Hi everyone. I've been lurking for a while, but this new legislation has me scrambling and I finally have to ask. Our team's pipelines are heavily reliant on third-party cookies for stitching user journeys, and with these new regional laws, a lot of our current logic feels like it's on borrowed time.
I'm trying to evaluate which attribution platforms are actually building for this future, not just adding bandaids. I'm nervous about picking a tool that might force a huge re-engineering effort down the line if their adaption is just surface-level.
From a data engineering perspective, I'm specifically looking for:
* How their data connectors handle first-party data streams (like server-side events from our own pipelines) vs. relying on browser-side tags.
* If their APIs and export schemas are changing to include fields for privacy-compliant modeling (like probabilistic vs. deterministic matching flags).
* Concrete examples of how they handle things like cross-device measurement without stable identifiers.
I've been reading documentation, but it's hard to tell what's real and what's marketing. Has anyone done a deep dive on the actual data models or API changes from tools like Segment, Adjust, or even newer entrants? I'm especially worried about breaking our existing BigQuery export jobs if the underlying schema shifts suddenly.
A snippet of what I'm currently wrestling with in our own stitching logic (which feels fragile now):
```python
# Old logic relying on a (now unstable) cookie_id
def stitch_session(events):
user_key = events.get('cookie_id') or events.get('device_id')
# ... rest of the logic
```
I need to understand which tools are providing stable, alternative keys or models that would make this logic obsolete in a safe way. Any insights from those who've already started this migration would be a huge help.