How can you compare inboxing patterns before and after updates?

Comparing inboxing patterns before and after updates requires baseline data and consistent measurement methodology. Track inbox placement percentages, spam placement, bounce rates, and delivery timing by provider before suspected changes.

After an update, measure the same metrics using the same methodology. Statistical comparison reveals whether changes are significant or normal variation. Large sudden shifts correlating with announced or suspected update timing indicate provider changes rather than sender issues.

Document baseline periods clearly and maintain consistent sending during comparison periods. Changes in your own sending (new content, different volumes, list changes) confound comparison with provider updates. Isolate variables to accurately attribute changes to provider filtering rather than your own actions.