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

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.

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]

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]

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.

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.

Resources Mentioned

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

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.