[00:00:00] Phil: Why do you think fake traffic has escalated so sharply? [00:00:03] Is AI really the main thing to blame? [00:00:05] Jordan: with ai, it's just so much easier to do. you don't need to be a hardcore coder to write a script anymore. [00:00:11] but the other thing to bear in mind, not all bots are bad. [00:00:14] it could be legitimate AI agents conducting research on products. [00:00:18] Phil: What are your thoughts on like distinguishing human digital behavior from these like hyper realistic bots that are inside our funnels? [00:00:25] Jordan: Analyzing behavioral signals like mouse movement, scroll activity. fingerprinting techniques, that's like looking at device characteristics, browser properties, network signatures. there are little giveaways, I think, marketing and marketing ops, uh, has a good chance here to have a seat at the table we're no longer living in a world where all bots are bad, [00:00:43] ​ [00:01:10] In This Episode --- [00:01:10] Phil: What's up everyone? Today we have the pleasure of sitting down with Jordan Resnick, senior Director of Marketing Operations at. Check. In this episode, we demystify go to market security in the fake traffic surge. We talk about how to detect bot traffic and how to reduce fake traffic and lead pollution. [00:01:27] We also cover how to calculate the revenue impact of fake traffic and how marketing ops should adapt to machine customers. All that, and a bunch more stuff after a quick word from two of our awesome partners. [00:01:38] ​ [00:03:41] Phil: Jordan, thank you so much for your time today. Really excited to chat. [00:03:45] Jordan: Yeah. Looking forward to it. Let's get into it. [00:03:47] 1. Demystifying Go-to-Market Security --- [00:03:47] Phil: So GTM security, I feel like it's a relatively new term. I was coming up with a, a bunch of different ideas to, to chat with you on the podcast, but you're at check. You guys are obviously really deep into this space. Um, so we're kinda like [00:04:00] framing issues around fake traffic as something that can derail a lot of marketing performance and not just like top line traffic, but also. [00:04:07] Revenue and there's a lot of security concerns there. Maybe we can start there, like what does GTM security strategy look like from the perspective of a marketing ops team and how is it kinda different from fraud prevention? [00:04:20] Jordan: Sure. Um, well, obviously, uh, fraud prevention is, is a part of it. I think the overall, uh, way to look at it is it's taking a more business centric view, um, of security, um, business context. Um, you think of security traditionally being very risk averse, um, you know, protects the company, uh, at all costs. Um. [00:04:44] Whereas GTM security, uh, is looking at things or GTM, um, yeah, go to market security is looking at things more, uh, weighing up risk and reward. Um, and also obviously, most [00:05:00] importantly, it's, it's looking at the, the go to market journey. So whether it's from acquisition to interactions and touch points, uh, down to purchases. [00:05:08] Follow up. Um, while traditional security and fraud is all about attacks, you know, taking down a website entirely, uh, ransom notices, things like that, uh, go to market security is more just what's the impact on the go to market efforts. Um, looking at invalid traffic, um, you know, how is that messing around with our analytics? [00:05:28] Um, fake form leads, uh, you know, and whether or not we're sending them to sales. Uh, and even, uh, as I mentioned earlier, like acquisition. So, you know, you're putting money into driving, um, people to your website or to your physical business, um, particularly online anyway. Uh, how many of those people that you're driving are, are real people and actually able to buy? [00:05:52] And then does that then pollute your funnel, um, as it goes along later? You know, we're looking at things like lost revenue and impact there. [00:06:00] Um, and so while it's not necessarily as, uh, stringent as, uh, traditional security, um, it still plays an important role, uh, and, and goes hand in hand with it. [00:06:10] Phil: And I feel like it's getting worse and worse. Right. With, with AI and a bunch of other stuff, like [00:06:14] 2. The Fake Traffic Surge --- [00:06:14] Phil: in the state of fake traffic report that, uh, check did kinda revealed that 18% of all web traffic was deemed fake as a big jump from the previous years. Why do you think fake traffic has escalated so sharply? [00:06:27] Like, what's going on here? Is AI really the main thing to blame? [00:06:31] Jordan: Um, yeah, I think so. Uh, I think AI powered automation is sort of the, the main culprit these days. Um, there's also, of course, uh, financial incentives, um, for the bad actors out there. [00:06:44] Um, but quite frankly, with ai, it's just so much easier to do. Um, you don't need to be a hardcore coder to write a script anymore. [00:06:52] Um, you can get ai, uh, to do it for you. Um, you know, there's also an incentive [00:07:00] even from the major players, like, you know, the more visits you have on your website, uh, there isn't necessarily an incentive to hide that from you because it, it looks good. Um, but the other thing to bear in mind, uh, that I like to think about and check is obviously, um, concerned with is, uh, not all bots are bad. [00:07:17] And so even though, um, you know, things might show up as, uh, a part of this fake traffic, um, it could be legitimate AI agents conducting research on products. It could be, uh, down the road. And even now, um, we've heard stories about how, uh, people are configuring a, a agents to do purchasing, uh, for them purchase orders. [00:07:42] Um, you know, lots of people may be shopping on Amazon through bots for all we know. Um, and so, you know, why not? Um, and uh, traditionally it's just not something we've had to deal with. Um, and so. Yeah, certainly so-called fake traffic is on the up, [00:08:00] but uh, most importantly we have to distinguish between a good fake traffic, I suppose, and bad. [00:08:06] Phil: Right. Yeah. Like machine, uh, customers. Uh, I do have a question there, uh, on that a bit later, but this, this whole topic, um, I don't, [00:08:14] 3. How the Dead Internet Theory Connects to Bot Traffic Growth --- [00:08:14] Phil: I don't know if you are familiar with the dead internet theory. Um, it's kind of like a pessimistic, conspiratorial view of, of all of this. Fake traffic. Um, it, it was posted in a form like way back in 2021, but it's a conspiracy theory, uh, that was written or it's been kicking around since like 2016. [00:08:32] And basically it goes like the majority of internet content and activity has been generated by bots and AI rather than humans. And this manipulation perfectly orchestrated by governments and corporations control public perception, blah, blah, blah. Um, but yeah, I, I don't know about the gov, corporate angles this. [00:08:50] But flash forward to almost like 10 years. There's a lot of reports indicating that the majority of internet traffic is in fact bots and in a lot of cases bad [00:09:00] bots, not the ones that are shopping and, and purchasing or, so like some of the reports I've seen, like there's. A lot of different, um, percentages out there. [00:09:08] It's like 37%, 51%. Aros Lab says that in 20 24, 70 3% of internet traffic was bad. Bots. Maybe that theory wasn't that far off after all. Um, what are your thoughts there? [00:09:21] Jordan: Um, yeah, I don't know, uh, whether there are governments or corporations behind it. I, I will say, um. I tend to be very interested in all these, um, theories. Uh, ever since, uh, I was young, I'm, I'm not one to just accept when I'm told something that that's the way it is. Wouldn't surprise me if that's the case. [00:09:42] I mean, certainly governments and corporations have been caught time and again, um, doing things that they shouldn't and saying one thing, but actually doing the other. So, um, certainly not surprising. Um, I don't have any hard proof of that. What I do think we do have hard proof of is regardless of how it's come to be, um, certainly. [00:10:00] More and more of what we're seeing on the internet is created through bots. Um, again, specifically even the bad bots. Uh, yeah, I wouldn't dispute that at all. Um, I mean, you, it's hard to say, even see it on LinkedIn, everybody complaining about, you know, uh, bot comments and, um, bought posts. I, it's also hard to, like, when I think about it, it's like, you know. [00:10:27] Ultimately there was some sort of some human behind it, um, behind these bots and, you know, what are their motives? What are their, what are they after? Um, at the end of the day, um, again, until like a more concrete evidence comes out, I don't know who's behind it, but I certainly would agree. Uh, no, I don't think it's too far off. [00:10:46] Um, in fact, you know, you go to any company's website and. It's a fine line between just sort of bad marketing copy written by a human or is chat GBT writing all this stuff. Um, you never know. [00:11:00] Um. Not that, by the way, I think that it's wrong to use these tools, uh, particularly as a first draft or something like that. [00:11:06] Um, I used to work in content marketing way back when, before I got into marketing ops. Um, whereas in the past I might have used writers to write a first draft. Now if I still had that business, sure I'd use chat GPT to hammer out a first draft for me. Um, what I have a problem with is, uh, taking that first draft and just posting it. [00:11:27] And not actually applying human thought. Human consciousness to, um, and also, uh, coming back to the conspiracy thing, um, you know, a lot of the times, uh, what Chad, GPT and others are, it's giving you, um, it could be blatantly making stuff up, blatantly lying, so to speak. Uh, and I've seen this when I've used it time and again. [00:11:48] Whether that's to help with some coding or even just writing small things. Um, so yeah, using your human powers to question things, um, [00:12:00] you know, take a critical eye to what you're reading and the numbers and metrics you're looking at, um, I think is vital and we'll never go beyond that. [00:12:08] Phil: Yeah, totally agree. Um, I think that like one of the ways to decipher if traffic. Was fake or not, at least a couple years back when I was doing this in house, was to kinda look at activity logs in the marketing automation platform. When a user performs 325 events in like 10 seconds, there used to be like clear behavioral signals that it was a bot activity. [00:12:31] 4. How to Detect Bot Traffic Through Behavioral Patterns --- [00:12:31] Phil: But bots are starting to look way more human from a digital footprint perspective. Nowadays, marketing ops teams are facing like hyper realistic bots that are mimicking. Genuine user behavior. Even like watching videos, clicking ads, like interacting with forms, using the mouse to kind of like do some of these things too, like mimicking the mouse tracking behavior, basically like they're creating fake engagement and it distorts a lot of the metrics that. [00:12:58] We then give to our GTM [00:13:00] teams around ROI and conversion rates and whereas like it makes it really hard to pinpoint if it's a bot or if it's a real human. What are your thoughts on like distinguishing human digital behavior from these like hyper realistic bots that are inside our funnels? [00:13:15] Jordan: Um, yeah, I mean, it's a real problem, uh, no doubt about it. Uh, speaking of mouse, it's a cat and mouse game. I mean, like, as detection picks up its game. The bad actors then develop something and, um, it gets worse and worse, I think. Um, obviously working for check, I mean, we make products that help to distinguish, um, between what's a bot and what's not. [00:13:39] Um, you know, depending on what sort of detection engine you're using and or, um, approaches, you can, you can look at things. Um, but even without, um, software or products, uh. I tend to look for like what's not explainable, um, in analytics. So like looking [00:14:00] for, uh, traffic patterns or, um, like for example, kind of like what you were saying, but more like, are they moving through the site more quickly than a human buyer would be? [00:14:11] Are they clicking on everything in a pattern that just doesn't make sense? Um, are they consuming more than a, he? Like maybe they're reading pages that you can only get to, um, if you have. Uh, the link already, uh, not from Google, or it's not in your, well, I mean, I suppose it would be in your site map, but maybe it's not in your [00:14:30] menu. Um, so anytime that there's anomalies going on, or there are anomalies going on, um, especially if it's done in a shorter time, like if you have access to how long that, uh, so-called person has been on your website, yet they're consuming way more pages. Getting to all those different areas, um, then it's more likely that it's bought traffic. [00:14:54] Um, now taking it a step further, uh, we wanna look at whether that bought traffic is legit or [00:15:00] not. Um, and you know, I don't necessarily know how to do this without check. I know that with check, we can see whether it's like a n AI agent [00:15:07] that's scanning the site or a good crawler, um, or a nefarious actor. [00:15:12] Um, so, you know, being that I work there, I get to use these products. Um. But, uh, regardless of how you're coming at it, um, just trying to determine A, whether it's a bot or not, and then B, okay, is this a good bot, um, or a bad one. Um, the main thing though is, is looking for, again, at those patterns, because as we all know, um, more and more like these bots, uh, tend to be able to get around caps and whatnot, which I'm sure we'll discuss later. [00:15:39] Um, so. Really trying to drill down as best you can to determine the source. Um, and then, yeah, whenever you spot like an anomaly, you then dive a bit deeper into it. Look at the time spent on the site where it's been looking, um, and then, um, make your determinations from there. [00:15:58] Phil: Yeah, some of this stuff is easier [00:16:00] said than for folks that, you know, uh, don't use a, a check or kinda deal with this stuff manually. Um, I, you know, I, I wasn't aware of. Some of these solutions, uh, and kind of prep for, for this episode discovered a lot of them. But like [00:16:13] 5. How Go To Market Teams Reduce Fake Traffic And Lead Pollution --- [00:16:13] Phil: the biggest problem for me with this whole area for mobs folks is that like fake traffic leads to fake leads and bot interactions can skew a lot of funnel metrics and KPIs and it makes your campaigns. [00:16:25] Seem way more successful than they actually are. Email marketers are kind of new, like used to this world, like open rates have never been a reliable metric, um, ever since. Apple changed a lot of stuff on, on MPP, but like. I guess the whole point of this episode is like Jordan, like what can we do to counter this crap? [00:16:43] Like in my research for the episode, I came up with a bunch of solutions and um, I know check does some of these things, but I'm curious if we can unpack some of these, get your take on them. Um, maybe we can go through them one by one. So I'll list them all and we can tackle them. One by one. So the, the first one is just like [00:17:00] simple non-AI stuff like data hygiene, validation checkpoints, um, on like forums and stuff like that. [00:17:06] Then we get a bit more complex with things that are around, like design in, in ux, like multi-layered security using like capcha or multi-factor authentication. None of these things are new, like folks are kind of, uh, aware of these things. But, um, then we get into things like AI driven, pro fraud, fraud prevention, so analyzing behavioral signals like mouse movements, scroll activity to kind of pinpoint what's a bot, what's not a bot. [00:17:31] Um, I know there's some folks doing like fingerprinting techniques. Then we've got dynamic JavaScript based tracking pixels that are collecting engagement data That's really hard for bots to mimic. There's a whole bunch of other things like real time scoring and API level traffic fi filtering, post-conversion, lead verification tools. [00:17:50] And then the last one is federated learning. So enabling collaboration across orgs and, and sharing some of this, the learning across like different companies. [00:18:00] Um, you wanna tackle these like one by one. Is there like one you specifically want to chat about? Just like, uh, leaving that up to you here. [00:18:06] Jordan: Um, no, let, let's go through them. Um, so yeah, assuming that someone's coming at this, so, you know, when I say, um, check makes products to solve these things, I'm, I'm looking at it primarily, uh, with an enterprise, uh, focus. You know, like you have to really assess like, all right. Forget about traditional security, just with regards to go to market security. [00:18:31] How much is this really affecting? My organization. And so, you know, I've worked anywhere from a tiny, like I had my own small business. I've worked at very small businesses. Uh, either they were my clients or I was employed by them. I've also worked for large enterprises before. Uh, this problem is really different depending on how big your organization is and how important it is that every single lead makes its way to sales, whether it's junk or not. [00:18:54] And so the reason why I'm giving this preamble is if you're listening and you're working at a small. [00:19:00] Zero to a hundred person company and you're only getting 10 leads a week, um, you know, obviously it's not gonna make sense to invest a billion dollars and, and a a lot of time into preventing it. Whereas if you work for a large corporation that's getting a hundred to a thousand people signing up every day, um, then we have a major problem because it's not just the fake leads that are signing up. Or screwing up your ad budget or visiting your website, potentially taking it down. But also furthermore, it's eating up data. I mean, every single user that gets created is sitting in your database. You're paying for it. Um, so the ROI starts to become more and more, um, relevant, uh, when it comes to pursuing, uh, GTM security solutions. [00:19:44] All that being said, of course there are ways to do it without purchasing software. It's much like anything else. You can always build out of the box. Now whether it's gonna be as far along or as easy to use or as nice of a solution, I couldn't say. Um, but looking at the solutions you've come [00:20:00] up with the general approaches. [00:20:02] Um, what was the first one here? So data hygiene, validation, checkpoint. So, um. Yeah, of course. Like the simplest thing anyone can do, whether you're using Marketo, HubSpot, things like this. Turn on the bot filtering. Like it's amazing how many of us don't even do that. Um, now is it the most sophisticated, um, solution? [00:20:23] No, of course it's gonna let, um, bots through. Um, but it's a start. Another thing, I don't know if it falls into this category, but you know, if you have the ability to, again, if you're selling to larger companies, I mean block free email domains, that's an easy one. Um, another thing, uh, the senior email marketing manager, uh, on our MOPS team at check, um, likes to do is just look for pattern. [00:20:47] I've been talking about patterns a lot, but, um, you know, a lot of time the spam signups, they have like, uh, a exclamation point at. Or something like that. I, I'm making up random examples. So as [00:21:00] you start to see fake users look for the patterns, is there always, um, a certain character that you wouldn't expect? [00:21:07] Um, and I feel like that may not be exactly the category you're after, but I just feel like these are some of the simple things that you can do and just like block them from your incidents altogether. Um, another thing in this category I would say is working with your security team on your, just your general website security. [00:21:24] Can help before they even get a chance to fill out your form, assuming they're front end bots. Um, so like for example, um, you know, like if you use WordPress, there are plenty of plugins that stop, um, spam comments from being made on your website. I'm sure it's the same principle applies to filling out forms. [00:21:42] Um, so things like that, those are the simplest, um, gro uh, homegrown things that you can do. Um, moving on to the next thing, uh, I was taking notes, capcha and multifactor author. So, the thing with Capcha, um, we know [00:22:00] that good bots can, well, bad bots that are good at what they do, um, can, can override caps. Um, does that mean you shouldn't use them? [00:22:10] No. I mean, everything helps. Uh. You still lock your door at night, even though you know some thieves can break in. I mean, that doesn't mean you leaving un, I mean, unless you're in Canada like us and everybody leaves their door unlocked, allegedly. Um, but yeah, so of course you want to put everything, uh, forward, put your best foot forward. [00:22:29] Um, so yeah. CAPTCHAs work, uh, to a certain extent. Um, are they, uh, you know, a, a, a complete solution? No, but they can work. But the other thing you have to bear in mind with, with all these solutions, particularly things like Capcha, um, as I'm sure you know, is that it then starts creating more friction, um, for the end users. [00:22:48] And so you always wanna balance like, all right, I'm gonna put this capture here to stop the bots, but then how many legitimate users am I losing because. Captions are frustrating or they're just blocking them out. Or me, I [00:23:00] use Firefox. Caps always give me trouble. Um, so how many, you know, good thing for most companies, I'm persistent, but you never know. [00:23:10] There might have been a form or two that I've just abandoned. Um, so yeah, that, and that's something that, you know, if you put your security hat on, maybe traditional security, IT departments might be like, no, we need this. It's, you know. Protection at all costs. Whereas GTM security is a little bit more like, Hey, are there solutions like Capcha that don't actually impact? [00:23:30] And that leads me to the next one. Um, uh, well, not necessarily the next one in your list, but just playing off that I idea of the capcha is like, what about honeypot fields? Um, so hidden fields on forms that only a bot is gonna fill out. So it makes it look like there's a field to fill out, but like a human that goes to your website is not gonna see a field not gonna fill out that field. [00:23:53] And so, you know, any form that comes with that field filled in, um, is a bot. And [00:24:00] so, um, these are little tricks, uh, that you can do. Um, again, check makes products, uh, that the whole benefit is that they work in the backend, um, in real time. And it, it eliminates that friction point. Um, but. Uh, that's, that's, that's how I look at it. [00:24:17] Um, your next one. Okay. Uh, analyzing behavioral signals like mouse movement, scroll activity. I don't personally know how to do this in real time without check. Um, maybe it's possible, maybe it isn't. Uh, definitely something you can do after the fact though. Um, and then based on that, perhaps block IP addresses from coming to your website in the first place. [00:24:40] Um, fingerprinting techniques, that's an interesting one. Um, that's like looking at device characteristics, browser properties, network signatures. Um, again, same as the last one. Uh, sure, great to do if you have the capability to do it. I am not a developer. I mean, like, I know how to code a little bit. Um, obviously working in marketing [00:25:00] ops, building websites, uh, C-S-S-P-H-P, whatever. [00:25:03] Um, but I don't really know how to, how to do that in real time. But again, um, you can work with your data science team, your security team, um. Particularly after the effect, or sorry, after the fact, um, to look into, uh, signs that, uh, you know, digital footprint, uh, fingerprints that give away whether something's a bad bot and then blocking in future. [00:25:29] Um, I don't see, I mean, that's a good example of one that's happening behind the scenes, um, is not gonna impact, um, front end traffic. Um, what else do we have here? Excluding suspicious traffic sources. Yeah, of course. Um, why not? Uh, but again, you need the ability to detect where the traffic's coming from in the first place. [00:25:52] Um, so a lot of these things, I would say, without, um, a platform like check are gonna be like, uh, you know, you put your site [00:26:00] up for a while. There's a learning period. You look at all these signals, um, behind the scenes with, uh, bigger brains than mind people that can actually identify these things. Um, and then you implement a plan of attack, uh, or well, a plan of defense. [00:26:14] Um, all right, we're gonna block anytime someone comes to the website, um, using an Apple computer, but a browser that nobody on Apple would ever use, we're just gonna block automatically. Or like for another one, like, uh. You can have things like, supposedly someone's coming on an iPhone, but they have no browsers on their iPhone. [00:26:31] Like there are, there are little giveaways, um, that these bots use, um, that you wouldn't necessarily see until you dig really deep into the, um, what's going on behind the scenes. Um, and then, yes, of course, uh, worth blocking, but also always worth bearing in mind. Um, you know, how big of a problem is it really? [00:26:54] Uh, is it really impacting revenue or is it just inflating your numbers? Can you present to [00:27:00] your superiors like, Hey, here are our visits, but actually we know 30% roughly are fake, so just, just use, do the mental math. Um, it's not really a hundred people, it's 70 people. [00:27:11] Um, and so, but really, you know, when it comes down to pipeline creation and opportunities, we're not seeing any junk having effects there. [00:27:20] And so it's not worth our time versus. Hey, uh, we work at a huge enterprise and we have thousands of people signing up with John Gleeds and it's taking up space in our instance, and our salespeople are getting mad at us. Nobody trusts m QLS [00:27:33] anymore. Um, that's a big problem. Also, by the way, when I worked at a smaller company, um, I would just validate things manually. [00:27:40] It's [00:27:41] Phil: Mm-hmm. Mm-hmm. [00:27:42] Jordan: this looks like an MQL. It has a decent email address, a real phone number. It's not, uh. I dunno, jeff@amazon.com, like you can, you can usually tell if, um, when the, by the time it gets down in the funnel far enough that it's requesting a demo, um, you should be able to [00:28:00] identify whether it's fake or not. [00:28:01] And it's just whether you have the appetite to look at it manually or not. [00:28:05] ​ [00:30:01] Phil: So imagine this example, [00:30:03] 6. Preventing Fake Leads From Reaching Sales --- [00:30:03] Phil: like, uh, your CRMs lead queue is suddenly full of form submission. It looks really good, sales team is excited, but a lot of them are gibberish or like fraudulent entries. [00:30:13] The sales reps are basically spending a ton of time or spent a ton of time this week, like chasing ghosts or real prospects are getting overlooked or kind of falling through the cracks. And, you know, one of the solutions here is. We talked about having this like instant qualification tool, like one of the sponsors of the show Revenue Hero. [00:30:32] You basically can't, like, instead of just having a form, you book something and then you wait, you get a thank you page, you wait for a call back, like Revenue Hero on the form lets you like book something, uh, directly into a rep's calendar and there's like a bunch of qualification fields. So you know, bots will have a much harder time answering those qualification questions and selecting a meeting time in that ui. [00:30:54] But I'm curious to ask you, like, what, what other things can, like rev ops or marketing ops professionals do that [00:31:00] you think aren't like super just for enterprise stuff that, um, you know, maybe we haven't touched on yet. And like, how can they build fail safes that, you know, we're, we're not sending sales teams a bunch of crap and they're not distracted by invalid leads. [00:31:17] Jordan: So, yeah, so I mean, beyond the things we discussed before, like, uh, blocking certain email domains, caps, honeypot fields, um, you could have like even simple JavaScript, uh, validation rules. So like, for example. Um, again, I'm not bringing this up 'cause I know how to implement this necessarily, but, uh, there are people that do, um, so JavaScript that, um, immediately, uh, you know, if someone spends a certain amount of time on the form or has, uh, odd looking mouse movements, um, it won't let them actually get to the booking part of things or it'll send them to a, uh, a fake page making them think that they've booked but they haven't. [00:31:58] You could even use JavaScript [00:32:00] validation rules for things like, you know, looking for your ICP. Like, hey, if the customer company size, based on your data enrichment platform, if you have one, is not a certain size or is self-selected, you know, somebody selects, they only have one to 10 employees. You know what? [00:32:14] You don't route them to the reps. You just wrote them an email that says, thanks for filling it out. Maybe we're not for you, or, why don't you try our smaller product, or whatever it is. There are things like that. Um, there are things that I think people don't necessarily have a good appetite for, but nonetheless work like double opt-in. [00:32:30] I mean, Nobo is gonna fill out a demo request form and then respond to the email saying like, yes, that really was me, I'd like to book. Um, so these are the types of things that I, in my own small business, uh, way back, I'm thinking even 15 years ago, like I made people put their email address in twice in the form and then after they booked. [00:32:50] I hadn't, uh, you know, you could set up an autoresponder that's like, hey, you know, nothing personal. But um, I don't have time for spammers. Are you real? Um, in [00:33:00] much nicer language. Um, or Hey, it was great to hear from you. I'm really looking forward to meeting. Just wanted to confirm it was actually 3:00 PM or whatever. [00:33:07] I dunno. So, um, and then if they don't respond, well no meeting happens. And so, but you, again, coming back to that idea before, you have to look at the appetite your organization has for. Missed legitimate leads. Like there are plenty of legitimate people that just won't respond to that email. Um, and you miss them. [00:33:28] And so you have to look at like, when you're implementing any of these so-called solutions, uh, do I want to go that far? Um, similar to how you would look at like, uh, what kind of friction do you want to introduce to the, um, person filling out your form? And that can go, you know, I'm not just talking about capcha, but even just having. [00:33:45] Many fields, right? Like we have lots of demand gen people that want our forms to have just like email address only. Um, which makes it very difficult to, um, uh, assess the quality of the lead. That's where data validation, or sorry, data enrichment programs [00:34:00] come in. Um, you know, uh, smart form fills and all that fun stuff. [00:34:05] Again, it really, it's a balance of, uh, how much time and money do you wanna spend on this? How much friction do you want to introduce? Um, and then. Assessing those types of different options, uh, accordingly. [00:34:17] 7. How to Calculate Revenue Impact of Fake Traffic --- [00:34:17] Phil: What advice do you have for folks to like assign a revenue number to this problem if they're trying to like. Create urgency around the fake trashion issue with like C-suite teams. Is there, like I, I know Chuck did some reporting on this. Like, I, I found one that was like a couple years back now, like 20, 22 reports that there was an estimated like 35.7 billion in ad spend that was wasted on fake fraudulent traffic. [00:34:42] I think like the ads angle to this, like if you're listening to this, you're like, we need to do something about this. I just don't know how people don't really care about it. If you're spending a lot of money in ads, do you think that like ads is a good argument to, to bring to the table? [00:34:56] Jordan: Yeah, so there's a lot to unpack there. Uh, to use that cliche, [00:35:00] um, let's look at ads first. So if 20 to 40% of the internet is fake, then biological conclusion, 20 to 40% of those clicks that you're paying for are never gonna buy because they're fake. Um, now. There's a certain level of, um, you know, you could probably reach out to your support rep at Google. [00:35:24] Don't quote me on this. Like, there's probably ways that you can, um, reduce it a little bit. Um, I don't think it's as, uh, or it's certainly not as, um, robust as, uh, you know, check has a product called check acquisition, which, um, can reduce those numbers significantly. Um. Can I promise that the human replacements, uh, instead of those bots are actually gonna buy your product? [00:35:47] No, of course not. But um, you know, if you owned a store and 30% of the people in there were robots that were never gonna buy, do you want them clogging up your cashier's line, looking at your, [00:36:00] your products? No, of course not. You want as many actual humans in there as possible. So with regards to your question specifically. [00:36:06] You can just look at the latest figures of fake traffic. Don't take checks word for it. It's out there all over the place. Forster, Gardner, whoever, um, all those companies you quoted, um, you just take that figure and you assume, alright, well of that figure, let's say it's 20%. If we had humans instead of those 20%, um, how much money would we save on our ad spend and how much money might we then get in the end? [00:36:30] So for example, if you know that for every a hundred Google ad clicks you get. 10 purchases. I'm totally making this up. Um, so for every a hundred you get 10. Well, that means really for every, let's say 70, you get 10. And so your conversion rate, um, increases dramatically once you start factoring in the fake traffic. [00:36:50] And so you can then make a case like, all right, well I can add another, let's say 25 to 30 legitimate users. If 70 turns into 10, then again, I'm not that good at [00:37:00] math in my head, but one seventh buy. So one seventh of 30 is how much, and you can show that missing revenue. Um, that's specifically with regards to acquisition. [00:37:10] Um, but even just looking down the funnel, you can apply the same approach like of every MQL, like how many of them are legitimate versus spam, and then you reduce or remove the spam numbers, replace them with humans. Your conversion goes way up the rates. And that's, I think, an easy argument to make to, um, the C-suite or your CMO, your CRO, um, to explain, uh, how it works. [00:37:34] Um, but also at the same time, um, again, you wanna look at like, if you are going to implement some sort of solution, make sure it's not canceling out legitimate good [00:37:48] Phil: right? Yeah. [00:37:49] Jordan: So. It's a really fine line. Um, you need to make sure you don't just blanket block everything because you're gonna be missing out on the other side of the equation. [00:37:58] Like we were discussing, [00:38:00] um, AI bots that are conducting research, um, for legitimate shoppers and whatnot, um, which would be a major, a major problem. [00:38:08] Phil: Yeah. [00:38:09] 8. How to Report Marketing Performance When Bot Traffic Skews Metrics --- [00:38:09] Phil: I wanna ask you about when bots make us look too good from a marketing standpoint. Like this one's a bit tricky. I'm sure a lot of folks have been here. We have this idea, this campaign is born. We're launching it, results are starting to roll in and the results look really good, and you're pumped and you share about it internally on Slack. [00:38:29] People think you're a genius for that idea. It's coming to fruit, but the next day you're kind of digging through the activity logs and it's a nightmare of bots. And you were way too early to celebrate, and now you kinda have to claw back and say like, yeah, you know, like, uh, the, the traffic we drove wasn't exactly as high, but it's still good. [00:38:47] Like, how do you tackle this? Like what, what's your take on how odds. Team should be handling performance reporting when the numbers are inflated by junk. And you kinda realize this after. Um, yeah, like the CMO still wants to like [00:39:00] have that slide. Sharon, like some of the results you had before, did you deal with that before? [00:39:04] Like what are your thoughts there? [00:39:05] Jordan: Um. I look at this like any, uh, as we say in mops and moops, so to [00:39:10] speak. [00:39:11] Phil: yeah. [00:39:12] Jordan: uh, and what I mean by that is, uh, you know, uh, yeah, you can be fooled by this, but once you know that it's a possibility, don't go sharing your numbers before you've looked into whether. But like it's, you know, it's okay to make that mistake once, maybe twice, but like one, like now that everybody's talking about this out there, or at least it seems to be a known, um, issue, let's not be so quick to share, um, good reports. [00:39:43] And I know that's kind of a cop out answer because it, you're looking at more like, okay, well assuming you have shared this report and then you find out after the fact, what do you do? Um, I'll get to that in a minute. But first and foremost, I think it's really important. Um. To be, um, thoroughly [00:40:00] questioning everything you see, um, before sending it on, um, and reporting and gloating about how wonderful such and such a thing is. [00:40:09] Also another thing, like just for me and my, uh, career, uh, in mops is really, uh, top of the funnel numbers. Uh, it's easy to celebrate them as a win, but do they really matter? Not so much to me, like, uh. We should be looking at things like revenue and pipeline creation. I think, uh, 'cause ultimately that's what the business is looking at. [00:40:32] They don't really care how many MQL you drive, or at least in my experience, you might be judged on it. But like in having conversations with the person who gives me that goal, we always ultimately come to the conclusion that, well, it doesn't matter. It's how many of those M qls convert to opportunities. [00:40:47] And so. I would be weary, uh, about sharing the fantastic, uh, visits, numbers, um, that I might have gotten on a certain campaign. All that said, if you do share [00:41:00] early, um, and you do find out that, um, picture isn't as rosy as you thought, um, I personally, I like to come clean. Um, I don't, I'm not, uh. There are some things that, uh, I consider myself good at. [00:41:17] One of them is not, um, pretending like something is not the way it is. So like, I would rather if I sent an email to the database and instead of sending it to, um, you know, like I sent it to all the unsubscribed, instead of only send to Subscribed, um, I'm gonna tell the my boss, Hey, uh, look, I screwed up. I sent this out. [00:41:40] We need to send a correction. Similarly, if I share a report that says we had, uh, you know, 30% success rate and 10 billion visits, and then I find out a week later, data science pulls me aside and it's like, Hey, we noticed these anomalies. Actually, it's more like 2% and um, only a hundred visitors. Um, you have to own up to it.[00:42:00] [00:42:00] Uh, I think that's the only way to gain trust. Um, maybe you'll suffer for it, but, well, it was your mistake, so. I feel like there's no way around it. And if you happen to find yourself in circumstance in which you work for A CMO that still demands that you present success, uh, sorry. Present a what you now know to be a failure as a success. [00:42:21] Um, personally speaking, I wouldn't wanna be working in that particular environment. Um, but that's just me. Um, sometimes you don't have the luxury, uh, of changing where you work. So, um, then it's just a matter of, uh, coming to an agreement like. Maybe you could alter your slides to show like, here's what the numbers were and now that we've, uh, investigated with data science, like, here's the adjusted numbers, but it still shows this, that, and the other. [00:42:45] Paint a rosy picture, however you like it. Um, but I, I personally would come clean about it. [00:42:51] Phil: Yeah, it's great advice. I, I love your point about trust too, and you know, it's okay to make that mistake once, maybe, maybe twice max, but in this whole. [00:43:00] World of like fake traffic and bots. I feel like, I don't know, like I have a bit more room for acceptance of mistakes because the rules change all the time. [00:43:10] Like when you send an email to people that. We're unsubscribed. Like that's, if you do that again, like it was the same situation, right? Like you effed up twice. But if you like presented a report and you didn't take out all of the fake bots, like you learned about it, you went back in the report, you're filtering out folks in the honeypot field. [00:43:32] And the next time you're more confident about it and you're sharing it, but then like you discover this new thing or like the bot changed the behavior and now it's this. And so like there's, there's this constantly changing world and you know, like, I guess the lesson there for folks is before you get trigger happy and sharing that result, like just. [00:43:50] Double check things, especially if it's something a bit more complex, uh, like this goes for any SQL queries, like double check with the data team there. But, um, [00:43:58] 9. Trust Erosion From Fake Traffic --- [00:43:58] Phil: I did have this fun question around like the erosion of trust. Like when you're continuously dealing with fake traffic inside your tools, it does create this sense of like. [00:44:07] Trust erosion and internal confidence in data drops. When you're the person doing that reporting and sharing the reports, like it, it almost feels like you, you have to take that personally, like the, the trust in your ability to confidently report it. It lowers a little bit like, and it makes teams like second guess or decisions you're defending budgets. [00:44:27] Question everything. What, what are your thoughts on like the psychological effect on marketers and analysts when you can't really trust your numbers and it impacts the org alignment and morale also, right? Like what are your thoughts there? [00:44:41] Jordan: Um, I think that's spot on. Um, I think there's a huge, huge, uh, impact. Um, and so when I'm presenting numbers, I not only would. Investigate to the ends of the earth, whether they're [00:45:00] correct or not. But as you mentioned, like, look, you, you're, we are humans, um, and the bots and the humans behind these bots are constantly coming up with new ways to fool us. [00:45:09] So I think it's important to present it as this is what we know today. Here are the numbers. Here are all the things we've put in place to filter out bots. Obviously, if you have the budget for it and the, um, the buy-in from the org use, use one of the check checks. I make no commission by the way. Um, but use the tools you have available to you. [00:45:32] Um, but even without those things, when you're presenting, you know, you, it really is a fine line to. Keep confidence up, but at the same time, be honest and say like, here, here are all the things we've done. Uh, can I guarantee you a hundred percent that this is, you know, there aren't, uh, false numbers and fake bots in there. [00:45:51] No, I can't, but I'm fairly certain and here's why. And here are the steps we've taken, and that's why I believe we can trust, you know, more or less. This [00:46:00] is the, these are the results. The other thing I always look at is, uh. I made a post about this on LinkedIn. Uh, you know, I don't think it's healthy or correct to believe in the numbers and attribution in and of themselves anyways, even without the fake bots. [00:46:21] And what I mean by that is, um, in that post I was talking about how when I was a kid, my, uh, dad would get corporate, uh, company tickets. He'd take me to the, um, the leaf game. [00:46:31] Phil: Yeah. Yeah, I [00:46:32] did see [00:46:32] Jordan: yeah. And there's always like this little ad where this moving company was like, Hey, it's the move of the game. And they brought someone from the worst seats in the house to the best and everybody was cheering. [00:46:41] And then the next commercial break they show, it was usually a kid and their parent, they show them like all happy and their new great seats right behind the bench or whatever it was Now that happened, uh, but I was like. 6, 7, 8, whatever it is. Um, and now I am, uh, of an old age, uh, when I need [00:47:00] to move, I'm always thinking about that company. [00:47:02] Um, now when I phone that company or I search for them and I come through as organic search, their attribution dashboards are gonna show me as at, you know, organic search or direct traffic, or I phone them. They're not gonna show that campaign from, uh, an embarrassing long number of years ago. Um, they're not gonna show that. [00:47:20] So, and this has nothing to do with fake bots. So, um, when I look at things like attribution and analytics, are they useful? A hundred percent. Um, should they be the, you know, the be all and end all and you make decisions blindly based on them? No, I don't think so. And so I think in that context, like the rise of the fake web, it definitely has an impact. [00:47:41] It's worse now than it used to be. But that doesn't mean we can't use those figures to like, help us make decisions. It's just, I, again, coming back to that concept of, of actually using logic and thought and, uh, human reasoning. Um, we should look at the numbers, take them with a grain of salt, um, and then apply like, you know, [00:48:00] if, if you can see time after time and campaign after campaign that certain things are working and certain things are bringing in numbers, then while you're onto something, obviously. [00:48:08] Um, so yeah, it's, it's difficult. Um, to maintain that psychological surety and trust in numbers. But I think if you can preface it with, I think these are reasonably accurate and treat them that way, then you can have, uh, decent, honest conversations and move on from there. [00:48:28] Phil: Yeah, love your advice there. It's almost like before you present something, you have like an asterisk next to the number and you say, I didn't just like pull this myself. I validated that number and the query with this person and that person. And it's like, if it ends up being wrong, you. You weren't the only person that was wrong, like multiple people that you checked with were, were also wrong there. [00:48:49] Um, I'm sure like anyone listening has dealt with this, like when you're dealing with data that lives in a bunch of different places and like, uh, I was at a startup where we were using Looker as [00:49:00] our BI tool, but when it came to like the conversion funnel, we had all of that in Amplitude. But when it came to actual like reporting data and campaign data, that was in our marketing automation platform. [00:49:12] Form. And so we were trying to centralize all that stuff in Looker, but the numbers weren't matching from one tool to the next. And so, you know, it, it, it like when you get confidence in a number, you can still put like an asterisk next to it and say like, this is the path that I took to get to that number. [00:49:28] I can't be a hundred percent certain that it's correct, but, you know, I did my best and, you know, maybe we'll get more information and we understand that it's, it's not the perfect number, but I think your advice is, is spot on there. Uh, Jordan, we're getting close on time, so I, I do wanna like save some time to chat about ai. [00:49:44] We, we kinda tease this up, uh, throughout the conversation here, but. [00:49:49] 10. How Marketing Ops Should Adapt Systems for Machine Customers --- [00:49:49] Phil: This whole topic of machine customers like check has highlighted, uh, cases where fully automated, uh, autonomous like procurement systems, placed large B2B orders without any human intervention. Um, a lot of folks talk about this as like the future and it could happen, but. [00:50:06] Do you guys have evidence that this is in place today? Some, some folks are doing this. What changes do you think marketing and sales ops need to make to accommodate these machine customers? Should CRMs and automation workflows treat them differently from human leads? What are your thoughts there? [00:50:22] Jordan: Um, yeah, I mean, this is the question for our time, so to speak, until the next best thing is invented. But, um, I, I think the biggest change is like a mental shift. Um, just. Understanding, like we all come to it from this perspective of all bots are bad. We need to block them at all costs. Um, I think, uh, marketing and marketing ops, uh, has a good chance here to have a seat at the table and start, um, bringing to people's attention across the organization, particularly IT security sales. [00:50:55] Everyone we can, we can start, um. Hey, we're in the trenches here. We're [00:51:00] the ones seeing these numbers and analy, uh, data science, of course. Um, we're seeing these numbers. We also are aware, um, keeping on top of the trends, like what you mentioned, like in that article, um, how, uh, agents are conducting research, even conducting purchases. [00:51:18] Um, we need to start communicating that, um, around and, and get people on board and get them to understand that. We're no longer living in a world where all bots are bad, some are good. Here are the examples of how and why. These are the reasons why we don't wanna have a blanket block anymore, um, and get security as a partner. [00:51:41] Like they're not your enemy. Like we have the same aims, sort of, uh, of course we don't want bad actors on the website, but. At the same time, if they don't, um, we need to start sharing material with them and, and get them to understand that, hey, you know, like here's the percentage of our [00:52:00] customers that are already using, or We project might be using ai, um, moving forward. [00:52:06] And so we need to adjust our security measures accordingly. Um, and you know, it's never good bringing up, uh, suggestions without something to back it up. So. Having ready made solutions, uh, things to talk about, like what we've been talking about earlier today, um, top of mind, um, showing examples, um, you know, communicating with other, the mops communities quite open. [00:52:30] Um, there's lots of these discussions going on in various mops, slack groups and LinkedIn and whatnot. Um, it's not hidden like there's no secret here. And so, yeah, it's really, for me, again, just coming back to it, it's more of a mind shift type of thing. Um, do I have all the answers as to how to identify good versus bad? [00:52:50] Personally, no. But that doesn't mean I'm not gonna try and work with the people that do. Um, again, just putting it out there so that everybody's on the same page and I understands [00:53:00] the problem we're facing here and why, in my opinion, anyways, it's, it's crucial not to just, um, carry on with the old traditional. Uh, ways of security and plugins and whatnot that just like outright ban something as soon as it seems like a machine. Because I really think you're then, as the evidence and articles, uh, that I've read show, um, I think you're gonna be missing out on genuine, um, prospects and, and customers. [00:53:28] Phil: Yeah. Yeah, totally agree. One of the things that makes this interesting as like a topic is that there's like. This idea of responsibility here, like does this fall under the IT team? Does it fall under the marketing team or the data team, or even some of the engineers, right? Like it, it's become this thing that it spans department now, like fake traffic, bot signups, junk leads. [00:53:55] It's a problem that. Crosses boundaries between marketing and IT and data team. [00:53:59] 11. Funnel Audits With Security Teams to Reduce Bot Traffic --- [00:53:59] Phil: How do you think marketing ops leaders should be working with their colleagues in security or IT or on the data team to combat like fake traffic and, and bots? Are we overdue for like shared KPIs or like routine funnel audits with security lens? [00:54:16] What are your thoughts there? How have you tackled this? [00:54:19] Jordan: Um. I would say two, two things. Uh, two main points for me. One, shared KPIs I'm not a big fan of, only because I believe that security teams in particular, like their end game, their goal is to prevent, uh, bad stuff at all costs. So how they don't. As far as I know, they're not typically judged on how much revenue and pipeline they're creating. [00:54:51] And so whereas marketing, almost everywhere I've ever worked sits either aside or under unfortunately, um, sales, depending on where you are. [00:55:00] And we can have a whole other discussion on that. Um, usually it sits next to alongside as part of the go-to market. Um, and so, you know, anyone part of the go, the GTM org, um, is is by definition gonna have different, um, KPIs. [00:55:15] That's just my opinion. Uh, feel free to disagree. Um, but the second point though, that you did mention, which is collaboration essentially. Um, yeah, I do think it's good to have routine, uh, like, you know, like web traffic final audits. Um, especially if you work at a large organization where you have like a data science department, um, in particular you can get them on the call marketing ops, uh, maybe even someone from sales and security. [00:55:41] It. Um, have a regular cadence, whether that's monthly, quarterly, whatever it is, um, even if it's just annually. Um, but you know, you come prepared, like show, uh, okay, here are our visits, here are our leads, M qls, SQLs opportunities, how much of this is junk? Um, [00:56:00] compare it with what they're seeing. Talk about what kind of security is being enacted. [00:56:03] Is it actually impacting the funnel or not? But just again, kind of like the previous topic we were just discussing, like, and also I agree with you, it's not, I don't think this is something that like mops should be tackling by themselves. Like, no way. Um, I think it's, it's in everyone's interest to work on it together. [00:56:24] I just think that there's like a little bit of extra work that's required to convince the traditional security IT people that like, hey. Um, you know, there's a big seat at the table for you guys here and we definitely need your help to prevent, uh, junk from coming to the website. But can you also work with us a little to perhaps, um, not just block everything? [00:56:45] Um, because, 'cause we have numbers we need to hit here and, um, we're not gonna hit them. If you're blocking legitimate, uh, you know, potentially legitimate people just to err on the side of caution, that's, that's not gonna work for us. [00:56:59] Phil: [00:57:00] Great advice, Jordan. Um, yeah, I I feel like, you know, hopefully a lot of folks in the audience are, are sharing some of these things here and, and, and feeling the importance. But, um, I think that I really like how you've like, coined this whole topic about, you know, like, look at the traffic. It, this maybe isn't like the number one problem on your list, but you know, it should be something that you look at. [00:57:22] 'cause it's not getting any better. It is getting pretty wild [00:57:25] out there. Yeah, a hundred percent. Um, awesome. Jordan, this has been super fun, really eyeopening for me, uh, personally, especially doing the research for some of this stuff. And, uh, we'll put out links to, to check and folks that are on the enterprise side can, can look at some of the tools that, uh, your team is building. [00:57:41] But it was really cool to hear like how your. Like dog feeding some of that, uh, yourself and your work. Uh, but [00:57:47] 12. Detachment as a Career Survival Skill --- [00:57:47] Phil: we got one last question for you. As you know, we, we ask this to everyone that comes on the show. Uh, you're obviously a marketing leader and a marketing operations professional, but you're also a home renovation hobbyist, a forest trail builder, a gardener, animal lover, and a bunch of other stuff. [00:58:01] Also, one question we ask every guest on the show is, how do you decide what deserves your energy at every, at any given moment, and what's your personal system for staying aligned with that and what actually makes you happy? [00:58:14] Jordan: Uh, great question. Um, I think the biggest of all. Cliches work life balance, um, is important. Um, I, I made it, maybe I don't look at it the same way as everyone else, um, in the sense of, you know, people look at work life balance as I'm at work or I'm doing my life and it's like, here, here I am at work, doing my work stuff and then there's all this other stuff like life that then, um, deserves my time and attention. [00:58:42] Yeah, that's part of it. But I also think having the right mindset, um, and approach. To your overall human goals while you're at work, uh, is important too. Um, and so the things that I like to do when I'm away from work, um, [00:59:00] while they help me maintain a balance or a grounded approach while I'm at my work and, and things, you know, like, uh. How can you determine, I mean, usually your job determines how much time you have to spend at your job. That's not really something we have in control, um, particularly as an employee. Uh, and you know what? Even less so when I had my own business, um, because you're constantly trying to win clients or making sure you don't let anybody down. [00:59:27] Um, I think it's really important to just stay detached. Um, and what I mean by stay detached is yeah, give it your all. Um, perform really well at work, but at the same time, work is work. Uh, it's gonna disappear. Nothing we build today, especially in today's environment, you build a website today, it's obsolete three days later. [00:59:45] Um, so yeah, do your best. But also, um, I like having that mindset that it's like. I can't really control whether people will like it or not, or whether it's gonna be successful or not. So you take it in stride constantly trying to improve, [01:00:00] um, and then move forward. And then, yeah. Uh, I'm sure anyone would give the same answer, but, um, when you're not at work, what types of things are you spending your time on? [01:00:08] Um, are they helping you or are they just the easy things that, um, you know, we, we can make choices that, uh, perhaps, uh, skew to. Comfort and pleasure more. Uh, but then we end up feeling a little bit more pain and misery later. Right? Because I don't, I, basically, what I'm trying to get at is I don't wanna live a life whereby it's like I'm at, you know, at work suffering and then constantly longing for that, you know, oh great, it's Friday afternoon and now I can go party. [01:00:40] And it's like, oh no, it's Monday morning, back to work. Um, I think it's. Uh, I think it's more important to keep a balance and, and do thi you know, the, the usual stuff, family, friends, um, and whatnot. But all these things pass. And so, uh, for me personally, obviously looking a little bit beyond, um, I've always been interested in different, you [01:01:00] know, historical, um, you know, mythical religious stuff, whatever it might be. [01:01:05] Um, do what works for you, keeps you grounded. Um, whether that's some form of meditation or yoga or whatever it is that people, everybody finds there. So-called happy place. Um, but I just find that it's most important not to do those things just while you're doing those things, but also, um, I think carrying that with you to your workplace. [01:01:23] Um, I remember like, I don't know in that the last Samurai movie, um, even like you see the Japanese people traditionally like so focused on whatever it is that their craft might be, um, trying to perfect it, but then also just moving on and doing the next thing. And I think, uh, many cultures have done that, not just Japanese, but I just, it always struck me when I see things like that, um, I think it's a good approach. [01:01:49] Phil: Super cool. Really appreciate your, your answer there. Uh, Jordan, thank you so much for joining us today and thanks for bearing with me with the all the internet crap we dealt with today. [01:01:57] Jordan: Not a problem. Um, [01:02:00] glad to, glad to finally meet and do this. [01:02:02] Phil: Yeah. This has been super fun to appreciate you coming on. Thanks so much for your time. [01:02:06] Jordan: Thanks, bill. Take care.