Define the population
State where records came from, which period they represent, and why the sample belongs to the question.

Refresh List Lab is the home for first-party research into email list quality. We publish a finding only when the sample, denominator, verification context, and privacy boundaries can be explained beside it.
Evidence-led research notes · Definitions and limits shown · Last reviewed 18 September 2026It is an evidence-first guide to understanding list quality without turning a demonstration into a statistic. The Lab separates observed outcomes from assumptions, keeps unknowns visible, and puts limitations next to every conclusion.
The reporting framework defines what a responsible summary should disclose.
Every rate must say what was counted, what was excluded, and when it was measured.
A reader should be able to reproduce the question a study answered—and identify the question it did not answer.
State where records came from, which period they represent, and why the sample belongs to the question.
Separate source rows, unique addresses, eligible checks, completed outcomes, and unresolved results.
Minimize identifying content, document authorization, and never treat a customer upload as public research by default.
Coverage gaps, provider behavior, timing, and missing signals stay beside the finding—not buried in fine print.
“Unique checked addresses” is not interchangeable with submitted rows. A future report would show both, explain the difference, and state which one supports each rate.
An Email Health Index should organize defined measures within a stated assessment window. It should not compress incomplete evidence into a universal quality percentage.
Every score should show its denominator, date, verification context, and coverage so readers can judge what it does—and does not—represent.
Read the index formatSeparate acquisition context, suppression rules, duplicates, verification, and later delivery feedback.
NOTE 02When does a domain answer stop being a mailbox answer?Catch-all behavior can preserve uncertainty even when a receiving server accepts many names.
NOTE 03How should an unknown result be handled?Keep the provider reason, checking context, and uncertainty visible instead of inventing confidence.
Refresh List only presents score-like summaries when the sample, denominator, date, verification context, and privacy boundaries are visible.
A real study would disclose its population, sampling and inclusion rules, collection period, duplicate treatment, denominator for every rate, provider coverage, privacy method, and known limitations alongside the findings.
No. Customer lists do not become public research data by default. Any future research dataset would require an explicit, documented privacy and authorization process, with identifying content minimized or removed.
Unknown remains separate from valid and invalid. A result that cannot be established is not silently converted into a failure, a pass, or a confidence score.
It organizes defined measures such as duplicate rate, malformed rate, verification outcomes, and supported signals when genuine observations and denominators are available.
When a study is ready, the method and the finding will arrive together.