of the categories, like, fashion, beauty, and personal care, inherently are categories that are more serendipity led,You go into a mall, you go into a market and you actually keep discovering products and then buying them. You don't go with the intention that, okay, I need a blue T-shirt with a graphic design,That is now how a fashion category operates. So fashion is a pretty big category, about $15 to $20 billion. And on top of it, again, $5-10 billion dollars. And this is only the online market that I'm talking about. The offline market is big enough. Some of these data points gave us confidence that this is a large opportunity. A lot of work has not been done because the playbook has not evolved as we would have liked it to evolve. And also some of the hard data here, right, if you talk to any brand, let's say today, and if you check the traffic source, where are they getting users from? About 70% of their traffic, even today comes from social media platforms, primarily done via ads. Now, ads, as Divyansh mentioned, right, it is getting saturated. It is getting costlier. So there has to be another way through which you can, cost-efficiently, drive those users to your platform and sales. So, those two observations wherein we felt that there is a need for this market, and we have also seen that in our journey. But yeah, the conviction on the observations and the size in terms of, these categories being big enough and being growing pretty rapidly, like in e-commerce right now, fashion is the fastest growing category. So those things gave us confidence that, okay, this is the right market. This is going to be the future of shopping. No one has solved serendipity-led shopping. So that is where we came into the picture.
Amit: Very interesting. So I'm hearing you say that we are going after the e-commerce market, and that's the right way to look at it. Some categories work better where many of my purchases are or users’ purchases are inspiration driven, but to categorize ourselves in a broader-commerce play and not in influencer marketing. Absolutely. Was there early feedback like back in those days? Again, if I look back to December 2021 from, I don't know, stakeholders, influencers users that gave you sort of that driver, again, that conviction to say, this is true, and this is the future of e-commerce.
Shaurya: Absolutely. So we had been having many conversations with users, creators, and brands. So what we did to get early science on this is we onboarded one of the influencers, who is our friend. He was into health and fitness and gave recommendations to his audiences on the best health and fitness products out there. So what we did was we very quickly gave him a no-code storefront. Our first storefronts were no-code storefronts. We gave him a storefront; he shared it with his audience on Instagram. Then we started seeing and tracking all of those things via Google Analytics, via our tracking mechanism. We started seeing a huge spike in traffic, which we were not anticipating.That was the first sign that, okay, this is something that users want. Then, some of the users started purchasing products from there and also started sharing about those on social media platforms. This is in October or September 2021. Traffic was going to Amazon back then. To test the hypothesis, what we did was we just leveraged all the readily available resources, and Amazon was one of them. Amazon has an associate program.
Divyansh: I'll also add a good story here. So around that time, September, October, what happened was Ankur Warikoo he was blowing up during COVID. And he started experimenting with affiliates, something that we knew. So I saw a Tweet thread from him wherein he recommended 20 books and 20 Tweets were posted with each tweet with an Amazon affiliate link of that book. All of them were Amazon affiliate links. So I sent him a cold message that we can give you a storefront so you can easily put all of these links on that storefront. Didn't get a reply. The next day I was on Instagram, and I saw 20 stories. Each story had a single Amazon affiliate, and those would disappear in 24 hours. So then I messaged him again that this was not a good way to do this. We can give you a storefront in your name, personalized, and you can organize all of these recommendations with a good UI. He replied we got to talking, and then we created a storefront for him, which resulted in a lot of Amazon sales for him. Immediately after this, we were also able to convince a fashion YouTuber with more than a million subscribers on YouTube, and he was creating a fashion essential for winter video, and that was, I think, like the eye-opening or that's what surprised us. He made this video wherein he recommended around 30 to 40 products for winter scarves, jackets, and socks. And all of those products, all of them were Amazon products. So we had Amazon affiliate access to Amazon affiliate. We linked all of that, gave him a storefront, and listed all these products on his storefront. We got 20,000, 25,000 people on the storefront on the first day. And in the first week, he sold five lakh products on Amazon. That was a video that gave us the conviction that this would work. If one video can drive this much sales, then the potential here is huge. And this also excited you, this story, when we came to you for the pitch.
Amit: In fact, I'm curious, how come today we don't have books or health, right? Like of the three examples you gave, and I think these were the three correct storefronts you had presented when we first met. Was fashion, like disproportionately powerful when you did fashion?
Shaurya: So what we did is we did an exercise back in Jan last year where we were testing out all the categories that which categories will suit well in this model. Right. So we tested categories like books, health, Fitness, and even tech. We were trying to sell mobile phones, fashion, et cetera. Then we saw that the pickup is really good in fashion because that is, and it's a lower-hanging fruit Because fashion in itself requires some bit of curation, some bit of inspiration. It also facilitates more impulse purchases. Right. If I already have 20 T-shirts, I can buy another T-shirt there. Right. Fashion spiked in terms of the user behavior we saw in it, the entire funnel views, click-through rates, everything,So that is when we prioritized that fashion should be the first category that we should go after. This model is applicable not just on, let's say, fashion or home decor or categories like that, but on online services as well, not just physical products. Those are some of the things we'll test out in the future. So imagine a scenario where let's say, a travel influencer is talking about all his experiences in Bali, let's say, and then his audience can go and purchase the same experiences. We partner with platforms like maybe Airbnb, booking.com, etc. Etc. Right. So fashion was the first category, but again, slowly and steadily, we'll keep expanding into the other categories.
Amit: You mentioned around the first store you spun out Ankur Warikoo doing products. Right. I'm curious. Most creators use Linktree. Sure, it sounds like a clunky way to present 20 books, but couldn't Linktree do it? Can't creators? You can go to a wix.com and create this website. So how did you think about what else the creator can do, and why does this need us to exist?
Shaurya: So, a couple of points here, Number one, creators use tools like Linktree. Now, Linktree is not specifically made for e-commerce,It is just a blanket solution where you can just share their links. Now, again, that gets cluttered. Let's say if I have to share, if I am putting, let's say, one post every day, and in every post there are, let's say, five products that I'm recommending, my Link tree will keep on getting cluttered,So that is one like the existing solutions are not made for e-commerce. And also, if I'm going on to try to make a website, that again is a very challenging task at the creator's end. One part of it, even the front end, would be broken to do that. The more important element here is the back-end stuff that we do, right, wherein we go and partner with each and every brand. So currently, we are working with about 200 brands, all top fashion, beauty, and personal care brands. For any one particular creator. It would be very challenging to reach those 200 brands,And that's the job we do for creators, that we go to brands, negotiate our commercials, et cetera, on behalf of creators,So that's the real value add that we do here.
Divyansh: And this was a huge surprise for us when we started. When we started looking at it, only Amazon had an affiliate program, and Nykaa had an affiliate program that was very selective. No D2C brand had an affiliate program wherein creators could register and get access to their affiliate links. So it was just Amazon, and for some beauty creators, Nykaa, that is it. So somebody had to go and integrate with each brand and get all of them together in one place for creators to start sharing recommendations.
Shaurya: Again, tracking is becoming increasingly important here because that was one of the key pain points brands started facing while working with influencers,So, for example, I'm paying one lakh rupees for a 60-second reel. As a brand, I would not know the outcomes of this one lakh rupee I'm investing in as an influencer. Apart from some of the top-of-the-funnel metrics, like views, engagement, et cetera, I don't know what is happening after that. Am I getting users onto my platform or not? Are those users converting or not? So that is something that was broken into the system. So that is the groundwork that we have done,Wherein we built our tracking infra, integrated with each of those brands, did the negotiations, et cetera, which is very difficult for any creator to do on their own. And most of the creators rely on agencies, so they are literally at the mercy of agencies to give them a paid collab. That results in their spending being concentrated in the hands of, let's say, the top 1-2% of the creators versus 99% of the creators struggling to monetize. So yeah, they don't have a connection with the brand, and that's where we come into the picture.
Amit: How did you guys come together as a team? And Chandan, the other co-founder, how did you find each other?
Shaurya: Yeah, all three of us knew each other from our college days, were friends at college, and were part of the same network. All three of us had that urge to start something of ours while still at our jobs. And Divyansh had also started up on his right after college. So we always had that urge to start something of our own. We kept on brainstorming a lot of ideas. I came from Bain and was deeply involved in consumer tech, retail, and e-commerce. So always had that ambition to do something in consumer tech and consumer space, which is why we are figuring out multiple ideas within this. One of them was, let's say, starting our own D2C. Still, we realized that, okay, there are other broader problems that can potentially impact the broader D2C economy as well in the form of, let's say, leading to discoveries cost-effectively. So yeah, we knew each other.
Divyansh: Shaurya and Chandan, both of them are my college seniors. I knew both of them from college. The three of us were a lot of times we were thinking and brainstorming on a lot of ideas. This really clicked, and it made for us to be a good team. Shaurya, he comes from a consulting background wherein he understands the macro of things and also has a lot of deep e-commerce experience because of some of the cases that he has worked on. So I started up right after college, then I spent around one and a half years with ClassPlus, which creates SaaS products for coaching institutes and teachers. And one very interesting thing that I saw there was all the teachers who sell the highest number of courses or who are doing crores in sales every month. All of them were big YouTubers with millions of subscribers. So I also understood the power of distribution that creators, in general had. And obviously, Chandan brought in a lot of an immense tech experience from all of his experiences. So the three of us, I think made a very good team. And one other common thing was that during COVID, I think the three of us were hooked onto social media. My Instagram time was 3 hours, 4 hours a day. Similarly for Shaurya, similarly for Chandan. The problem statement came very intuitively for us because all of us were social media addicts at one point during COVID. So this was another common theme. Now I can justify my guilt and say that it is work, but it's still three to 4 hours a day. So I would like to ask you here, we've told you how we developed conviction and went about this. What was your thought when we first talked to you? Or how did you build the conviction to invest? Because it was a pretty early stage and we had a few POCs, we had the product in place, but it was a very early bet. So how did you go about making that decision?
Amit: Yeah, so I think for me and us as Elevation, I think a few things happened, and maybe not a lot of people know this, but we were called All Things Good; Wishlink happened later. So I remember back to that sort of first time we met. I think I had a bunch of folks at Bain ping me saying you absolutely must meet these guys. They're doing something very interesting. I was obviously at Meta. I was deep into this world personally as Elevation also we've seen this world very closely in social. My Instagram time is 15 minutes a day. But I have a screen time and then I keep extending it by 15 minutes. But anyways, I think jokes aside. So I think, look, what I had seen and what I already had a view on was, to some extent this macro problem you highlighted. So creators have distribution, they have influence, but what else can they do with it being an open space, and so how do you help creators be successful? How do you leverage that? Distribution was a problem statement that we were thinking about. On the user journey, a lot of users are now discovering things are being inspired on social versus being very intent, driven was again something that was very evident to us. So we were sort of catching these two, three trends discreetly,And then, on the brand side, brands are struggling with ROI. Classic performance is tapping out. Brands are worried about a lack of accountability, lack of measurement when it comes to engaging with influencers. Again, that is something I've seen very closely at Meta. So part one for us, and for me personally, was look, all of these things were sort of there somewhere in the back of the head, but at least I hadn't pieced them together. So one part knows. I remember that our first conversation was, I think you guys sort of brought it all together. And suddenly I could visualize one model where all of this made sense. I remember that hacky All Things Good page for Ankur Warikoo. And it all made sense. Suddenly it solved all of these three things. And as an early-stage investor, it felt like this was the answer to bringing it together. A lot of questions remained, but this sounded like a very good answer. So that was sort of one right where I could also resonate with the same gaps. The second part, I think, was on the market opportunity. Somehow when we jammed, and I think we'd spend a couple of hours just like talking through, what can this become? Why will it not work? Why will it work?So those open discussions, I think I personally walked away feeling like this is a big opportunity otherwise, classically like the question I had for you guys classically, I would always think of this as influencer marketing therefore, how big can this really become? Sure, there's a good company here, but is this really a really large outcome? And I walked away saying, look, this is the future of e-commerce and we are talking about the next big movement in e-commerce happening. So, personally for me, I walked away from our jamming session saying, almost seeing the light of saying, look, this is that really exciting thing happening. A couple of more things, I think. Third, for me was, we had spent a lot of time again, I reflected back to those early couple of weeks on just what design choices. Do we work with Amazon? Do we work with big brands? Do we work with small D2C brands? What kind of creators, and what categories? I think again. I don't think we had the answers back then. I feel like we're still obviously discovering some of those answers. But I felt the design choices you guys made were very thoughtful. And so, for me, what stood out was saying, look, there is this very sound logic to why we are making some design choices. There is a big board on which we can take many decisions but we are being very thoughtful, very intentful about that. And so while commerce is serendipitous, I think the design choices are very intentful. And for me, that really stood out. And last thing, I think to your point of like it was really early. Of course, it was very early. We were pre-product, almost obviously pre-revenue. But this no-code website you'd spun up, so almost that hackiness, that hustle, I think I really appreciated that. And so that was very encouraging for all of us at Elevation to see that we created something. We tried to test it out. Again, in consumer it's very important. The good thing in consumer is you get many shots, but you need to be very fast. You need to really learn very fast. And we could see that coming through right in that early hustle. I think those things came together, and this felt like a journey I wanted to be a part of and very excited to be a part of.
Divyansh: I think that we were talking to a few investors at that point in time, and it was the first time after our first conversation wherein we felt that, okay, these guys are exactly where we are in terms of how we are thinking about this market, how we are looking at creators, creator, economy in general. And felt that connection very early on. And I think it was a very fast turnaround time for us, especially, wherein we, I think, closed after our first meeting and the final handshake or term sheet. It was 24 hours. That was amazing. Fast movement from you guys.
Amit: Yeah, I think we were speaking the same language. We wanted to solve the same problem. Felt like you guys were the rebels in this world, trying to fix things, trying to break things where things have worked a certain way. So it just all felt very think. You know, we spoke briefly about this. One thing I wanted to spend more time on is actually a little bit of now going deep into the product. Right. Like at level one, I feel it sounds fairly simplistic. This is a curated store. You've got Amazon affiliate at the back. Sure, you have a much better experience. Nice store for a creator, their personal identity to it, all of it. But actually walk us through the product. What does it entail? You mentioned there's a back end. What is this back end? How complex is it?
Shaurya: So, a tech stack can be broken down into two parts. One is a post content stack wherein a post has already been posted on social media. And then what happens after that? And then there is a pre-content stack, like what all goes into put that content out as well. Right. So in the post content stack, basically we are making it easier for the users to transact after they're discovering products. So some of the things that we do is we equip every creator with a storefront, and all of those storefronts are personalized for every creator. So each creator would have its own unique storefront. Then we kept building and shortening the user journeys as well. So one of the features that we launched recently was Wishlink Engage, which is a comment to DM Flow. And obviously, then there is a tracking mechanism, end to end, right, which tracks users at each step. Like what content are you watching? On what content pieces are you commenting on? Which influencer storefronts are you visiting, then? What brand websites are you then subsequently visiting? Are you making transactions there or not? If you're not making transactions, when are you coming back to that brand website? What is the source from which you are coming back to that brand website? So all of that tracking mechanism which is very deep, which is, I would say, like it's one of the best globally as well. We have seen some of the players operating in the US. So our tracking mechanism is something which is top notch.
Amit: So the brands you work with, do they not have this? Google, and Pixel does some of this, and so on. Where do you find them today? And you mostly work with larger brands,I would expect they are more evolved.
Shaurya: What we have observed is that, let's say, some of let's, if I pick up the top tier of the brands,They might have an in-house tech team, but again, they would be just like their bandwidth would be blocked with some of the other developments the brand is doing for them. Right. This never really came up as a priority because brands traditionally looked at influencers as a marketing channel, not a performance channel,So they were not actually focusing on tracking each of those things. They were using some of the hacks, like seeing a spike in their Google Analytics ticks, but they were not able to tell which creator is driving what sale. Some of the mid-tier brands that we have seen they've actually outsourced their tech. So they don't have an in-house tech team. So that is also one of the reasons why they were not able to build this tracking infra. They were looking at creators as one off marketing campaigns. So that is why, again, they never really focused on building this ongoing engagement with the creators. On the brand side, I would say some of the mechanisms they use are like the traditional ones, like UTM sources, et cetera, et cetera. This required basically putting up some code snippets on the brand website. So there is continuous tracking of users coming in, going out, etc.
Divyansh: So, like I mentioned, only Amazon had an affiliate program, and they've built it very well. Flipkart tried building it in front of us, I think mid last year, and they were not able to launch it by themselves. Very few D2C brands, only a handful I can count on my fingers, have an affiliate infrastructure in place wherein they can track the users and the sales that are coming from a particular creator. On top of it, you also have to build a payout mechanism wherein you have to pay first track and then pay to the creator.
Amit: Do they track like typically when a brand does a campaign with an influencer? Generally you pay a fixed amount, then create some content. Do brands even track at that level, or is it a part?
Shaurya: So it's a very broken tracking mechanism. As I mentioned, they typically would use UTM parameters. Now, UTM parameters would, first of all, they won't be able to identify at a creator by creator level, though they might be able to track the traffic that is being sent, but not able to track what was sold, what's the conversion like via UTM,What's the timestamp, all of those things? A lot of insights are hidden in those details which the brands are not able to capture. Other methods that brands used to study or used to leverage were, let's say, coupon code mechanisms,And again, you would see a lot of attribution issues there. So they were using some mechanism.
For example, some of the brands that are ahead in the curve of tracking what's happening with influencers, what they typically do is look at the spikes at an overall level. That okay, I'm working with ten influencers right now. Am I seeing any spike in my traffic? And that is it.They can only just measure the deltas of what's happening. But to optimize this, you'll have to measure it better. How do I know that? Okay, out of these ten influencers, five worked, and five did not work. Brands won't be able to identify that. They can say, okay, across these ten influencers, this is the delta that I'm getting. So they are able to track, but in a very broken manner versus our, let's say, the tracking mechanism is something which can give details at a user level, like not just at an influencer level, but also at an audience level of a particular influencer. So that's how robust the tracking mechanism is. Correct.
Divyansh: So they were not able to attribute 100% of the value that the creator is driving. UTM only captures the impulse at that moment. If I click on a link, go and purchase then and there, then only that sale is captured in the UTM. Otherwise, the UTM gets overwritten. Secondly, even if they were capturing something or making sense of it, this data was not flowing back to the creators. So there was no feedback loop for creators to optimize or make their content. So these were the major problems that existed because of which we felt that, let us build this infrastructure ourselves.
Shaurya: Yeah. And let me just add upon that by walking you through the pre-content stack. What happens even before content goes out? Right. So, as Divyansh mentioned, in traditional ways of working with influencers, there is no feedback loop for the creator versus what we do because we are tracking each and every data point. We are creating those data-driven feedback loops for the creator. So essentially, what we can now tell a particular creator is that, hey, whenever you put this subcategory at this price point, we see a spike in your funnel. So maybe next time, whenever you are putting out content, include Jeans prices between Rs 1000 to Rs 1200. These are the ten brands that we have for this subcategory within this price point. Within these ten brands, let's say these are the 200 SKUs that are most suited to you,So that's the pre-content stack wherein we are doing very detailed matchmaking of a particular brand and a particular creator at SKU level. So, pre-content stack, one is this, which is how do you tell a particular influencer what to include in your content? Secondly, one of the problems that we identified here is that even if we tell them that, hey, you need to put out this particular product, let's say they did not really have that product,And that is where another tech stack kicks in, which is a sourcing mechanism that we have created which actually allows creators to source those products, shoot content on it, and then return it back to the brand after they have shot that content. So there are these three, four elements in our pre-content stack as well, which make sure that with every content the influencer is putting, there is compounding happening,So if I'm putting out content today, if I'm earning, let's say, Rs 20,000 as commissions on that particular content, next time when I'm putting content, you'll earn Rs 25,000. Because that data has compounded, we are actually able to pinpoint that. Okay, your audience wants this. So include these products. We'll also help you in sourcing those products. We also have, let's say, a content and selling playbook where we tell them what are the best practices while putting out content pieces. For example, what's the right call to action to give, what should the timing be, what should the hashtags be? So that your funnels are also improving. So this helps us in actually adding much more value to the creator, not just in the form of monetization, but also making their work very easy in the sense that we have automated a lot of flows. We also, to an extent, solve for their, let's say, blockers that they keep on facing. That what content should I put? Our recommendation engine keeps on giving them these insights based on their data based on the overall trends in the market. For example, let's say Monsoon is coming up. So why don't you, let's say, recommend products related to Monsoon, let's say during summers? Why don't you recommend sunscreen? And here are the five top sunscreens out of our partner brands that we have.
Divyansh: So, just to add to this post, the content stack is making it easier and easier for end users to go from social media to brand websites in the most seamless manner. Pre-content stack is essentially making creators' lives and their content creation journey easier and easier and easier. So this is an evolving process wherein, as Shaurya mentioned, we've built a lot of products to make creators lives easier and the journeys of end users from social media to the brand websites very easy. Now, one product we built that actually lies at the intersection of both categories was Wishlink Engage. So what happened was every creator had a storefront which was in their link in their Bio on Instagram. But still, the journey of an end user was still a lot of steps. So I'm scrolling reels, I'll click on the creator's profile, click on their link in Bio, find the products, and go to the brand's website. So what we did was can we shorten the idea in our head, was can we shorten this journey? And what we built then in association with Meta was can we automate this flow wherein a lot of users, the existing user behavior is they comment for links and product details. So a lot of creators get comments on their reels. Can you give me product details, can you share links, link please, et cetera, et cetera? So we automated this flow so that whenever a user comments with any of these keywords, they automatically get a DM from the creator's handle with the exact product links that were in that reel. So the idea was to shorten the funnel and increase sales, which happened crazily. But there were some second-order effects that we hadn't imagined, which lie in the second bucket, which is pre-content. So what happened was we ended up saving one to two hours of creators' lives daily because they didn't have to reply to each and every comment and send links and DMs manually. And the second thing was, which we absolutely did not expect after seeing this, we gave this product the name Engage. Their engagement rates really shot up because more and more users were commenting, they were getting replies from the creators, and other users were seeing that they were also commenting. So I think we have a few creators where some of the reels have more than one lakh comments on Instagram, which is something we've never seen on any content piece. This was one feature that sort of lies at the intersection of making it easier for users and making creators' lives easier and better.
Shaurya: And the third order effect here is that now the Instagram algo will kick in. If you're seeing more engagement in a post, Instagram algo will also push that particular content piece,So it is just improving the funnel throughout. You are getting more. So after a creator starts working with Wishlink, they get more engagement on their post and more views on every content piece. They know what to create, and what products to include in their content pieces, and on top of it, they're also monetizing each and everything. So the life of a creator changes actually after they're onboarded onto Wishlink. We make their lives super easy. We help them monetize 100% of the content pieces versus, let's say, just monetizing 10% of your content pieces via paid collaboration, so that's the value of our tech stack in a creator's life.
Amit: Very interesting. Creators' lives are obviously changing. How's life changed for you? Beyond the shirt, obviously a lot more colorful than before. I presume you're hanging out with creators. You're part of the IT crowd, I guess. How's life different? What are funny stories? What was the ramp-up to actually learning to talk to creators now that your customers are.
Shaurya: I think what I used to see or what we see from the outside, it's not exactly that. They're very normal people. They are fun to hang out with. They're fun to chill with. I had certain notions that how would I chill with them or how would I party with them. And eventually, I realized they hang out or party in the same way that most of us do. So it has been fun. It has been fun mingling with them, understanding them, trying to understand how they work, and how they create their content. And obviously, I have picked some sort of fashion from them, and that is true for most of the people on our team. There are people who will spot a t-shirt from a distance and tell you the brand of that t-shirt. So those are some of the things that happen. But yes, in general, the experience has been really good. I'll give you one interesting incident that happened with us very early on when we were just starting out. So we had around 10-15 creators onboarded, and there was no dashboard for creators to see any of their earnings and everything. So what I used to do was every single day, at the end of the day, I used to create a PPT with that creator's individual numbers of the day, and I used to send it to them that these are the numbers for the day. So obviously, there was a lot of trust deficit. And then there was this creator, a very dear friend. Now, she gave me a two-week deadline: either you give me a dashboard in two weeks, or I'm not working with you guys. So me and Chandan, we started building the dashboard. And on the 14th day at, I think, 10:00 PM, me and Chandan were in the office, and I got a message from her that, where is the dashboard? And I literally sent her a photo of Chandan coding that we are deploying in 1 hour. And we actually deployed it around 1130 on that day. It was a basic dashboard where they could see their numbers. They pushed us to create our product at a very fast pace because that was a need of the hour, and that is how we've built our product wherever there, so we experimented with hacky stuff, and then there was actual need, or they creators were behind us. We then built the products.
Shaurya: So, one more thing to add here. I think Devyansh obviously works more closely with the influencers, but he's also a meta influencer. So typically, we follow influencers, but it's the other way around here where influencers are following him.
Amit: One thing I've noticed when we talk on WhatsApp we talk normally, I say hey, you say hey, I say hi, you say hi, I say hey to you, and you say ‘heyyy’, then every word is three Ys or multiple. Is that influencer speaking?
Divyansh: It is an influencer thing but this is also my thing. So I have a younger sister who talks like, yeah, he was made for this. I text like that. Yeah, that has completely become all of my professional conversations as well. I try not to do it, but it just on WhatsApp it happens.
Shaurya: Yeah, you should also look at our town hall PPTs. It's just full of memes, and it just communicates the messages beautifully.
Divyansh: Absolutely. So that is one thing because of the virtue of we are in this space. There is a lot of fun environment at the office in general. So all the presentations, the meetings, and everything, they have this fun element or this Gen Z social media element in it. Literally, all PPTs are just full of memes. And we have three-hour-long town halls, and I've not seen a place wherein 50 people were completely attentive for 3 hours. It is just because it's filled with memes.
Amit: I think so far, we've spoken a lot about that early journey, what we are building, how we came to it, and all of that. I'm curious what scale are we at? Where is the business today? What scale are we at?
Shaurya: So, currently we are working with about 600 fashion influencers. About 200 or so fashion brands. Some of the names would include brands like H&M, and Westside working with e-commerce platforms like Myntra, Meesho, and Amazon. So all top-tier fashion brands. It's a deep integration both on their websites, and if they have apps as well, then we are tracking things on their app as well. So it's a very deep integration. So that's the groundwork that we have done so far. Every month we are redirecting about 10 million or so unique users to our partner brands' website. So just to put this in perspective, this means every month, we are reaching about 5% of the online shopper base in such a short span of time and with just 600 creators. And the 600 creators are just 0.2% of the overall creator base, overall relevant creator base that exists in terms of GMV or conversions. In June, for example, we drove close to Rs 12 crores worth of GMV across our across our 200 brands. So, yeah, that's the scale at which we are. And we are growing about 60% month on month.
Amit: And as you think about this, business has so many layers. As I see it now, what is the what is the North Star? What are a few things which really matter to you? What do you solve for? What do you optimize for?
Shaurya: Yeah, so the North Star metric for us is creator earnings. It's not GMV, it's not, let's say, the traffic that we're redirecting, et cetera. It is creator earnings because the creator is the persona that is central to all of those things. It is the glue that is keeping all the stakeholders together. Users are following creators. They trust the authenticity of that. Creator's content brands, again, are getting benefited because creators are sending their audiences to different brand platforms. So creator is something that is absolutely central to us. So, yeah, the North Star metric that we focus on is, are we improving the creator earnings month on month? Is our matchmaking and pre-content stack kicking in or not? So that's the one North Star metric that we focus it.
Amit: One is obviously what earnings we drive for them. But creators do so many other things. So what do we aspire to? Do we want to move these earnings to a place where they work only with us? Or how do you measure success on this dimension?
Shaurya: So I'll tell you how to visualize this. Right. So, before a creator is onboarded onto Wishlink, let's say hypothetically, they're earning one lakh rupees as part of paid campaigns. They would be doing, let's say, three to five paid campaigns in a month when they start working with us. This is incremental earning,So instead of now just earning one lakh rupees, they'll be earning two lakh rupees, three lakh rupees, et cetera. Most of the creators that have matured with us in the sense we have been working with them for, let's say, six months. Plus, we contribute like 60, 70% of their overall earnings. And this is an incremental earning. It is not like out of one lakh now. We are contributing 60,000. We expanded the pool, and then we are 60% of it. So we have more than doubled their earnings.
Divyansh: For a lot of creators, we are at 70, 80, 90% of their overall earnings. And this is, as Shaurya said, completely incremental. So their brand collaborations are there, they exist, but this is on top of what they were earning. And on this earning, there is no ceiling because you can do, let's say, you charge Rs 50,000 for a brand collaboration. You can do 5 or 6 or 7 or 8 brand collaborations at max in a month. But when you are doing commerce, you can sell as much as you can and as much as your audience buys, and you can earn as much as possible. I'll give you an example. Last a few months ago, I think there was a video that sold one crore in sales for Meesho on YouTube. So things like these give us an idea of and set new benchmarks for us. Every month something like this happens, and we realize, okay, the potential here is huge.
Amit: when we think creators, we naturally think Instagram. But how are our creators split across social media platforms? Who are these creators?
Shaurya: Yeah, our tech stack is basically platform agnostic. So it currently works on Instagram as well as YouTube. These are the two primary channels as of now. But we have seen very organic pickup on other platforms as well. For example, Pinterest is another platform that has started taking up shares. Then Telegram is another one wherein some of our creators themselves are managing communities on Telegram or on Reddit. So some of those channels are also picking up. But as of now, yeah, Instagram and YouTube are the biggest, but we have seen a very good spike in other channels as well. So it will continue to grow.
Amit: Interesting. Yeah, very interesting. Got it. So that gives a sense of scale today. Stepping back now where you guys are, what do you think about this? How big can this become? And one question I was reflecting on, you mentioned pre-content. You mentioned, look, we have the ability to match a creator with the brand, tell the brand what's the right creator, or other way around. And then you mentioned 10 million unique users. It seems you know more about this user than potentially the brand or the creator, or even the platform knows. Is there in the spirit of saying like, where can this be? Do you know more about users than what is classically available? Can this become a ‘Why don't I go to Wishlink and start there’? Do you see that happening? Are you just bookmarking Wishlink links like what's happening?
Shaurya: So there are two parts to look at it again,One is the core, which as of today, will obviously continue to expand as we keep on working with more brands, as we keep on working with more creators. But the second and the bigger opportunity here is again actually solving for that discovery-led shopping for users. Because just to give you some insights on the type of data that we can potentially capture, let's say even Meta won't be able to capture as of now is that what we know is a particular user viewing a particular content. Meta would know that, okay, this user has seen this particular content. In addition, we know what the products are as well in that particular content piece. So that's a new data set that we have on a particular which Meta doesn’t know. Then very deep user data that we capture, which potentially brands and creator won't know. So we are able to tell for a particular user we know what their purchasing power is based on their past purchase data across e-commerce platforms, we would know it across different brand platforms as well. So we can make a more holistic picture of a particular user. With the data that we have right now, we are now able to predict what this user wants to buy and what is the potential timeline at which he is going to buy. What we can predict by looking at all the content he has currently seen, and what all brand websites he is visiting is this particular user right now looking at jeans. A couple of weeks later, he might be exploring footwear, and a couple of weeks later might be exploring accessories, et cetera. So we know what this user potentially will buy and we can also predict when this user will buy because again, we look at their purchasing patterns. For example, I can tell that, okay, this particular user typically visits a brand website three times, and then the fourth time is when he is most likely to convert or purchase. So we can actually predict that. And we can also know the average number of transactions for a particular user in a month. So we can make cohorts and say that, okay, these are the users who transact four times a month. He has already transacted twice now he's expected to transact again within this month. So we have a lot of data on the user side, and that opens up a lot of opportunity. Currently, it is being used for matchmaking, but again we can go directly to that user as well. What would that shape or form be Is something which we are still debating discussing iterating on, on what that exact would be. But things like you can discover products here, maybe create mood boards. One of the minor features that we had built, and we did not know it would have such a huge pickup, organic pickup, was giving users wishlisting capabilities which are you are visiting multiple creator storefronts. Can you start wishlisting those products, and can you get that wish list onto your WhatsApp right without any push from our side? There are about two lakh people, and two lakh unique users who are maintaining wishlists with us,So users themselves are also telling us that, hey, I am right now, let's say, wishlisting jeans or wish listing shoes. Now this has a lot of value. We can go back to our partner brands and say, hey, you are selling Indian ethnic I have 50,000 users right now who are wishlisting Indian ethnic products. Can I push your brand to that particular creator? We'll also have to see how we do it in a non-intrusive manner. But that is something which is a work in progress. Just building that POV again, leveraging the extensive data that we are capturing. So in future, there is definitely a user side play that is possible here.
Amit: Very interesting. Is that why we're called Wishlink? A play on wishlist?
Shaurya and Divyansh: So you wish for links and we give you links. And we are linking your discovery and purchases.
Amit: Super. I think shifting gears a little bit. The last thing, and this gives a very good window into the journey so far, but the last thing I want to spend some time on, something that a lot of our listeners, our viewers, are very curious about, is really early days. So almost pre-visioning days of starting. How did you guys think about starting out? And I guess some questions for me were what you spoke briefly about, but what was your journey like either before you quit your jobs or just at the time of quitting your jobs? I think a lot of people are just nervous to take that plunge, and a lot of people have great ideas. So how did that happen? Did you have an Excel of ideas, and market sizes? But those really early days of taking the plunge, like, how did that happen?
Shaurya: So again, one of the things that I mentioned, right, which is those macro trends is something that we kept on observing, and us being users ourselves, we knew that, okay, this is one of the pain points. For example, if I have to purchase, let's say, headphones right now,What I'll first thing I'll do is I'll go to YouTube, watch five videos, make my point of view, and then scramble and try to find that product as well as where to buy it. So we ourselves as users, had starting facing those issues. Macro trends again were at the back of the head now, and I think absolutely right. How do you take that plunge?
Amit: At what point did it call out to you? Look, I am meant to solve this problem. I see a lot of problems. These are problems. I hope somebody solves them. So I think what, first of all, the idea really excited us. Basically, the space. Really excited us. There is social media and e-commerce. This is the most exciting space that you can work in consumer-tech. So obviously, the thesis and the idea excited us. The next step was how do you start building conviction on the thesis because theoretically, everything would make sense, but how do you then start executing those things? So what we did was while we were still at our jobs, we started finding time at the end of the day or during weekends. Started doing very quick iterations. Again, on no code. The first product was a no-code product. Tested it out, had different variations of storefronts. Should all creator content be put out on just one single storefront, or should there be multiple storefronts? Right. So there were iterations on that. Tested it out while we were still at our jobs. Again, some of the anecdotes that Divyansh shared right. One of the fashion influencers selling five lakh rupees worth of products in five days that we witnessed while we were still at our jobs. So that kept on giving us the conviction that hey, correct, this is an exciting space. We know we have a fair bit of sense of how this can be solved. We have seen some early proof points as well. Now is the right time to take a plunge, quit our jobs, and focus on this problem statement full-time.
Divyansh: Yeah, I think we wanted to work on something from my point of view and this was a starter. And before this also, we have picked a couple of problems, tried to get into them and then at some point figured out that either we didn't want to do this or this was not a big enough opportunity for us to continue. But what happened here was the idea, the initial thought of an idea, and the possibilities here really excited us. And then it's a journey, curiosity-led journey wherein every single day you are reading up on something or you are talking to a few people or you are building something, putting it out in the market and getting some feedback. So every single day, there are more inputs from the external environment that makes your thesis, which adds some elements to your thesis. And for us, what happened was it kept on making our thesis stronger and stronger and stronger. We would do some expert calls with Instagram's team, talk to Amazon or some of the other players in the US, or talk to users and creators. So it was a very curiosity-led journey. We were figuring out and finding new answers and insights every day and kept increasing our conviction throughout this journey. And I think we've been fortunate here that what we started with is exactly what we are currently working on. And we've just gone deeper and deeper and deeper into the same problem that we are solving and didn't have to change paths drastically throughout the process. So from day one, it was getting deeper and deeper into the problem, finding new insights, building our solutions around that, and then creating a path.
Amit: I guess now you are close to two years into that journey from starting to think about it when we partnered very early to now. Now, as you reflect back, are there obvious mistakes you made, things you would have done differently? Like when you think about it, either pre starting out or just in those early days, are there things like, you know, are obviously wrong, or we would have done things differently?
Shaurya: So I think one very good habit that we developed midway is to have checkpoints, let's say every couple of months, to retrospectively see were there anything that we could have done differently. And I think I would like to mention one of our angel investors, right, Rahul Chaudhary. He actually just sent us an email and said, hey, are there things that are important but not urgent that you have not focused on? Would you do those things differently? So that actually put us in the habit of just at every point of time, just keep checking that hey, are we doing this correctly? Is there something that we could have done differently? Playing devil's advocates to each other's thought side, that hey, why are you saying this? This could have been done that way. So one of the, I think mistakes, or let's say, and that would be a learning, obviously, is that let's say November, December, January last year, like 2022, what we started doing as a competitive response was started giving out some minimum guarantees to the creators. Now we realize that that's not the right way,Because it doesn't align with the overall goal. We want creators to stick with us not just because of money but because of our product. If we are, let's say, making them comfortable by paying them money is something not how we would want to operate. And again, get some feedback and some learnings from you, from our angel investors on what's the right approach here. And we were very quick in correcting that,So it was only a couple of months of mistakes, I would say, that we were doing. And then we realized that, okay, this is not making sense. This is not how this would play out. And luckily, that has actually now been a bonus point for us, which is creators also actually making an effort, being as involved in the problem statement as you. Otherwise, they would have been lazy because they are just getting money out of it. But now they are deeply involved in the problem statement along with us on how can I, with every post, increase my earning,So that was one of the mistakes that we did. But the good thing is we were able to correct it in a couple of months' time.
Divyansh: Absolutely. I think as Shaurya said there were tons of mistakes that I can think about. And that usually happens when you're trying to move at a very fast pace. Obviously, you spend some time on the problem, you quickly execute, and move on. But what we did right was we had a lot of points in our journey where we just sat and reflected on whether we were doing this in the right way or if there an opportunity to correct it. And we did that very fast. So I'll give you an example. When I talk about a user-side product, the storefront, I think there have been six or seven versions of it that have been released from first was the no-code one to the current one. There have been six, seven versions, the analytics dashboards or the entire creator side dashboards. I think currently the one is a fifth or 6th version of that product. So obviously, if I look at it that way, all five of them were mistakes, but they were just building blocks for us to get to the product where we are right now. So it's just very quick, if you want to execute, there will be subpar products, and there will be mistakes, but you have to iteratively solve them and move very fast. That is, I think, something that we've done.
Amit: It's been very exciting to see both the platform grow and your growth journey as founders. So personally, I've had the privilege of seeing that up close. I guess this last question from my side and before we close is again, back to very early days, how did you think about Capital and who to partner with back in those days? How do you think about it now as you think about future rounds of capital as you continue to build this company?
Shaurya: So, two things,One is why was capital important. And second is basically which Capital partner to partner with, basically. So why Capital was important because what we are building here is sort of a new category creation, which would involve molding behaviors to a certain extent from a creator point of view, from a brand point of view, because they had three, four years of working together in a different manner. Right now, this involved basically driving some sort of behavior changes. Now, there are two approaches that you can take here. One is that you slowly and steadily try to drive those behavior changes. Or the other approach is that you try to cross this path in a quick manner and with scale, you will be able to do all of these things at a much faster pace with much more ease and also, the network effects will start kicking in. For example, we took three or four months to get to the first hundred creators, but now we are getting 50 sign-ups every day from creators. So at scale, it starts getting in some of the network effects. Now to be able to cross that path. I think that is why Capital is something which was important for us also to be able to experiment in multiple directions, to be able to test out what categories will work or not, et cetera, et cetera, what cohort of creators would work or not. Right, so Capital was something that really helped us in executing all of these things at a very rapid pace. Then what sort of, let's say, capital partner to choose? I think one of the lenses that we had was we would want to extract maximum value, and there are three things there,One is knowledge and expertise in that particular sector, the second is the network, and third is also what sort of conviction you have. Do you believe in that iterative process or not? I think those were the two-three lens that we applied and that naturally did fit in well with Elevation. And basically, our first, I think, 10-15 brands were all Elevation portfolio. So that really helped us in jumping that cold start on the brand side. And I think the same principle is what we'll apply going forward as well. Whether or not we are getting partners who have conviction in this thesis, who believe in this idea, or who believe in this new future of e-commerce also evolving,Can you have that conviction that, okay, today's e-commerce is 30 years old, and there has to be a new form of e-commerce going forward. So conviction is the most important one. And second, obviously, like the network basically, can we keep on getting more and more connects, which we saw at Elevation as well. Which is getting connects at Meta, getting connects at Google, getting connects at different brands, et cetera. So I think we'll apply a similar principle or a lens going forward.
Divyansh: Just one thing to add here was throughout our journey, and our partnership with Elevation, something that was very important and really stood out for me was the empathy towards founders and towards the decisions that we are taking and where we are coming from. That was really present throughout all of our discussions, and that empathy was again backed by a very strong conviction wherein there was a strong belief in the decisions that we were taking, in the design choices that we were making, and there was constant support throughout the process in all of those decisions. So those were some of the very important things, I think empathy, strong empathy, and agai, conviction on the founders, on the thesis, and the decisions that we are taking. So these were very important, and I think we would expect the same going forward as well.
Amit: Amazing. This is great. Obviously, the pleasure has been ours to partner with you guys, to see this journey up close. We feel privileged to see this category-defining company being created, like you guys are saying, almost reimagine the future of how commerce will happen. And all the best. This has been a very exciting conversation. All the best for the journey ahead.
Shaurya and Divyansh: Thank you so much. Thanks a lot. Amit.
Harnessing Unique Supply and New Audiences: Marketplaces Unleashed Part 2
Exploring the first two pillars of our marketplaces framework through case studies