Hello, quick question on the Activation metric that can be set for experiment analysis. In our case, we decided to have 2 dedicated events when: • a user is assigned to one or multiple experiments (as there can be multiple concurrent experiments): it's

experimentAssigned

• a user should be "activated" for the experiment meaning only from this point on they should be considered for it, and not from the start (this is because some of our experiments are assigned Server side and for other reasons). This is

experimentViewed

Now, our Experiment assignment table exposes all the fields as required and it's working fine. We've then added a very simple metric for the

experimentViewed

which will expose the

user_id

and

timestamp

. But the

experimentViewed

metric does not seem to be precise enough for the analysis to work. Take the following example: • User is assigned to Experiment A - variant 1 and Experiment B - control • This creates 2 distinct experiment assignment entries which share the same timestamp • Let's say that they navigate to a part of the UI where the

experimentViewed

is triggered for Experiment A (experiment B is triggered in another place of the UI) • If i use the

experimentViewed

metric in my analysis of Experiment B, the user with that given user_id will be included because the event was triggered, but not for the right experiment_id Is there a way to specify the right experiment_id in the Activation metric exposed fields for this to work? Or am i doing this the wrong way? Thanks!