Cracking the Code: Why Data-Driven Marketing Isn't What You Think
Does "data-driven marketing" from digital agencies sometimes feel like an empty buzzword? Get the real story from Tommy Anderson, a sales exec at Bateman Collective who has an insider's perspective. In this candid conversation, Tommy pulls back the curtain on how top-tier agencies truly operate.
Curious if "data-driven marketing" is just another empty buzzword? Join Tommy Anderson from Bateman Collective as he reveals the real insights into top-tier agency operations, debunking myths and emphasizing sustainable results over superficial metrics.
"Hello and welcome back to another episode of the Collective Clicks podcast. This is your host Brandon Baitman, and today I have Garett Craen from our paid media team joining me. We're going to talk all about targeting your lists from other channels for digital marketing. How you doing today, Garrett?"
"Doing great, how are you doing?"
"Hey, doing fantastic. Thank you, it's good to be back on this track with you. We took a little break and plugged a bunch of content we had from other places for a little bit there because you had a baby and then I had a baby."
"Yeah, and there were like, I think, two other people in the company. One is going to have a baby very soon, and then one..."
"Yeah, so it's been crazy. We're just making it by with everybody on paternity or maternity leave, but we're back at it. So that's good. Babies are happy and healthy, and the podcast will go on. So I'm super excited for our topic today. We're going to talk about different targeting that you can do online."
"That sounds really good. These are the kind of questions that we get asked from our clients all the time, and I think the root of this is Real Estate Investors. The way they do marketing, for the most part, is through lists. You're going to do your cold calling to a list, you're going to do your texting to a list, you're going to do your direct mail to a list. Oftentimes, you're doing all these different channels to the same list of people, and that's how you succeed with a lot of other marketing channels. It's not always quite that way with online marketing, so that's where we have a lot of clients whose first approach to digital marketing is, 'What's the list and how do I target the list?'"
"So let's talk about some of the things you can do, because when a lot of people ask us about this, it's kind of a hard thing to respond to. There are a lot of things that you can do with online ads, but some of them work and some of them just don't. We can get to the bottom of some of those aspects today."
"Yeah, I like it. So let's start with the most obvious. Let's just say I'm an investor and I have this list, whether it's like my stacked list from a bunch of data sources, or I've got 8020 or Attom or PropStream or whatever the case is. Any type of list-building, predictive, or other list that I can use, and I really want to target a certain type of seller because they're on that list and they're likely to sell. Or maybe sometimes I specialize in foreclosure or I specialize in probate, and I want to target those specific types of motivation points. What can be done to target that kind of stuff online?"
"Yeah, so there's two main ways of targeting, and if I miss one, just add it in there. But the two that come to mind with that kind of a list is targeting by either the contact information, so the email or the phone number of the lead, or targeting by the address of the property. Would you add any more options beyond that?"
"No, that's pretty much all I know, and both those options aren't available everywhere. Like with Facebook, there's no way to target a list of addresses, but you can target a list of phone numbers or of email addresses. You need some type of... I think in Facebook, you either need a phone number or an email address. I don't know if there's anything else that could work, and then you can add information like the name and the zip code they're in and stuff like that can help the match rate. But you need at least either a phone number or an email address, which for most investors means you have to have a skip-traced list, which means you're paying 15 cents a record or whatever you're paying to get that done. Which would mean it would absolutely never ever make sense unless you already had that list skip-traced because you're doing some direct... not direct mail, but like specifically cold call or text."
"Yep, yep. So you can do that with Facebook, and Google has a customer match list as well, right?"
"Yep."
"So do you recommend it? Do you not recommend it?"
"Yeah, that kind of is the core of the debate. The way I look at it is digital functions in a very different way than what I call one-to-one marketing tactics like cold calling, cold texting, direct mail. Those are less a volume play than direct, where in general, the larger your audience on digital, the cheaper your cost per thousand views is going to be. So if you're targeting a super small audience, one, you'll be paying a pretty high premium to reach the audience. And on social, let's say a good CTR is 1% if we're generous. That means if we have a thousand views, we are going to have a tiny number of people that actually get to the page. And then if our page is efficient and converts at maybe 10%, you know, you can see how that math gets really small really quickly."
"So yes, there are these super cool ways of targeting that sound exciting and sound hyper-efficient, but when it comes down to it, they go against what makes these channels effective, which is marrying volume with data. And when we cut down that volume and overlay our own data, not data that comes from like own learning, we cut off the arms and legs of the platform."
"Yeah, I totally agree with you. I mean, different channels have different strengths, right? What I feel a lot of people are doing when they do this kind of marketing is you're taking the strength of a different channel and you're trying to apply it to a new channel. People like to view Facebook as a very targetable platform, and it is on some level, but it's more targetable because you can filter through a lot of stuff in-platform. Like, just have just the right creative that gets you just the right person, than it is that it's extremely like hyper-targeted with the ads themselves to a really specific audience."
"So it is a lot more like a mass advertising channel than a targeted channel when you're talking about how it's done. I think a channel you could compare it to is like TV advertising, for example, where you know you're just reaching a lot of people. Doesn't mean that the leads you get from TV are bad because they're not targeted. No, they're good leads, but it's only because you have the right kind of ad that the right kind of people are going to reach out based on. You don't just spray something out there that gets you everybody."
"So you're basically taking a channel that's good at mass advertising and you're giving it a really niche list to market with. And I think that the nature of what's going to happen there is you'll end up with a campaign that's ineffective or extremely low volume. And I take it to the level that like, I've been doing this in this industry for about six years. I've probably had more than 50 like deep dives in this, like clients we've done it for, so like other people doing it, and I have never ever seen it work. Just truthfully, out of all of those times, I've never ever... We've tried it, I've even talked to people that say that it works for them."
"So I ask them like, 'Well, can I take a look? I'd love to see how you have it set up.' I go in, I realize that they're actually getting all their results from cold audiences in Facebook, and then they also happen to be running these lists and they just didn't realize that the lists are getting them nothing and the cold audiences are what's generating all of their results from Facebook. So I've found probably four or five people that think that they're getting success with this, but they're not. They just don't even understand what they're doing and they're actually not having success with these kinds of campaigns."
"So it's, you know, just to give you an example: Like you start with 10,000 records, you're probably going to have what, like 50% of a match. So you're going to have a Facebook audience of 5,000, and not all 5,000 of those people are going to use Facebook all the time. So within your monthly that you're trying to target, it maybe only 3,000 come on to Facebook. And then you have a 1% click-through rate when they see your ad, so there you've got 10 or... I'm sorry, 30 people that could click. And then you have 1% conversion, which means you don't get a lead. Like that's just how... You think, 'I got 10,000 people, it should be good,' and for direct mail, for texting, for cold calling, yeah, you're awesome. But for online, it just... it just doesn't work."
"There's also something called lookalike audiences that are another category of what you can do here. How does that work in this industry?"
"Yeah, so on Facebook and on Google, you can't use those audience types because it's housing and it's restricted. It can be used on like either OTT or programmatic, those kinds of channels. And those, I've seen... I think that's a better play if you have a good list, is doing a lookalike list as opposed to just a one-to-one like just find these emails, but find people like these contacts. That works pretty well. You definitely have to have enough budget to have enough data to train the platform well, to sort through all of the people that it thinks look similar. Because obviously, there's so many different attributes that can link different people that aren't just that they're in distress or foreclosure or have a property that's inherited. They might like the same TV show or the same politician. There are all kinds of things that I could have in common that aren't the traits that you want. So you have to have enough data in there from an audience size and a budget side to really help the platform hone in on what traits to look for when building that audience."
"So the hardest thing that I found is it has to have a pretty good guide to help it find that target that you're looking for as it builds that audience. In case anybody is confused here because maybe they think they were doing this or something, it hasn't always been this way. Back in the day in Facebook, you could do lookalike audiences, and then a few years ago they took that option away if you're in the housing industry specifically. And then they replaced it with a special ads audience, which was the same thing that just didn't use any predictive features that were potentially discriminatory - gender or age or whatever the case is. And then I think it was this year... Well, not this year because it's the new year just started, but I think it was '23 when they got rid of even the special ads audience, which was sort of the handicapped lookalike audience option. And now you just can't even do it in Facebook."
"Facebook... Google still does have customer match though, if I understand. You can upload a customer list and it informs the bid strategy. It's a piece of the bid strategy, and that I think we've had good experience with because you can take... you can have an account that's new and then you can add this data that isn't from the history of that account specifically to help the algorithm kind of catch on a little bit faster with the data that it'll be gathering in that account. So we've done things like uploading a list of deals that all of our clients have done across the country into the customer match audience for a specific account to basically kickstart that bid strategy so it learns a little faster."
"Yep, and in Google, until recently they had an audience type that they called a similar audience, which was basically their attempt at a lookalike. But that keyword 'attempt' - it was not great. It's like, it literally performed... I've seen so many studies showing that those audiences performed literally equally well as a completely random audience. Like, it had absolutely no value, just a smaller average audience."
"Correct, yeah."
"Those are gone, and they are now only available in a demand gen campaign in Google Ads, but again, they aren't great. So if you're going to do it, it's probably best done in other platforms than Facebook, given the rules against it in Facebook."
"Yeah, and even Google... People want to layer like when they're doing Google search PPC with us, they want to like layer in their data in there. And I think the keyword here is just imagine you like layer a list of 100,000 people and then they also need to be searching... Like, okay, maybe it's a brilliant strategy, but you might get one click a month. You'll end up with one lead every five months. Like, it's just... And you probably overpay for that lead because you have to bid so aggressively that you like must buy whatever click comes across like that."
"So I think the... I think like what how I'm understanding is... is we probably just don't want to look at options to target lists online. However, there are some viable options to use those lists to create stronger online audiences or help fuel an algorithm, whatever the case is. But that's different from like directly targeting the list, and they operate really differently. And the core difference there is in one case, you use the list to help inform your strategy. In the other case, you use the list to be your whole target. So you end up with a much larger audience if you're just using it algorithmically."
"But even then, still, I'd say your list of like people who are in foreclosure in your markets not super useful for that. It's much more useful to have a list of like hot leads that you've had historically or deals you've done, or even hot leads for deals that have happened in the industry as a whole. That's where we can use a lot of aggregate data there because if you've got a list of 10,000 people going into foreclosure this month and I've got a list of 10,000 real estate deals across the country, and we're just talking about what's going to... what's going to fuel an algorithm better so that it can better understand who a motivated seller is, it's going to be the list of people who actually did the behavior, not the list of people that might be more likely to have a behavior."
"Like, you can't use as fuel for your algorithm something that is a feature. You need to have the end behavior measured and then use that as a predictive feature. I hope that makes a little bit of sense. It's just so much more powerful."
"Yeah, I... because like someone that's in like foreclosure might be a deal given just the odds, but a person that was a deal... like, we know that they are definitely the kind of person we want. And trying to time a lead's journey is like trying to time stocks. You might like have an ad hit them right as they're still in foreclosure, but odds are you'll miss them and they'll already have made a change, you know, a different way. And then you're just working off of a really poor list."
"Yeah, that's cool. Let's talk about geofencing. So at the beginning... I can tell you're smiling already. It's fun. At the beginning of this conversation, we talked about there's two different ways you can target your list. We're going to target it based on customer information like their names and addresses and emails and stuff like that, or you could do just address-based stuff. And obviously the advantage of this is going to be that you don't need to have the data skip-traced. However, you're cutting out most online ad inventory as you're doing this. You're cutting out Facebook and Google because they won't let you target a list of addresses and because they're a little bit more careful with how they do location targeting."
"But for anybody that's not aware, I guess I'll just explain briefly what programmatic advertising is. Programmatic advertising is like this weird like decentralized side of advertising. Like, in most cases, what happens is you have like Google has ad inventory and Google sells the ad inventory to advertisers on their platform, right? It's usually pretty simple like that. Then you have this weird like programmatic world where it's like the dark side of online advertising where you just have all kinds of different publishers that don't sell their own inventory and just sell it to exchanges. And then you have all kinds of different marketers that are buying inventory from these exchanges and it's just a wild world."
"Like, it's estimated... nobody knows for sure, but it's estimated that more than 50% of impressions through programmatic ad inventory are fraudulent to begin with. It's not even real inventory. This is the world where you get into like dirt cheap CPMs, whereas on Facebook you're dealing with 10, 15, 20, $40 cost per 1,000 impressions, which is what the CPM stands for. In programmatic, you might be dealing with $2 or $4 per 10,000 impressions. So we're talking about like dirt cheap ad inventory with sometimes a lot of sketchy stuff going on. Stuff like, you know, like fraudulent inventory, or it's a display ad and the company stacks like 80 ads on top of each other so the consumer only sees one but they get paid for 80. Like, it's just a weird online world."
"So that's programmatic. The thing that's neat about programmatic though is there's not many rules. Like, you could do a lot of stuff and... and honestly, if the average American knew a lot about programmatic advertising, it's... it's... it's wild to me that like Facebook's the one getting sued and Google's the one getting sued when in programmatic, stuff way sketchier is happening like every day. But people just don't know it even exists because it's... it, you know, a lot of people would say it's like roughly like 20% of the ad inventory online, whereas most of it's going to belong to like major publishers."
"While on Google you might be able to target like a one-mile radius or in Facebook maybe 15-mile radiuses in this industry, programmatic you could target kind of anything you want. There's even programmatic demand-side platforms where you can target literally the outside... like you target within the perimeter of somebody's property. You can even target like floors of buildings within... there's wild stuff. Like I can target, I want to target people in this exact precise location in this building on the fourth floor with ads. You could do that kind of stuff, which it sounds really cool."
"But it introduces something called addressable geofencing, which is basically the ability to say I've got these 100,000 people that are in pre-foreclosure, you know, whatever it is... my list, and I want to target those people and I'm going to find those people based on their GPS location being within the bounds of a property. So anybody who like lives in that house, for example. And it's... yes, it sounds really cool. I'll give it that. What are your thoughts?"
"It's definitely an easy channel to sell and overestimate how well it actually performs in practice. And as we were talking, I thought of a way to explain this a bit. There's two main forms of targeting: there's firmographic and there's psychographic. And an address or a job title or an income is all going to be firmographic, and that's what is preached pretty heavily by programmatic. Is we can get you their exact address, you know, reach just these incomes and like just these zip codes that aren't possible on Facebook or on Google. And it sounds great, but what's been found for years and years in marketing is that the better way of targeting is by far behavioral, where it's based on like... for instance, if I owned, let's say, like a business that sold shoes, I could target women and do pretty well, you know, women this income. Or I could have an audience of high spenders that have an interest in these things that historically during this season... and that's going to be so much more effective than just going for like certain like genders or income ranges."
"And that's the like misunderstanding of programmatic. Is that it's just a very static kind of targeting that's just much less efficient in an increasingly machine learning-driven world. And that's where these platforms fail. Is they don't have super advanced options for targeting with machine learning. There are some that are better, but they're still so far behind Facebook and Google that in this industry, I think that's where it falls short. Sorry, that was a huge ramble, but I was thinking about it as we were talking and I thought it was helpful."
"No, it is... it is super interesting. One of my favorite models for targeting that I've ever seen shows that like... picture it like a pyramid. At the base of the pyramid, you have demographic targeting, and that's what a lot of people consider and important. And as you move up the pyramid, you're moving to data that's less available but more predictive of behavior. So you go from demographics to like psychographics, and then you go from psychographics to behavior. And behavior is more predictive of behavior than psychographics are of behavior or than demographics are of behavior."
"Because, you know, what tells... it's just like the concept of what tells you I'm likely to go to Hawaii next month? That I've been searching on Google for plane tickets to go to Hawaii. And that's like my behavior predicting my behavior. Or like, what tells you that somebody's likely to gamble? Probably that they gambled before is like the number one thing. Could it also be like relatively likely that they could end up going to a casino if they, you know, they fall in some income range or whatever? Yeah, that stuff helps, but like the fact that they were at the casino yesterday... like that's more meaningful to me than that they have this income or whatever the case is."
"So I totally agree with you, and I think it's... I think it's an interesting way to think through things. Now I think at the core of it, like the same reason that we're not seeing... so this just happens clockwork. Like I just... it feels every month we have another client reach out to us and they say I want to do this kind of marketing. And then sometimes they leave us to go do that kind of marketing with some other company. And I've truthfully... I've never seen it work. I think the same reason it doesn't work is because the same reason that Facebook doesn't work. It's just more or... Facebook doesn't work for niche lists, but just even more pronounced because you're with programmatic. You're doing even more... what's it called... like an even more low-quality ad inventory. Like it's the worst inventory pretty much that exists online for the most part."
"And then you're going with a niche list. So you're playing the game where usually the game with this is I'm going to pay like a $2 CPM. So I'm going to pay for extremely cheap ad inventory and I'm going to reach a ton of people. And just because I reach so many people and it's so cheap, that's how I'm going to get my results. But then you're taking that model and you're applying it to a niche list. And then also the company that you're working with realizes that's what you're doing, so then they actually charge you a 12 or $14 CPM because otherwise they'd have to quote you $30 for your ad campaign."
"So then you think you're actually doing like marketing with a larger budget than you actually are because, you know, programmatic has all these margins built in it for agencies. And it's just... at the end of the day, it's ugly. But the my favorite part of the scam is when you add in view-through attribution. And to explain to you how this works... like pretty much this is how, in my opinion, marketing channels generally work. People look for direct response ways to say like, 'You generated these leads and that produced, you know, this outcome in your business.' And when that doesn't work, they basically chalk it up to, 'Oh, it's probably brand.' That's probably what happened."
"And I'm not saying... I'm not like a believer in brand. 100% believe in brand. Like, brand drives more decisions that people make than a direct response does. I'm just saying the right way to build your brand isn't $2 CPM crappy programmatic ads. That's not... that doesn't build brand awareness. There are ways to build a brand and there are ways to not build a brand. The ad at the end of an app that somebody really wants to skip but has to watch unfortunately does not build brand."
"So I guess... I guess what I'm saying with that is... so they end up doing this view-through attribution. And the way that works is, okay, you're going to be targeting for direct mail, cold call, texting, all that stuff. You're going to be targeting these 100,000 records. Okay, let's just run some online ads to those 100,000 records too. At the end of that, tell me which... which of those people from which of those homes ended up, you know, ended up selling their house to you. And we'll tell you which of those actually saw the ads."
"And what you'll find is, wow, that was relatively inexpensive and it impacted a ton of those people that we ended up doing deals with. But it's just because that's what programmatic advertising loves to do, is just basically shove itself in front of somebody who's going to convert anyways and then take credit for it."
"So there's a way to do this, and I've never seen it done in this industry. I've never seen a company actually be able to like show results, but it's called the conversion lift study. You have to basically take half of your list and not show them ads through programmatic, and you have to take your other half of your list and show them ads. And then you have to see how do those two halves of the list perform in terms of their likelihood to become a deal through a different marketing channel for you."
"And if you do that, what you likely find is that your programmatic advertising expense is just not actually producing much for you. And it's just like... the whole advantage is that it sounds really sexy, doesn't cost a ton of money so it's not like a huge line item to cut out, and then the value is mostly hidden amongst results that were already going to come through other marketing channels."
"Sorry, that was a monologue, but there's a lot to unpack there."
"Yeah, and I think it gets to be a dangerous concept when it's chosen over channels. I think it's fine if it's used as a complement for, you know, retargeting air coverage. You know, I think that's fine. But when you take money away from like true drivers like paid search, for instance, that is going to feed your pipeline and drive revenue, and push it into programmatic that is low volume, low quality, and just not going to be a one-for-one replacement, that's when it gets dangerous."
"Yeah, yeah, 100%. There's a lot of things like this kind of... 'cause like we're... I mean, we're not like... in general, people doing marketing are not idiots. Like, we... we all know that usually people, when they become a deal for a real estate investment business, oftentimes they're going to have interactions with multiple marketing channels making that happen. So to say that one marketing channel is solely responsible for it is a little bit ignorant. It's not how it actually works. Like, the buying journey is a little different than that."
"But then there's a lot of these things like retargeting, branded search, view-through programmatic conversions, you know, all these things that are like these little sections of marketing that are usually given way more credit than they deserve towards the end outcome. And it's just because they're like relatively cheap things that happen to shove an ad somewhere in someone's path to conversion that they were already on anyways. And it's known... it's... it's just known super well amongst marketers, but it's sometimes a little bit harder for business owners to understand."
"Absolutely, yeah."
"All right, let's talk about one last twist on this. This is a question that we get from our clients sometimes too. Let's just say we're talking about this opposite. So maybe our list that we have from whatever company we get our lists from isn't going to do a ton for our online marketing. Well, can our online marketing do something for those other channels? Is there a way that we can use the, you know, the data that we're generating from online marketing to help find better targets for our direct mail, our texting, our cold calling, etc.?"
"Yeah, this is a pretty new concept for me. At least I didn't start hearing about this as... as a tack, so probably, I don't know, two years ago or so. But basically what... like how this works is you can throw a script on your website landing page, certain landing pages, and what it'll do is it will match the IP address of that traffic to an... to an individual. And then you'll get from this vendor different ranges of info. I've seen anything from just name, email, and phone number all the way to more of a like real estate-focused offering where they give you address, you know, bedroom count, bathroom count, data was constructed, like what the area is, near or zone for... like all kinds of things."
"And the idea of it being... it's basically retargeting, but instead of just getting a pixel hit and a user added to your audience, you're... you're getting actual information to contact this person that came on your site but just didn't convert. And... I think it's still to be determined how effective this is as a channel. What I've seen is that the intent of this audience is low for a reason. They didn't convert for a reason. Just because they came on your site doesn't mean that they are your ideal buyer. And you're paying a... a premium for that contact that's quite a bit higher than you would be paying in just retargeting them on display or Facebook or YouTube. And so in theory it sounds good, but the intent is just as high as it would be doing retargeting, but you're paying 20, 30 times more for the same contact."
"Yeah, but it is a more impactful thing if you can call the person. Like, that's a contact. That's... you know, there's a reason direct mail works at 40 cents a card. At 40 cents an impression on Facebook, you'd be bankrupt by the time you ever got a deal. Yeah, so... yeah, it's interesting. And I think some of it could depend on, you know, what kind of traffic you're targeting. If you're targeting top of funnel Facebook traffic, you're probably getting a pretty low-quality list there. But if we're talking like paid search, for example, you know, someone searched this keyword and then they came to this website and then they just didn't fill out my form. If you have a chance that you can match that to a person's phone number that you can call, chances are they have a house to sell and they're looking for something because it's an intent-driven campaign."
"So I see potential for... for these kinds of campaigns. I think the... the moral of the story... we tried it some for Baitman Collective for like our own marketing just to play around with this and didn't really see any success from it. We just haven't really tried this for real estate investors yet. That said, if you're a client of ours and you're listening to this and you want to try something like this out, I... I could see this being awesome or really not that good. I think a lot of it's going to depend on the actual quality of that data. Like, we can't assume that the quality of the data is going to be huge. Like, you're always going to get the right person, especially with like how IP addresses work on mobile devices, which is just a little bit trick... like, I know a lot of people that we talked to that try to do this reverse IP lookup have a hard time matching mobile devices to... to a person."
"So I guess... I guess what I'm saying is, for me, I haven't experimented with this enough to really know how it could work, and I haven't found anybody else... I found other people doing it. I haven't found anybody that can show me a measurable result that convinces me that this does work, just that it... just like that they think it's a good idea and they think it will work. So... but haven't actually gotten there... their full circles. So I guess the answer is like, that's what we know about how that can be done, but there still is a lot to be discovered from that. But I think there's certainly a case for how you could do... you could do really well building like colder lists that could at least be better quality than... than your other lists from your online traffic. I think there's a case for how it could be true, but it would take some testing."
"Yeah, I think the key to making it work is to build the audience around certain UTMs or certain pages that they've visited that maybe are deeper in... in the funnel than just your homepage. So like, you could build the audience of like people that... that came, like you mentioned, from my paid search or... whereas I probably wouldn't build that audience of like people from like Facebook or from programmatic, just because those are just like naturally less defined users. But if you can find like an already qualified list and then use this tool to get more one-to-one contact with them, I... I think that's where it... where the math starts to shift in its favor."
"Yeah, that's a good point. I mean, I'd be shocked if it doesn't work. I guess the question would be to what extent can it work. For example, if you were just to target like the very best keywords on only desktop devices, which would be more likely to have more accurate data, then would it work? Yeah, probably. But you'd have such a low volume and you might get one deal for the next four years doing this. Or you could just target it for people that have been to your website more than three times. So it shows that they're like, you know, they're engaged on some level."
"So there's... I bet you... like at some point, you get deep enough into your targeting and slicing and dicing the data just right that you can make it so it's worth paying whatever it costs for the reverse IP lookup. It's just the... so the question isn't as much could it work or not. It's just like how, you know, how much volume could you make it work with and would the juice really be worth the squeeze? Because if you could make it work for Facebook cold traffic, then you're building a massive list and there's a lot that could be done from that versus if you're like just looking for hot Google ads traffic that clicked twice and hasn't converted from desktop devices. Then maybe you've got like the core... the target there and you'll get your one deal over the next decade at some point, but it'd be worth the money. So... yeah, that... that'll be fascinating."
"So yeah, of course, if anybody's interested in that, reach out to us. Like, we're interested in experimenting with it, and I'm honestly on the fence. I don't know how well it will work. I... I could see it working well, I could see it working poorly, but that's all we have for you guys today. I hope this... hope this gives you a little bit more context into what you can do and gets you thinking about some different ideas of how you could improve your online marketing, and I'll see you next week."
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