How can you reconcile conflicting data sources?

Your ESP says 1,200 clicks. Analytics shows 850 visits from email. Your CRM credits 620 conversions to email. These numbers will never perfectly match, and trying to make them match exactly is a trap. The goal is to understand the gap well enough to make good decisions anyway.

Step 1: Designate a source of truth for each metric type. Don't debate which number is "right." Pick one system to own each data type. ESP owns delivery events (bounces, complaints, clicks). Analytics owns post-click behavior (sessions, conversions). CRM owns business outcomes (leads, deals, pipeline). Once you've decided, stop comparing numbers across categories.

Step 2: Align your time zones. A click at 11:50 PM UTC might appear in different calendar days across your ESP (UTC), your GA4 (local time), and your CRM. Standardize all timestamps to UTC at the point of capture.

Step 3: Align your attribution windows. If your CRM attributes a conversion to "the last email clicked in the past 30 days," a week-old campaign might be getting credit for this week's purchase. Make sure your attribution window is explicit and consistent across systems.

Step 4: Use a consistent message ID. Most ESPs embed a unique message identifier in links and headers. Carrying this ID into your analytics events lets you join data at the individual-message level rather than comparing aggregate totals.

When numbers are still different after all that, focus on directional consistency. If both your ESP and CRM show a 20% lift from one campaign over another, that's probably real even if absolute numbers differ.

For the specific case of multi-ESP setups or ESP vs CRM data gaps, those guides cover the platform-specific causes. cohort analysis is also a clean way to measure performance across time without constant reconciliation headaches.