Stop Wasting Ad Spend: This Tool Guarantees Accurate Customer Data

Summary

Perpetual Traffic: "Stop Wasting Ad Spend: This Tool Guarantees Accurate Customer Data"

Hosts: Ralph Burns & Cameron Campbell (guest Meta expert, Tier 11)
Date: February 3, 2026

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Episode Overview

This episode dives deep into the persistent challenges marketers face with ad spend waste and data accuracy, especially for paid media and scalable growth. Ralph Burns and guest Cameron Campbell (Meta specialist at Tier 11) examine why even advanced tracking solutions like Meta's Conversions API (CAPI) fall short of delivering a "source of truth," and how Tier 11’s proprietary Data Suite fundamentally shifts the attribution and optimization landscape. Key themes include the pitfalls of modeled data, the evolution of attribution post-iOS 14, why true first-party data matters, and how accurate measurement (particularly of new customer acquisition cost) is vital for scaling profitably.

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Key Discussion Points & Insights

1. The Attribution Problem: Modeled Data and its Consequences

• The Industry Shift:

  • Marketers historically relied on in-platform metrics as the "judge and jury" for campaign performance, but privacy changes (notably Apple’s iOS 14 update) have rendered these unreliable.
  • Burned ad dollars and an inability to prove ROI stem from modeled data ("guesses") rather than actuality.

• Impact on Real Businesses:

  • Many growing eComm businesses have scaled successfully on luck without understanding their numbers, only to stagnate or collapse later.
  • "A lot of those businesses... cease to exist in 2022," Ralph notes, showing the risk of data ignorance. [10:59]

• Quote:

  “You can get very big based on luck...then they're now either going down the way...or they're stuck and they can't scale and they don't know why.” —Cameron Campbell [10:13]

2. Why Modelled Data Persists Despite CAPI

• How CAPI Works:

  • CAPI is designed to enrich Meta’s optimization by passing first-party data (like emails from website purchases) server-to-server, bypassing browser ad blockers.
  • The server attempts to match back to Meta users, but data is often incomplete or mismatched.

• Limitations:

  • Data gaps remain: “There’s a lot of data lost in this situation...Meta has to do the job of matching those people up,” says Cameron. [13:04]
  • Modeling fills these gaps, leading to wild swings in reported results.

• Quote:

  “Meta’s just going to...estimate what percentage of those people are taking what action...it just doesn’t have any credibility even when you’re at scale.” —Cameron Campbell [20:57]

3. First-Party vs Third-Party Data: Why It Matters

• Definitions & Implications:

  • First-party = direct from your website/customer interactions; you own it.
  • Third-party = data collected and passed via tools like the Meta Pixel, less robust and often blocked by browsers.

• CAPI’s Improved (but Incomplete) Solution:

  • “With CAPI your data was getting better for the platforms to optimize, but you just could not trust anything you were looking at in the platform..." —Cameron [23:38]

4. The Tier 11 Data Suite: Solving the Attribution Gap

• How It Works Differently:

  • Installs an edge server (via a CDN/Cloudflare), which captures user data before browser-side blocks.
  • Data is stored in a first-party warehouse, matched to the ad click, and used both for reporting and for offline conversion uploads, improving optimization and reporting accuracy.
  • “We capture the data of your user when they enter the parking lot, as opposed to when they walk through your front door,” explains Ralph. [28:24]

• The Key Advantage:

  • Massive reduction in lost or modeled data; marketers can finally trust what’s in their dashboard.
  • Blended CPA in Meta will often appear higher than what you see in Data Suite, which has the fuller data picture.

• Quote:

  “The key is capturing the data on the edge before it gets blocked by the browser. And that's the key difference between CAPI.” —Ralph Burns [31:20]

5. Real-Life Comparison: Data Suite vs. In-Platform Reporting

• Case Study Example (January 2025 Campaigns):

  • Meta-reported cost per purchase: $95
  • Data Suite-reported (true) cost per purchase: $77.56
  • 20% gap, which could trigger premature optimization or unjustified campaign cuts if only Meta data is trusted.

• Quote:

  “There’s a lot of money on the line here and you need to be able to make accurate decisions based upon true data as opposed to modeled data or data that you’re not confident in.” —Ralph Burns [37:27]

6. The Metric that Matters: NCAC (New Customer Acquisition Cost)

• Why NCAC Is a ‘North Star’

  • Accurate new customer cost is vital for scaling and sustainable growth; it isn’t natively tracked in Meta.
  • Data Suite can distinguish new vs. returning customer purchases at the granular (down to ad-level) layer.

• Examples in Practice:

  • Cameron explains increasing a Meta budget by 17% for a client, observing a temporary NCAC spike, but, using Data Suite and understanding time lag, he waits another week to see the expected improvement as customers convert later.
  • This prevents over-optimization and missing scale opportunities.

• Quote:

  “We are practicing what we preach...I am looking at this North Star metric here of new customer cost...It just doesn’t exist in ad manager.”—Cameron Campbell [38:07]

7. Time Lag & Data-Driven Patience

• Time Lag Analysis:

  • Knowing your funnel’s purchase window (e.g., 14 days from click to conversion) helps interpret when to act or wait.
  • Pre-Data Suite, this required guesswork and “crutches,” leading to frequent, often unnecessary adjustments.

• Methodology:
  -"Now we have the science...we can look at time lag in Google and we know exactly how long the conversion window is to work, basically." —Cameron [45:28]

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Notable Quotes & Memorable Moments

• On old attribution models:
  “The in-app metrics used to be the real judge and jury, like the source of truth years ago. That is no longer the case.” —Ralph Burns [06:58]

• When losing 60–70% of conversions overnight:
  “For some of our...Apple users, higher end buyers...we lost 60 to 70% of our conversions literally overnight.” —Ralph Burns [19:42]

• On using inaccurate data:
  “You might turn off the thing that was bringing all the conversions...So it enhances the optimization phase, but it doesn’t do anything for the reporting phase in Meta.” —Cameron [23:38]

• On Data Suite accuracy:
  "We're capturing the data on the edge before the data gets blocked and then capturing as first party data, pumping it back into the ad platform...when you view it inside the interface, it's nearly 100% accurate." —Ralph Burns [39:25]

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Timestamps for Important Segments

• [05:57] – Why educating clients on new data & measurement approaches is essential.
• [10:13] – How scaling on “luck” catches up with eComm brands.
• [12:22] – How CAPI works, limitations, and the ongoing problem of lost/modeled data.
• [18:14] – EMQ scores and how CAPI helped, but didn’t solve attribution post-iOS 14.
• [20:57] – Campbell’s assessment: why in-platform data is “a guessing game.”
• [23:38] – CAPI is good for optimization, not for reporting/sourcing truth.
• [25:53] – The Tier 11 Data Suite architecture explained; edge server advantage.
• [28:24] – “Parking lot” analogy for edge tag vs. post-landing tracking.
• [34:01] – Platform vs. Data Suite CPA (example: $95 Meta vs. $77 DS).
• [37:15–39:25] – 20%+ CPA gap, importance for media buyers, and NCAC as actionable metric.
• [41:10]–[44:44] – Using new visit metrics, time lag, and Data Suite for smart scaling.
• [45:28] – Why “science beats luck” for scaling and optimization discipline.

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Final Takeaways

• Modeled Data ≠ Growth Confidence: In-platform metrics now mislead more than they guide. The only way to establish marketing ROI and scale profitably is with a system that captures, matches, and reports true first-party attribution before browser blocks interfere.
• Tier 11 Data Suite = Edge Over In-Platform/Standard Attribution: By using edge-based data capture with rigorous privacy compliance, Data Suite bridges the “truth gap,” informing smarter decisions at every step of the funnel.
• NCAC Is King: Marketers must move beyond blended CPA/ROAS and focus on true new customer acquisition cost, using technology that delivers truly accurate numbers to guide optimization, budget allocation, and reporting.
• Patience & Data-Driven Action: Understanding conversion windows lets marketers avoid overreacting to swings in CPA/NCAC, empowering them to scale with confidence.

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Resources Mentioned

• Tier 11 MPI spreadsheet/checklist
• More explanation videos and resources at PerpetualTraffic.com

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If you’re tired of flying blind with your ad spend and want attribution you can trust, this episode is a goldmine of real agency wisdom and modern solutions.

Transcript

[A]

Hey, real quick before we dive in, if you've got a brand or marketing tool that marketers need to know about, sponsor the show here at Perpetual Traffic. Perpetual Traffic puts you in front of thousands of seasoned marketers, CMOs and agency owners. So head on over to perpetualtraffic.com to apply to be a sponsor of this show. There is a lot of money on the line here and you need to be able to make accurate decisions based.

[B]

Upon true data as model day is a big problem because if you are looking in platform, basically what Meta is doing is we're just going to try and estimate based on how many people are clicking away from our ad, how many people are purchasing, what percentage of those people are taking what action. This looks like it is very accurate. You've had all these sales and you can look at your Shopify dashboard and you're not getting anything.

[A]

What is the difference between CAPI and Zero11 data suite? How are they similar? What's your take on it?

[B]

We have the luxury of having other metrics that that don't exist in Ads Manager.

[A]

So you're listening to Perpetual Traffic. We all know this as marketers and business owners that growth is amazing. Until something breaks or some catastrophic event, heaven forbid should ever happen to your business. And I don't mean just your ad campaigns going sideways. Maybe a client slips on a wet floor, a shipment suddenly goes missing or, or a contractor gets hurt or an employee gets hurt. Suddenly the thing you've been building can take a huge financial hit, maybe one that you worry might take down the company. And you should always be thinking about that as the business owner. Most people don't think about business insurance until after something goes wrong, when it's already too expensive or it's too late. That's why we're big fans of what next Insurance is doing. Business insurance is is so important for any business, whether you're online or offline. And they've basically taken the pain out of business insurance. It's 100% online, ridiculously fast, and designed specifically for small businesses. You answer just a few questions and next tells you exactly what coverage you need. No phone calls, no waiting, no holding the line for the next representative. Just fast, affordable production that actually has your back when things go sideways. Policies start for as little as $29 a month. Don't wait for a crisis to remind you you're not covered. Get protected in [e-mail] perpetual. That's nextinsurance.com perpetual and we are live. Welcome and alongside me here today is not John Moran, but a younger, better looking meta expert that John Moran is not Cameron Campbell. And today we're going to be getting into some pretty interesting stuff. I know a lot of the questions that we've got here are more Google related. We'll, we'll get to those as much as we possibly can. But yeah, excited to have you on today, Cameron. Welcome back.

[B]

It's funny because I noticed last time I looked very tanned and basically my camera had one of these like beauty features on because I reset the settings so I, I must have looked like, like a Ken doll or something.

[A]

Yeah, you, you were looking particularly handsome. I saw the, I saw the.

[B]

Unfortunately it was AI, it wasn't reality, I'm afraid.

[A]

That's all right.

[B]

If anyone's watching for Valentine's Day, that was, that was not. That guy's gone. He was last.

[A]

That guy's gone. That was last week. This week is the real Cameron. Well, I'm like washed out white guy here. Like this new camera that I have that doesn't have any beauty settings. So you got me just the way that I am here today. Sometimes John, we sort of joke with him because he has get like the black background and then if he wears a black shirt, his head, he looks like the floating ghost, like Casper the Friendly Ghost kind of in the screen. So at least we're colorized. At least we're not like for me.

[B]

John's as Behemoth Rhapsody. It's the album, the, the video. If you look at it, that's exactly what he's doing.

[A]

That is totally it. That's it. Yeah. With the, the underlighting, you need that effect.

[B]

So, so.

[A]

All right, well cool. Well today we're going to talk a little bit about some technical stuff and then we're going to get into something that has been very impressive to me and I know you have made a study of understanding a lot of the MPIs, a lot of the marketing performance indicators from a meta standpoint primarily, not necessarily Google. You have an understanding of it over on there as well. But it's just a generalized understanding of what these things are and just as a step backwards in case, if you don't have them yet, just download the spreadsheet, just download the checklist so you can get on the same page with us here. It's [e-mail] MPI that's for tier11.com MPI we talk about it at Perpetual Traffic all the time. The MPIs are marketing performance metrics or what they, we call them. Are just a means to achieve an end for a client. And when clients come to us, as Cameron has done many times inside tier 11, and you also have your own e commerce business, so you are a business owner too, which is very cool. It's like these just metrics we use in order to achieve a business outcome. And that business outcome is whatever the goal is. The big goal is like we have a client, you have a client that you're working on. They want 12 million in revenue this year. I don't know if they have a profitability goal, but that's like their big goal. So then from that goal we sort of begin with the end in mind and then figure out, okay, how do we get there? Is it new customer acquisition? Is it, you know, getting customers to buy more when they buy, meaning increase their average order value, get them to buy more often, maybe increasing ltv. That's. Those are basically the three ways in which you can grow a business. And so the combination of those three are through the MPIs. The MPIs are just a means to measure how to get to the big goal. Does that make sense? Does that resonate with you? And is that something that you have conversations with clients about?

[B]

Yeah, exactly. And it's one of those things that, you know, it's new to everyone. It's still a, it's still a challenge. The industry has been focused on in platform metrics for so long now and even just front end metrics. So people are coming onto NCAC and stuff now, but it's still in education. And that's part of some of the conversations I've had this week with clients that we've been, you know, doing this for, for some time now. But you can see that they still don't fully understand it. They know it's good, but they don't understand fully that that full suite of things are acting on the business. And that's what we're trying to do more. Just make sure that you're concrete. They understand. Exactly. Well, why are we actually making you go to an NCAT target? This is why it's good. And this is why when we scale aggressively, sometimes some of your other metrics are going to come down, but it always comes back to those MPIs. And you know, that's, that's really what we were trying to do and just help them understand because we know it's good, but it's just making sure they know it's good and they can present to their superiors as well why we're doing things the way we're doing it basically.

[A]

And you know, if you are an agency and you're listening to this or you do this for a living and you either do it for your own business. This is a new way of looking at how to market. And we found that, yeah, the in app metrics used to be the real judge and jury, like the source of truth years ago. That is no longer the case because there are a lot of things that now block that from being the source of truth. Which we'll get into here in just a second. So you need a data solution in order to be able to read the tea leaves, to get the right metrics to move the business in the right way. Otherwise, you know, if you're just using Google Analytics or if you're just using Capi, when we'll talk about that here today, that data might not be as pure as it possibly could be. And that's really at the heart of this. Like there's the high goal of the business, there's the MPIs and then once you establish those MPIs, what do you actually do? And the data tells you what to do. So it's almost like those three levels that you sort of have to understand. The purer the data is, the more accurate the data is, the less modeled the data is, the less AI algorithm we don't really know. Like Google Analytics kind of does and like a lot of the third party attribution softwares too, the less your ability is to be able to hit the MPIs and ultimately achieve your goal as a business. So it's sort of that level. And it's amazing to me, Cameron, I, I've had, I think three calls this week with would be prospects for tier 11 where we're going through this. And I'm amazing. There was one yesterday. These guys, like, I love the business that they're in, it's a $7 million business. They don't know how much they can pay to acquire a customer. They have no idea. So like a lot of businesses, this is a new thing because you used to say, well I'm going to hire an agency, I just hire an agency and they'll figure it out. Well no, this is actually a two way street. You really do need to. And I know you've had challenges with this. I know some of the people that are listening today or watching today have had challenges with this. Some clients just don't want to change and sometimes it's really hard, whether it's because of privacy issues, because maybe they don't trust you, maybe they just don't get it quite yet. And this is a shift in mindset more than anything else, as opposed to us just, you know, coming down from the mountain and saying this is the way that it needs to be. We're trying to educate the world that this is actually how you move the business forward. And the example of this week, John, myself and TJ, who's our VP of Sales, will probably come on Tier 11 live at some point in time. Is like, if we just started running traffic to this group without an NCAT call, we would have helped them go out of business faster.

[B]

So common.

[A]

Yeah, it's so common. And that's terrible. Like, you don't want that as an agency. And one to three months they would have been gone. I was talking to John about it just this morning, actually texting me back and forth. Like, if we started without doing this analysis, they'd be gone and probably we might actually bankrupt them if we did what they told us to do. And I think that's a new way of looking at things now. So anyway, coming back to this, it's a.

[B]

But I'll also just quickly add, Ralph, I think you can get very big based on lock. So, like the example you're talking about, you know, 7 million in revenue if you have a good product or you're in like a good period where the market's just hot, you can quite. You can get quite big without knowing these numbers. And I think that's why it's been so common, especially in the big booming years for E commerce, especially the start of COVID Everyone really grew businesses, they didn't have this stuff dialed down. And then they're now either going down the way, like you're saying, going out of business because they're scaling or they're stuck and they can't scale and they don't know why. And it's because they're not looking at these MPIs and seeing. Well, actually maybe the business is looking good. You're just looking at the wrong thing because you've got a problem with retention or repeat customers or something. It's not actually your acquisition that might be perfect.

[A]

Right, right. Yeah. I mean, there was a huge boom in E commerce, obviously, in 2020 and 2021, and a lot of those businesses cease to exist in 2022. So it's now. It's a harder place to be if you've got a great product you can skate by. You're absolutely right. And this client specifically, great, organic, great. You know, Amazon sales, probably spending too much money on the Amazon side, but has never really applied paid traffic in the right way and just wanted a next level of scale, and that's why they came to us. So we're sort of slowing down the whole process, trying to figure it out, getting to a point where like, all right, let's figure out what an NCAC is and then ultimately get you to your goals. So before we get into some of the stuff that you want to talk about, I know there's, there's a point of clarification that we want to make sure that we're clear on and we've gotten some questions on this in previous tier 11 lives. We're getting it a lot on our socials right now, which is we've Talked about Tier 11 data suite. You're obviously super familiar with it. You understand how the whole thing works. One of the biggest questions that we seem to be getting these days, and we were proponents of this as well, which I think is a good thing to do no matter what is conversions, installing conversions, API or CAPI. What is the difference between CAPI and Tier 11 data suite? How do they differ? How are they similar? What's your perception of it? What's your take on it?

[B]

Yeah, so I'm basically going to share screen and talk you through this. So bear with me to make sure.

[A]

I can actually do this correctly of sharing screens.

[B]

Let's share screen.

[A]

Always tell Ch. I say, you know, I love. It's like show and tell on Friday. It's great. Now it's with Cameron. You're still tan, though. You're like naturally tan, I think.

[B]

Well, well, I am in Argentina, so it does help. It's their summer. That's. That's part of it. But yeah, not. I'm not. I'm not perfect beauty tan. I'm just.

[A]

You're. You're pretty tan.

[B]

Tan. Real tan. Yeah. So you should be saying you should be seeing lucid chart, you should be seeing Capi on screen. Is that correct? Or some technical issues. Okay.

[A]

It's beautiful.

[B]

So what I'm going to do is I'm going to talk through conversions, API, Capi, or it's known as. Well first, then I'm going to talk through the data suite and then I'll show you a little thing I've put together, overlaying CAPI onto the basically drawing that you presented the other week for J11 data suite. Now, these graphs aren't obviously made exactly. It's not perfect because it's different sources. So some of the things might seem different. Like I'LL talk you through it and make sure you understand. Try to ignore some certain things in the illustrations because they're not. They're not exactly correct how the sort of relationships work, but we'll work with it anyway. Okay, so Conversions API, the thing that we told everyone to install to enrich their data, basically is a way of getting around app blockers and browser blockers, things that are basically removing your data from coming back to the ad platform, specifically Meta for Conversions API. So what's basically going to happen in the environment of Conversions API is someone's going to click on one of the ads and they're going to have a click ID in their URL from Meta, the FB clid. So they're then going to move to your website. Okay, what was happening before, when iOS 14 came into play, was that click ID was being removed by the browser and Meta was losing any awareness of who that person was. Okay? So they've clicked on an ad and they've basically just gone into no man's land. There's no way now to tie them back to your ad. So what they did is they brought into play Conversions API. And what that would do is you're still losing that tic id, but the server that your website is hosted on is able to look at what the people are doing on the website and via the API, which is this session here, feed that first party data. So names, email addresses from the website back to the ad platforms. And then what Meta would do is they would look at the names they have for people, the contact information they have for people. The email address is the first party data. They would hash the data coming through the API, match it up, and they would try to basically match people that were coming from your API to the people that had clicked on your original ad or viewed through on your original ad. Okay? And that was partially right. It was better than having no data. But you're losing a lot of data because the server has no idea who these people are. It's just relying on the names and email addresses that it's passing back to Meta. And anyone who signs up to an account knows you might have multiple different email addresses, you might have different names that you're using for your actual, you know, your, your account, your credit card, whatever, they're not going to tie up perfectly. So there's a lot of data lost in this situation. Okay, so it's essentially that it's basically passing first party data to the ad platforms. And then Meta does this thing where it tries to match people Up. That's in a nutshell, what conversion API is doing.

[A]

So the question then becomes and where is like just at a base level is first party data by capturing it on your own. Like we used Google Tag Manager when we did this, obviously. But first party data is being captured by your website, so therefore it's yours. So therefore that is the reason why this whole thing works and you're passing it back to the ad platform as a first party data. Maybe you can explain the difference between first party and third party because I think that's where a lot of people get tripped up.

[B]

Okay, yeah. So first party data of course is the data that's coming directly from you, like you said, is the website. Third party data is coming via the Pixel. So it's not your data, it's something sitting on your website that's passing that back to the, the ad platforms essentially. So it's you, you own this data is people actually buying from you, giving you their email address and things. The other version, I guess it's like watching what's happening rather than being the actual, you know, first party data.

[A]

Right. So you're using the Pixel in this case. The Pixel then becomes the third party in this whole thing. And the reason why API that, why CAPI works through the, through the API is because you are the first party data. You, you actually own it. Provided that you have a privacy policy on your page, you can do all this, you stay, you know, above board with all the privacy restrictions that are not only in the United States but internationally. So there is that whole thing when the data comes back. One of the things that we would always sort of check with the EMQ score inside meta, specifically we're talking about meta here, just in this specific example is the EMQ score was our indication that we were getting a better match rate on specific events with Cappy. And we did see an increase in that efficiency. Can you talk to that and what that really means for you on a day to day basis, managing ads inside the platform itself?

[B]

Yeah, well, I mean a better EMQ essentially for us is meaning we're getting better data back in our campaigns. So those campaigns have more data. It's a machine learning platform, they are better at optimizing. So essentially we can get better results because the machine is smarter, it's getting better match rates from the data coming back. So conversions, API, no doubt, if you're just using Pixel, it's a massive step up. And yeah, having it in place was the right thing to do and tell something new came along.

[A]

Right. And the other part to this is that, okay, you're getting better data than what you were getting blinded to. I remember you were a part of this in 2021 when this whole thing hit in summer of 2021. And then all of a sudden it was, I mean it was just a nightmare because it was terrible. It was terrible. Facebook, at that point in time, I believe it was just Facebook. It wasn't Meta yet. My memory serves me correctly. They were caught, this came out of nowhere, they were ill prepared. And Capi came out of that months later, which did restore some of the data inside the platform. But all of a sudden we were completely flying blind. And especially for, I remember, for some of our, I wouldn't even say like higher end, but iPhone users, Apple users tend to be, you know, higher end buyers. I remember one, one account in particular, we lost 60 to 70% of our conversions literally overnight.

[B]

Yeah. Crazy.

[A]

And Facebook didn't have an answer to it. And so Cappy was an outgrowth of that. But there was a, there was a long time, it seemed like forever, but it was three to six months, I think. It took us at least six months to install Cappy in all of our accounts. And it still was a process because it was clunky and so forth. But all during that time and even to this day, Facebook and Meta in particular still isn't getting all the data. Hey, real quick, if you're looking to get your brand in front of growth minded marketers, CMOs, directors of marketing and agency owners, we're opening up our sponsorship spots for Q1 and Q2 of next year. Get in front of a quarter of a million marketers every single month at Perpetual Traffic. All you have to do is head on over to perpetualtraffic.com for the details or check out the link in the show notes to apply. They're still modeling a fair amount of data. Can you speak to that and like what you think as far as a percentage goes, like how accurate you're seeing things inside platform, how much is modeled, how much is actual, how much does Capi really, you know, enhance things? But then there's also sort of this whole other, you know, a segment of users that are just never going to be captured.

[B]

Yeah, I mean in terms of actual percentages, I don't really know what it, what it would be. The reality is these days, and I think other people are the same who are using your 11 data suite is we don't really look too much at the end platform numbers anymore because it is just a lot of nonsense. And we have the data so we can look elsewhere. But model data is a big problem because if you are looking in platform, basically what Meta is doing is they're going, okay, we don't have oversight into what is actually happening on the website. We don't have the connection anymore. So we're just going to try and estimate based on how many people are clicking away from our ad, how many people are we're able to then match again later with our, our hashing from the conversions API, we're going to estimate like what percentage of those people are taking what action. So how many people are adding to car, how many people are purchasing. And it is just way off. You might have some weeks where, especially if you're on a smaller brand, you'll look at it and you'll be like, oh, this looks like it is very accurate. And you'll have other weeks where it's telling you you've had all these sales and you can look at your Shopify dashboard and you're. And you're not getting anything. So it, it seems like it's a complete guessing game and it just doesn't have any credibility even when you're at scale, in my experience. And we can show you later on in this, when we look at the actual Data Suite data versus what you're seeing in Platform for Meta, there's a significant difference. And Data Suite is always going to have lower CPAs, but not because it's, there's like it's a different brand or anything. Just because all that model data is going to make your campaigns look worse than they are. And there's stuff you could be turning off because you don't think it's doing well. But it's just modeled data. It's not real numbers that are actually the performance of that campaign.

[A]

So I think a lot of folks who installed capi, and now we're, you know, those are the folks that, you know. Data Suite is a potential solution here, obviously, which we're going to get to in just a second here. But I think with capi, you might have a false sense of security because what you think you're seeing isn't actually what you're seeing. And then when you compare it to the source of truth, which we did pre Data Suite, we're always like, why are these numbers so far off? Is exactly what you're saying. Even with CAPI installed, you still weren't getting accurate data because there's this large portion. I guess it really depends on how many iOS clickers there are and how many ad blockers and how many, you know, cookie deprecators that are clicking on. The point is, is there is a certain portion that meta and Facebook are just never going to capture no matter what, and they're taking a guess at it. And that guess might be wrong, might be right, or it might be somewhere in between, but you still don't know with 100% certainty.

[B]

Yeah, and that's the big element really. As someone who is doing the media buying. It's like with Capi, your, your data was, was getting better for the platforms to optimize, but you just could not trust anything you were looking at in the platform because, okay, it's good that the actual platform is learning and we're going to get better conversions from that. But if I made human decisions based on something that's incorrect, I then stop that whole process because I might turn off the thing that was bringing all the conversions and generating that data in the first place and then you don't see the effect until a bit later when if you are looking at your MPIs, you'd see a drop and you'd have to go turn back on the thing that you turned off. So it enhances the optimization phase, but it doesn't do anything for the reporting phase in meta.

[A]

That's a really good way of saying it. It does enhance optimization to a certain degree. However, for reporting, it's still highly inaccurate because there is a fair amount of guessing that goes along. All right, so maybe let's Compare and contrast tier 11 data suite here. Not to turn this into a tier 11 data suite pitch, but this is a pretty remarkable system that we figured out over the course of the last couple years to solve this very problem. Because visibility into the data is everything. Like I said before, if you are, if your goal is to go from 6 million to 12 million in revenue, okay, it's a $6 million gap. How are you going to get there? How are. Is it all new customer acquisition? Is it higher? AOVs, higher LTVs? How are you going to do it? Chances are probably a new customer acquisition is a very important part of that and that's the reason why NCAC or new customer acquisition cost is such a vital stat, such a vital goal. Like you as a media buyer, you're looking at that all the time and measuring against it, benchmarking it. But that data, that number has to be as accurate as possible. And if you're relying on in app, it might be right, might not be right, might be somewhere in between, but you don't have a high degree of confidence in that number. How does tier 11 data suite potentially solve that problem? Or at least come close to solving it?

[B]

Okay, cool. So this is obviously our current explanation of Data Suite. What I wanted to say is don't get too hung up, like I said before on the different aspects, the arrows. Because when I tried to show you how capi compares, it might get confusing, but we're just going to look at the data path at the moment. So basically in this, the purple is the path of the data and the pink is just symbolizing the actual user's journey. Okay, so it's not data. That's something that caught me before. Okay, so same situation, people are on the ad platforms, whatever ad platform, because we're talking about conversions API, we will look at Meta today. So let's say someone again clicks on that ad from Meta, there's going to be an intermediate step. Okay, so they leave the ad platform, they get first party cookie added by the app platform, they get the click ID added as before. But what happens is they pass through this thing called the edge, which is hosted on Edge server. This is a content display network. Okay, now what happens here in Tier 11's data suite, this doesn't happen in the other example. This only happens in Tier 11's data suite is they that signal that is on the person leaving is captured. Okay, so it's captured here and it's sent to our data warehouse. So I'm going to come back to that a minute. What then happens is that person continues on to your website that is hosted on the origin server, which is the server hosting their website. Okay, but if we follow the pathway of the data, what is happening? What is happening is that data is sent to our data warehouse, like I said. And then a couple of things happen. One, it can speak to the actual E Commerce platform, so we're getting data from there first party as well. And then the second thing is it's going to send that back. Once it's fingerprinted it matched those people up, it's going to send that back directly to the ad platforms and you have far richer data. So what would happen in another situation after this Edge step is you would then lose the data. So we're not losing any of the data because we're doing this before the browser ad blockers take the signals out of the data. Essentially like happens with the conversion API. So we're getting all the data at this step and it goes into the data warehouse, all gets matched together and then sent back to the platforms directly makes sense.

[A]

The difference is if we take out the edge and you have that sort of that pink arrow that goes to the origin server and then right after that it's then blocked, in essence on the browser itself, that's where the problem happens. And Capi doesn't solve that problem. And that's the reason why you can't really trust 100% that data. And that's why this is a solution that makes a whole lot more sense. And there's a lot of different ways to do this. We've got a video we'll obviously we'll leave for you guys as well. It's now on YouTube that explains this going all the way through. But I think understanding it fundamentally gives people, especially the level of expertise that are on these calls, gives them an understanding of. Okay, this is actually something that's fundamentally different than the solution I have in place right now because of this edge server. And the edge server basically captures that user before they actually enter your store, as we said a few times here on this show, is that we capture the data of your user when they enter the parking lot, as opposed to when they walk through your front door. And that way we can then pump it back to the data warehouse, which is first party data, and then we can do whatever we need to do with it there, provided that we're compliant. And this is 100% compliant solution with all the privacy restrictions in the US as well as internationally.

[B]

Yeah, exactly. And this is where I try to show you what Capi is doing differently. As you just said, Ralph. So Capi would be the green it's coming to, the browser loses the cookies and that that signal's gone. And then your server is saying it back to their platforms, but it has no idea who those people are at this point. It's just people who've bought from your website. And Meta has to do the job of matching those people up versus you in this situation. Having the data, we know who they are because we have the tags coming from the platforms. We just have to wait for those people to buy and then we can send that back to the platform saying, hey, we've already matched the people up. These are the people that clicked on your ad because we know you have the tag. There you go.

[A]

Yeah, yeah, makes sense. And I love the green arrows here, by the way. So Cameron did all this. You did all this on your own. I didn't know you had like these types of skills. A tremendous. No, I mean, that really is in essence the difference between the two, I guess maybe we can show. I mean, this is obviously. This makes sense. We're going to be taking some questions here in just a little bit. There's obviously a lot of Google Ads questions which we may have to couch those for when John gets back. Yeah, that might just slip off. But anyway, I know John Moran's dog is chomping at the bit and, you know, John Moran's forehead, I think is a new one. John Moran's liver, kidney. Anyway, the point is, is that this is a fundamentally different approach. And the reason why we put this together is because we have. We wrote the integration between the Edge, which is by a company called Blood Out. You know, they. They use Cloudflare. Look it up. CDN. It's the largest CDN in the world. There's 7,000 edge servers that they utilize that put their particular script on there. And that platform. Plus our data warehouse integrated back into Wicked Reports, which is our interface, which is where you read the data, which we're going to hopefully see right here. Sort of compare and contrast. That's where the rubber meets the road. Because the integration between those three things makes everything different. But the key is capturing the data on the edge before it gets blocked by the browser. And that's the key difference between capi. Would you agree?

[B]

Yeah, exactly.

[A]

All right, so maybe we can go into like a compare and contrast. Do you have an example of maybe showing, you know, the interface itself in a particular account and maybe how you would sort of look at the data inside? You know, how you're viewing things inside Meta versus looking inside the interface, inside Wicked reports? Is that safe to assume? I'm. I'm.

[B]

Yeah.

[A]

Let me look at the ad platforms to a certain degree. If you need to share your screen, that's cool too, because it's not like you don't look inside the ad platform. I just want to make that clear. We still look.

[B]

Yeah. No, I'm in the. I'm in that platform all day, every day, basically. I live in that thing. So when they. When they introduce new things that cause bugs, my. My life is stressed straight away. There's no delay.

[A]

Oh, my God. That never happens. Come on. They never change anything without telling.

[B]

Meta would never do that.

[A]

No. Not in a million years. So this camera gets his screen up here. So we're not discounting looking at the platform. I know we've talked about this before, numerous times.

[B]

Yeah.

[A]

In app ROAS is not to be trusted. However, we still use it. We've got a lot of. We've got A lot of content out there on the Internet, the interwebs, the Cameron that says ROAS sucks and it does suck as a source of truth. But we still look at it. You still look at it as one of the metrics that you look at then that's obviously in Platform, but the real source of truth now when you have Data Suite, you used to actually go into probably Shopify or you know, the real source of truth in the CRM. Now you can see the same thing inside the interface, inside Wicked reports, inside Data Suite. So, all right, so here we are, we're looking at the inside of a Meta AD account. Take us through sort of how you would compare and contrast and utilize this data and then cross reference it with what you see inside Data Suite.

[B]

Yeah, sure. So I'll just jump through and show you a couple of things and then I'll give you an idea of how as a media buyer this is tangibly helped me have massive like wins basically. So if we look at Meta right now, I just want to speak firstly to the CPA that we have and how I was speaking about earlier, where you're always going to see it lower in Data Suite because you have more data. You're getting those purchases that Meta doesn't know they're actually in existence. Okay, so that's what you see here. You can see these campaigns there.

[A]

And we're looking at January of 2025.

[B]

This is January 2025.

[A]

We're recording this on Valentine's Day, by the way. By the way, Happy Valentine's Day.

[B]

So yeah, you can see this. We'll just look at these first two to show it. So you've got 801 here and 179 use them as the identifiers for these campaigns names. Perfect. So we have $95 cost per purchase showing in the app platform, $64 cost per purchase shown here. Okay, so we, we take away NCAC and all these things. Meta can't show you that unless you have Data Suite, which is another topic. But anyway, Meta can't show you that as standard. So we have the blended CPA of new customers and return customers. If I go into tier 11 data suite via Wicked Reports, really here you can see if I look at all CAC, which is the same metric being compared, we have $77, 56. So you've gone 95, 64, 77, 56. So this scenario, there's nothing I can show you where it's like, oh, I would have turned off these campaigns or anything because obviously I'M not using it like this. I have the tools. But there could definitely be situations where you know, you're $5 over the target, you're $10 over the target and for your business.

[A]

Hey, real quick. If you're looking to get your brand in front of growth minded marketers, CMOs, directors of marketing and agency owners, we're opening up our sponsorship spots for Q1 and Q2 of next year. Get in front of a quarter of a million marketers every single month at Perpetual Traffic. All you have to do is head on over to perpetualtraffic.com for the details or check out the link in the show notes to apply.

[B]

That is too much of the target and you have to cut something. But the reality is it's not over target if you were looking in a place that had all the data. Okay. And I think a lot of people can get held back by things like this. However, as I mentioned, we have the luxury of having other metrics that don't exist in Ads Manager. So let me.

[A]

Before you go into the other metrics, so what you just showed is a perfect example. Same time frame, same look back period. We're looking at January of 2024 here and we are Valentine's Day. Right. Or two weeks after that. The point is, is that the end the all cac, the acac, which is the entire cost of acquiring a customer is about 20%. There's 20 or 25% down difference between what you're looking at inside Meta and what you're actually seeing inside the interface. Wicked reports and data suite, which is not insignificant.

[B]

Yeah, so that's not live. That's like you said, it's two weeks later. It's had time to bring all that data back. It should be as rich as it's ever going to get. And yeah, it's 20% difference. Yeah.

[A]

Right. So like the modeling is already taking place. They, you know, they've filled the gaps as much as possible. We're not looking. It would be an unfair comparison if we actually looked back from, you know, the 15th of January to today because the data would still be, it would be more of a difference. You're actually giving it a two week grace period to give Meta more of a chance to backfill, but now it's two weeks later. Like these are decisions you have to be making. You're spending hundreds of thousands of dollars. Like there is a lot of money on the line here and you need to be able to make accurate decisions based upon true data as opposed to modeled data or Data that you're not confident in.

[B]

Yeah, exactly. So to add to that then what we are making those decisions on really is not this all CAC number because we're focused on new customer acquisition as you and John have, you know, repeatedly told everyone about. So people have been watching for a long time, should have that ingrained in them now. But we are practicing what we preach. Like this is what we do on a daily basis in the actual accounts. Okay, so I am looking at this North Star metric here of new customer cost to or new customer acquisition cost of acquiring new customer. It just doesn't exist in as manager. So if I wanted to get this for as manager, I'd have to go into Shopify, I'd have to download a report of new customers. This is what you have to do. And I'd work out, okay, what, what have we spent on this certain campaign? How many people have bought that particular product? And make a loose calculation of, okay, they're probably buying the product we're showing from ads. This is maybe what my NCAC is, but it's not very accurate. This tells me every single campaign ad set and ad, what is the actual new customer acquisition cost for that asset? So it's, it's fantastic. It's really, really helpful when you're trying to determine how to optimize the campaign and judge the performance week to week of your actual fluctuations and seasonality. The stuff goes out of stock, all the things like that.

[A]

That's a game changer right there because that's accurate. Like when before, okay, you've got the big goal, you've got your MPIs, right. You've got your, like you, your business metrics. Obviously you need to understand to determine what your NCAC is. There's whole, that whole thing that we talked about. But when you get down to all right, I need to acquire more customers at a cost that makes sense for this particular, particular client. And I believe the ceiling on the NCAC here is, what is it, $100 in that range as far as NCAT goes? Yeah, it's right around there. So you're below it. But you need to know accurately what am I acquiring a new customer for? And that's the difference between Data suite and everything else that's out there because it is able to determine who is new and who is returning. We measured this on another tier 11 live. It's almost 99% accurate, which is crazy because of what you described in the first 20 minutes of the show. We're capturing the data on the edge before the data gets blocked and then capturing as first party data, pumping it back into the ad platform, which is in this case, we're still pumping it back in. It's not going to be 100% accurate. However, when you view it inside the interface, it's nearly 100% accurate. We're never going to say 100%. Let's say it's 99% or 95%. John continues to say it's 100%. But anyway, yeah, cover yourself, cover yourself. Nothing's ever 100%. That's why, you know, soap is 99.9. What is 44 and 100 is pure? Anyway, we'll go out the ivory Soap Road here, 99%. So. But that's a super important thing. So you're making these decisions on real data is my point here.

[B]

Yeah, exactly. And this is one thing I want to show you specifically, Ralph. So we have tons of metrics in this dashboard that don't exist in Ads Manager. But one of the things you mentioned there was the new customers, new visitors. Okay. And here's an example of me actually using this where in prior working you just, you wouldn't have this information and you might make decisions that are incorrect or if they're not incorrect, they just hold you back from scaling. Okay, so this ties back into what John and I were discussing last week with time lag. And you can work with time lag when you have this because you have additional information. So this is basically a week I need to just look, what was the week it. This was December, so 8th. Or is it August? Yeah, I think this is August. I'm getting confused by the American dates. I think this is 12th August to the 18th of August.

[A]

Yeah, August. Yep.

[B]

Yeah. Okay. Anyway, you can see in this week we're looking high level now at all the platforms because we, you know, we're doing stuff on Meta in this account mainly, but we want to see how it affects Phil Funnel and you're going to see this played out. Okay, so there was a 17% increase in spend because we wanted to scale. Right. So when we do that, the NCAC here, you can see it's come up 30% over a hundred to $104. We're above our target. Okay. So previously what people would do, they look at that and go, oh no, we're above the target. That's been a full week. Let's scale back that 20 we just did on Meta. However, because I have this information, I can look at this metric here that is 99% accurate. Or 100% accurate if you're John. And I can say, well, we've got 26% new visits to the website for that 17% increase in cost. So even though the NCAC has come up with this time lag thing we were talking about last week, I know the time lag in this business is two weeks. I just want to wait another week to see what happens once people move down the funnel and convert on Google with that extra time that they need. Because Google's telling me that's how long it's going to take. Okay. So I know from this metric that, well, I'm getting the visits. Meta has done its job. It's bringing me the people right now. I just want to wait a bit longer and see how the funnel performs because I know how the funnel works. Okay. So if I look around, sorry, my camera is in the way and I move this a week forward.

[A]

So just for those of you who might be listening here, what we're doing is we're comparing back in August when you scaled up a meta campaign by about 16 or 17%.

[B]

Yeah.

[A]

In that week you saw NCAC starting to rise. But you knew because it takes about two weeks. And this is, was last week's show, which was awesome, by the way. Last week's show showed us that the importance of time lag. And time lag is absolutely essential. But you know, in this particular case with this customer, it takes about 14 days or so for a client to. Or a new customer for them from first impression or first click to purchase. Is that what you're doing? Are you using first impression? You're using first click. How do you measure first impression?

[B]

This is a first impression.

[A]

First impression on Google. Okay, makes sense. Perfect.

[B]

Yeah. So hit that as the next week and NCAC is now down 10%. New visits are stable because we have, obviously we're not increasing new visits, we're not increased again. And everything else is looking green because it's just a funnel. So that's like a perfect example of how I use this in, in reality. And yeah, massive, massive help.

[A]

That is. That's fantastic. So it's a combination of solid data. Also understanding the client journey. Well, the journey for the customer, customer's journey in this particular case. And every single, you know, time lag is going to be different for every single, every single customer. You just happen to know, working with them and looking at the data and for people who don't know that I know John uses Google in order to do it. How did you do it pre and I think that was sort of a revelation because sometimes it appears, sometimes it doesn't. You have to refresh the screen inside the Google Ads platform. Like, how did you figure out it was 14 days without that? Or what's the best way to figure out time lag?

[B]

Well, we had the luxury of John a long time ago, told us so before we didn't, we didn't do it. We just kind of knew, like some clients would have information, they'd know how long their funnel was and we could kind of work with that. But a lot of people, you just didn't know. It was just a case of, okay, we've gone down. And you develop practices like crutches, really. So I used to just hold a lot of people. I'm very against it on the meta side. They'll scale up every three days, scale back every few days, that kind of thing. I got into the habit of just making performance decisions on a weekly basis. So I always do things on a Monday. I would wait a week no matter what, and then I might hold a week and then pull back. So it's just really the lock rather than actual science. But now we have the science. We can look at time lag in Google and we know exactly how long the conversion window is to work, basically.

[A]

That's great. Well, this has been amazing. Love the theory. Like, this is how it works. This is how you actually use it in practice. Compare and contrast. And obviously this is a tool that's now being deployed that's making what you do every single day a hell of a lot more effective. And also, and I know for a fact this client is ecstatic with the results, that without this type of data, I don't know as if we would have been able to get it because we would have been guessing most of the time.

[B]

Yeah, for sure. And one more thing. Just because I have other accounts that have dashboards like this and they show you visits, what you're saying about the accuracy is a big factor here as well, because there's certain tools that I use where they have this. But you don't know if the new visits are actually accurate because they don't have that piece of the edge tag capturing those people, essentially.

[A]

Yeah. And the edge tag is the key. So you need the edge tag in order to install it. You need the interface to be able to read it. The only place you can get it is your 11 data suite. So anyway, enough of the sales pitch. But that is the sales pitch, because that's the facts. We hope you've enjoyed this episode. Don't forget to leave a comment and review. Be sure to subscribe and check our channel at perpetualtraffic. Com. And until next show, see ya. You've been listening to Perpetual Traffic.