Numbers below are illustrative and representative of this engagement type. The subject is anonymized, and every figure sits inside published benchmark ranges.
The situation: one email to convert a 14-day trial
The product ran a 14-day free trial, and the entire email program to convert those trials was one welcome message sent at signup. After that, nothing. The list held about 12,000 contacts, and trial-to-paid conversion sat at 9.1%. Every trial that did not activate in the first few days was left to convert on its own, with no nudge tied to what the user had or had not done inside the product.
Engagement was thin. Email click-through ran at 1.2%, roughly half the all-industry average, and the unsubscribe rate of 0.41% was double the typical 0.2% mark. A list shedding subscribers that fast signals mail people did not ask for, or did not arrive at the right moment.
What the audit found: 88% inbox placement
The deliverability picture explained part of the weak conversion. A seed-list test put inbox
placement at 88%, so roughly one in eight onboarding emails missed the inbox during the only
window that mattered, the 14 days before the trial expired. SPF and DKIM passed, but DMARC sat
at p=none with no enforcement, leaving the domain exposed and the reputation soft.
The content gap mattered just as much. With no behavioral triggers, the single welcome email could not respond to whether a user had set up their workspace or invited a teammate. In a recent onboarding rebuild, the accounts that completed one core action in week one converted at several times the rate of those that did not, which is exactly what a sequence is built to drive.
What we built: a sequence mapped to the trial
The deliverability fix went first. Moving DMARC to enforcement and tightening authentication lifted inbox placement before a single new email was added, so the new sequence landed where people would see it. That work follows the same method as the deliverability service.
The activation sequence was mapped to the 14-day trial rather than a calendar. Day-one orientation pointed to the single setup action that predicted conversion. Mid-trial emails fired on behavior, one path for users who had activated, another for those who had stalled. Days 11 to 13 carried a clear upgrade prompt before expiry, and a short post-trial win-back caught accounts that lapsed. The build is detailed on the lifecycle automation page.
The results: a 9-point lift in inbox placement
Inbox placement rose from 88% to 97% after DMARC enforcement, so the sequence reached the trials it was written for. Trial-to-paid conversion moved from 9.1% to 11.1%, a 22% relative lift, and the unsubscribe rate dropped from 0.41% to 0.17% because the mail now matched where each user was in the trial.
| Metric | Before | After | Change |
|---|---|---|---|
| Trial-to-paid conversion | 9.1% | 11.1% | +22% rel. |
| Email click-through rate | 1.2% | 2.4% | +1.2 pts |
| Unsubscribe rate | 0.41% | 0.17% | -0.24 pts |
| Inbox placement | 88% | 97% | +9 pts |
Click-through doubled from 1.2% to 2.4%, in line with all-industry averages, because behavioral triggers put relevant mail in front of active trials instead of a fixed blast. These figures are illustrative of the engagement type, not a guaranteed outcome for every account.
What it means for similar SaaS: 88% placement caps activation
For a trial-driven SaaS, the onboarding window is the whole game, and an 88% placement rate quietly caps it. Adding more emails to a soft-reputation domain does not fix conversion. The sequence has to land first, then it has to respond to product behavior rather than a calendar.
The pattern repeats across these rebuilds: enforce DMARC to lift placement, then build the activation path around what predicts conversion. If your trial-to-paid rate is stuck in single digits, the Growth retainer covers this scope, and the other results show how the same method plays out in DTC.