Reklaim Ltd. (MYID.V) Earnings Call Transcript & Summary

Hi. This is Rob Breza from Lytham Partners. Today, we have a presentation from the CEO of Killi Corporation -- or Killi IO. I'm sorry. With that, I'm going to introduce Neil, the company's CEO and Founder. With that, we do have a presentation on our website that you can download and follow along with the presentation. With that, I'll turn it over to Neil. Thank you.

Okay. Thanks very much. As mentioned, I'm Neil Sweeney. I'm the Founder and CEO of Killi. Killi is a publicly traded company that trades both in Canada as well as in the United States. And Canada trades under the ticker symbol MYID on the TSXV. And in the United States, it trades in the OTCQB under the symbol MYIDF, F obviously standing for foreign. To give you -- to give everybody a little bit of context as to what the investment philosophy here is -- specifically for Killi is, what we are trying to do is really democratize data specifically for consumers. As all of you likely can appreciate, every single person on the planet today over the age of 16 has a digital profile today that is being collected and sold by various different companies around the world. The challenge in the market for consumers today is that there is no access to the data. As a byproduct of there being no access to the data, there is no optionality for you as the consumer. Should you choose to opt out, opt in, share data or be compensated for your data, these things are outside of your reach because the data market, which is a $400 billion a year market internationally and $250 billion a year market in the U.S. alone, isn't including you. Our philosophy is that if we can actually empower consumers, put increasingly more data underneath the control of the consumers, downstream, we have the ability to solve challenges for companies who are looking to actually use data that is compliant. And that's a really important piece. And before we quickly go into the presentation, a quick synopsis specifically as to sort of the macro trend as to what the catalysts are around privacy. So I think we would all agree that when we're watching BNN or CNBC or Bloomberg, virtually, every second story is about data or privacy, whether that's antitrust conversations, new releases from Apple and Google, COVID surveillance and/or tracing. These things are all rooted really in the use of data and surveillance. What's happening around the world, and this started 2 years ago, is that the European government introduced a new privacy regulation called GDPR. GDPR is by far and away the most onerous privacy regulation really ever enacted in the world. And in short, what it requires specifically to happen is that should you, as a company, want to use people's data from the EU, you must have explicit consent from those users. Additionally, you must give consumers the opportunity for them to opt out, to get access to the data, to edit the data, et cetera. Failure to comply with this results in fines of up to 5% of top line revenue. Now most people might think that who cares, that's the EU. What does that have to do with U.S.-based companies or Canadian companies or other companies? Well, what's been happening since then is, we've been saying is that there's been a privacy tsunami that has started in Europe and has now kind of come across the ocean and landed firmly in the U.S. market and the Canadian market. The consequence of GDPR is every country in the world is rewriting its privacy laws to include the consumer. This is probably the single biggest digital migration or data migration that the planet has ever seen. The byproduct of actually rewriting this privacy legislation is it is forcing that $400 billion market to move from a black box unconsented market to a market that is consented and includes the consumer. The question from an investment point of view is, who are the companies that stand to benefit from this migration that will take place over the next 12 months? And who are the companies that stand to lose? We clearly are biased, but we believe that we are the company that stands to benefit from this migration because in putting data underneath the control of the consumer, it is inherently compliant, which allows every company that is looking for a new supplier to actually purchase data specifically from Killi to not only solve their issues as it relates to data, but also ensure that the data that they are putting inside of their ecosystem is actually compliant. The takeaway from that is, as we increasingly move forward, data equals liability. Unless you can have consent specifically from the consumer, that's where Killi steps in. So if we refer back to the presentation that the team has here online, there's about 11 slides that you can quickly go through. I'll skip a little bit of a few of these. I won't go through it one by one. I would draw your attention specifically to Slides 4, 5 and 6, specifically. For us, there's a number of things that are important for everybody to understand. The most obvious being is, it sounds like a great philosophy meal, but how do you make money? So let's dig into that. So in Slide 4 here, what's really important to understand about the data market -- and just a little bit of background on me. I've been in the data in advertising and marketing ecosystem for over 20 years. I've started a half a dozen companies. When you look at the actual incubation, when you actually look at Killi, Killi was founded by me. It was actually incubated in my last company, a company called Freckle. That company, Freckle, was incubated inside of my last company, a company called JUICE and so on and so forth. So there's a history here of innovation and commercialization of emerging tech. All of those previous companies, whether it was Freckle, JUICE or even the one before that, StreamTheWorld, all -- are all companies that have actually been scaled and sold. We believe that Killi offers the best opportunity of all these. But just quickly coming back to Slide 4, how does the company actually make money? And there's 3 things that are really important to understand about the data market. The first is that if you would like to sell data to a Procter & Gamble or to an Experian, you must have scale. Without scale, you're a science project. So how do you take -- how do you create an ecosystem where you have an enormous amount of scale, where you don't have millions of users inside of your ecosystem, but you actually have hundreds of millions of users in our ecosystem? At Killi, over the last year, we've actually moved -- and we'll talk about this specifically on Slide 6. We've moved from having tens of thousands of individuals in our ecosystem to having hundreds of millions of people in our ecosystem. For us today, we have a profile. We have 320 million deduplicated profiles sitting inside of our ecosystem, which approximately is a profile on virtually every single adult American today. So we have the scale. The second component that's really -- that's vital in order for you to actually make money is distribution. The best way to think about data distribution is the same way that you think about grocery distribution. Inherently, the more places that your data is located, the more places you can actually drive revenue. So if we were selling coffee, the more grocery stores that your coffee is in, the more coffee you can sell. It is the exact same philosophy as it relates to data. These integrations are not trivial, but they are international in nature. When you do an integration into a platform like Google or MediaMath or [ Viant ] or Lotame or LiveRamp, these are all integrations that we've done over the past year. This is the equivalent to us putting our product in Costco, in Walmart, in Trader Joe's, in Safeway, in Loblaws. It gives us an opportunity for us to drive more reoccurring revenue. So the other thing that I think is really important is that unless you've been in the data ecosystem, knowing your way around these huge distribution partners is not trivial. These are not easy deals to do. Doing the deals, doing the integrations and then moving data into those platforms on a reoccurring basis is something that we think is competitively unique to us. And then the third component is this notion of unique data. You can have scale. You can have distribution. But the biggest challenge in the data market today, remember, that's a $400 billion a year market, is why is the data inherently different than the other person's data? And if you cannot differentiate that data, it clearly has an impact on actually how much money you make. If you have unique data, like we do at Killi, where consent and compliance are tied to the individual consumer, and you marry that with scale and distribution, you are setting the foundation for a revenue model that, as you continue to expand that distribution and drive more sales, you can begin to crank that revenue up. So those are the tenets and the core components that you actually need in order to actually drive revenue. We launched this business. So we've launched this business full time in the middle of COVID. We've built the infrastructure, the scale and the distribution to get us ready. We are now starting to crank the machine. So from context, from a revenue point of view, if you look at last year, last year, you did a couple hundred thousand dollars in revenue. We're now doing $300,000 per quarter. So you have a growth rate that is up into the right while maintaining a monthly reoccurring revenue ratio of over 70%. Inherently, if you can maintain those while continuing to -- continue to grow the business by adding more clients and partners, you'll be able to grow the business very quickly. So early innings from a revenue perspective, but the rationale for that is you needed to build these 3 tenets, the scale, the distribution in order to actually crank the revenue. And that's where our focus is as -- right now is really trying to double the size of the sales team, which is all primarily U.S.-based, really trying to help drive that initial revenue. Last kind of comment that I'll say specifically on revenue is that it's very important to remember that every company in the world today already buys data. So we are not trying to convince companies to buy data. That already happens. What we are telling companies is that the data that they're buying is going to either go away due to compliance or needs higher fidelity from us. And so it's really about using our data versus the data that they're using today. And a metaphor for that or a similarity will be nobody denies that the automobile industry is moving from gas-powered cars to electric vehicles. The question is, is really how quickly is that migration going to happen. Every time Apple makes a change or Google gets rid of the cookie or there is another privacy breach, it accelerates that move and brings more clients into the ecosystem to allow us to capitalize on that. So Procter & Gamble is spending millions of dollars today on data. When they buy data from us versus one of these noncompliant firms, we take 50% of that data. We redistribute 50% back to the individual consumer, thereby cutting them into the equation specifically that the consumer hasn't been involved with. So the revenue models are quite simple. The more data you sell, the more money you make. The more money you make, the more you can distribute back to consumers. The more you can distribute back to consumers, the happier the consumers are, which gives them an incentive to share more data, which helps us drive increasingly more sales. And around and around you go on the flywheel. So hopefully, that's clear. I would -- if I was an investor and looking at this, I would be looking at how the scale and the distribution and the number of clients is manifesting on the revenue line and how that growth rate is continuing to actually roll. So I'll skip over to Slide 5 and just kind of quickly jump to Slide 6 because I think that this is really important. Because I think we're all very quick to kind of say, like, what are we doing right today -- what are we doing in the business today? If you look at where we were last year compared to where we are now, when you look at the number of accounts that we had, we said that we had tens of thousands of accounts at the beginning of 2020. We now actually have over 300 million accounts. So incredible growth, incredible scale. The more data you have, you have an unlimited ability to drive revenue based on that scale. Unlimited. We wouldn't have to add one net new profile to our data to continue to grow our revenue line in perpetuity. Important to note about that, too, is that we also don't have this huge overhang as it relates to a cost of good or a cost of acquisition. Because we've been partnering increasingly with publishers and other data companies and bringing data that's readily available on consumers to the Killi ecosystem, allowing Killi users to come into the product, put in an e-mail address or a mobile phone number, unveil -- we're able to unveil the data that's readily available to them, put it underneath their control and begin to compensate, is that our cost per acquisition from a data perspective is virtually nil. And that's a huge component because again, in the beginning of 2020, our cost per acquisition was approximately $3 per user. So 10,000 users times $3, there's your cost. Now you have 320 million users with no cost. So this is important because as you drive revenue specifically on the individual users, you're not having to generate $1 per user in order to get to cash flow positive. If your cost per acquisition is $0.05, the moment you start to generate $0.01 or $0.05 or $0.10 or $0.50 per user, it's all margin, and it's all -- the revenue line goes almost completely vertical. So the scale and the cost per acquisition, you need to be looking at sort of in combination. Secondly, distribution, I just spent a lot of time talking specifically about this, is that you could have all the data in the world, and it could be really, really unique, but if you cannot get it into the store, nobody can buy it. It's essential for you to actually -- can only sell so much -- so many pieces of data or so many products at the back of your car. You need to get it into the individual platform. So again, going back to the beginning of last year, we had no scale. We had no distribution. We started by integrating our data into some of the bigger platforms, the first couple. Moving now, we're at a dozen of these individual platforms, and we're actually adding anywhere from 2 to 3 of these platforms per quarter, so almost one per month. So as you scale the number of accounts and you increase the distribution, you're increasing the opportunity for you to actually drive revenue. Also important to note is that all of the platforms that we're working with today are all international in nature. So when we put data into a platform like LiveRamp, it's available in the United States, Canada and every other market that they support around the world. When we put data into a Lotame, same thing. It's not -- you're not having to do one platform by one. And so for Killi, which supports a half a dozen countries, can pay what we're selling in, in half a dozen countries, and we add additional countries, we do not need to actually change our distribution because our existing partners already support that international market. Last but not least is sort of the uniqueness of the data points per user. So again, when you think about the product today, knowing that there is a data profile on you in the market today. So sometimes consumers or investors will say, "Well, I don't want to sell my data or I don't want to put your data in here." The important thing to recognize is, your data is already in the market. The only difference is that you're not included. Failing to participate in the Killi ecosystem is a suggestion or acknowledgment that you do not want control of your data and that everybody else should be able to use it without your involvement. No consumer really wants that to happen. The only way that you can change the market and begin to take back control of your data is by being inside of Killi. So as we built this ecosystem and we've accumulated more and more data on behalf of these consumers, we're slowly but surely allowing them to amalgamate all their data from these other platforms. The downstream impact of this is that if you have 320 million accounts that are fully consented, thereby adhering to the privacy law, and Procter & Gamble, who has inherently been buying data from this other side of the market, wants to get compliant, they're going to move their spend to the compliant market, which sucks the oxygen out of the room for those companies that do not have that consumer compliance. And so there is this slow shifting of dollars from that noncompliant market to the compliant market. And that comes back to the general thesis of the entire USD 250 billion data market and the $400 billion a year global data market is going to go through that process. It is going to move through -- from an unconsented market to a consented market. We really believe that we're the ones that stand to benefit from that. So just to kind of quickly wrap up, why you should invest in Killi or what you should be tracking, we've listed a number of these things specifically on Slide 7. This is an early stage company that you can participate in exceptional growth. We have enormous scale. We have great distribution. The revenue line is reoccurring and growing. We believe that we are the market leader in this movement of the data transition that I made reference to. We believe that similar to how Robin Hood is democratizing data, democratizing, trading consumers or wealth simple is [indiscernible] more things for wealth management for Canadians, there is no kind of definitive brand as it relates to the democratization of consumers. The opportunity here really is that every consumer over the age of 16 can be -- can potentially be not only a client, but also an investor specifically in what we're doing here. We think that, obviously, the potential here is enormous. So we are trying to mainstream and to take as much share of that $400 billion transition as much as possible. We have a number of announcements kind of coming out between now and the end of the quarter, with some bigger announcements coming out at the end of this quarter, specifically as to how we're going to be dealing with things like social data. So I would say, as you continue to kind of monitor the market, if you are looking for a way to participate in the changes that Apple and Google are making as it relates to the cookie, et cetera, or you're looking to participate in the macro trend of privacy and data, I'd encourage all of you to really look to the public market to see what companies are out there. I think when you do that, you'll realize that Killi is really at the forefront of that. So with that, I'll pause there, and we can have a couple of questions. And yes, so let me know where you want to pick it up from here.

Great. Thank you very much, Neil. That was a great overview. And I agree, the tailwind seems to be very strong and definitely in your favor. One thing I wanted to dig into a little bit more was the integration platforms, and you talked about adding approximately one per month. What does that entail more in depth? Is it a fairly lengthy integration? Does it take 3 to 4 weeks? I mean, obviously, now that you have a dozen or so, it seems like it would be quicker and faster. Maybe talk us through in detail maybe a little bit more about the platform integration and how that looks from a timing perspective and maybe a workload perspective on the company.

Sure. So maybe starting at the front of the house. The way in which our sales team is structured is that we have a team that works exclusively on these relationships with the individual platforms. Their whole job is specifically to bring new platforms to the table while growing organic revenue in the platforms that we've already integrated. So from a timing point of view, that team spends an enormous amount of time kind of bringing this platform through the gate to get the contracts in place, then we move it into the engineering queue. It typically depends on the size of the individual company. It usually takes approximately 2 weeks per platform to do that. And that's down considerably from where we were before, where it was 3 or 4 weeks. Inevitably, there's always some nuance. Every platform is slightly different than the other. So while there are some economies of scale there, there's always a little bit of customization. But we've fine-tuned that now to the point where I would say the engineering side of the business is actually shorter than the sales cycle associated with the business.

That's great. From an overview perspective, I really think it's really interesting, and you're right, the uniqueness of each platform is going to be slightly different. But it's good to see that the integration time has roughly been cut in half. So with that kind of in mind, when you think about -- you talked about the customer acquisition costs getting down close to nil. What do you think of a long-term model might look like maybe 3 to 5 years out? I mean, from a -- maybe just to think about maybe operating margins, do you see that in the 25% to 30% range? Or how do you think you'd handicap the longer-term model?

The margins are 2x that. So the margins are 50% to 60%, so -- and growing. So it is a very high-margin business because if you just use me as an example, if I'm a Killi member and I've unveiled all of the data that's available to me in the market today, I've consented to put it underneath my account, that data has been acquired. So that's a onetime cost. The subsequent sale of that data can be sold to one client or 50 clients. Every subsequent sale is obviously additional revenue. So for us, that's why the important piece is, you have to have that scale. If you have that scale -- the first question legitimately every single data company asks you is, great idea, how much scale do you have? And this is an important piece to remember because the data market is inherently commoditized because consumers have never been involved in that negotiation. And so people have been buying enormous amounts of scale, whether it's credit card data, browser data, behavioral data. This data is floating around in the market. So if you don't have a scale, Procter & Gamble or one of these companies can't dump their existing provider if you can't match the scale they currently already have in their ecosystem. That is not a trivial thing because, again, trying to bring consumers into your platform, if you can't build that scale, you're always going to be handicapped in your ability to drive revenue. For us, we accomplished that. We went from tens of thousands to hundreds of millions, which puts us in the conversation really with any company that is looking to replace its individual data providers. So from a revenue point of view, we're trying to grow revenue as quickly as possible. And the reason for that is that flywheel that I made reference to is that, inherently, the more revenue or the more dollars that we can redistribute back to consumers, the sicker they become as a dopamine hit inherently for the individual consumer. We think that the big catalyst here is really about kind of this deprecation of the online cookie. And not to bore kind of you or everybody with the details sort of specifically around that, but the changes to privacy law that I made reference to in kind of the presentation are manifesting in the platforms. Apple's announcements to remove the ad tracking or kind of scramble the email address, these are all a byproduct of the implementation of that European law 2 years ago. Apple getting rid of the third-party cookie is the exact same thing. That's a byproduct of the implementation of the European law 2 years ago. The difference here, though, is that, that third-party cookie, every single publisher has a dependency on that third-party cookie in order to run its revenue model. Google is actually turning that third-party cookie off. The end result here is 50% of publishers in the world are going bankrupt in the next 12 months. Nobody is talking about that. It's an enormous, enormous disruptive thing. And the byproduct of that is all advertisers are either then going to have to go and spend more money with Google because there's nowhere else to go. What we've learned is that people want an alternative. These advertisers want an alternative. And so if they can buy data specifically from a consented marketplace controlled by the consumer and not have to go into -- not have to increase their dependency on Facebook, Google and others, that's something that they want. And it's something that they have today, but some of these moves that are being made in the market are to reduce that additional option for them. So it's really important that we're successful because if we're not successful, a lot of these companies are going to be completely beholden to the walled garden. And so we think that as we move increasingly closer to cookie deprecation and some of these more -- to the additional privacy lives, it just is moving more and more clients towards us.

No, that makes great sense. And I think it's clearly on the horizon as people are concerned, and it will be very interesting to follow the company as you make further announcements around the social platforms, et cetera. With that, I want to wrap it up and say thank you very much, Neil. And anyone who does want to schedule a one-on-one meeting, you can e-mail me at [email protected] or you can sign on to the web page at lythampartners.com/virtual and click on the one-on-one meeting request. With that, thank you very much, Neil.

Great. Thanks so much. All the best.