If attribution settings change without annotating reports, start by preserving one representative example. It gives the investigation a concrete reference and makes the eventual correction easier to judge.
Find the likely cause
Different periods use different accounting rules.
Treat this as an explanation to verify against the actual work. Look at the input, the relevant decision, and the final result together. If the evidence does not support this diagnosis, investigate the mismatch before applying a convenient but unrelated fix.
Make the targeted correction
Record the change and interpret comparisons accordingly.
Attribution is an accounting framework for observed touchpoints and should be interpreted alongside the limits of the available data.
Check that the repair worked
Do not present model-driven shifts as purely behavioral changes.
Repeat the check on the final version that the reader or customer will encounter. An approved draft, a preview, and a published result can differ; the acceptance decision should concern the version people actually use.
Prevent the next related failure
A separate issue to watch for is this: two analytics systems assign different channel revenue. Document each system's assumptions and reconcile the underlying outcomes.
Monitor the useful outcome
Track reconciled outcomes and explain differences between reporting systems before comparing channel efficiency.
Keep a short record of the original symptom, the evidence behind the diagnosis, and the result of the acceptance check. That record makes the solution reusable when the same condition appears again, without assuming that every superficially similar problem has the same cause.
Official reference for the platform or standard discussed: Google Analytics: attribution settings.