Every outreach and cold-email platform publishes glossy case studies with eye-popping open rates. "We hit 98% opens in our cold outbound." "Our clients average 87% opens on first-touch." "The industry benchmark is 24% — we are 4x above."
The numbers are not fabricated. They come from the vendor's own dashboard. But the dashboard was designed to produce those numbers, and understanding the mechanism helps you evaluate what the vendor is actually selling.
Trick one: list composition
Cold outreach lists are dominated by Apple Mail and Gmail users. Apple Mail users register near-100% open rates due to MPP pre-fetch. If your list is 60% Apple, your reported open rate starts at roughly 60 percentage points before any humans get involved.
Aggressive vendors further skew this by filtering out hard-bounces, soft-bounces, and any address that fails initial verification. The remaining "delivered" base is then used as the denominator for opens, producing a tidy 80%+ headline.
A rigorous benchmark would use the sent-message count as the denominator, not the delivered count. Most vendor dashboards use delivered.
Trick two: time window
Apple MPP fires the pixel within minutes of delivery. If you report opens within a 1-hour window, nearly every Apple recipient has already registered. Over longer windows, actual human opens may accumulate on top. A seven-day open rate will be higher than a one-hour open rate — but if the list is Apple-heavy, the first hour is already near the ceiling.
Vendors often quote "first-hour opens" because the number looks dramatic and speedy. It actually just measures pre-fetch saturation.
Trick three: unique vs total
Is a "98% open rate" counting unique opens (one per message) or total pixel fires? A unique open capped at one per message is a more honest denominator. Total pixel fires include every scanner, proxy, and reload, and can easily push the ratio well above 100% of messages sent — at which point some vendors simply report it as "high" or clip it at 100%.
A clean benchmark requires: unique opens (not total pixel fires), broken down by mailbox provider (Apple vs Gmail vs Outlook), measured over a 24-hour window. Anything else is marketing sleight-of-hand.
Trick four: case-study selection bias
Vendors publish their best campaigns. For every case study showing a 98% open rate, there are dozens of campaigns at the same vendor running at normal rates. The case study is representative of what is possible under ideal circumstances with heavy Apple-Mail list skew — not of what a typical customer will see.
Trick five: the cold-outreach boutique effect
Some agencies specialise in cold outreach and optimise every element for pixel-firing. They send to Apple-heavy lists. They avoid domains with strict image policies. They use warmed-up inboxes with high sender reputation. They time sends to maximise pre-fetch. The resulting open rates reflect the optimisation, not the marketing content.
None of this is fraudulent. It is just a different activity from what most marketing teams are doing, and generalising from the agency's numbers to yours is category error.
What the claim is hiding: reply rate
The real scandal in outreach-tool claims is not the inflated open rate. It is that vendors rarely lead with reply rate, because reply rate is much lower and not nearly as impressive.
Typical cold-outreach numbers for a well-run sequence:
- Open rate (reported): 70–90%. Mostly pre-fetch.
- Click rate: 2–8%. Some scanner contamination, but mostly real interest.
- Reply rate: 1–5%. Almost entirely human.
- Positive reply rate (qualified): 0.5–2%.
The meaningful number for a sales pipeline is positive reply rate, which is typically 40–100x smaller than the headline open rate. A vendor that leads with open rate is choosing the metric that makes them look best, not the metric that predicts your pipeline.
A buyer's checklist for outreach-tool claims
- Demand per-provider open rates. If the vendor can only show aggregate, they are hiding the Apple inflation.
- Ask for the reply rate on the same campaign. A real number is between 1% and 5% for cold outbound. Anything above 15% is either a warm list or a misleading number.
- Ask whether opens are unique or total. Unique is the honest denominator.
- Request the time-to-open distribution. A distribution with a huge spike in the first 5 minutes is diagnostic of pre-fetch.
- Ask for inbox placement testing. Not pixel-based open rate — actual folder placement at Gmail, Outlook, Apple. If the vendor cannot show that their mail reaches the inbox, open rate is irrelevant.
Inbox Check runs your outreach message through 20+ seed mailboxes and shows exactly where it lands at each provider. If your cold-outreach vendor cannot deliver inbox placement over 60% at Gmail and Outlook, the open-rate number is a distraction. Free test at the homepage.
A worked example: breaking down a "90% opens" case study
A well-known outreach agency published a case study claiming a 91% open rate on a 50,000-prospect campaign to SaaS founders. We reverse-engineered plausible composition:
- Founders skew heavily Apple Mail: roughly 65% of the list.
- Apple pre-fetch contributes 65 percentage points deterministically.
- Remaining 35% is Gmail/Outlook mix. Assume real engagement of 25% on that subset — that adds 8.75 percentage points.
- Scanner contribution at enterprise-style domains adds another 3–5 points.
- Total: 65 + 8.75 + 4 ≈ 78 percentage points from non-human sources plus real engagement.
That still does not quite hit 91%, but the remaining 13 points are easily explained by scanner double-firing and a list curated to maximise deliverability. The number is real. It tells you almost nothing about whether the content works.