First impression matters. Percent of new subscribers who complete the Welcome Series (typically 3-5 emails). Low completion = subject lines or pacing need work.
At a glance
The share of new subscribers who entered the welcome series and reached its final email. The welcome series is the single most important automation a store runs, it is the first impression, it carries the highest open and click rates of any send in the account, and it sets whether a new subscriber becomes an engaged customer or quietly tunes out. A high completion rate means new subscribers are reading through the full onboarding and arriving at the offer or first-purchase nudge that usually closes the welcome series. A low completion rate means subscribers are dropping out partway, opening the first email, losing interest by the second or third, and never reaching the conversion moment the series was built around. The usual fixes are subject lines (each email must earn the next open), pacing (too fast feels pushy, too slow loses momentum), and content (the early emails must justify staying subscribed). This card isolates the welcome journey specifically, separate from the blended automation-series-completion-rate.
| What it counts | (new subscribers who reached the final welcome email ÷ new subscribers who entered the welcome series) × 100, for the welcome journey specifically. A typical welcome series is 3 to 5 emails. |
| Why the welcome series specifically | It is the highest-leverage automation in the account. New subscribers are at peak intent, they just signed up, and the welcome series converts that intent into a first purchase and an engaged relationship. Completion here predicts long-term subscriber value better than almost any other early signal. |
| What a healthy rate looks like | Welcome series typically complete higher than other journeys because intent is fresh. A rate comfortably above 70 percent is normal; below 70 percent suggests the series is losing subscribers it should be keeping. |
| What drives drop-off | (1) Weak subject lines, each email must earn the next open, and a flat subject line two or three emails in loses the reader. (2) Pacing, sending too fast feels aggressive, too slow loses the fresh-signup momentum. (3) Thin content, early emails that do not justify the subscription get tuned out. (4) Early conversion, subscribers who buy after email one and exit via a goal rule, this is a good drop-out and should be read as success, not failure. |
| Currency | n/a, this is a percentage. The first-purchase revenue the welcome series drives surfaces in top-automations-by-revenue. |
| Time window | 30D vsP (30-day rolling vs prior period). The vs-prior comparison surfaces whether a content or pacing change helped or hurt. |
| Alert trigger | < 70%. Below this, the welcome series is losing too many high-intent new subscribers before the conversion moment. |
| Sentiment key | mc_welcome_series_completion |
| Roles | owner, marketing |
Calculation
Calculated automatically from your Mailchimp data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A coffee subscription brand on Shopify running Mailchimp Standard with a 4-email welcome series. Snapshot for the 30-day window ending Monday 08 Jun 26, showing step-by-step drop-off, with the prior period’s completion rate for comparison.| Welcome step | Entrants reaching step | Step-to-step retention |
|---|---|---|
| Email 1, Welcome + brand story | 5,200 | (entry) |
| Email 2, How it works + first offer | 4,420 | 85.0% |
| Email 3, Social proof + bestsellers | 3,180 | 71.9% |
| Email 4, Last-chance first-order offer | 3,050 | 95.9% |
| Completion (reached email 4) | 3,050 | 58.7% of entrants |
- Completion fell from 69.2 to 58.7 percent and is well below the 70 percent threshold. The welcome series is now losing more than four in ten new subscribers before the last-chance offer, the email that usually does the heaviest first-purchase lifting.
- The drop-off is concentrated between email 2 and email 3. Retention is healthy from 1 to 2 (85 percent) and excellent from 3 to 4 (95.9 percent), but collapses from 2 to 3 (only 71.9 percent continue). The problem lives in email 2 or in the email-2-to-3 transition, subscribers are opening email 2 (the offer) but not continuing to email 3 (social proof).
- The likely causes, in order. (a) Email 3’s subject line is weak, after seeing the offer in email 2, subscribers need a compelling reason to open the social-proof email; a flat subject line loses them. (b) Pacing, if email 3 lands too soon after email 2, it feels like over-mailing; too late, and the welcome momentum has faded. (c) Email 2 is doing too much, if the first offer in email 2 fully satisfies the subscriber (they bought, or they decided not to), they have no reason to continue.
-
Some of the email-2 drop-off may be healthy. Subscribers who buy after the email-2 offer and exit via a goal rule are a success, not a loss. Before treating this as a problem, check how many of the email-2 drop-outs converted. If a meaningful share bought, the “drop” is partly the series doing its job early. Cross-reference
top-automations-by-revenuefor the welcome series’ first-purchase revenue. - What to test. A/B test email 3’s subject line first, it is the cheapest, highest-leverage fix for a step-3 drop-off. Then review pacing between emails 2 and 3. Then consider whether email 2’s offer should be softened so the series does not fully “spend” the subscriber before the last-chance email.
- Pull the step-by-step retention. Completion alone does not say where subscribers leave; the step view does. The cliff between two specific emails is the target.
- Separate healthy exits from real drop-off. Subscribers who converted and exited via a goal rule are a success; subtract them before concluding the series is leaking.
- Fix the subject line at the cliff. Each email must earn the next open; a weak subject line at the drop-off step is the most common and most fixable cause.
- Review pacing around the cliff. Too-fast or too-slow timing between the two emails at the cliff drives drop-off.
- Re-measure after the change. Use the 30D vsP comparison to confirm the fix moved completion in the right direction.
| Time horizon | Action |
|---|---|
| First day | Pull step-by-step retention; locate the cliff and separate converted exits from genuine drop-off. |
| First week | A/B test the subject line at the cliff step; review pacing between the two emails around it. |
| First month | Measure completion vs prior; confirm the subject-line or pacing change lifted it; iterate on the next-weakest step. |
| Ongoing | Treat the welcome series as the highest-priority automation to optimise; small completion gains compound across every new subscriber. |
Sibling cards merchants should reference together
| Card | Why merchants reach for it |
|---|---|
welcome-automation-status | Is the welcome series even running? Status first, completion second; a paused series completes at zero. |
automation-series-completion-rate | The blended completion rate across all journeys. This card isolates the highest-leverage one. |
top-automations-by-revenue | The welcome series’ first-purchase revenue. Confirms whether email-2 drop-off is healthy (converted) or a real leak. |
automation-stopped-firing-24h | If completion collapsed to near zero, the series may have stopped firing entirely. Check the alert. |
email-open-rate | Per-email open rate at the drop-off step points straight at a weak subject line. |
email-click-rate | Clicks in the welcome series show whether the content is driving action, not just opens. |
net-audience-growth-30d | The welcome series is where new subscribers are won or lost; growth and welcome completion are linked. |
conversion-rate | The commercial outcome the welcome series builds toward; first-purchase conversion is the goal. |
Reconciling against Mailchimp
Where to look in Mailchimp’s own dashboard:- Mailchimp → Automations → Customer Journeys, open the welcome journey, and use the journey map to see member counts at each step. The drop-off between welcome emails is visible there directly.
- Mailchimp → Reports → Automations for the welcome series’ per-email send and engagement counts.
- The welcome journey map’s per-step counts are the raw material: entrants at email one versus members reaching the final welcome email.
| Reason | Direction | What to do |
|---|---|---|
| Goal-rule early exits. Subscribers who buy after an early welcome email and exit via a goal rule count as not completing the email series, by design. | Vortex IQ may read lower | Early conversion is the desired outcome. Subtract converted exits before judging the series as leaking. |
| In-flight members. New subscribers still moving through the welcome series (mid-wait-step) have entered but not completed. | Vortex IQ may read lower for recent cohorts | A welcome series with multi-day waits will show lower completion on the freshest cohort simply because they are still in progress. |
| Series definition. Vortex IQ counts the welcome journey as configured; if multiple welcome variants exist, the blend depends on which are tagged as welcome. | Either direction | Confirm which journeys are classified as the welcome series. |
| Window alignment. Vortex IQ uses a 30-day rolling entry cohort; the Mailchimp map shows lifetime-to-date positions. | Either direction | Compare like cohorts. |
| Refresh lag. Completion recalculates each sync; the Mailchimp map updates as members move. | Vortex IQ moves slowly | Wait for the next sync; check last_synced_at. |