GA4 Pipeline -Episode 4: Interpret | Why GA4 Doesn’t Explain Behavior
- Arif Khan
- Jan 6
- 2 min read
Updated: Jan 8
--author Arif Khan | founder zinzu.io
By the time data reaches this stage, it has already been:
Defined, Sent, Collected & Processed.
What remains is interpretation.
This is where most users interact with GA4 and where its design tradeoffs become visible.
GA4 interpretation is aggregate-first
GA4 is designed to answer questions like:
How many users?
How often?
How much?
It does this by working primarily with aggregates.
What gets lost early in interpretation:
Story across events
Rich behavioral context
Long, irregular user journeys
Once data is summarized into aggregates, these details are no longer visible in standard reports.
Filters are shallow and rigid
GA4 filtering is mostly UI-driven, supports limited conditions, and breaks down for behavior-level questions.
Behavior-level questions are difficult to express, such as:
What behavior results in coupon upselling
What actions lead to coupon usage
What sequences result in errors
How different paths lead to conversions
How behavior differs by acquisition source (Google vs Facebook vs other sources)
In essence, extracting stories from data using GA4 UI is not easy.
Conversions flatten context
In GA4, a conversion is simply: an event you label as important
By default, a conversion captures that it happened, not:
What led up to it
What happened after
How different users reached it
Complex behavior is reduced to a count unless the journey is reconstructed elsewhere.
Funnels in GA4 are complex by design
They require you to define exact events, parameters, and order upfront.Even small changes in tracking can break or invalidate them.
Funnels work best for validating known, stable flows not for discovering real-world behavior.
The learning curve is high for meaningful answers
Basic metrics are easy to access.
Meaningful answers are not.
To go beyond surface-level insights, you need:
Deep GA4-specific knowledge
Familiarity with undocumented quirks
Trial-and-error exploration
Workarounds for missing concepts
GA4 looks simple.
Using it deeply is not.
BigQuery shifts the burden, not the difficulty
BigQuery removes UI limitations, but:
All logic moves to you
Behavioral reconstruction is manual
Session and identity handling is your responsibility
You must already know what question to ask
BigQuery gives you data.
It does not give you understanding.
The core limitation
GA4 is optimized for:
Reporting
Monitoring
Standardized metrics
It is not optimized for:
Behavioral reasoning
Sequence discovery
Explaining why users behave the way they do
This is not accidental. It’s a design tradeoff.
Interpreting What the Data Is Telling You
GA4 does a tremendous amount of heavy lifting. It collects events, applies structure, and even provides storage at scale.
But interpretation is a different problem.
Each event a user generates is part of a larger story. When we look only at aggregates, we lose the context that explains why users behave the way they do.
Extracting that story from raw event data is possible, but it’s complex and requires deep technical expertise.
We’re building zinzu as an interpretation layer, a way for both technical and non-technical users to express behavioral questions as naturally as they think, without having to rebuild the plumbing underneath.
What’s Next?
Let’s continue the journey on video
We’ll host a virtual session to walk through these ideas live, including whiteboarding and deeper technical discussion. Details will be shared soon.
To get notified:
Email your interest: team@zinzu.io
Follow on LinkedIn: https://www.linkedin.com/in/arifkhan3/
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