Email campaign reporting should explain what happened, why it may have happened and what will change. A dashboard of opens and clicks is incomplete without delivery, audience, conversion and negative signals.
These ten questions create a repeatable post-send review.
Audience and delivery questions
- Who was targeted, excluded and actually sent, and did the counts match the approved brief?
- Which providers, domains or segments produced unusual permanent or temporary failures?
- Did SPF, DKIM, DMARC, TLS, PTR and provider compliance signals remain healthy?
Preserve the reporting definitions
Write the formula, denominator, source and delay for every KPI. If definitions changed, version the report rather than comparing unlike metrics.
Use provider-level evidence
A blended delivery rate can hide a severe issue at one mailbox provider. Keep SMTP codes and Postmaster evidence beside the campaign summary.
Message and interaction questions
- Did the subject, preview, body and landing page make one consistent promise?
- Which links received likely human clicks after automated activity was filtered?
- Did replies or qualitative feedback reveal confusion that the aggregate rates missed?
Outcome and risk questions
- Did the intended business or customer action occur, and what attribution model assigned credit?
- How did complaints, unsubscribes and support contacts compare with the baseline?
- Were differences large enough and samples comparable enough to support a decision?
Decision question
Use the tutorial to run an email A/B test when a focused hypothesis can explain the result. Avoid testing several unrelated changes at once.
The ListNumber1 analytics guide provides a complete model for opens, CTR, engagement and reporting.
- What will continue, change, stop or be tested next, who owns it and when will the effect be reviewed?
The ten questions turn campaign reporting into an operating decision. Preserve audience, infrastructure, content, outcome and risk evidence so the next send is based on more than a headline rate.
Archive the brief, deployed message, audience counts, metric dictionary and final decision together. That package becomes a trustworthy comparison set for future campaigns.
Begin the review with the approved campaign brief. If the deployed audience, offer or CTA differs from the brief, record the variance before interpreting performance. Otherwise the report may judge a campaign that was never actually sent.
Separate observed facts from explanations. 'Yahoo deferrals rose after 10:00' is evidence; 'the subject caused throttling' is a hypothesis. List alternative causes and the next check needed to distinguish them.
For revenue, show gross orders, cancellations, refunds, discount cost and margin where relevant. State the attribution window and whether conversions were deduplicated across devices or channels.
Add a qualitative sample: replies, support tickets, rendering screenshots and a few anonymized journey traces. These examples can reveal confusing terms or broken handoffs hidden inside a reasonable average.
Close with one prioritized decision. Ten observations that produce no owner or deadline are a status report, not campaign learning. Estimate the expected effect and specify how the next send will confirm it.
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