Hi Silver:
1. activation metrics are used when your experiment assignment and the event that shows the experiment variations are not the same. A good example for this is a modal window that might trigger, but you have to assign all users to that page to the variation. By using the 'modal open' event as the activation metric, you make sure that you're not including users who did not see either variation when doing the analytics.
2. Phasing is entirely personal choice- many experimentation programs start with a ramp up, to check for implementation bugs, then a main experiment to test for significance, then a holdout group to make sure that the results that were seen in the experiment persist and were not due to some other effects (like primacy/novelty effects)