Understanding Lift Reports
Lift reports are critical for understanding the efficacy of your campaigns. I speak with my good friend Matt Drengler of Podsights about how you want the honest truth from about attribution.
- Matt Drengler of Podsights
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Bryan: Lift reports, tags and device graphs. That's what we're talking about. Stay on. Sounds Profitable with me, Bryan Barletta.
This episode is sponsored by Claritas. Check out their recent, the marketing insider podcast, and learn how to use current trends such as industry specific lift success and CPM comparisons in podcasting. To increase advertiser adoption, you can find out firstname.lastname@example.org.
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It's a bit technical, but they're an intrinsic part of understanding how effective your advertisements are. There's a bunch of different methodologies for using them and I've detailed them at great length. And the two-part article on linking in the description in trying to help explain this as best I could.
I spoke to Matt Drengler from Podsights, a great friend and colleague for too many years about his extensive knowledge in the field of lift reports and attribution. So me and Matt have had a long history together. We were a part of the founding team of barometric that was acquired by Claritas, and it's still kicking around in the attribution space, big fans of theirs as well.
And Matt helped me a lot with my two part series on understanding lift reports because Lyft reports is an extension of campaign. Attribution are really important right there. The pretty visual at the end of it, that can be used to optimize the campaign or. Honestly for a lot of you out there that hopefully will find value.
And it's the type of thing that you send to the brand, or you send to your boss to say like, Hey, thumbs up. We did good. So, you know, Matt, let's, let's go over a few, like quick definitions here to make sure everybody's up to speed. So how would you define the attribution in podcasts? Advertising attribution
Matt: very simply put is the act of identifying if podcast media exposures is driving a conversion or whatever the KPI or key performance indicator is for that particular
Cool. So this, this podcast, we have ads on here. And if, you know, we mentioned like, Hey, check out Podsights.com. If there's a pixel in here, what it's doing is it's grabbing your IP address and it's trying to identify as much as it can about that and match that for the exposure. And then there's a pixel on the Podsights website.
So when you visit there, it's trying to learn as much about your visit there as well, match it to a device graph and try and link the two to say the person who visited the website definitely was the person or even the household more likely. That listen to the act. Right,
Matt: exactly. Right. And what you're describing now is pixel based attribution.
Right? Originally, when we talk about just general podcast attribution, I would argue that that those terms include the, how did you hear about us survey, the vanity URL, the coupon code, and things like that, which, you know, to be very transparent on how we feel about that at Podsights, then I would argue everybody else in the pod, the pixel based attribution space feels, um, is that the vast majority of advertisers, that's just not good enough.
Um, I know we hear a lot of. I would say chatter around this idea of, Hey, like 75, 80, 85% of people that convert actually fill out that, how did you hear about a survey? And then the next question is like, but do you believe what they said? And that's always, my biggest question is if I'm scrolling through the thousand or so shows that exist on some of these, how did you hear about us surveys?
Is my finger going to get tired? I'm just gonna stop and click on whatever am I going to find a show that I really like. That I want to give the credit and just select that and then move on. Or did I actually hear the ad on that show? And then like another thing to call out is do we, as humans even fully understand what it is that drove us to purchase?
That's that's the biggest thing. Like I bought a new microphone recently. Don't I sound nice. And what's the reason that I bought this microphone because I gave you a shift for it. Cause you get okay. That's reason number one. Right. But like how much credit do I give the shit that you gave me? Should I give that the full credit or was it also the ads that started to hit me as I looked for the best and easiest microphone to use?
Um, and so there's all these different things that from a human psyche perspective, I don't think we always know what drove us to buy and what is causing us to do things it's not always very cut and dry. And so, um, that's why I think pixel based attribution specifically is what gets around that bias. Uh, you always made fun of me for saying this Barletta, but like it's this guy go guy.
Go. Exactly. Garbage in garbage out, no matter how good your methodology is or your math is to derive the answer. If the data going into that analysis is garbage, then the data coming out is garbage. I
Bryan: super agree what I want to set up for everybody here is that me and Matt worked like hand in hand for five years ago.
So the people, the people who are used to talking to me or listening to the podcast and hear me go on a tangent and go there. Well, you just saw for Matt, like imagine five years of working closely together. And they're two of us tangenting. Like, it was a lot of fun. We got a lot of cool things done, but sometimes we even needed a translator.
Yeah, absolutely. You know, man, I love working with you on all this stuff, because like, when we think of the split, like your sales with a lot of tech and I'm tech with some sales, right. And it's always worked really well. There you went all of that. You covered so many different things. We've covered non pixel attribution.
We covered, uh, the, the access schedule side of it, the, uh, the survey and the mental and the psychology side. Of that, which I'm probably going to sit on for a little bit. I got Tom Webster on at some point who could probably answer a little bit more there for both of us, but like, you're right. Like when we think about the surveys, like there are a lot of people out there that are very pro surveys and profanity or Alison pro.
Coupons, you know, I don't think that they're bad. I think that none, no attribution. And my point of view is a hundred percent accurate. It can never be a hundred percent accurate, right? Because even if you're talking directly to a human they're walking into your physical store, you get in their way before they come in or they're at the counter and he looked them in the eye.
Like they can lie to you. So. You know, I think that I look at these lower tech options of the vanity URL and the, uh, coupon code, and they have a lot more room to be scammed. Right. But I constantly look on coupon sites when I'm going to buy something to see something's out there. And there are coupon codes for podcasts stuff all the time and the band, the URLs and everything, because it is in that benefit of that publisher or the services out there to make those available to more people.
So there is a little bit more Roman it's way, lower tech to S. Kim knows. So it's not that like, they're not completely valuable. It's just that they have a higher margin of error,
Matt: actually the best part about the scamming thing. And I don't mean to interrupt you sometimes advertisers scammed themselves because they'll have an offer that's out there with a podcaster.
That's like, yo get 15% off. And then you go to the homepage or the advertiser and the homepage has a 20% off coupon on the homepage. And it's just sort of like when you sit there and you look at that and you go, why would anybody ever use the podcast coupon? Yeah. Why. And now, and now you've completely destroyed any possibility of like looking at any results that this podcast could have driven, let alone something getting posted to a coupon code site or like, you know, via honey, which now I don't know if you've heard about this, but a lot of it, you don't actually have to search coupon code sites, just click a button with a Chrome extension, and now it just.
Pops a coupon code,
Bryan: right. Until honey starts sponsoring. We don't give them too much credit on here. No, but I mean, it's a cool thing. No, but you're, I mean, like you're super right with that. Like I was just talking to someone the other day about the fact that like marketing and the marketing team and the advertising team are very different teams.
Right? Like. They don't always communicate in the same way. So the people that are handling those deals on the website are not necessarily the people that are cutting the deals with these podcasts and advertisers. So that 20% on the site might make sense today, but it's super under cuts that 15% and it just makes the campaign look useless.
Now, again, pixel base, when we look at it right now, there is a massive hole with cellular and business. IP addresses, almost shirtless everything's household, where. Fortunate, I guess for ad tech, who awful to say that in the world of, uh, the panel, like most things are happening on a home wifi connection.
My phone yells at me every night when I try, like I'll disconnect from my phone and I'll be like, don't worry, I'll reconnect at midnight. And I was like, Okay. Okay. Thanks. I didn't know I wanted that, but we're there. I think, yeah. Most podcasts downloads happen when you're connected on wifi connections. If you're doing a download, if you're streaming on Spotify or other services, like yeah, it's missed.
But, uh, enough of those downloads, I think I'm comfortable saying enough. Downloads and podcasting and enough streams in podcasting, ham in the household that these numbers for attribution can be directional. And I don't, I don't really want to go into it because I think that it is a massive amount of effort and it's fear-mongering that there are ways to scam impressions and downloads, but we're talking like tens to hundreds of thousands of dollars in investments for it to be a noticeable thing or an uncatchable thing.
And so at the end of the day, like, Putting a pixel on, uh, when the media is served and putting the pixel on the website and calling that a day as good enough for directional is fantastic. If you are counting and you're saying I only got 10 conversions, you're looking at it the wrong way. And that's where we get into lift reports, which is this whole idea is that that 10 conversions isn't accurate.
And we know it's not accurate going into it because it doesn't catch everything. So what that means is that with the lift report, which I'd like you to explain what it is. We're able to see, like what, what is the actual picture? What does that tend 10 mean in the landscape of how the performance of the site was already doing?
Matt: Yeah, exactly. I mean, th the overly academic way to talk about Lyft's studies is, um, it isolates the impact of the campaign that you're measuring with the lift study. And the reason that that's important, think about any large brand that spends tens of millions, hundreds of millions, billions of dollars in the advertising ether.
As it were and those individuals are, or those individual brands are working really hard to figure out like, which of these marketing channels or, or publishers or tactics are driving the best results. And they're all spending a metric crap ton. That's a scientific term that metric crap, ton of money bringing all of this data in as much as they can into a, an MTA provider multitouch attribution provider or a media mix modeling, uh, would say organization or company.
And trying to figure out what is working. And the reality of it is, is getting those types of data feeds, set up is really challenging. And using that type of data with the actual algorithm is challenging. I distinctly remember, and I go back and we'll get back to list studies. But like, I go back to my time when I was at staples and we spent a lot of time bringing in a multitouch attribution provider and we had to stop once and go to a different provider based on the results that we're seeing.
It took a year to get to a point where we knew we didn't want to work with the first one and we wanted to go work with the other one. And so that amount of time means it's really challenging to get any channels, new channels into this mix and even really interpreting it. Right. Because now you start to talk about like, Well, podcasting is at the household level.
And display is at the individual level. And how do you account for that within your actual algorithms? And so it's lifts studies that allow you to basically get those results without having to plug all of that data in, into your multi-touch attribution provider. Here's what that means. If I'm a very large company spending tons of money in this space, I've got, I don't know, direct mail live display, live billboards, live insert your favorite channel here.
Right. They want to know. Okay. But like all of the conversions that I just saw take place for podcasting, like how many of those would have happened anyway, because I have so much other marketing out there that's live. And a lift study is designed to answer that because you create a control group. Now we're going to dive into that a lot where we create a control group and we observe how this control group behaves organically.
And the idea of a control group is one it's about mutually exclusive group of individuals compared to the exposed group or the people that are actually being hit by these podcast ads. And the activity that this control group is exhibiting on the website is. The assumption is, well, that's a result of all of the other marketing channels that are out there, that's driving that activity.
So if I can see what that baseline activity looks like, then I can subtract that from the results that I see from the exposed group. And then the difference between what the control group is doing and the exposed group is doing that is the isolated impact of the podcast campaign. Again, just removing all of the other channels.
Bryan: Yeah. And, and so I want to rewind just a little bit. Yeah, I think that you're right. Like I think that first off the lift reports are the right way to go for people who are getting ready to get up and run. Right. I think that if you have a smaller team or if you heck, if you are only allowed to focus on podcasting or if your, you don't have, yeah.
You don't have the reach to the other channels, you don't have the time you want to get something up and running. You want to prove it. Let's study is the only answer podcast based lifts study. In my opinion is the only answer because it just removes reliance on anyone. But you. Right. As a brand, you control everything.
It's a pixel on the website. It's a pixel on the campaign. And what you're looking for is does this strategy work is the strategy podcasting in general. Cool. Probably too broad. You're going to get a yes, that's fine. Is it the states you want to do one by state, maybe a little too aggressive, unless your spends there, maybe it's by demographic targeting, maybe it's by all these different things, but that lift report is going to let you answer as quick as possible with his little reliance on anybody else.
Does this work right now? Multi, multi touch attribution, like Matt said, is the, the mindset of that. The same company measuring everything are measuring the podcast. One is going to measure everything and you know, you you've painted in a, in a picture like, um, is the overlap worth it? Like I got my catching these people on podcasts that I'm already catching somewhere else.
And, um, I want to give a little bit of credit, the people in the touch space, you know, uh, have justified and shown that like, it's not only about just like, is there overlap, but does that overlap help? Right? Do I need four impressions in podcasting for a conversion or is it for impressions across all media and mold?
I think multi touch is great. I mean, Heck to be super fair. Me and you like fought for it for like four years at barometric, a thousand percent trying to make a little bit. And the reason that it didn't happen was that nobody who wanted to buy the product could affect it that much change.
Matt: Correct. And it's not only that.
I agree with you that the outcome or the output. Of multi-touch attribution is insanely valuable. Yes. But the question is, is the work involved to get it set up worthy of the time and effort? Because again, after you set this up and start receiving some outputs, the next question you have to ask yourself is, is this believable, like.
And defensible, and then you have to start poking and prodding and testing that out rhythm to be like, are the results sort of expected as they should be? Almost like you're creating a test that, you know, the end result for to see if the algorithm agrees with you. And that right there is what
Bryan: takes a lot of time.
You're right. Basically the companies that will get the most value about multi-touch attribution are the companies that take three months to sign a basic contract. Right. And that's, it's very clear there. And what I can say is that if you're exploring multi touch attribution, you should be at a company that has your own internal data science team.
I don't mean like one nerd who likes to look at data like me and Matt. I mean like a true team that can go through it. And you probably don't care about any of the platforms you use as internal analytics. You get the raw data and formulate it yourself. That's the people that multi-touch is for. It has immense value, but like Matt said, when you are one person or a small team or trying something out or trying to prove, should we go from spending $50,000 to $500,000 to $5 million?
Like you. We'll spend more time and money setting up MTA. MTM might be an evolution of something you do. It might be at a later point in maturity, but podcasting is still in the advertising space, in the infancy. And the fastest way to test an idea is a left report. You did, you meant Chyna media mix modeling.
And that's one thing that me and you've talked about a little bit, but I'd love for you to explain the differences between that and MTA, if you don't mind, that's more of a report, right? That's less of like an actual. Like tracking the full campaign in real time and seeing the results. It's more of like an end result.
Like here's your scorecard. Yeah.
Matt: Multitouch attribution is typically a custom attribution methodology. Whereas media mix modeling is typically some form of aggression. I I'll start to. Like go to a place where I don't know as much because I haven't actually done the calculations for media mix modeling before.
Um, but the biggest difference that I have heard and have seen personally in my time, especially at staples, is the speed with which these reports come out. So multi-touch attribution will typically, if not, real-time might be a daily or a weekly update, media mix modeling is typically something where it would require.
A month or longer worth of number crunching and data collection in order to create the output. And more often than not what you're doing is you're seeing the output. Six seven weeks after the measurement period has ended. So one of the biggest complaints, and I believe one of the biggest reasons that MTA exists is media mix modeling is really not immediately actionable.
Like if I see for instance, right? Like my back to school season, Really didn't seem to do well for, for one channel versus another. I can't react to that with media mix modeling fast enough, because back to school's over and I just received the report for it. Whereas MTA, I have an opportunity to actually see that information in front of me within a decent amount of cadence.
And, and react to it. So that's, that's the biggest difference
Bryan: between the two, you know, that's a great idea back to school season and things like that. I'm typically of the mindset that Facebook and other mediums have driven us to this belief that we need to be able to see that sale in real time, on a one-to-one basis.
Oh, boy, does it suck dealing with people who have that anxiety coming over from Facebook into podcasting and like even 48 hours or a week is enough for them to like literally drive you up a wall. Um, but, uh, you're right. There are some seasonalities of things that are really important. And so, you know, being able to at least see something super comprehensive on a weekly basis, like a lift report or every two weeks or every month, um, being able to see the attribution on a daily basis, that you can make a gut call on.
Um, these are things that are really powerful because podcasting, you know, you can be flexible and you can change it. You can change budget from different, especially if you're, if you're targeting by like unique characteristics of a listener, you can change that. Day to day, if you want you shouldn't, you gotta get enough data.
You gotta get like a week of data before you heal. And we like
Matt: to say, you wait three to four weeks before you make any changes or optimizations to your campaign, you need to have a critical mass of data. It's, it's very easy to, to, to react to data that looks like you need to react to it immediately, but then like, yeah, but your last optimization was like yesterday.
So give it a little bit of time. Yeah. Um, so that's, that's definitely something that we,
Bryan: the lift reports they're very cool because like, There's a whole in education and understanding in ad tech in general. And I'm seeing it a lot in podcasting. And the truth is, is that those of you in like the lower end roles, like the account manager, ad ops, operations, sales, and all that, like you are some of the most knowledgeable people at your company, like the decision makers, your managers, the people above, you know, what you've passed on to them?
No, it has surface, they don't know the hands-on, they should, and they kids. Right. And I hope that they start spending more time on it. But, um, one of my favorite advantages of something like Lyft report is you can take a screenshot and you can send that to your boss because the biggest account management tip I ever learned was nobody opens your attachments.
If they have to open your attachment, they're probably pretty frustrated with you. So if you can tell them success in a screenshot in the actual body of the email, like you are their favorite person. So Lyft reports help there and, you know, It's it is. If you set up your lift report, if you set up an attribution campaign too broad, right?
One pixel for all of your podcasting endeavors, like he might not see success, but if you get granular, right, if you do it by the strategies, like we talked about, you're going to see both success and failure. And Matt, me and you, we spent a lot of time when that, that was the hardest one, because we would get these people on the phone who were like my job's on the line.
Like, I don't know how to, how to tell you this. Like this was supposed to be successful and it's not going in the direction we want. And I have to explain this to my boss and like, I'm ready to pull this money out and go to Facebook. Like, what are the things that you tell somebody who's freaking out because they don't have a positive lift report in.
The percentage that, you know, the baseline or industry standard was, or like a neutral or a negative, if you want to go through each of those that I think that could be a really empowering thing to hear for these people who have to defend those. Yeah.
Matt: I mean, if I, if I see something that is negative, There's a few ways to go with that.
So, first off, if we're talking about a very, very large advertiser there, they're in the tens of millions, hundreds of millions, billion dollar range, and they put $50,000 into podcasting. There is no chance that you're going to achieve incrementality. You're spending so much damn money elsewhere, that there is no doubt that that $50,000 is being cannibalized by your TV and your print.
And your banner and your paid social, Andrew retargeting, Andrew, yada, yada yada. And so your favorite channel here. So that, from my perspective, if I'm talking to a very large brand and they don't achieve any incrementality on a small test, my immediate reaction is, yeah, but like, if you were dipping your toes into TV, now this is a little bit ridiculous because podcasts is not TV, but like, just to be grandiose to make the point, if you are going to be dipping your toes into TV, how much would you spend.
And if they start coming back with million multimillion dollar numbers, and I'm saying there is no way that $50,000 is going to overachieve. Or achieve over and above what you're spending on TV, then
Bryan: you there, because like, let's take logic out of this situation because unfortunately that person who came in with that $50,000 campaign for that billion dollar spend company is like three steps removed from the person who like actually cut the budget.
So they don't have the authority that 50 K campaigns coming through. That is a negative lift, but like, we all understand it, right. That, that. The specific brand that me and you are dancing around right here, as an example is very clearly like a household name. Everybody knows it it's every brand that I've gone to.
So if they're one of the 250 people who are not my mom listening to this podcast, maybe they'll give me a call about this and yell at me. But like the end of the day, like there are hustled name. That's it's so saturated. So they get a negative lift on that end. What, w what do you tell them? Because they didn't want to hear you at the first part where you're just like, Hey, This, this is a drop in the ocean.
This isn't enough. You are so well known that I could run this, this exposure pixel on a podcast that doesn't even have your ad and get similar results. Yeah. So what do you tell them on that? You get that report back in his name? So, so,
Matt: um, the first thing that I remind them, Is just by adding attribution to something does not mean it's going to be successful.
So keep in mind what a third party attribution provider is doing. It is giving you based on all of its knowledge of this campaign, as much information as it can to tell you in an unbiased way,
Bryan: what happened are you telling me that I, when I pay the CPM to you, it's not for you to justify my decision and say that.
Yeah, Bryan, your idea was successful. I don't cut a check to Podsights to be like your ideas perfectly, what I'm telling you, bring logic into it. And that's great. I
Matt: throw logic out the door,
Bryan: but I decided against it, but that's true, but people need to hear that. So many times people are there like attribution and, and lift reports.
It's just to justify your point of view. Like you're
Matt: paying me, you're paying me to tell you if this shit worked. And if I tell you it worked, and then you start diving deeper into the data and you're like, man, this didn't work. Then what I, what am I supposed to say? What am I supposed to like be, oh yeah, you're right.
No, you're right. I wonder what happened there. No, no, no, no, no, no, no, no. Like I have to be honest with you on what worked and what didn't. So anyway, back back to the question, right? So, so very large advertiser. My answer to this is true for a very large advertiser, but also let's say a medium to smaller size advertiser that doesn't have as much spend out there in the marketing world.
Which is just by looking at the overall lift study results. It is a great, like wet finger in the air. Did this work or didn't this work, but the, the job of an attribution provider from my perspective, and I carry this throughout our time working together, Bryan, and throughout the time that I've been here at Podsights, and I would argue that every attribution provider should, should think this way, our job is to tell you, okay.
But yeah. What, like, what next, what am I supposed to do with this information? Because if I don't, if I'm just telling you success or not success. There's nothing. There's nothing I can do with that. So the way to look at lift results is by breaking them down into the relative performance, relative lift. So within a singular campaign, like we've been talking about before, there's going to be individual line items or tactics or shows that you're going to be, um, uh, that you're gonna include in this plan.
Right? And so if I take a look at a lift study and I break it down by those line items, by those placements, by those shows. Then I can start to see sort of the building blocks of that lift study. And it can start to identify, here are the pieces that showed incrementality and here are the pieces that were not incremental at all.
So now you've got almost like a breadcrumb trail that tells you go do more of. A go do less or completely divest from B. And now you have your next step, which is
Bryan: go do that. That's certain, and that's so killer because the amount of companies that come to you and are just like, Hey, here's our go-to, here's where we always target go do the same thing in podcasting.
And like podcasting is different. Right. We have to treat it different. Right? If you treat it the same, please don't treat it. Like, yeah, don't treat it like radio, don't treat it like programmatic audio. Like you got to treat it different. Like if you just want to get the cheapest out there and get brand recognition and you don't care about attribution, then do it chase low CPMs, get a compelling out and call it a day.
But if you're going to take podcasting seriously, what Matt said is really great. You come in with a preconceived notion. You're just like this worked in TV, this worked in display. I'm going to combine it, target that same type of thing. In podcasting. If you break your strategies out, deep enough, you can start cutting out shows that don't work there.
You can see the overlap in demographic or geo or all the, or behavioral, all these different things that can tell you that like, oh, the people in podcasting that respond to this are different than display and video and everything else. And you can change it. You can put more money into the shows that's working.
You can put a, you can find what's similar about the shows that are working and find new shows that do that you can find targeting across multiple shows that seems to be successful and expand your reach. That's the key thing here, because like Matt was saying, if you just do all the podcasting is exposure, but this big brand, it's just going to show negative lift.
But if you break out your strategies is going to be a little bit of growth, there's going to be something that just peaks third or even worst case scenario. There's going to be something that is less negative lift than the others, which is still incremental, which is still a positive direction. Like it's
Bryan: my job to say, like,
Matt: if you find this lift result, And the lift results are not that positive.
And you can't find any positive, then your options are sort of like either go try something completely new. Go spend more money because perhaps that's, the problem is you're just, outspending another channels or maybe podcasting isn't right for your audience. Like you have to say that because that's what these results may be showing you.
Now, I don't like to turn people away from the podcast industry. I want more and more brands that come into this space because one I'm a believer myself. Like I started listening to podcasting back in this week in tech days, I listened to Leo LaPorte. All the time, listen to Kevin Rose. When he created Diggnation he was one of the first video podcasts, or maybe they call them blogs.
I don't remember what they called it bloggers back then. Right. I want to see, yeah. I want to see that the success of this industry, but like our job as an attribution providers, just to give you the, like, this is, this is the data. This it is, it is like accurate and this is. We just have to act on what con what came through.
So like that these are the options that you have to throw out there is perhaps the channels aren't right for you, or you just didn't quite go about it the right way. And like, to go back to this idea of like podcasting is unique and needs to be treated differently. It's so true. I, what I hope doesn't happen is this space goes full programmatic and the ads are being created within the same shop as, as the place where the radio ads are being created or that the creative control is not sort of shared with someone who understands the podcast space, because that that's what.
From my perspective, those are the types of things that ruined other marketing channels as marketers. We're really good at ruining channels.
Bryan: I like to describe the scene and up. Where the old man's house is in the center and everything else is bulldoze like advertising is that dude in a suit, like they're not big ad tech isn't in podcasting.
Like they're not standing on the sidelines out of the goodness of their heart. It's that they can't figure out how to get rid of your house right now. So can
Matt: we talk about QR codes? Like a few, our codes were $150,000 to create a single QR code. People would be thinking really hard about the right way to do that, but because they're free, they're on billboards.
Yep. Why the shit are you putting a QR code on a billboard, right? It's things like that, that marketers will always
Bryan: ruin. Yep. Yeah. But you know, this is a great place to wrap up because what I want to say here is that mattering LER is probably one of my favorite people in this space. He can go toe to toe with me on all this stuff.
And I really got to emphasize, as Matt knows when Podsights is the right solution or not. When at podcasts, advert, advertising is the right solution or not for you, he's not going to sell you all day long. So. Well, you enjoy talking to me. If you want to get a different perspective, you're tired of hearing my voice.
You want to hear it from someone with better hair. Um, then, you know, definitely reach out to Matt and I, and I really want to take this moment to say thank you to the entire Podsights's team, who I pitched the entire idea. It sounds probable to right after James bought into it. And they were my first sponsor and they're a repeat sponsor throughout 2021 and hopefully the future.
So. You know, pod sets, releases amazing data matter, English spits, great knowledge. We got to get you on Twitter, posting your thoughts and opinions or whatever is useless on there for everybody, all 40 of us that care about it. But, um, Matt, thank you so much. I want to ask you and gonna put you on the spot.
None of this mainstream crap. What is the podcast that you're listening to the most recent?
Matt: Would it be now the mainstream? I want to hear about nice one
Bryan: for the person who said that. Yeah, but it's a good show. That's great. What else tell people where else?
Matt: Um, I, man, I'm listening to mostly mainstream stuff right now.
Like I'm listening to a lot of Joe Rogan. I love that Elon Musk interview that he did recently, like three hours of just like ear candy. I can't, I don't know what else to give you. I don't have a Dungeons and dragons podcast that I'm listening to. Right.
Bryan: Just start one. I think it's, it's, uh, ad tech, uh, like, uh, ad tech and dragons or Dungeons and ad sales.
Like we're going to make it happen. Ooh.
Matt: I love that idea. Here we go. All right. I'm in that in a 20 sided die, we've got herself a podcast
Bryan: school now. Thanks again for joining me here. And I definitely we'll have you back. All right, man. Sounds good.
And stick around for some special bonus content. At the end of the episode, I've teamed up with Evo Terra to give you a minute long strategic thought that is guaranteed to shift your perspective on the present and future of podcasting. As we all work. To make podcasting better. Thanks to Matt Dengler for coming on.
To help us expand on my articles, understanding lift reports, part one and two. If you liked what you heard and want to connect, you can find me Bryan Barletta on LinkedIn, way less formerly on Twitter as high-five RPG. And of course you can email me, Bryan, at Sounds Profitable.com. The most important part about sounds profitable is providing you with more resources and making sure that I can answer your questions.
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