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Garrett: Awesome. So thanks Garrett for coming to the podcast. If you could share more on your previous kind of experience and also your role at Kochava, that would be awesome.

Garrett MacDonald: All right, thanks for having me, Casey. Thanks for having me, Garrett. It’s nice to be in the presence of greatness. So yeah, I’m Garrett Macdonald. I work with Kochava. I’ve been here about just over four and a half years now. Prior to that I’ve really been in corporate sales mainly with fortune 500 companies. But over the last eight years I’ve been with a venture backed and bootstrapped adtech companies, but primarily focused around sales and that’s probably it.

Casey: Are the startups also in mobile?

Garrett MacDonald: Yeah. So I was with the world’s first mobile specific, demand side platform called StrikeAd,

Garrett: Before?

Garrett MacDonald: Yeah, that’s right. But we weren’t self serve. Yeah. You got us on that. We were building a self-serve but yeah. And then I, I went over to Air Push to build the DSP and the SSP. And then had always had a kind of an admiration for, for working for coach Kochava and finally made it stick in 2014. So.

Garrett: Awesome.

Casey: Nice.

Garrett MacDonald: The rest is history.

Garrett: Cool. So can you tell us more about your, you know, the entire suite of products Kochava offers in terms of attribution, the data collective, you know, exchange, media guide, things like that?

Garrett MacDonald: Yeah. So it’s been a really interesting experience for me. You know, our customers are our only investors. So by virtue of being very intentional about building a business that pays for itself, we’ve had the luxury of doing things that other companies haven’t been able to do, which is really fulfilling our platform strategy. So if you know, you think about the, the workflow of a marketer, we kind of set out to really streamline the workflow for marketers by building technology to solve common problems across both sides of the ecosystem. So on the one hand, advertisers on the other hand, publishers but also the agencies that serve them. And so building technology to really streamline that workflow has really evolved into the Kochava unified audience platform that—the platform itself really kind of handles the, the workflow from planning a campaign to, you know, picking a target audience to activating that audience against said publishers and then measuring that feedback loop. But also optimizing not only the workflow, but optimizing you know, the performance of those campaigns. And so we’ve had this, this platform strategy from media planning to you know, targeting and activation of audiences. And that’s really how each of these products has developed really all within one single code base, one data model, and one login to really make it, you know, more, more easy for not only disparate teams and, and systems but also, you know, all the different logins that a marketer has to use. You know, I guess a MarTech Series, Scott Brinker says there’s, you know, the average marketing company has about 91 enterprise SAS solutions in their stack.

Garett: That’s a lot!

Garrett MacDonald: And we’ve been really intentional about trying to replace a lot of those point solutions. And in doing so, we’ve been able to really consolidate seven or eight different families of SDKs to one single SDK. So,

Garrett: Yeah. Yeah, I think that’s the holy grail of kind of ad tech having one end to end, you know, platform where you can log in, you can media plan, you can, you know, kind of activate audiences. You can execute you know, all these different media buys and you can see reporting and ideally there’s a full, you know, feedback loop. We’re where you can tell the partners which publishers and sub IDs are working and then be able to quickly remove those as you’re running the campaign. So I think it’s been, you know, many companies haven’t really been able to execute on that. So it’s great to see that Kochava, you know really pushing the, you know, kind of pushing the envelope there.

Garrett MacDonald: Yeah, we’re, we’re so like 2012 to 2014, it was all about, you know, SDK bloat and you know, wanting to minimize the footprint as apps became bigger and bigger and its experiences on mobile devices got even more rich. Now the conversation seems to have flipped to more about just consolidating vendors and it’s really for three main reasons; One you know, on the, on the heels of the GDPR and on kind of the, you know coming of CCPA and, and you know, Virginia laws that are shortly to follow shortly thereafter soon to be every state will be adopting some type of increased scrutiny around privacy and data handling. And so privacy has really, you know, not broadcasting device identifiers to partners to multiple partners when you can consolidate that data pipeline, automate those data flows. And the second reason is really around functionality. So if you think about all of the different partners that are in the ecosystem, whether it be a measurement company, either in-app analytics or attribution or you know, even a container solution or even a push company. So you know, the companies that use a push tool but also have an attribution vendor, all of their installs that are paid installs from, you know, the self-attributing networks like Facebook, they show up in the push tool as organic. And so I think marketers are really tired of that and they’d like to have a unified solution to handle not only the acquisition but also the re-engagement and then the same thing with container solutions. If you think about you know, any company that’s not an approved MMP, we as an MMP can’t send data to those companies that you know, enables them to do things like sub-second optimizations. And so by unifying that data model, by unifying the code base and having it all within one single system of record, marketers can literally do real time optimizations which is the first of its kind.

Casey: And is this data from the data collective offer?

Garrett MacDonald: No. Collective is it can be for sure, but what I was just talking about is like, if I’m a marketer and I’m doing attribution and I’m buying on Facebook and any other number of sources, but I also have a push vendor or I also have a you know, a container solution like a DMP or some type of a, a unified data model. I can’t send, I as an MMP can’t send them data because you know, breach of Facebook’s and other self attributing networks privacy policy. So in their system it shows up as an organic install. And like, you know, a majority of the marketers that we talk to are just tired of having this disparate, disconnected experience where they know that’s a Facebook install. They know that a Snapchat or Twitter or whoever it is, Google but they can’t actually have those two systems connected. And so we’ve, we’ve unified that under one login and one system of records so that they can literally optimize with sub-second optimizations at the sub publisher level.

Garrett: That makes sense. So you guys actually work with a lot of big brands, kind of like fortune 500 companies. Do you see a lot of big brands jumping into the mobile app space, you know, in terms of spend or in terms of investment into their mobile app in the near future?

Garrett MacDonald: Yeah, I mean, I, I think I think for most of our clients, I mean we’ve, we’ve really been intentional about serving the head of the market because, you know, as a bootstrapped company, they’re the ones that are writing the checks and so, you know, we’ve gone after not only because of the enterprise tech that we’ve built is a perfect fit for the enterprise businesses, but we’ve really kind of set out to be the trusted system of record for these brands. And if you look at the majority of our customers, you know five years ago it was like 40, 45% gaming, right? Cause our roots are really, our DNA is really in gaming but you know, the gaming numbers by percentage of total customers has now, you know, more like 30%, not because those companies have left us, but because of, like you say, the brands have really entered in this space in a big way. It’s still, it’s still kind of a, I guess a guesswork to say that the brand spend is coming because I think we’re kind of onto the next thing, which is for us is really you know, getting out of just being known as an app attribution company. I mean, that’s what we really set out four years ago to broaden our horizons from just the being known as the app attribution company to a holistic measurement company for all connected devices. And so if you think about some of the signals, you know, whether it’s mobile and online ads, in-app promotions, SMS, search emails, social, wearables, iBeacon, TV, AR, VR, OTT, fire TV, I mean all of these signals are really just vectors of data that are fed into our object model. And then through the UI and through the presentation layer, marketers are able to visualize the performance. But if you think about where kind of the puck is going we really are kind of making big bets on OTT and connected devices and fire TV and other connected experiences beyond just mobile and app.

Garrett: Yeah, yeah. I mean, it seems like the OTT space is really growing rapidly. There’s a ton of new apps coming out. I think we were talking about the other day, like Pluto and Xumo and fubo and, you know, they kind of all sound the same, but do you see a lot of, kind of a lot of these brands or a lot of your customers buying on OTT devices or, you know, even other devices that we don’t even know that can be bought on? Like VR, AR, you know, refrigerators, things like that.

Garrett MacDonald: Yeah, we’re not, we’re not necessarily, seeing a lot of advertisers race out to be on the refrigerator, but yeah, I mean, connected auto is, is something that’s a big focus for us you know, home automation, not just refrigerators, but home automation in general and IOT is a big space for us. And really kind of thinking about signal as an input for understanding, you know, how people are interacting and engaging with brands and products and services. So I think for us, you know, whether it’s CTV, advanced TV or any other kind of initialization or acronym for you know, where brands are investing. I mean, if you think about, if you think about our client base, you know, we’ve got you know, most of broadcast media with the exception of one or two that use Kochava and so, you know, that’s obviously very native to what they’re doing to, to be evolving into OTT and Fire TV. And that’s why we knew we had to be first. And we knew we had to build something that was going to be better than our competitors could build as copycats. And so we kind of do a lot of work at up front and understanding and listening to our customers and building technology to solve those common problems.

Casey: Okay and you know, we, we read a lot about attribution and fraud in this space. You know, and it’s becoming, you know, more, more and more prevalent. We, you know, I guess, I’m sure everyone read around here about the Cheetah Mobile SDK fraud, I guess click injection, attribution stealing, them earning revenue on a lot of the organics that was possibly passing through. Can you, you guys publish kind of like a massive report about that. Can you guys talk about that and maybe what other kind of like novel methods you’ve seen in this space.

Garrett MacDonald: Yeah, so I can’t speak about the specifics because of obviously the, the importance around I guess clarity of message and the details, they matter. But I can share with you that we did break one of the hardest or one of the largest hard-coded attribution fraud schemes in the business. And that was being perpetrated by big publicly traded companies that you know, we sat on this information for quite a long time and debated whether we were to launch or to announce or not. And, and ultimately what it came down to is, you know, our advertisers that are being defrauded at scale. And if we didn’t say something about it you know it might’ve turned around, turned the tables on us. And so what we did is we basically took a look at about eight different apps. We took an Android device and we wiped the Android device. We downloaded the app that was suspected of fraud, and then we launched and closed the target app and then we went to the app store and downloaded a bait app. And it turns out that when we downloaded that app that there was impressions and clicks that were manufactured and the data was being re-brokered through multiple parties. And so it starts with a fraudulent app. It passes an impression, a click, and then the package name of the app that just got downloaded to the first party who then in turn upends the data and then passes it onto the next network. So basically what you, what you had was the app wasn’t even on the device, but there was apps and clicks being dynamically spawned. And you know, there’s a full record level detail. Some video, Buzzfeed made a pretty large announcement about it. We were pleased that Google had validated our findings, we were also very surprised when we kind of took another dig and had found about 56 other apps.

Casey: Wow.

Garrett MacDonald: Doing very similar things. And so this is sort of I guess testament to the fact that we are not like other companies in this space. We are the very best in this effort. And it really, the details and the timeline really matter. So if you think about, you know, back in February of 2015, we acquired a company that was a predictive algorithmic optimization technology platform. Think of it like a layer of predictive analytics that sits over top of the bidder and tells it what to buy and what not to buy based on the campaign specific targeting objectives of the advertiser. And what we wanted to do is give the advertiser the power of the pen to control the optimization so that the publisher doesn’t control the yield optimization, the revenue prioritization, ECPM fill rate, stuff like that because the advertisers really, you know, at the end of the day, who’s writing a check to Kochava. So we bought this company and it was, you know, a lot of bayesian modeling and applied non-parametric statistics that really focused on the quality of the impression or the likelihood to convert, as opposed to just sort of spraying clicks around and, and hoping for conversions that all of that tech, all the team and all of the, you know, the patents and all of the machine learning and AI and predict, really led to the launch of our enterprise standalone fraud product in May of 2015. So we were first to market with that. And again, first, you know, is not always the best, but if you build technology that can withstand copycats, you’ll see that, you know, what we’ve been able to do with the technology that we built with four years under our belt. So we launched our fraud product in May, shortly thereafter we launched a traffic verifier, which is a realtime fraud prevention capability that enables you to at the tracker level to say, ‘Hey! I want to buy iOS 12 iPad mini in San Francisco’. And if I get something that falls outside of that, I can tell the attribution engine how to treat it. So do I want to attribute it or not? Do I want to attribute it and send a postback or not? And the obvious implication there is if you don’t send a postback, you’re not going to pay the publisher.

Garrett: Yeah.

Garrett Macdonald: We actually want the advertiser to send a postback because the publisher is their partner, right? So if the publisher can know that it was invalid traffic, they can tell their sub publisher and not make the payout or just tell them and optimize more effectively. So this real time technology for fraud prevention has evolved quite a bit. We’ve now added things like frequency capping at both the impression and click for both the user agent site ID, device ID and IP address. We’ve added time to install processing. So if your app takes 35 seconds to load or one second to load, you can plug in a time that no attribution will be counted before that. We’ve got the ability to turn on a global fraud block list that we’ve been developing and curating over the last five years, which is that the site ID, device ID and IP address. And so there’s a ton of technology built into this traffic verification that will enable the advertiser to tell our system what we should be attributing and not. And, and if you think about the broader definition of fraud, you know, it’s really for our clients, it’s anything that falls outside of that, which they intended to buy. So if I wanted to buy a, you know, iOS 12 iPad mini in San Francisco and I got an iOS 8, you know, I’m going to monetize differently on those device types. So it’s really important for the advertiser to be able to have what we call IO insurance, which is literally making sure that the attribution conforms to the rules that are governed by the IO.

Garrett: Yep. That makes a lot of sense. And you know like, earlier you mentioned something about a blacklist, you know, kind of a blacklist for IP addresses, devices, you know, other things. Is there, are there kind of like centralized black lists that a lot of ad verification companies or fraud detection companies share or do you think that may happen in the future?

Garrett MacDonald: So, I know there’s, I know there’s some companies that have asked us to license their own block lists and we always, you know, say to ourselves why? I mean, we see an order of magnitude, higher volume of traffic and both impressions clicks and installs and post install events than maybe anybody in the space. And so, the likelihood that they have Intel that we don’t at the either the site ID, device ID, or IP address is very low probability. We do have some groundbreaking announcements and technology that’s going to be launching here in Q2 that I can’t talk about, but that is going to be a new way to ensure that device spoofing is kind of kept to a minimum and so there’s a, there’s a lot of particularly on Android and there’s a lot of companies that are trying to develop these consortium’s around you know, data and around block lists or black lists depending upon which vantage point you’re looking at it, but ultimately we don’t believe in just a band hammer on like heuristics of like block 10% or 5% or 15%. It’s really very custom to not only the advertiser, but also just the campaign itself with the publishers and the creative and all that sort of thing that really determines how the advertiser can extract more cash from their ad buys with Kochava.

Casey: Are you seeing in terms of channels, you know, what channels are performing the best? And for which type of marketers? So for example, like Facebook or Snapchat, maybe Programmatic or kind of affiliate networks, what are kind of like the best, best performing channels you see?

Garrett MacDonald: I mean…

Casey: And is that really, I guess it’s really specific on the ads.

Garrett MacDonald: So, yeah, so specific. I mean, I think if you were to ask somebody in our client analytics or data science team, they would have a very strong opinion about that but what, what I see as a sales person might be quite a bit different and doesn’t mean one’s right or wrong. It just means that it’s a different vantage point. But from my vantage point, what I can tell you is that in working with a lot of prospective companies and customers, companies that use other measurement tools have, I don’t know what it is, but consistently stopped spending off of the sort of big five or big six because they can’t invest with confidence on channels that they are sort of like the, the wide open ocean of potential fraud. And so companies that really have just said, I’m going to stop spend on all channels except for, you know, these five, you know, our customers, their competitors are having opportunities to gain, share a voice where they’re not even in the ball game. So by using our technology to sort of, you know, like the IO insurance and some of these other things that we’ve done to help advertisers invest with confidence they’re able to, to acquire users perhaps at a fraction of the cost because then competitors aren’t there.

Casey: On these niche sources and channels…

Garrett MacDonald: Yeah, but I think for like thinking about channels specific it would be hard for me to say, I would be totally guessing. I would say you know, the majority of advertisers that we work with are kind of, you know at the sort of top of the food chain in terms of ad spend. And so, you know, most of those advertisers, you know, they, they want to diversify their spend outside of the big six or whatever but a lot of times their measurement choice has not afforded them the opportunity to do that, so…

Garrett: I know you guys offer, also offer kind of a web attribution product. How do you guys approach cross device user tracking and can you go into, you know, more into the methods that you guys use to do attribution for mobile devices as compared to, you know, browsers?

Garrett MacDonald: Yup. So, yeah. In March of 2017 we launched our web SDK. We’ve been doing web conversion tracking since 2011 as long as we’ve been doing app based attribution. So, our fingerprinting, our user identification, and device recognition technology is second to none. But we launched this web SDK because as the majority of our clients run multichannel campaigns, they’ve got a web campaign, they’ve got a web presence, they need to be able to stitch it together. So we launched this web SDK, it’s effectively called a web SDK because that’s the nomenclature that our customers understand, but it’s really a piece of JavaScript code that lives on the page that enables an advertiser to track all of the actions and engagements with their web properties. We also developed in 2011 a technology called identity link, which is both a deterministic and probabilistic audience attribution technology that helps marketers stitch together users across screens, channels, devices, and platforms. So if you think about you know, you’re an advertiser you have a unique user ID customer ID could be tied to an email on a login. They can send us a real time feed of their user ID and then we stitch it up and sew it up with their mobile install and post install event data. To give them a picture that, you know, Garrett McDonald is a S8 user on mobile and an iPad mini in the home. And that helps them do things like, you know, primary device targeting or device targeting or targeting to the primary device as opposed to an ancillary device. But it also enables them to just have a better understanding of, you know, how their users are interacting and engaging. And the newest development with that technology is the ability to, in a deterministic way identify devices and perform accurate attribution on web. So if you think about Kochava, we’re processing billions and billions of clicks every month, every day. And these clicks, those clicks that are in in-app inventory, we see a device ID go figure, right IDFA or an ad ID. At that moment, we can drop a first party cookie in the native browser. And then as we see that user again, we can make these deterministic web attributions in the absence of you know, hard-coded device identifier. So that’s, that’s probably the most exciting thing that you’ll hear all year. I’m just kidding. [Laugh] But no, that is, that is like a world’s first for us because you think about, you know, an advertiser, a market first, maybe not a world’s first, but if you think about an advertiser looking to buy you know, some of the, some of the new creative executions are in web, most of the new creative executions are in web environments or hybrid environments. So it enables them to be able to improve their conversion rate but also for the publishers, I mean, the publishers have, a lot of them have turned off web buying just because it’s not profitable for them. Well, now, if they have the ability to close the feedback loop, I mean, again, everything is about closing the feedback loop and being able to optimize signal. And so this is this is a really huge breakthrough for all of us in advertising.

Casey: Cool yeah, I think this is one of the products we’ll be using with one of our clients to get set up with.

Garrett MacDonald: That’s exactly right.

Garrett: Yeah. Actually I did, I mean, you know, when people mentioned deterministic kind of cross device attribution, usually you have to like, I guess integrate third party data where that other third party has a user login that will allow you to, you know, kind of deterministically stitched together a certain desktop browser with a mobile device. So are you able to share the third party data partners that are used for, you know, kind of that stitching together or how you guys do it?

Garrett MacDonald: Yeah, so it, it, it’s kind of a long wind up to, to answer the question, but we have our enterprise platform- Kochava trusted brand of choice for all the, you know, largest growth advertisers. Their data is their data. It’s never sold, shared, marketed or remarketed internally or externally. It’s literally in a charter database schema. And as soon as we get done with the data handling agreement with advertisers, they say you’re not going to use my data, right? They say, okay, cool. They sign and then they say immediately thereafter, you know, so, can I buy some of my competitors data? And we’re like, what about what I just told you? Did you not understand? So we started thinking about this like in 2015 and you know, we wanted to create an open marketplace for buyers and sellers, we knew that publishers had very unique audiences. They just oftentimes don’t know a lot about their audience. And so we created the Kochava collective on the basis of creating an open marketplace for buyers and sellers to transact. And what we, what we realized is that a lot of publishers or some publishers can’t target by device ID. And so even if we could create the marketplace and an advertiser could query this interface and say, Hey, I want, you know, users that have this that look and smell and act exactly like my highest LTV users, we could send those in a programmatic, automated fashion to the publisher, but they couldn’t target by device ID. And so what we did is we launched the free app analytics.com version of our enterprise platform. So we’ve got an enterprise and a free version, the free version is a scaled down version. You don’t get, you know, real time fraud prevention. You don’t have fully configurable attribution down to the tracker level. You don’t have a realtime traffic verification. You don’t have an account management team that you know, is there with you every step of the way from onboarding to ongoing support. And it’s really like the only free MMP that works on Facebook and 4,200 as other sources. So it’s been wildly successful like we’ve, we’ve now we see data on about 30,000 apps, but we actually see a meaningful amount of data on about 10,000 apps on a day to day basis. And it’s now our SDK has been a, these apps have been downloaded over 5 billion times now and so you can think about 5 billion unique device IDs. This is a great control group and really enabled us to do this deterministic web attribution because we’ve got an entire data set that we have transparent first party license to. So when a developer signs up for free app analytics, they’re basically signing up for a transparent, you know, first party license to Kochava of their data in exchange for a kick ass attribution and analytics platform that they get to use free and unlimited.

Garrett: Yeah.

Garrett MacDonald: And so the dataset itself, because our SDK is in the app, it’s a deterministic dataset. We see all of the apps that are on their device. We see all the actions that they take inside the app with our SDK. We see all the locations they visit and then we see all the ad interactions they’re exposed to. So it’s that identity and addressability that we’re really providing to the marketplace through a really slick UI. So in the UI, you can build custom audiences, you know, with about 15 different query filters by geo, by interest in behaviors, by POI, by apps on device, app usage, you know, age, gender, demo, language carriers. We get MVNO cause our SDK is in the app as well. So we can have a really, really rich dataset. That’s also what we believe to be the world’s largest independent mobile data marketplace on the planet. And not only can they build custom audiences, but they can also buy prepackaged or syndicated audience segments and then activate them single click to a publisher of their choice. So it’s a pretty cool piece of technology that we developed. In addition to that, a brand or sorry, a marketer, any marketer could import their own audience that they have. You know, there’s a photo and sharing video app and they’ve got a bagillion device IDs. They can upload or import those device IDs into a secure S3 bucket. And then what we do is we have penned all the data, the metadata that they don’t know about the device. Cause typically in a marketer knows.

Casey: Oh that’s pretty interesting.

Garrett Macdonald: Yeah. So a marketer knows the ad interaction data and they know the app interaction data, but what they don’t know is the interest and behaviors, the age and gender, or the demo, the points of interest that they over index for. So they import their audience and then they can do, you know, generate a lookalike against that audience. They can extend that audience through a partnership that we just announced with Drawbridge, which is pretty cool. And then they can do audience insights. So if they want to learn more about the audience that they have comprised, I mean think about it. You know, you’ve got a million device IDs, you know, the ad interaction data and you know, that they did post install events. You can now import that audience into the Kochava collective, spin up a look alike or look at audience insights to inform your intel, your, your media buying going forward.

Casey: And is that free for the advertiser to do this? To get the data back?

Garrett MacDonald: Yeah. So the audience insights are free. When Facebook got rid of their audience insights, we rolled out an alternative because we know that the marketplace really kind of lived and died by the, the audience insights. So for an advertiser to use the collective, it’s free until they activate audiences.

Casey: And activate means?

Garrett: It’s probably like you basically send that audience to buy that specific audience on a DSP or in that…

Garrett MacDonald: Yeah so you create an audience, custom audience or pre-packaged audience and then you can just push it to the publisher of your choice. So if you’re running with Facebook and whatever other source, you can literally enter your creds and it’ll end up in your Facebook ads manager account in about two seconds. So it’s a pretty slick, like seamless integrations that we have with all the major social platforms, every DSP, and most major ad networks. And so that way you know, an advertiser can like build their audience and then push it to the partner of their choice, rather than having this, you know download a file.

Garrett: Export it, send it…

Garrett MacDonald: Yeah Mickey Mouse stuff. So we’ve tried to streamline that workflow.

Casey: Cool. Do you want to talk about you know, block chain for adtech has, was a big I guess conversation definitely in 2018. You know, I know that Kochava was trying, or building something within the blockchain space. Can you talk about that?

Garrett MacDonald: Yeah. So this again requires a little bit of appreciation for the history but in 2015, our CEO got really excited around you know, primarily around Bitcoin and Ethereum and, you know, everything that we do is you know, trying to apply learnings to what we build, and what we are providing to the marketplace. And so we were trying to find an angle where block chain could you know, improve some of the inefficiencies of the marketplace that we serve. So we filed patents in 2015 we filed like 60 different assertions. We just got approval on about 30 of them. So we’re very pleased in that regard, but we’ve made a lot of momentum over the last three years. We, we knew that we couldn’t announce in 2015 because the world was like just getting over the programmatic RTB and initialization hangover of all the different acronyms in ad tech. More shiny objects in 2015, 16 and 17 was not going to help our cause. But also there was two things that we knew we needed to nail before we could announce block chain. And that was really our enterprise fraud product. And then the second was our targeting product with the collective. And so once we got those out the door, we announced in Q4 of 2017 and have for the last, you know, year and a half, been very vocal, very active in the blockchain community about the technology that we’ve built. Now there’s a lot of like speculation about blockchain. You know, a lot of the blockchain projects are really just ad networks that are kind of disguised under the guise of blockchain. And so I want to kind of set the differentiation right there because what, what we’re building is not an ad network. We’re not in the business of buying media and, or selling media. We never will be. What we’re doing is fundamentally changing and transforming digital advertising with a protocol based blockchain backed distributed ledger technology framework to put ads on blockchain, and that’s a mouthful. I’ll kind of take that in, in smaller bits, but basically we’ve built our own ground up blockchain, or we have built our own blockchain from the ground up, which includes our own peer-to-peer network, our own consensus engine, and our own smart contract framework. And so what we have set out to do is to create a truly egalitarian way of buying and selling media. And there’s really five key benefits to our blockchain project. One to facilitate the buying and selling of ads through a smart contract IO. Two to enable the related targeting and activation of audiences. And again, that’s our collective product, our targeting product. Three to drive efficiency, security and transparency in the advertising industry, which is like

Garrett: The most important thing.

Garrett MacDonald: What we’ve been talking about since 2012. I mean, it’s, you know, it’s about time. And then four to drive adoption around a common ledger framework. So a system of record framework that’s in a distributed ledger technology. And then five to transform digital advertising and do a true asset class so that there’s real market dynamics right now there’s, there’s not market dynamics when agency or international multinational media buying agency doesn’t upfront for, you know, $10 million of, of ESPN inventory and allocates it to their five media buying agencies. If one of those agencies has to pause campaigns or has to shut down campaigns, they can’t reallocate that inventory to other agencies because of the lack of portability in that media, and there are other opportunities for us, but really the creating advertising as a true asset class so there’s real liquidity and scarcity and market dynamics to facilitate the flow of, of advertising.

Garrett: Interesting. All right, cool. So I guess last question for whenever you meet a layperson that’s not an ad tech. What do you tell them?

Garrett MacDonald: I don’t talk, I don’t talk to anybody that’s not on there. [Laugh]

Garrett: All your friends who are ad-tech. [Laugh]

Casey: Automatic filter.

Garrett: DSP, DMP, if not I don’t want to talk to you. [Laugh]

Garrett MacDonald: Yeah, exactly. So what do I tell them? I’m sorry, I cut you off into…

Garrett: What do you tell them you do?

Garrett MacDonald: I do, I work for a mobile advertising technology company. I mean, it’s like as basic, plain vanilla as possible. I think, you know, uncles and, and family members around, around the dinner table it’s probably the best thing. It’s almost like politics and religion. Like you don’t talk about advertising technology at the dinner table. But yeah, I try to, I try and keep it pretty basic, you know helping brands connect with their audience, helping brands understand how the users are interacting with their brand.

Garrett: Yeah, so no words like attribution or, no MMP.

Garrett MacDonald: No I feel like I’m amongst greatness, so yeah, you guys, you guys can handle all of those words and know your audience.

Garrett: Only ad tech people know this. Cool. Well, Garrett, thanks again for coming on the podcast and hopefully we see you again soon.

Garrett MacDonald: Thank you very much guys.

Casey: Thanks Garrett.