Episode 675: How Meta Ads Manager Is Lying to You & What You Can Do About It

February 28, 2025

Ralph and Lauren are getting into the nuances of Meta’s audience segmentation and why relying solely on in-app metrics could be costing you big. They break down how Meta categorizes audiences into “new,” “engaged,” and “existing” and why that distinction is crucial for optimizing ad spend. If you’ve ever wondered whether your ad dollars are actually bringing in new customers or just retargeting the same warmed-up leads, this is the episode for you. Plus, Lauren shares an eye-opening moment from a recent mastermind, telling us just how many high-revenue brands are still dropping the ball on AI-driven customer engagement. Get ready for some critical insights, a little beachside humor, and the one Meta Ads setting you must double-check today.

Chapters:

00:00:00 – Enter the Perpetual Traffic Arena
00:01:58 – Digital Marketer & The Founder’s Board Blueprint
00:05:24 – Masterminds: The Hidden Growth Accelerator
00:06:06 – AI’s Customer Service Takeover
00:15:27 – Data: The Make-or-Break Factor
00:18:02 – Meta’s Audience Segmentation Secrets
00:26:44 – The Ad Set Performance Lab
00:27:51 – Audience Segmentation vs. Attribution Windows
00:29:38 – Ads Manager: Audience Setup Masterclass
00:31:33 – Data Integrity & Attribution Warfare
00:36:50 – Meta’s Attribution Minefield
00:39:42 – Tier 11 Data Suite: Your Competitive Edge
00:49:53 – The Final Word: What’s Next?

LINKS AND RESOURCES:

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Read the Transcript Below:

How Meta Ads Manager Is Lying to You & What You Can Do About It

Ralph: [00:00:00] Hello and welcome to the Perpetual Traffic Podcast. This is your host, Ralph Burns. I’m the founder and CEO of Tier11 alongside my amazing co host.

Lauren: Lauren E. Petrillo, founder of Mongoose Media.

Ralph: You always chuckle whenever I say that it’s like, Oh, he said something nice about me. Uh, well you’re in a pretty nice spot right now. You’re a much better place than I am. I’m in Brookline where it’s like 40 degrees outside. You’re in, tropical paradise in Mexico. Where exactly are you?

Lauren: I’m in Punta Mita at the Four Seasons, near Puerto Vallarta, recording this in a swimsuit.

Ralph: Right after this call, the only thing that’s standing between the end of this call and what our obligation here is Lauren jumping in the pool. So for me, it’s [00:01:00] like lunch, but anyway, so you’re down there for digital marketers who digital marketer used to own this podcast and we used to do it together as a, partnership.

Ralph: we parted ways about three years ago, chair 11 ended up buying it. Actually the media company that we own ended up buying it. So we’ve got a great relationship still. Like I text with Ryan all the time. super good guy. Been on here many, many times. If you’re not familiar with who Ryan dice is just Google, who is Ryan dice?

Ralph: There actually was a website for a while. Who is Ryan dice? That’s how I got to know him. but anyway, one of the smartest marketers on the planet and he runs a mastermind, which you’re in. This week, right? And it is called

Lauren: Founder’s board.

Ralph: founders board. Okay. So for those of you who aren’t familiar with it, we’ll give a little plug to Ryan and the boys there, because of many, many years working together on this show and also being a speaker myself there for many years, like this is their highest level of masterminds, correct?

Lauren: [00:02:00] Kind of, kind of, kind of. So

Ralph: got

Lauren: it’s scalable as parent company. Digital marketer is one of their smaller brands. So as you know, I’m a coach for Elite, formerly known as M3. Which is a mastermind for brands that want to grow their business closer to a million, Or they’re like really focused on their marketing side.

Lauren: So I coach on that. I have a call every week. I review their ad campaigns. Then scalable is the brand is the company entity for brands doing at least a million a year, but they’re really trying to grow. Like they’re trying to go from three to 10 or from 10 to 50. and that is a higher price mastermind.

Lauren: So that’s called founder sport. And then within scalable, there’s another tier. Which is round table. So they only have 10 clients and that’s at a significantly steeper investment, but that gives you founders board for three years, plus direct access to the three yards, Ryan, Richard, and Roland. so that they’re consultants for your business directly.

Lauren: So while founders board is the mastermind. there, [00:03:00] because I mean, they also have epic separate group for mergers and acquisitions, but, founders board is the higher tier mastermind because there’s roundtable, it’s access to the mastermind with exclusive consulting an add on. So I don’t know how they look at it, but I’m like, yes, sure.

Ralph: Yeah, I think at that level, they’re pretty intimate with those clients and then those customers rather, and they might even, be working on some kind of equity deal in exchange for working with them, taking ownership. I know that there’s that component to it, obviously, with Roland being involved there and Ryan, I’m not.

Ralph: sure with, Richard, but obviously he’s a great operational guy. Uh, which you obviously need to scale that next level. so much of his stuff we’ve actually implemented here at tier 11, which he’s been a great advisor for me personally. , but yeah, there’s different levels.

Ralph: So this is really sort of the larger mastermind group. This is sort of the thing that War Room maybe was at one point in time migrated to. Got it.

Lauren: Yeah. So they have retreats [00:04:00] everywhere. We’re going to Nashville next. But this one like was set up as a retreat. So we only did three and a half hours of work during the day. So we were in a conference room, but it was a lot more like discussion based. And then the entire afternoon and evening minus this like major luau blowout that we did, which is fun.

Lauren: you’re like networking. And so I spent like an hour and a half building some strategic planning in the hot tub. Fully working, a hundred percent working, just, barely dressed.

Ralph: Swimsuit on,

Lauren: Fully unveiled marketing strategy, yes, but like, let’s be real, there’s, one in Mexico, there’s different levels of swimsuits, I was not in a burkini.

Ralph: You were not in a what? A Bertini?

Lauren: Burkini?

Ralph: Berkini. Oh, a Berkini. Got it. That’s how you say it there in Mexico. Uh, well, so obviously this

Lauren: No, a burkini, wait, no, a burkini is like, if you’re, conservative and you’re not showing any skin. It’s like neck full coverage.

Ralph: got it. Okay. I didn’t even know that.[00:05:00]

Lauren: I have minimal

Ralph: know about women’s fashion.

Lauren: just leave it at that. Ralph, this is not what this episode is about, but yeah, I worked on my tan lines, I saw whales jumping free Willy style on the sunset while doing things for my business growth and discussing ways that the colleagues in the hot tub could grow and scale their businesses.

Lauren: Sorry, not sorry.

Ralph: Sorry, not sorry. Well, it’s a great but I mean, we’re huge believers of masterminds here. both of us have belonged to masterminds for years and years. Even previous co hosts, not to be named, been involved in that as well. Going all the way back to Molly Pittman way, way, way, way back.

Ralph: she actually operates a mastermind as well. So I think they’re just a great place for business owners to get together and help grow the business, but also made a pretty cool environment in which to do it, it doesn’t get much better than that place. I’ve been to that resort before.

Ralph: That place is fabulous. So, nuggets. Before we get into today’s episode, anything that you picked up, like one of the cool things about these masterminds is that [00:06:00] there’s always something that you learn from somebody else or a nugget that you learn from stage. Anything worth mentioning here before we get into the show?

Lauren: Well, I got to do my own like mini breakout. So I got to do a full session on AI with customer service. So in teaching that and having like this intimate group, like it was super packed first day. My takeaway nugget, at least for my business, was that most people were still asking if AI assistants make sense for their brand,

Ralph: Hmm.

Lauren: where I’m in my own closed world, we’re eating and breathing, but there are some like really large brands that are leaving money on the table. it’s not like a learned nugget from something that was taught. I can share ; one next, but for me, the big nugget was like, Oh my gosh, some of these brands that are doing 10, 30 million a year.

Lauren: Are still ignoring comments on Facebook. They’re still having terminal conversations. Their customer service team is like liking and validating comments, but they’re not turning those conversations into conversions, even at minimal for like lead [00:07:00] generation and lead qualifying. So it was An amazing moment because there were notable brands in the room and it’s not that they’re not doing it.

Lauren: They just because AI is so evolving. It’s so complicated, they’re accustomed to hiring offshore VAs or bringing in someone’s nephew to handle that. And like the brand’s voice gets a little lost. there’s still a level of fear that I hadn’t anticipated. so that was an awakening moment for me.

Lauren: I’m like, Oh, well this will help give really stronger language and connectivity for it. What we sell and provide. So that was like my biggest takeaway. I was like, Oh yeah, this is still super new for a lot of people, but we’ve been doing AI chatbots with many chats since like 2018 when we were both the conversations conference, even so like, so that was, that was a really big takeaway.

Lauren: For me personally, and then I think in terms of

Ralph: that these larger brands have not engaged with this technology at all, that was really a big lesson. So it was more of a surprise than anything [00:08:00] else.

Lauren: it was a surprise, but also of the simplicity of just like simple implementation for FAQs. I mean, we’ve talked about case study before where we have teams, like we’ve taken over accounts where they have like multiple customer service agents and they’re still bogged down. They can’t keep up with it.

Lauren: , but it was just the shift watching the shift saying like, for me, my language is if your customer service team is a liability, they’re an expense. You’ve hired the wrong person or you’re they’re doing customer service wrong because customer service by itself with AI with all the automations and like scalable systems, you can do your customer service team should really be an extension of your sales team.

Ralph: And a retention tool, 100%.

Lauren: getting into that customer, ensuring they got the product, ensuring they’re using the product correctly. that’s customer service. I don’t know how or when the switch change. And it might be like, sorry, I’m just like thinking about this.

Lauren: It might be like a cultural thing because there was such a shift to taking customer service outside the U. S. And maybe that’s why it’s a little [00:09:00] different. And then like culturally we’ve adapted and accepted that just responding, just showing up Just is just good enough. I’m like, absolutely not. Your customer service team should be a revenue generating line of business and they should not be a liability on your book of account on your chart of books.

Lauren: Book of chart. Insert accounting language there, on your P and L. So it was just like reminding things that everyone already knows. I believe there’s just been a cultural shift to say, I just want to acknowledge what I’m like, not at all. Comments should become subscribers. Subscribers should become leads.

Lauren: Lead should become prospects and conversions We use AI to, they have like 200 people on your account at any hour of the day, no questions asked. You don’t have to retrain them on all your products and services. But it was like going through and like, yeah, we’re making people feel seen.

Lauren: I’m like, cool. They feel seen ’cause you liked it, but they don’t feel heard. And if I don’t feel heard, I don’t feel inclined to buy. that was just a really big, I [00:10:00] assume, especially in the marketing bubble that we’re at, everyone’s using AI. People are definitely using chat GPT and they’ve adopted into like refining their creativity.

Lauren: Some people are using operators as well. but still the more simpler installations. Are not being introduced, even if like you do nothing else but train it on your F. A. Q. S. You’re paying for in house or offshore. It doesn’t matter to do low priority tasks like low productivity tasks versus like, okay, what if you collated all of those?

Lauren: Responses and use it for consumer insights. Hey, we’re getting a lot of comments about this product working at the beach. We’ve never marketed as a beach resource. Here’s an idea that we can take something with that data and run with it. That’s what a customer service person, if they’re just replying, needs to then be providing consumer insight.

Lauren: But they’re not doing that either. So that’s why I was like, that was my big breakaway. I was like, Oh wow, Lauren, you [00:11:00] live in a bubble.

Ralph: Yeah. Yeah. I think, with AI now and being able to create. your own individual large language model based upon your documentation based on the information that’s on your website, PDFs that you have on your business. I mean, it’s easier now than ever to do it and like to get so. If you’re not doing this, you should be at least doing it or having somebody in your business starting to do it.

Ralph: We have someone that’s doing it. We have not implemented the chat bot on the site yet. However, we’re building because we’ve added so many new services. We want to make sure that they’re all accurate and they’re all correct before we put it on because it does take some time to, Write it all out. our latest project is tier 11 data suite.

Ralph: there’s so much to know we have all this documentation where we’re making sure that that’s done. But the point is the end result is a chat bot on the site to be able to [00:12:00] answer questions, but also use that for training. As well. your customer to know you training your team, cause then they can keep going back to it. But like what you’re saying too, is really common thing. People are afraid because once I let it go, it’s going to use everything in my website, which there’s a fair amount of. Fear cause I don’t know what’s on my website.

Lauren: People have been building blogs. I think I’ve got like 300 blogs on one of my brands. even on long goose media, we’re doing, almost a blog a week, So we’ve got a lot of content and some of it could be outdated. we’ve done Facebook ad strategies.

Lauren: And so probably blogs from 2022 aren’t super relevant. that’s a real thing. But, where I do try to warn people is like. If it’s on your website, it’s fair game for the AI chatbot to pull and call from. So the only danger is do you have outdated pricing? And if you do, that’s fair game for the bot.

Lauren: So someone can find access to it. But at the same time, I’m like, I get it. you want to make sure everything is right. But if you don’t install something and someone finds those. [00:13:00] Inconsistencies, it’s still going to be out there for the world. See, like there is a page on my website that shows really outdated pricing.

Lauren: I’m like, Oh my God, I better remove that before this is launched, because a few times someone has found that I’m honoring it because it’s what was advertised. it’s a security feature that helps you find inconsistencies because you’re always going to have someone monitoring the conversations or you build an agent that’s going to send you a summary of the conversations from that week, that day, that month, depending on the volume of comments and messages and chats that you’re getting.

Lauren: I would just invite you to consider that. So for anyone who’s listening, like, I don’t know, I need to check. I need to check first. I’m like, you can. Or you can use the chatbot to do those checks for you. And when someone finds it, you honor it, respect it, and then you pull it down. You can do it in a reactionary thing in a mea culpa situation.

Ralph: So bottom line is if you’re not working on it right now, you should be working on it.

Lauren: line is it’s more affordable and allows your brand to be more accessible than ever. We’ve seen pretty much [00:14:00] across the board, 25 percent conversion lift when you install a chatbot on your paid traffic pages. And the way I say that is, as marketers, we make assumptions of what people want to see and read.

Lauren: On your sales page, we hire people like the highest I know is 50, 000 plus a 3 percent to do all your copy for your sales converting copy. I know other individuals that charge 1800 an hour to have really good converting sales copy. Amazing. You invest all of that, but then you don’t install like a 50, 60 widget a month to help those that you assumed wrong. Someone has a question. Maybe they don’t want to read that long a sales page and they just want to ask direct questions. And by opening that conversation, that two way dialogue, you can address their immediate points of friction, soar them without assuming because pages are made to talk to one too many, but customers buy as individuals.

Lauren: So. And sorry, that was that’s totally not the purpose of this episode, but that [00:15:00] was my biggest takeaway.

Ralph: Well, I mean, it’s, amazing that you’re there with some very large businesses and this is not a priority. It sort of seems like to me, it’s like, this is old news. Shouldn’t it have been a priority way back when, but if you’re not doing it. You should at least be considering it or working on it to a certain degree and assumptions are, uh, when you assume that, you know, these things being done, usually you’re shocked at what you find.

Ralph: Today’s show is actually about assumptions because we talked about this in an episode a few weeks back. We’ll leave a link in the show notes to that. We were talking about how to determine your NCAC. If you don’t know what the NCAC is, it is the cost to acquire a new customer. Just got off a call with a brand new potential prospect.

Ralph: And we determined through, we do sort of an analysis before they come on. It’s like, all right, well, what’s your number? Because we can start traffic today, and if we don’t know what our number is, and if we don’t know the [00:16:00] accuracy of that number, which is two things, know the number, know how accurate it is, then we could run a lot of traffic spend a lot of money on paid media, but put you out of business.

Ralph: That’s not the goal. The goal is for you to have profitable growth so you can ultimately achieve your vision as an organization. How do you do that? You go back to determining your NCAC and we’re not doing this for just clicks and likes and shares. We’re doing this because we’re trying to sell stuff online and how much you can pay to acquire a customer.

Ralph: We did a pretty extensive show on that. like I said, and That NCAC number is like new visits, new customers getting that actual number from in app very hard. And I think people are assuming that what they’re seeing inside the apps is the correct number when in fact it isn’t. And you discovered this and I know we’ve since implemented this on our side and our media buying is that [00:17:00] there is a way.

Ralph: Inside meta, we’re gonna talk about meta here specifically in Facebook, I guess it’s meta. It doesn’t really matter old meta Facebook. We’re going to say the same thing is that there is a way to show new audiences, engaged audiences and existing audiences because you want to know who those new people are and how much are you paying?

Ralph: What’s your cost per purchase, which is really a new customer coming in? And the numbers that the in app metrics show versus what we see when the data is actual. It’s two completely different things. And I think today’s show is not, a pitch for any service here. We just so happen to have, a data solution that shows exactly like within 99%, 99.

Ralph: 99%, it’s like 99 point, 44, 100. It’s like ivory soap. it is so accurate. So we can make actual data driven decisions. But the point is, is that if you’re looking at app. You’re going to be led astray. And I think everyone that listens to the show needs to [00:18:00] understand that at a base level.

Ralph: And what are they going to do about it? So you found this out, this audience segmentation, we’re going to do a screen share here today. So is that accurately depicts what we’re going to be discussing today?

Lauren: Fair fair fair fair and the the piece has been around Not even like a year like the way you can find the audience because meta Wants you to see and understand who is new, engaged, and existing customers. It’s like the two way conversations from the data you know and have into the data that Meta can have access to, to help shape how you do your campaign planning.

Ralph: so the three categories are basically new, engaged, or existing new audience. Okay. That’s pretty straightforward.

Lauren: It is straightforward because it’s new, but in the nuance of it, it’s new to your product or service, not necessarily new to your brand. So the new pieces that they haven’t visited your site, they haven’t left [00:19:00] meta to see a product or service of yours. So it’s like new visitors to your website, but then you have, if you’re in e commerce and you have catalog or shop.

Lauren: It’s excluding visitors to that shop or catalog interaction because it’s new visitors to the product or service you have most time like Easiest is website centers. But if you’re in commerce, it adds the shop because that’s like a separate website. So it is new, new, new, but I’m just going to like small

Ralph: the small nuances,

Ralph: so we’re going to, all right, so we’re going to do a screen share here today to sort of show you where this is, because this is important for you to know, and it’s also important to set it up correctly. And we’re going to go sort of go through sort of a step by step. I think we’re also going to do this in 1 of your accounts where you set it up.

Ralph: It wasn’t set up and then you did set it up and then, the before and after. So we can get into this a little bit. more deeply here because this is super important because the data that you see when you’re making decisions has to be accurate data. And we all know that even with [00:20:00] the addition of cappy or conversions API, which we talked about here many, many times, the data is still faulty.

Ralph: And it’s not a true depiction of what’s actually going on when you’re running, in this case, and we’re going to, in this example, we’re talking about hundreds of thousands of dollars a month in spend. So I’m going to do a screen share here. If you don’t subscribe to our channel over on YouTube, make sure that you do that’s over at perpetualtraffic.

Ralph: com forward slash YouTube,

Ralph: All right. So we are inside. We’re gonna have to. We’re blurring some of this out, obviously, to maintain confidentiality. This is a tier 11 client who has been on conversions API for well over a year. They have also been on and have been gathering data inside tier 11 data suite, which we talked about many times.

Ralph: So it’s a good depiction. So this is really This is about as pure data as you’re going to get on the Facebook meta side because Cappy is integrated here. If you don’t know what Cappy is, we’ll leave links in the show notes.

Ralph: We did, two different shows [00:21:00] about two and a half years ago on how to do Cappy, how to install Cappy on your ad account. And it’s pretty straightforward. We actually had two engineers from Meta that were on, I’ll leave links in the show notes for that.

Ralph: So if you’re not familiar with Cappy and conversions API, it’s the best way in which to get data back into the ad platform. Especially in light of the iOS 14 updates from 2021. So we’re still sort of living in that shadow to a certain degree. There is a certain amount of visibility that is just being blocked by right now and inside the platforms themselves, whether it’s Google, whether it’s meta, the reality is, is that a lot of the data that comes back into the platforms It is modeled based upon what Meta actually thinks is happening as opposed to what’s actually happening until you actually have fingerprinting and tying the user, the click data to the purchase outside of the platform. You really don’t get a true depiction as to what’s going on. So I’m showing my screen here and maybe you can take us through some of these [00:22:00] columns here.

Ralph: This is a campaign. This is actually at the ad set level of, Selected one particular campaign. If you’re watching this over on YouTube, great. we’ve gone into ads manager. We’ve selected one campaign or are probably our most popular campaign for this particular client. And then we’re at the ad set level and we can actually see the individual ad sets.

Ralph: Sorted by impression reach, as well as amount spent for the last 30 days. So this campaign has spent, 250, 000, just in the past, month. And the ad set that we’re looking at here is actually spent about 141, 000 in the last 30 days. So take us through these audiences here. I’m going to highlight where we actually find this data, but also sort of take us through a little, what it actually is.

Ralph: As far as like new audience, engaged audience, existing customers and unknowns.

Lauren: Yeah. So just as you were hovering over underneath the ad set, what you need to do is break this down. But before I show you how to break this down, I’m going to explain what you’re seeing in this breakdown, if that’s all right. [00:23:00] The first eye that you’re hovering over, in the breakdown of this ad set is new audience.

Lauren: So again, the meta language here, if you’re not watching on YouTube says these are people who have not interacted with your products or services. So again, that nuance being, they haven’t visited your website or your shop or your catalog. They haven’t interacted with that. That’s your, true new audience, because if you go down beneath that, you have engaged audience.

Lauren: And when you hover over that info icon, It’s saying that this is engaged audience is an audience that you defined. See you, the advertiser, you, the brand defined in the ad account settings as people who are aware of your business or interacted with your products or services, but have not made a purchase.

Lauren: So this could be super debatable of what do you include as engaged audiences? for me, the new audience is always going to be shop, website visitors and catalog engaged audience. Now it’s bigger, expansive. They [00:24:00] could have watched your videos. They could have interacted with your Facebook profile, your Instagram profile, all these, it’s a much.

Lauren: Bigger audience, right? Cause they’ve engaged, not purchased. And then underneath engaged audience, we have existing customers. So existing customers as defined by Meta is an audience that you defined in an ad account settings as people who have purchased your products. Or services or purchase your products are signed up for your services.

Lauren: So big disclaimer here, engage audiences and your existing customers must be created in your meta ads manager. So you go to the audiences. So if you hover on the left. For those again watching, we’re hovering on the left underneath campaigns. Ad reportings is the audiences. It looks like three little people.

Lauren: You go into that audiences tabs and that’s where you’re creating the custom audiences that met is going to blend into your engaged audience and your existing customers so that they can then determine who are your new. Visitors and new customers. So if we hover back onto the ad [00:25:00] set level, those are the three like critical

Ralph: and we’re going to just interrupt you there. We’re going to do a show on that particular subset, that audience is just to make sure people understand this, because these are people who have interacted, with your catalog video view audiences, you know, if you’re using. obviously website custom audiences, which is basically you’re retargeting audiences.

Ralph: But setting these audiences up correctly is the key to this whole thing actually working in this particular account. It’s been set up accurately. It’s been set up correctly. but we’re going to go through that in a separate episode. So anyway,

Lauren: Love that. Yeah, no, no. It’s good because again, it’s what is correct. And even if it’s not correct, it’s you start somewhere, but we can totally go to that. So those three, you create the engaged and existing audiences metacreates for you, then the new audience. And then there’s other options you might see as unknown.

Lauren: Or the other one is, on track or. Unaccounted for, but there’s two additional ones, which they count as Oh, uncategorized and unknown. So [00:26:00] here we can see that there are unknown. This is going to happen because people turn off their pixel. People switch different devices. Like it’s an imperfect system.

Lauren: here, you’ve got Two impressions from unknown. It might be someone that’s using the dark web or whatever, in all of that, you can hover over unknown. So we can see as defined by meta unknown as audience segments that weren’t defined for this campaign. at the time of the impression.

Lauren: So the results weren’t categorized as new audience, engaged, or existing, but there is an additional two unknown as an uncategorized. So we know that this was set up well because we don’t see uncategorized. So those are the five. And if you look at this, Ralph, go up to that top one.

Lauren: what is that discrepancy? what is that percentage for those that can’t see? the first asset here has 11 million impressions.

Ralph: like I said, we’re on the ad set level inside meta ads manager here. So I encourage you to watch this over on our YouTube channel and perpetual traffic. com forward slash YouTube. but we’re going to try and call this out as much as possible here. So in this [00:27:00] particular ad set, we’ve got in the last 30 days, okay, we’ve got over 11 million impressions.

Ralph: Okay, reach, you’ve got a frequency potentially here, like probably two thereabouts. I didn’t put frequency in here, but anyway, we’ve spent about 141, 000 in the last 30 days on this ad set. And if you look at new audience, engaged audience, existing audience, you’ll see that the largest portion, if I highlight it here, of that 141, 000 in spend.

Ralph: Is $124,000. So meta is telling me that of the $140,000 I spent on this ad set, 88%.

Lauren: 88%.

Ralph: 88%. Thank you for the math. I was gonna say 87%, but 88%. 88% is new. Now, new as defined, these are people who have not interacted with your products or services. So, it’s [00:28:00] dependent upon your audiences, but the misnomer here is also, let’s talk about attribution windows.

Lauren: Mm. Mm hmm. Mm hmm.

Ralph: Another big factor, we are not looking at all time. These are not people who have not interacted with your products or service all time. These are people just that are in your audiences, but also really in a 28 day. Look back window at the maximum.

Lauren: because depending on how this ad set is set, it’s going to report the attributions. If it was a one day, click one day view, seven day, click one, whatever that is at the attribution level, you assigned this to is what it’s going to attribute in the breakdown. But there’s like here, there’s ways that you can also see, even though it’s not attributed to, you can add additional days up to a 28 day look back.

Lauren: But It’s optimized for the attribution window you set, but the other attribution windows are available. Um, but 100 percent that 28 day, it went away and then it came back and it’s not super easily [00:29:00] accessible, but yeah, you’re still looking at a very marginalized attribution window.

Ralph: Okay.

Ralph: we’ve got new audiences, engaged audiences, existing customers and unknowns. We’re assuming it’s within a seven day look back period. Okay. That’s the default. We’re not breaking it down. There is a way in which to break it down inside ads manager to show 28, seven and one by default.

Ralph: We’re going with seven here. So where do you actually find how to enter these in and actually actually show in your ad set. You can also see this inside campaigns. We’re just using ad set here. It is, I believe under the breakdown setting, which is right here.

Lauren: Correct. So for if , you’re running or you’re listening in the car, forgive me if I butcher this explanation, but bear with me. you’re probably familiar with your columns. Those are the three parallel lines. We do that to look at performance and clicks. We make our own custom columns arrangement because I want to look at the KPIs that matters to me.

Lauren: When meta gives you like 200 plus, I care about [00:30:00] like my 40. Immediately to the right of columns and breakdowns.

Lauren: So you’ll see it as

Ralph: columns here. I’ve made it super, super basic, just keeping, purchases, cost per purchase, purchase, conversion value, amount spent, frequency and, impressions and reach. So just for the purposes of today’s call, however. You can add a

Ralph: ton of stuff. Yeah. these are the columns that

Ralph: we can

Lauren: hundreds. So then the

Lauren: columns, as they are saying, are what’s happening on the x axis, So when we’re looking from left to right, that is what’s the KPIs that are showing. Breakdown goes on your y. So that’s why we can see under each ad set, Underneath the ad set is new audience engaged, existing unknown, and then you might also have uncategorized.

Lauren: So the breakdown is going down in your y axis, so it’s immediately to the right of the columns button with the caret. It says breakdown. So what you want to then do is if you scroll down, you could [00:31:00] either search and type in audience segments, but if you scroll down on breakdown, you go to demographics, and then in demographics, you have audience segments.

Lauren: So it’s to the right of audience segments. You turn that on and then full disclosure, it’s a really good cheat. If you’re auditing an ad account to know if the media buyers. are doing this because you want to make sure that they’re setting up your audiences. Because it’s not just about clicking buttons, I know that there’s a lot with AI, but there’s so many things that go into ads manager. They’re like 16 different places to go to. So we’re going deeper, going more ninja to this. So if you go into breakdown, you go to demographics, you click on audience segments, then what that will do is add to your y axis up to five additional Lines to which you can see the columns break down was how we knew 124, 000 of the 141 was spent on new audiences.

Lauren: New, in quotations, air quotes, being what meta identifies as new, based off of [00:32:00] what you’ve identified as existing and engaged.

Ralph: So just knowing that this even exists and using it as a benchmark at the very least. Is an education unto itself because did this actually get installed inside ads

Ralph: manager? Do

Lauren: to say November 2023,

Ralph: Okay. So it’s been around a while.

Lauren: but not that long. I mean, yes, just barely over a year. none of those, a lot of these rollouts, like unless you’re like, so we have seven full time media buyers, right? they live in the platforms and even they will find stuff that’s new.

Ralph: They might not announce it either.

Lauren: or if they do it’s in like buried pieces.

Lauren: We’re really lucky. We have access to agency reps account reps, so they’re Often promoting newest updates. i’m part of uh, meta business leaders network I’ve gotten to be on their global innovation committee. Like there’s benefits to having the access because They’ll tell us about stuff sometimes if you [00:33:00] follow, um, that is like Instagram for business accounts or Adam of CEO of Instagram.

Lauren: Like he’ll often share a lot of updates on his broadcast channels. Like there’s just different resources you can go in. Like, I’m just saying it’s a lot of different places. If you didn’t know, it’s okay. Even if you’re a media buyer and you’re like, Oh, this is like another, it’s okay. Cause there’s a thousand and a half things that can affect your campaign.

Lauren: But now you’re empowered to understand the distribution of your media across the various audience types to get a better understanding of MetaTries. And Meta guesses, and Meta will guess wrong if you don’t give it direction. These algorithms are like toddlers, you have to give them guidance, you have to feed them data back.

Lauren: It’s almost, if not more important than how you set up your campaigns, is how you feed that data back. Which is where, like, in this you can see, okay, cool, I know that there’s still over 10 percent of my budget on this ad set [00:34:00] that’s going to non new. So that can help you decide how you do your messaging.

Lauren: However, Ralph, what you then have is an additional layer because we know that Meta’s doing the best it can.

Ralph: This is doing the best that it can. And our media buyers and I know the media buyer quite well on this. He’s been on perpetual traffic a couple of times. Like I know he’s got this stuff dialed in, but he’s also looking at a cost per purchase here for new claiming new of. Let’s see. It is 149, which is not within their KPI.

Ralph: Their KPI is 80 to 90 ideal as sort of a scale range, but definitely under 100. So If my media buyer was looking at this specifically and broke this down with new audiences, I’m acquiring new customers at 149, that would be

Lauren: hmm. Woof.

Ralph: very bad. That is 50 60 percent higher than it needs to be. [00:35:00] So,

Lauren: But also, wait, before you jump to this, like, look at that, you’re new is 149, you’re blended is 128, so you’re already given a different handicap if you’re not breaking this down. Because you can see, existing customers are Last click attribution is to this ad within the seven day window. They clicked or viewed the ad and you have 21 purchases from your existing customers.

Lauren: So that 2874, I mean, they might’ve had an email, they might’ve had an SMS. There might be, this is where like you can have multiple attribution pieces. But if you’re like, Oh, 128, that’s not as bad as one 50. Can we break it down? But if you don’t do this, you’re not looking at the one 50 number. You’re looking at the one 28 and you’re not excluding that you’re engaged audience. That you’re returning customer not returning customer, but like your warmer audience your cost is 66 And maybe that’s, again, without a scope because you’re relying on email to do more of that, all that data, again, it just helps you make more informed decisions, but then you’re saying, Ralph, [00:36:00] you would turn this off

Ralph: Yeah, I mean, we would probably say, well, this is a terrible ad set. this is clearly coming in way above KPI. I mean, if I didn’t know about any of these individual columns here, breakdown under the breakdown section, which is engaged to audience segments, or audience segments rather with new engage in existing, I wouldn’t really even have an understanding as to meta is focusing their efforts. Is it what they think are on new customers? What they feel are on engaged existing. it’s kind of a big mess unless you actually have a way in which to, you can benchmark this saying, okay, in this particular ad set, 128 is actually is okay if you double check it with a third party attribution tool.

Ralph: And so the reason why we’re. Exemplifying this is first off to say, like, the ad account itself is not giving you a true measure of what’s actually happening. It’s using a seven day window. It’s [00:37:00] blending audiences together. clearly they’re stating that 88 percent of your traffic is new. That is totally not the case.

Ralph: and that’s one of the biggest things like when John Moran and I talk about this in our. Our tier 11 lives every single Friday. We’re like, in app ROAS is a faulty metric because of this particular issue right here. As long as I know that even with all my exclusions in this ad set, and I know all the exclusions are made, the audiences are set up correctly.

Ralph: if I exclude all of those audiences for me to try to target new customers, I still can’t do it because meta is going to blend those audiences together no matter what. And the reason we know this is that if we look inside data suite, the exact same thing, exact campaign, all the ad sets, we’re going to show this in just a second here last 30 days, look back, let’s look at this ad set here, which we spent 141, 000 on last 30 days.

Ralph: If we go into

Lauren: 30 being [00:38:00] January 27th through February 25th, so this is at the time of the recording, like, this is 2025, this isn’t skewed to Black Friday or anything, it’s like truly last 35 days, right? 30 days.

Ralph: last 30 days and here is the ad set. Okay. The numbers actually match almost exactly 141, three 72. , it’s only off by like a few dollars, which is insane, but also there’s reporting, they match basically it’s a hundred percent match. So here’s how we would then look at this. We would say, okay, 141, three 72 for this ad set.

Ralph: we know that meta is going to. Put your ads in front of previously engaged, either customers, audiences that know about your brand. They’re not truly cold. And we know that because we can then fingerprint or tie this together with a click. As long as there is a click, we can then determine about 42 percent of these individuals who are [00:39:00] targeted in this ad set are new.

Ralph: It is not 88 percent as Meta says over here in this particular going back into the meta ad account, which is 88 percent of all of our spent. We’re using spend here impressions. You can do the same sort of thing. So we realized that, okay, there is 42 percent that is new. But

Ralph: unless we know what we are paying to acquire a new customer.

Ralph: And there’s the number right there. We know in this campaign, cold traffic. Okay. There’s some warm in here. Obviously. All right. 57 percent is warm. 42 percent is cold. But we separate out the new versus the returning by using this NKAC metric. And this is why the tier 11 data suite is so powerful because it’s actually pulling real data, piecing it all together, matching it with the user on meta and then showing it inside the interface here.

Ralph: So we know inside meta in this campaign, it says our [00:40:00] purchasers were coming in at a CPA or a CAC of 126 and this particular ad set was coming in at. 140. What we actually know is that the new customers, the cost to acquire the new customers, the 42 percent that are brand new is well within our metric, which is our NCAC metric right here, which is 8, 992.

Ralph: And this campaign is actually doing really well. Yes, it is targeting return visitors. Yes, it is targeting people who have bought previously. Absolutely. And if we do even a further breakdown, we can actually see a CAC, which is different. A CAC is all CAC. This is new visitors. Okay. These are engaged visitors, but also returning customers and that a CAC or the all.

Ralph: Customer acquisition cost. ’cause you are gonna get some, returning ones is even lower at $82. So we

Lauren: always be lower

Ralph: it’s always

Ralph: going to be lower. And let’s just explain for people like the difference [00:41:00] between, how you explain it, ACAC versus just CAC or cac.

Lauren: So for a cag being all cack or when i’m like This is your cack your cost to acquire a customer. It’s I don’t care who or how that customer has been with you But your n tag a new customer always has extra Friction, unless you have some like, viral one off exception where your NCAC ends up being cheaper because it penetrates a new audience that was never exposed to it, and you’ve minimally spent into that audience.

Lauren: Your ALCAC, because it blends your evangelists and your returning, um, and your warm audiences, like it’s all of it together. So 99. 9 percent of the time it’ll be cheaper. I’m leaving that 001 percent for the exception. But NCAC is new. They are not in your existing customer database. They have not given you a dollar before. So you have upselling, ascension that are in your AllCAC.

Ralph: So, uh, yeah. ACAC is always gonna have, there’s cac, a lot of people talk about cac. But you really do need to [00:42:00] differentiate the two between, everybody. Cause you’re always going to be, as long as you’re using meta platform, the Google platform, they’re always going to target some of your warm traffic, no matter what, but they’re going to claim as we see over an ads manager, that most of it is brand new.

Ralph: Here, and that’s the learning from today is like, you can’t just look at these platforms and assume that the data is correct. This ad account has Cappy installed, and a lot of people are asking, well, what? Hey, what’s the difference between data suite and Cappy Cappy is good. It’s a good first step. However, it doesn’t even compare to the precision that you actually see inside here on.

Ralph: It’s because of the way that it works.

Lauren: I think like a lot of the component for people to understand is that Meta’s not doing this maliciously, they’re doing the best they can based off of the information they’re able to glean in on your account. It’s to their benefit for you to want to spend more. If you were to turn that campaign [00:43:00] off, Meta would then lose 140, 000.

Lauren: In profit, because I mean, that’s their asset, right? But with legislation, with privacy policies and cookies and all that type of stuff, it’s restricting what Meta can do. So it’s doing the best that it can, but if you take nothing away, it’s like, Meta’s trying, and they’re trying their best, and they’re always going to try, but you have to take it with a grain of salt, and that the assumptions and dependency on in app numbers only, Is never going to paint the full picture What we’re showing with the breakdown is adding more color to your picture Which can inform your campaign planning your campaign management campaign messaging.

Lauren: Maybe you’re introducing some more direct mid funnel Language because you’re not just capturing new as much as I only want new. I know we all only want new, but it helps you make more data informed decisions. And then, what you’re showing with here is when you’re able to [00:44:00] add in a supplemental additional information, you can have even stronger informed decisions because you’re not it’s your pictures.

Lauren: You’re zooming out and zooming out and zooming out. And when you’re spending more, well, you know, even for the small business owner, even if you’re spending less, every dollar is important to the end user. So if you’re not incorporating a, an outside party tool and you’re doing nothing else, just bring in the breakdown so that you can, again, start to understand what’s happening.

Lauren: Cause a lot of people will try to treat metal like an ATM. You could 10 years ago, put a dollar in, get 20 out. there’s campaigns that are still treating metal like an ATM. But when you put it a part of your bigger media mix, you have to understand that where’s this. Where are these assets playing?

Lauren: Is it like a billboard? Is it like a radio ad? Is it like a TV sponsor? Is it satellite? it’s an element of your greater marketing strategy. And when you see that there’s new and middle of funnel, bottom of funnel people exposed to your Facebook ads has to help understand, like, does it become brand awareness stuff?

Lauren: Is it beyond just [00:45:00] conversion? Like all of this comes into effect where I’m just like, if you take nothing away from this, know that. In app numbers are inaccurate and providing the best that it can. And then additional tools like this provide a way better picture.

Ralph: So there’s two things in this. So, the tier 11 data suite, you cannot manage the campaigns inside here. You still have to toggle and our, media buyers toggle between the two. But my guess, Actually asked the media about this is like, we use something that’s called benchmarking and we know he probably knows that if I’m getting a cost per purchase in this ad set, that’s about 128, which is in essence.

Ralph: 40 percent above what I’m actually getting for NCAC, then that’s okay. So even though inside ads manager, 128 per purchase or a CAC of 128 is unacceptable for the client. We know that the in app metrics are faulty. And so that benchmark, [00:46:00] he probably, my guess, and we should probably have him on to talk about this is, Hey, if I’m getting a cost per purchase between 120 and 130, I know I’m well below my NCAC when I double check it with data suite.

Ralph: And the way that we used to do this is we used to compare what we were doing inside of ads manager, as well as Google with the CRM. And then pull manual reports, and it was such a manual process because we wanted to just make sure are we bringing in customers that actually make sense for the business at a price that is profitable for them.

Ralph: this customer has a longer term view of their business, but they realize if they can acquire a customer. For 92, their lifetime value is hundreds more, they know their numbers infinitely. So if we have an accurate way of figuring out exactly what we’re paying to acquire a customer and then double checking it against what’s actually happening inside the campaign or inside to a really granular level inside the actual ad set [00:47:00] itself.

Ralph: Then we know that we’re within their KPIs and we’re helping move their business forward. Does that make sense?

Lauren: It makes a hundred percent sense for a 25 percent accurate. I’m making those arbitrary numbers, but no, it makes sense. It’s just.

Lauren: It’s marketing in a time where we used to have so much more data than we had before. And then the data is getting pulled back, pulled back, pulled back. So it’s looking at, I mean, we talk about Mer all the time. Like these are non negotiables that must be incorporated for you to understand where you’re putting your money and how you’re making revenue.

Ralph: Absolutely.

Ralph: So yeah, so I mean, the old way of doing things is comparing it with, the CRM and it’s incredibly manual, but that’s the source

Lauren: the CRM or the bank account, where you’re like,

Lauren: okay, I’m looking at the CRM. I can see what was attributed, what goes through and doesn’t match what’s in the bank account. That’s manual. That’s, almost counting Florida election ballots.

Ralph: Right.

Ralph: what we would do is on a weekly basis, we [00:48:00] would do a true up with the CRM or inside Shopify. I believe this is a Shopify store and we would just double check. All right. For all customers that have come in this week. What is that cost? how many are new? How many are returning, inside Shopify?

Ralph: It’s a little bit harder to determine that, but it’s more accurate data than it is inside of meta. Because once again, you’re using I mean, people can change their email address and subscribe or buy and using a different credit card. Like there’s all sorts of ways in which it can be not 100 percent accurate inside the CRM or inside Shopify or whatever your e commerce platform is.

Ralph: The point is, is that’s the best way of doing it. And that’s how we used to do it. And that’s how you use Murr in order to. Guide decisions here on how much you should spend on which campaigns. problem is, is that true up takes a long time to do. And we would typically do it every seven days.

Ralph: Now you can actually see it almost in real time, exactly what’s happening. what is my NCAC by campaign? By ad set by individual [00:49:00] ad. We haven’t even gone into the individual ads here, but you can actually break that down even more so. And you can see which creatives are the ones that are getting the majority of cold traffic that are actually, getting the best.

Ralph: and pack and, in this particular case, we can actually, we’re looking inside. one particular ad, about 42 percent of this is, is new, which is pretty good. That’s pretty good. That’s pretty healthy. So this creative here is probably one that we’ve iterated on multiple times. And it’s the reason why this ad set and this campaign overall is getting such good results because we’re making those decisions based upon nearly a hundred percent accurate data.

Ralph: Like I said, 99 and 44 one hundredths. I’m not going to ever say it’s a hundred percent, but it’s pretty damn accurate. It’s, it’s nothing like I’ve ever seen before. So it’s like this secret weapon that you have. The point is, is, and this is not a pitch for data suite. By any stretch, however, you’re probably going to take that it is, well, whatever, like, if you want to get it, come to tier 11, we’re going to [00:50:00] certainly talk to you, but the point is, is like, we’re so excited by this because we were living in such like the stone age prior and making all of this incredibly manual, but I think for those of you who don’t have a solution like that, the bottom line is this, is that the platforms Are not accurate. And you have to take that with a grain of salt. And if you are cross checking it with your source of truth, then you can benchmark, a profitable CPA in essence, which is in this particular case, inside this ad set. CPA or cost per purchase, which is acceptable is around 128, even though it’s above what your allowable cost to acquire a customer is.

Ralph: Does that make sense?

Lauren: It does because you might have even further monetization opportunities because other people that are going after that customer might even be shutting off those campaigns. there’s a lot of opportunity with the data. And so not knowing [00:51:00] is not an option.

Ralph: Not knowing is not an option, but also being aware that. The data isn’t 100 percent accurate, I think is the biggest, we’ve never really talked about this. We’ve never actually done a screen share where we’ve going in and shown it side by side. We always sort of said, well, in app ROAS sucks because it does.

Ralph: Cause it’s a faulty metric in app CPA is not accurate because it’s

Ralph: not.

Lauren: app, in app is doing the best it can Ralph. we

Lauren: got to give meta, it does the

Lauren: there’s no motivation for them to lie. They make money by showing you good results, so they’re going to capture all the results that they can, which is why there’s attribution, there’s an attribution war of everyone taking credit.

Lauren: Sorry, I’m still going to go after a tentative, and they have the assumed 28 day attribution window for a text. But everyone’s competing to claim credit. For the same component. And then so metal like any other platform is doing the best it can to show you all of that it has available. But there’s legal restrictions, cookie restrictions, set up restrictions that will never provide [00:52:00] accuracy.

Lauren: So you again, we say this all the time. You cannot be solely dependent on an app. They provide very strong trend recommendations and can give you a lot of campaign insight. But there’s still more to the picture. Yeah,

Ralph: So, all right. we’re getting mad at the benefit of the doubt here and Google’s the same way. I mean, but you have to be aware of it. That’s all though.

Lauren: you listen to this, you take it with a grain of salt, or take it with a splash of salt in the ocean that’s literally right behind me from

Ralph: And that’s why we’re going to end the episode. So you can go, yeah, use your bikini. anyway, we are going to do an episode where if you found this episode helpful, first off comment and obviously share like the episode as much as possible again, over on Spotify and wherever you listen to podcasts, leave us a rating and a review.

Ralph: We love you guys for doing that. We

Ralph: so appreciate it. And, we are going to take you through in a, maybe the next episode or one within the week or so, over on how to set up audiences correctly here, [00:53:00] because that’s one part of today’s show, which we didn’t really discuss quite as much, and those have to be set up correctly.

Ralph: So at least you’re seeing more accurate data inside the platform itself so that you can make better decisions, obviously. Always cross check it, with your source of truth to make sure that what you are seeing is accurate. But the point is, is like setting this stuff up for what we refer to as, campaign hygiene is super, super important.

Ralph: And we’ll go through that in a secondary show here. So, once again. Check us out over on our YouTube channel. If you didn’t, if you’re listening to this, you’re walking the dog, you can definitely check it out over there, over at perpetual traffic. com forward slash YouTube, but you already knew that. And Lauren E.

Ralph: Petrillo is going to be heading into the ocean momentarily. So on behalf of my amazing cohost, Lauren E. Petrillo,

Lauren: Adios, vamos a la playa.

Ralph: until next show, see ya. [00:54:00]

Episode 675: How Meta Ads Manager Is Lying to You & What You Can Do About It

How Meta Ads Manager Is Lying to You & What You Can Do About It

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