TL;DR
Your Facebook Ads say 50 conversions. Google Analytics says 30. Your CRM says 20. None of them are lying. They’re just measuring success using different rules. This guide explains why those discrepancies happen, which numbers to trust for different decisions, and how to use “Blended ROAS” to cut through the noise and make confident budget decisions. The only number that’s 100% accurate? The money in your bank account.
Introduction – The Wedding Analogy
Imagine you hire three photographers to shoot the same wedding:
- Photographer A (PPC Platforms): Uses a high-power zoom lens focused intensely on specific smiling faces (the guests who saw the couple’s “Save the Date” ad)
- Photographer B (Last Click): Only takes pictures of the bride and groom kissing at the altar (the final moment of commitment)
- Photographer C (GA4): Uses a wide-angle lens to capture the crowd, the venue, and the entire flow of the event (the full journey)
At the end of the day, all three were at the same wedding. But when you flip through their photo albums, they look completely different. One has close-ups of individual moments. Another only shows the ceremony. The third captures the big picture.
The Problem (And It’s Not What You Think)
Here’s the reality: It’s completely normal to see data discrepancies of 20% to 50% between platforms (sometimes even more for social media campaigns). This doesn’t mean something is broken. It doesn’t mean you’re being overcharged. It means different tools are measuring success using different rules.
Clients ask us all the time: “Which number is right?”
The answer? None of them are lying. They’re just telling different parts of the story.
This guide will help you translate the data so you can make confident decisions about where to invest your marketing dollars. Because at the end of the day, understanding why the numbers differ is more valuable than obsessing over which platform reports the “correct” number.
Defining the Players: Who Is Reporting What?
Before we can decode the discrepancies, we need to understand the “personality” and methodology of each data source. Think of this as learning the rules of the game before placing your bets.
PPC Data (The Platform Data)
What it is: The data reported directly inside platforms like Facebook/Meta Ads, Google Ads, or LinkedIn Campaign Manager.
How it thinks: These platforms are selfish (in a business way). They want to prove their value so you keep spending money with them. That’s not inherently bad; it just means they’re optimized to show you every possible way they contributed to a sale.
The Methodology:
- Meta (Facebook/Instagram): Defaults to a 7-day click + 1-day view attribution window. Translation: If someone sees your ad (doesn’t even click) and buys within 24 hours, Facebook claims credit. If they click your ad and buy within 7 days, Facebook also claims it.
- Google Ads: Often defaults to a 30-day click window. If someone clicked your ad a month ago and finally converted today, Google Ads says, “That was me!”
According to Meta’s attribution window settings, advertisers can customize these windows, but most businesses stick with the defaults (which favor the platform’s reporting).
Real-World Example:
You’re scrolling Instagram in bed at 11 PM. You see a Nike ad. You don’t click; you’re just browsing.
Two days later, you’re on your laptop during lunch. You Google “Nike running shoes,” go to Nike.com, and buy.
Instagram says: “I did that!” (View-through conversion)
Your perception: “I just Googled Nike…”
The disconnect? Instagram counts the ad impression as the catalyst. And honestly, it might be right. You probably wouldn’t have searched for Nike if you hadn’t seen that ad.
GA4 (The Neutral Judge)
What it is: Google Analytics 4 is your website’s traffic tracker. Unlike ad platforms, it tracks all sources: organic search, email, direct visits, paid ads, social media, etc.
How it thinks: GA4 tries to be the “source of truth” for onsite behavior. It’s less interested in claiming credit for individual ads and more interested in understanding the full customer journey.
The Methodology:
- Data-Driven Attribution: GA4 uses machine learning to assign fractional credit to different touchpoints. Instead of saying “This ad gets 100% credit,” it might say, “This ad deserves 40%, that blog post deserves 30%, and that email deserves 30%.”
- 2025 Context: Because of privacy restrictions (hello, iOS 14+ and cookie deprecation), GA4 now uses “Modeled Conversions” to fill in gaps when it can’t track users directly. This makes it more accurate than old-school Google Analytics, but it’s generally stricter than PPC platforms because it requires a site visit to track anything reliably.
According to Google’s official documentation on GA4 attribution models, data-driven attribution looks at thousands of conversion paths to identify which touchpoints actually drive results.
Real-World Example:
Back to the Nike scenario. GA4 didn’t see you scroll past that Instagram ad in bed. It has no idea that ad existed. All GA4 saw was:
- You typed “Nike.com” directly into your browser (or Googled “Nike”)
- You landed on the site
- You bought shoes
GA4 says: “This was a Direct or Organic Search conversion.”
Instagram says: “This was my conversion.”
Both are telling the truth from their perspective. GA4 is reporting what it can see. Instagram is reporting what it influenced.
For a deeper dive into how these attribution models differ in practice, check out our post on data-driven vs. last-click attribution.
Last-Click Attribution (The Closer)
What it is: The traditional model you’ll often find in CRMs (HubSpot, Salesforce) or eCommerce backends (Shopify, WooCommerce).
How it thinks: “The only thing that matters is who crossed the finish line.”
The Methodology:
100% of the credit goes to the very last interaction before the purchase. Everything else (the awareness ads, the blog posts, the email nurtures) gets zero credit. It’s the “What have you done for me lately?” model.
This approach is valuable for understanding which final touchpoint triggers buying behavior, but it completely ignores the “assists.”
Real-World Example:
A potential customer’s journey:
- Monday: Clicks a Google Ad → Reads your blog → Leaves
- Wednesday: Clicks an Instagram ad → Browses products → Leaves
- Friday: Opens your email newsletter → Clicks “Shop Now” → Buys
Last-Click Attribution says: Email gets 100% credit.
Google Ads and Instagram: Zero credit.
But here’s the thing: Without those first two touchpoints, that person probably wouldn’t have been on your email list or ready to buy. Last-click tells you what closed the deal, but not what created the opportunity.
Quick Reference: Platform Comparison Table
| Platform | What It Measures | Attribution Window | Best Used For |
| Meta Ads | Ad clicks + impressions (view-throughs) | 7-day click / 1-day view | Creative testing & ad optimization |
| Google Ads | Paid search & display clicks | 30-day click (default) | Direct response & keyword performance |
| GA4 | Full website journey across all sources | Data-driven (up to 90 days) | Budget allocation & channel strategy |
| Last-Click (CRM) | Final touchpoint before conversion | Session-based | Sales closing tactics & offer testing |
Why Do the Number Discrepancies Exist?
Now that you know who is reporting what, let’s talk about why they disagree. Spoiler: It’s not a bug. It’s a feature.
Attribution Windows (Time Travel)
The Concept: Each platform has a different “memory span.”
- Meta: Looks back 7 days (clicks) or 1 day (views) by default
- Google Ads: Looks back 30 days for clicks
- GA4: Uses data-driven lookback up to 90 days, but weights recent interactions more heavily
- Last-Click: Only cares about the immediate session
The Impact:
Let’s say someone clicked your Facebook ad on January 1st but didn’t buy. Then on January 20th, they Googled your brand name and made a purchase.
- Facebook: “That’s mine! It was within my 30-day window!” (if you changed settings)
- Google Ads: “That’s mine! They searched my keyword!”
- GA4: “I see both touchpoints. I’ll give fractional credit.”
- Last-Click: “That’s Organic Search. Period.”
Result: You’ll often see more conversions in ad platforms than in Google Analytics because ad platforms are counting sales that started weeks ago, while GA4 is focused on the recent, measurable journey.
View-Through vs. Click-Through
The Concept: Social media ads (especially Facebook, Instagram, TikTok) generate demand through impressions, not just clicks.
The Impact:
Meta’s ad platform uses the Meta Pixel and Conversions API to track people who saw your ad but didn’t click. If they later visit your site and convert (even through another channel), Meta counts it as a view-through conversion.
GA4, on the other hand, only tracks people who actually visit your website. It has no visibility into ad impressions unless someone clicks through.
This creates a permanent “gap” where social platforms always report higher numbers than Google Analytics (especially for top-of-funnel brand awareness campaigns).
Pro Tip: This is why turning off your “non-converting” Facebook ads can backfire. Those ads might be generating view-throughs that GA4 is crediting to “Direct” or “Organic” traffic. Kill the ads, and you might see your “organic” traffic mysteriously drop.
The Privacy Gap (iOS 14 & Cookie Deprecation)
The Concept: Privacy updates (like Apple’s App Tracking Transparency and Google’s phase-out of third-party cookies) have made it harder for platforms to share data with each other.
The Modern Solution:
Platforms now use tools like Conversions API (CAPI) and server-side tracking to bridge the gap by sending conversion data directly from your server to the ad platform, bypassing browser restrictions. But even this isn’t perfect.
The Impact:
Facebook might know a conversion happened (because your server told it via CAPI), but it can’t always “tell” GA4 about where that user came from due to privacy blocks. GA4 sees the conversion but attributes it to “Direct” because it has no referral data.
According to Adobe’s marketing attribution fundamentals, modern attribution is increasingly reliant on probabilistic modeling rather than deterministic tracking, which means estimates are baked into the numbers.
For more context on GA4’s technical capabilities, Search Engine Land published a comprehensive guide to GA4 attribution that dives deep into how these privacy-first models work.
Real-World Scenarios: How to Interpret the Reports
Let’s get practical. Here are the exact situations you’re probably seeing in your reports (and what they actually mean).
📊 Scenario 1: “Facebook says we have 50 sales, but GA4 only shows 30.”
The Diagnosis: View-through conversions + cross-device behavior.
How to Interpret:
Those 20 “missing” sales likely saw your ad on mobile (while scrolling Instagram on the couch), got interested, but then Googled your brand name on a desktop or laptop later to complete the purchase.
- Facebook’s perspective: “I planted the seed. I deserve credit.”
- GA4’s perspective: “I only saw them arrive via Google search.”
Both are technically correct. Facebook did create awareness. GA4 did see the final journey.
What This Means for You:
If your Facebook Ads are driving brand awareness (not just direct clicks), you should expect GA4 to show fewer conversions than Facebook reports. This is especially true if you’re running video ads, carousel ads, or other high-engagement creative formats.
💡 Pro Tip: Look at branded search volume in Google Search Console during your ad campaigns. If branded searches spike when ads are running, your social ads are working (even if GA4 doesn’t give them credit).
Action: Don’t turn off those ads! If you do, those 20 “organic” searches will likely disappear, and you’ll wonder why your overall revenue dropped.
📊 Scenario 2: “Direct Traffic is our highest source of revenue.”
The Diagnosis: The Last-Click Trap.
How to Interpret:
Very few people actually type your full URL directly into their browser unless they already know you. So where did they learn about you in the first place?
“Direct” traffic is usually:
- Returning customers who were originally acquired through ads, SEO, or referrals
- Mobile app traffic that doesn’t pass referral data
- Email clicks that stripped tracking parameters
- HTTPS → HTTP redirects (rare but possible)
What This Means for You:
Your CRM might be giving 100% credit to “Direct,” but that’s ignoring the Google Ad they clicked 3 weeks ago, the blog post they read, and the email that reminded them to come back.
Action: In GA4, switch your reporting view from “Traffic Acquisition” (which shows the session source) to “User Acquisition” (which shows the first touch source). You’ll likely see “Direct” shrink dramatically, while “Paid Search” and “Organic Social” grow.
If you need help setting up GA4 properly to avoid these misattributions, our team offers professional Google Analytics setup and interpretation to ensure your data tells the real story.
Which Data Source Should You Trust?
Here’s the thing: All of them. But you need to use the right tool for the right job.
✅ Trust PPC Data When… Optimizing Creatives
Goal: A/B testing and day-to-day ad management.
Why: If you want to know whether “Ad A” (the red button) performs better than “Ad B” (the blue button), trust the platform data. Facebook, Google, and LinkedIn have the most granular detail about individual ad performance: creative quality, audience engagement, cost per click, etc.
Use Case Example: You’re running two versions of a Facebook ad. One has a 2.5% click-through rate; the other has 1.1%. The platform data tells you immediately which creative resonates more.
If you’re looking for help managing and optimizing your campaigns, check out our strategic PPC management services.
✅ Trust GA4 Data When… Allocating Budget
Goal: Macro-level channel strategy and budget decisions.
Why: When deciding how to split your marketing budget between SEO, email, paid ads, and content, use GA4. It shows you how channels work together and models the “invisible” touchpoints that other tools miss.
GA4’s data-driven attribution is specifically designed to show you which channels assist conversions, not just which ones get the final click.
Use Case Example: You’re deciding whether to invest more in Google Ads or Facebook Ads. GA4 shows you that Facebook drives most first clicks, while Google drives most last clicks. The answer? You need both. They serve different parts of the funnel.
MarTech’s detailed breakdown of attribution models in GA4 provides excellent context for how to interpret these multi-touch journeys.
✅ Trust Last-Click When… Tracking Immediate ROI
Goal: Tactical closing and short-term offer testing.
Why: If you need to know exactly which email subject line, landing page headline, or discount code triggered someone to pull out their credit card right now, last-click is your metric.
Use Case Example: You send two promotional emails. One offers 10% off, the other offers free shipping. Last-click data shows you which offer converted better in that moment.
Our conversion rate optimization expertise helps you test and refine these closing tactics to maximize immediate conversions.
🌟 The “North Star” Approach: Ecosystem ROAS (Blended Data)
Here’s the method we recommend using to avoid getting lost in attribution debates: Blended ROAS (Return on Ad Spend).
Instead of arguing about which platform “owns” a conversion, we focus on the only number that’s 100% real: the money in your bank account.
The Methodology (The Spreadsheet Strategy):
Step 1: Track Individual Spend
Log your ad spend for Google, Facebook, LinkedIn, etc., separately. This lets you monitor efficiency at the platform level.
Step 2: Calculate Total Investment
Add up all marketing spend for the period (ads + tools + agencies + content creation).
Step 3: Track Total Revenue
Use your bank statements, Shopify backend, or accounting software. Ignore the pixels. Just look at actual dollars earned.
Step 4: Calculate Ecosystem ROAS
Formula: Total Revenue ÷ Total Marketing Investment
Example:
- Total marketing spend: $10,000
- Total revenue: $50,000
- Ecosystem ROAS: 5:1 (For every $1 spent, you made $5)
Why This Is the Winner:
✅ Prevents analysis paralysis: You’re not arguing about whether Facebook or GA4 is “right”
✅ Protects assisting channels: Awareness ads (like Facebook video) won’t get cut just because they don’t get last-click credit
✅ Forces holistic thinking: You evaluate marketing as a system, not as isolated campaigns
Visual Tip: Think of Ecosystem ROAS as the CEO’s dashboard, while individual platform data is for the Marketing Manager’s daily optimization.
If you’re struggling to build a cohesive measurement framework, our comprehensive marketing strategy services can help you establish your “North Star” metrics.
Conclusion
The only number that’s 100% accurate is the money in your bank account.
Use these attribution tools as compasses to point you toward revenue, not as strict accounting ledgers. Focus on trends, test intelligently, and remember that a 20-50% discrepancy between platforms isn’t a crisis. It’s a sign that your marketing is working across multiple touchpoints.
Still Feeling Lost in the Numbers?
You’re not alone. Attribution is one of the most confusing (and most important) parts of modern marketing.
Let Enleaf handle the data triangulation so you can focus on what you do best: running your business. Our team will help you build a custom measurement framework that cuts through the noise and shows you exactly where to invest for maximum growth.
👉 Schedule your free consultation today and let’s turn your data chaos into clarity.
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