How we compile the email deliverability benchmarks
What this page covers
This is the methodology behind our email deliverability benchmarks page. Unlike the cold-email, warmup, and LinkedIn comparison pages — which are vendor comparisons with rankings — the deliverability benchmarks page is a neutral citation source. No tool or vendor is ranked or recommended in the body. Every number on the page traces back to a named primary or secondary study with a citation ID, a live URL, and a Wayback Machine archive link.
The page is built to be cited. Journalists writing about email deliverability, researchers comparing ISP behavior across years, operators looking for a hard number to anchor a planning conversation — anyone who needs a verifiable, sourced figure for inbox placement rates, cold-email reply rates, LinkedIn outreach benchmarks, or authentication-protocol adoption can pull a number off the page and cite the underlying study directly.
What the page covers
The benchmarks page is organized into seven sections, each with its own data table and analysis. The sections cover: inbox placement rate by mailbox provider (Gmail, Microsoft 365, Yahoo, Apple iCloud, regional breakouts), cold email response benchmarks (open rate, reply rate, bounce rate, spam-complaint thresholds), cold email by industry (SaaS, agencies, finance, healthcare, manufacturing, legal, retail), LinkedIn outreach benchmarks (connection acceptance, message reply, InMail response, daily safe caps), email warmup timeline expectations (new domain, established domain, recovery scenarios), the spam-filter signals that actually matter in 2025-2026, and the global state of DMARC, SPF, and DKIM authentication compliance.
Every row in every table includes one or more citation IDs (C1, C2, C3, etc.) pointing to the citation index at the bottom of the page. The index lists each source with its publisher, year, and both a live URL and a Wayback Machine archive link.
Source-quality tiers
Citations on the page are drawn from three quality tiers, applied in priority order:
Tier A — Primary measurement
Independent deliverability firms publishing their own measurement data (Validity, Sinch Mailgun, Litmus); platform telemetry studies (Expandi, Belkins, Botdog publishing aggregated data from millions of outreach attempts); mailbox-provider documentation (Google Workspace Admin Help, Microsoft Sender Reputation Data, LinkedIn Sales Solutions); and established outreach-tool benchmark reports (Mailshake, Apollo, Lemlist, Instantly, Mailmodo) that publish their own measurement methodology. Tier A is the gold standard — these are the sources we lean on hardest.
Tier B — Secondary aggregators citing Tier A
Industry resources that compile and republish Tier A data with their own analysis (MailReach, dmarcian, Valimail, dmarcreport). Useful for cross-checking Tier A figures and for filling in gaps where Tier A doesn't break out a specific cohort.
Tier C — Industry commentary
Marketing-team blog posts, sales-team summaries, and trade-press articles that cite Tier A or Tier B but don't add measurement of their own. Used only to corroborate Tier A figures, never as a sole source.
How the data is sourced
For each cell in each table, we cite the highest-tier source we can find. Where two Tier A sources disagree (which happens — different measurement methodologies, different time windows, different sample cohorts), we report both values with their respective citations rather than picking a winner. The reader gets the full picture and can weigh the sources themselves.
Every citation entry in the index includes a live source URL and a Wayback Machine archive link. The Wayback link is the durable receipt — even if the original publisher takes the page down or rewrites the figures, the archive snapshot preserves what the source said at the time we cited it.
How every figure is dated and sourced
No number on the page floats free. Each one carries four things: the value itself, the publisher and year it came from, a citation ID that links down to the index, and the source's own measurement window where the source states it. We use the year the data was measured or published — not the year we happened to read it — so a 2025 report stays labeled 2025 even if we cite it in 2026.
A worked example: reading one figure end to end
Suppose a row in the inbox-placement table reads: "Gmail inbox placement: 84% (C7)." Here is exactly how to read and verify it, step by step:
- The value is 84% — the share of legitimate mail that reached the Gmail inbox rather than spam or the promotions tab, as measured by the cited study.
- The citation ID (C7) links to the citation index at the bottom of the page. Following it, you might find: "C7 — Independent deliverability firm, 2025 inbox-placement benchmark, measured Q3 2025. Live link · Archive link."
- The year and window tell you the figure was measured in the third quarter of 2025, so you know not to compare it directly against a 2023 figure without noting the gap.
- The live link opens the publisher's current page, where you can confirm today's wording.
- The archive link opens a Wayback Machine snapshot showing exactly what the source said when we cited it — your permanent receipt even if the publisher later revises or removes the report.
When you cite the figure in your own work, cite the original study (C7's publisher and year), not WarmySender — we're the aggregator pointing you to the source, not the researcher who measured it.
How "No public benchmark available" works
Some cells on the page read "No public benchmark available" rather than a number. This is intentional and important.
When no Tier A or Tier B source publishes a clean, comparable figure for a specific cohort — for example, cold-email reply rate broken out by the healthcare vertical, or inbox placement specifically for Zoho Mail — we say so explicitly rather than fabricating a number. Three filling-in shortcuts we refuse to take:
- Don't impute from related cohorts. Cold-email reply rates for the broader "professional services" vertical can't be safely substituted for "legal services" specifically, even though one contains the other. The measurement context matters.
- Don't average across non-comparable sources. Two studies that use different definitions of "cold email" (one counting opt-in newsletters, one counting fully cold prospecting) can't be averaged into a meaningful single number.
- Don't substitute internal platform data. Our own platform's measurements are not neutral or independently verified, so they don't belong on a citation source.
If the published evidence isn't there, we say so. A "No public benchmark available" cell with a note explaining the gap is more useful to a citing reader than a confidence-inspired estimate that doesn't trace back to anything.
Why we date every citation
Industry benchmark reports are routinely revised, gated behind email walls after a few months, or removed entirely when a vendor changes positioning. Each citation on the page carries a Wayback Machine archive link so the cited claim remains verifiable years later. The archive pattern is a wildcard URL that resolves to the nearest available snapshot, so even if the specific date we accessed is no longer the closest snapshot, the citation still resolves.
This matters most for the deliverability vertical because the underlying data is constantly being re-measured. The Validity 2025 benchmark report and the Validity 2026 benchmark report look very similar at a glance but report meaningfully different numbers; without a year-stamped citation, year-over-year comparisons become impossible to interpret.
Refresh cadence
The benchmarks page is reviewed and refreshed every 180 days — roughly semi-annually. This is a slower cadence than the vendor comparison pages (which refresh every 120 days) because primary deliverability studies are published less frequently than vendor pricing changes. The 180-day window catches the major annual report cycles from Validity, Sinch Mailgun, and the LinkedIn-data publishers without forcing a refresh more often than the underlying data actually changes.
If more than 180 days have passed since the last review, an amber stale-data banner appears at the top of the page until a full re-verification is complete. Anyone can also suggest a new source at any time through the correction form linked from the page footer.
A note on open rates and Apple Mail Privacy Protection
Apple Mail Privacy Protection (launched 2021, extended 2024) pre-fetches tracking pixels regardless of whether the recipient actually views the message. Across every major outreach tool, this systematically inflates reported open rates by roughly 10-20 percentage points. The inflation isn't uniform — it depends on the recipient mix between Apple Mail clients and other clients — but it's large enough that year-over-year open-rate comparisons are no longer reliable as a measure of recipient engagement.
We report open rates as published by the cited source, but the analysis sections flag the privacy-protection caveat repeatedly. Reply rate, click-through rate to a tracked landing page, and downstream pipeline conversion are the more trustworthy engagement metrics for 2024-2026 onward. A serious deliverability analysis should lead with reply rate, not open rate.
How to submit a correction or suggest a source
The page has a "Submit a correction" link at the bottom. Three correction types we welcome: a citation link is broken or has been moved; a number has been revised by the original source and the page hasn't caught up; a Tier A study has been published that we missed. Less welcome: requests to remove a benchmark because it makes a vendor or industry look bad, or requests to add internally measured platform data that isn't independently verifiable.
Frequently asked questions
Can I cite the numbers on the benchmarks page in my own article?
Yes — that's the entire point. Every benchmark is sourced to a named primary or secondary study with a citation ID, a publisher, a year, and both a live URL and a Wayback Machine archive link. We ask only that you cite the original source (not WarmySender) since we're an aggregator here, not the primary researcher. The Wayback link makes the citation durable even years later.
Why is no vendor ranked on the benchmarks page?
Because the page is a neutral citation source, not a buying guide. Vendor rankings are on separate pages (the cold-email, warmup, and LinkedIn comparison pages) that are clearly labeled as comparison frameworks. The benchmarks page contains zero tool recommendations in the body so that citing publishers don't have to worry about endorsing a vendor when they pull a number off the page.
How do you handle conflicting numbers between two Tier A sources?
We report both values with their respective citations rather than picking a winner. Different measurement methodologies, different time windows, and different sample cohorts often produce honestly different numbers; the reader is better served by seeing both than by us silently averaging or selecting one.
Why is the refresh cadence 180 days instead of more frequent?
Because primary deliverability studies are published on annual or semi-annual cycles, not weekly. Refreshing more often wouldn't pick up any new data; it would just consume time. The 180-day cadence catches the major annual report cycles (Validity benchmark, Sinch Mailgun state-of-deliverability, LinkedIn outreach studies) without forcing churn.
Are you publishing your own measurements on this page?
No. Our own platform data isn't neutral or independently verifiable, so it doesn't belong on a citation source. Every number on the page traces back to an outside primary or secondary publisher. If we have internal numbers worth sharing, they go on our blog or in product documentation, clearly labeled as our own measurements.
Related pages
Spot a broken citation, a revised figure, or a Tier A study we missed? Use the correction link on the benchmarks page or email [email protected] with the source URL you'd like us to add.