The symptom is specific: two analytics systems assign different channel revenue. Start with the affected item and identify the decision or input that could produce this behavior.
Find the likely cause
They use different definitions, windows, or models.
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
Document each system's assumptions and reconcile the underlying outcomes.
Attribution is an accounting framework for observed touchpoints and should be interpreted alongside the limits of the available data.
Check that the repair worked
Compare like-for-like records before declaring either report wrong.
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: the last recorded click receives all strategic attention. Review the broader observable journey and supporting evidence.
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.