How can you compare inboxing patterns before and after updates?

Suspecting a mailbox provider update affected your delivery is one thing. Proving it is another. Here's how to actually compare.

Step 1: Establish your baseline before you need it. You want 4-8 weeks of data captured at the provider level before any suspected change. Track inbox placement rate (what percentage of sends are landing in the inbox vs. spam), spam placement rate, and delivery timing by provider. If you're not measuring by provider today, you won't have baseline data when you need it.

Step 2: Use consistent methodology. Seed list testing (sending to test addresses at target providers) is the most reliable method because it gives you direct inbox/spam placement data. If you're using open rate data instead, beware of Apple MPP inflation. Open rates alone don't tell you whether you're hitting the inbox.

Step 3: Apply a consistent comparison window. Measure the same metric over the same period length before and after the suspected change. Comparing 3 days post-update to a 30-day baseline isn't valid. Normal variation can look like a change at that scale.

Step 4: Look for provider-specific patterns. If your Gmail delivery dropped 20% but your Outlook delivery is unchanged, that's almost certainly a Gmail-specific algorithm change, not a content or authentication problem. Cross-provider comparison is often the most useful diagnostic.

Sudden large shifts (15%+ in a week) that correlate with announced or suspected provider changes are meaningful. Small shifts (2-5%) within your normal variation window probably aren't. If you're not sure what your normal variation looks like, you don't have enough baseline data yet.