I can't speak for Google Ads, but things like ROAS optimizations are definitely on my radar, and I agree that doing them with the 3-bit event level API would be difficult. I think the best thing you could try is to apply some discretization of the value (e.g. in log space) and do a post-processing step where conversion metadata is translated back to value on the server side, though I understand it will have a lot of error.

For the privacy risks, we want to make sure conversion reports cannot be used to:

• Join user identity between publisher / advertiser sites, even after repeated conversions
• Learn too much about any one user's activity on the advertiser site after an ad click

These two principles led to our API design. These challenges come up because a conversion report in our API has the capability to be associated with a user on the publisher page (via the 64 bit ID). If we move away from reports (potentially) identifying individuals and move to aggregate reporting it is much easier to get more accurate data (e.g. with central differential privacy) that can encode more information like conversion value. I think it would be valuable to see how far you could go with training a bidding system that uses a combination of event-level and aggregate data for this purpose.

Hey @pinaik-msft , we have published the following document to attempt to solve (to some extent) the ROAS use-case with event-level data:
https://github.com/WICG/attribution-reporting-api/blob/main/flexible_event_config.md

Please take a look and feel free to file issues related to that proposal. I'll close this one for now.