GA4’s data-driven attribution requires 400 conversions over 28 days to even activate—most WooCommerce stores don’t qualify. If you’re below that threshold, you’re silently using last-click attribution. And even if you do qualify? You still can’t see how Google assigns credit. You’re making budget decisions based on an algorithm you cannot audit, built by a company that profits from your ad spend.
Here’s what you’re actually dealing with—and how to take control of your attribution data.
The Black Box Problem: What GA4 Won’t Tell You
Data-driven attribution sounds impressive. Machine learning. Algorithmic credit assignment. Google’s sophisticated modeling applied to your customer journeys.
But here’s what Google doesn’t prominently advertise: the algorithm is proprietary, and Google does not reveal how credit is assigned to your marketing channels (Arcalea, 2025). You can’t see the model. You can’t audit the logic. You can’t verify whether the credit distribution makes sense for your business.
Think about what this means. You’re deciding to shift $10,000 from Facebook to Google Ads because GA4’s attribution says Google deserves more credit. But you can’t actually verify that claim. You’re trusting an opaque algorithm from a company that directly profits when you spend more on Google Ads.
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The Threshold Trap: Most Stores Don’t Even Get DDA
Before worrying about the black box, there’s a more fundamental problem: GA4 requires a minimum of 400 conversions over 28 days for DDA to activate (Google Analytics Help, 2025).
Do the math. That’s roughly 14 conversions per day, every day, for a month. For a WooCommerce store doing $50-100 average order value, you’d need consistent daily revenue of $700-1,400 just to qualify. Many small and medium stores don’t hit this—especially outside peak seasons.
When you’re below the threshold, GA4 silently falls back to last-click attribution (Google Analytics, 2025). No warning. No notification. Your reports just quietly switch to a different model. You might think you’re getting sophisticated algorithmic attribution when you’re actually seeing last-touch only.
This creates a bizarre situation: your attribution model changes based on your conversion volume, not your choice. Good month? You get DDA. Slow month? Back to last-click. And the transition happens invisibly.
The Trust Problem: Who Benefits from This Opacity?
Let’s ask an uncomfortable question: why is the algorithm secret?
Google controls the attribution model. Google profits from Google Ads spend. Industry analysis suggests DDA may favor Google touchpoints—and without transparency, you cannot verify whether this is happening (Industry analysis, 2025).
This isn’t conspiracy thinking. It’s basic conflict of interest awareness. When the company measuring channel effectiveness also sells one of those channels, the measurement deserves scrutiny. But GA4’s DDA is designed to prevent exactly that scrutiny.
Marketers cannot audit or verify DDA credit assignments (Napkyn, 2025). You can see the outputs—channel X got 30% credit, channel Y got 70%—but you cannot examine the inputs, weights, or logic that produced those numbers.
What You Actually Need: Auditable Attribution
The solution isn’t abandoning data-driven attribution. The solution is owning your attribution data and building models you can verify.
When you stream raw event data to BigQuery, you get something GA4 cannot provide: complete transparency. Every touchpoint recorded. Every timestamp preserved. Every user journey available for analysis.
With your data in BigQuery, you can build custom attribution models with SQL. Want time-decay that matches your actual sales cycle? Write it. Want position-based that weights first and last touch according to your business model? Define it. Want to exclude branded search from attribution entirely? Your call.
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The difference: every credit assignment is auditable. You can trace exactly why a conversion received the attribution it did. You can modify the logic when your business changes. You can prove to your CFO that your marketing spend decisions are based on verifiable math, not a black box algorithm.
How to Build Your Own Attribution Model
Here’s the practical path from black box to transparency:
Step 1: Capture complete journey data. GA4’s data is sampled and limited. You need every touchpoint, every event, every timestamp. Server-side tracking to BigQuery gives you the complete picture.
Step 2: Define your attribution logic. What model fits your business? Consider your sales cycle length, the role of different channels, and which touchpoints actually influence decisions versus which are just present.
Step 3: Implement in SQL. BigQuery lets you write attribution logic that matches your exact requirements. Linear, time-decay, position-based, or custom weighted—you define it, you audit it, you own it.
Step 4: Compare and validate. Run your model alongside GA4’s DDA. Where do they diverge? What does your model reveal that Google’s hides? The gaps often expose exactly where DDA’s opacity matters most.
From WordPress to Transparent Attribution
For WooCommerce stores, getting raw event data to BigQuery doesn’t require a data engineering team. Transmute Engine™ is a first-party Node.js server that runs on your subdomain—streaming purchase events, add-to-carts, and complete customer journeys directly to BigQuery without touching GA4’s limitations.
The inPIPE WordPress plugin captures events from WooCommerce hooks, batches them via API, and routes to your Transmute Engine server. From there, data flows simultaneously to GA4 (if you still want it), Facebook CAPI, Google Ads, and BigQuery—where you build attribution models on your terms.
No 400-conversion threshold. No silent fallback to last-click. No algorithm you can’t see. Just your data, your logic, your attribution.
Key Takeaways
- GA4’s DDA requires 400 conversions in 28 days—below this, you’re silently using last-click attribution without notification
- The DDA algorithm is proprietary—Google does not reveal how credit is assigned, and you cannot audit the logic
- Conflict of interest exists—Google controls attribution for channels including Google Ads, which Google also sells
- BigQuery provides transparency—stream raw events and build custom attribution models with auditable SQL
- Server-side tracking captures complete journeys—bypassing the sampling and limitations of client-side GA4
Data-driven attribution (DDA) is GA4’s default model that uses machine learning to assign conversion credit across touchpoints. Unlike rules-based models (first-click, last-click), DDA uses Google’s proprietary algorithm—which means you cannot see or verify how credit is assigned to your marketing channels.
GA4 requires a minimum of 400 conversions over 28 days to activate DDA. Most WooCommerce stores don’t hit this threshold. When you’re below it, GA4 silently falls back to last-click attribution without notifying you—meaning your attribution model changes based on volume, not your choice.
No. Google does not disclose the DDA algorithm. You cannot audit how credit is distributed, verify the logic, or understand why one channel received more credit than another. This is a fundamental trust problem when making budget decisions based on attribution data.
Industry analysts have raised concerns that DDA may favor Google touchpoints since Google controls the algorithm and profits from Google Ads spend. Without transparency into the model, you cannot verify whether the attribution is neutral or systematically biased.
Stream your raw event data to BigQuery and build custom attribution models with SQL. This gives you complete control—define any logic you want, audit every credit assignment, and verify your attribution matches your business reality. Your model, your rules.
Ready to own your attribution data? Learn how Transmute Engine streams complete customer journeys to BigQuery—no black boxes, no thresholds, no algorithms you can’t see.
