Welcome Email Sequence Template
Four documents and four sheets that time the sequence to the day your own subscribers order, rather than to a generic five-day cadence.
Free download · No account needed
Conversion Timing Curve · by acquisition source
Two peaks, seventeen days apart
| Day band | Popup 7,320 | Guide 3,480 | Blended 12,000 |
|---|---|---|---|
| 0 to 1 | 3.361% | 0.805% | 2.400% |
| 2 to 3 | 1.301% | 0.637% | 1.033% |
| 4 to 6 | 1.017% | 0.525% | 0.828% |
| 7 to 10 | 0.868% | 0.410% | 0.687% |
| 11 to 14 | 0.701% | 0.471% | 0.596% |
| 15 to 21 | 0.647% | 5.588% | 2.150% |
| 22 to 34 | 0.636% | 2.881% | 1.288% |
The sequence sends on days 0, 1, 2, 4 and 6. Shaded rows are the days it says nothing.
What the blended column cannot say
Blended, day 15 to 21 reads 2.150% against 2.400% on day 0 to 1, so the second peak looks like a bump on one decaying curve. It is a second population. 5.588% is the highest hazard in the table, it belongs to 29.0% of the list, and the sequence has been silent for nine days by the time it arrives.
Hazard, and why it is not a conversion rate
First orders in the band, divided by the subscribers who still have no first order at the band's start. The denominator shrinks as people convert, so the number can rise. A cumulative conversion curve only rises, which is why it can never show a dead zone.
What the quiet cohort is worth
The guide cohort converts at 12.90% over 90 days against the popup cohort's 9.34%, and at $78 rather than the $66 the day-4 discount pair sells at. It is the better half of the intake, and not one message is timed for it.
Every hazard from day 7 onward was measured with nothing in market, so 5.588% is an unassisted rate.
Tallow & Ash sends five welcome emails over seven days. Nobody there chose that schedule: it arrived with the sending platform's starter flow in 2021, and the copy has been rewritten twice since without the timing being touched. It is also the cadence in every published welcome-series template, which is a fact about the templates rather than a finding about anybody's list. Run the numbers on one real month of signups and the sequence is timed for the 61.0% who arrived through a discount popup, and silent on the days the other 29.0% buy.
A cumulative conversion curve only rises, so it cannot show you a dead zone. A hazard can. For each day-band it asks what share of the subscribers who still have no first order place one in that band. The blended answer here runs 2.400% on day 0 to 1, down to a 0.596% trough on day 11 to 14, then back to 2.150% on day 15 to 21. Split by acquisition source, that last figure is not a bump on one curve at all.
Popup signups peak at 3.361% and decay from there. Care-guide signups open at 0.805% and reach 5.588% on day 15 to 21, the highest hazard in the table, nine days after the sequence stops. So this pack ships two sequences rather than one longer one, alongside the lifecycle email programme pack that decides what one subscriber may receive in a week and the customer segmentation template. Send River two exports, or take the files blank from the template library.
What's in the pack
Conversion Timing Curve
Nine day-bands with the at-risk population, first orders and hazard for each source, plus the blended rows underneath to read against.
Engagement and Stop Rule
Where each sequence ends, split on fourteen-day opens and split again by source, because one threshold gets one cohort wrong.
Sequence Map
Nine messages with the send day, the hazard of the band it sits in, the audience size and one sentence justifying the date.
Performance by Step
What the sequence in production actually earns per message, including the unsubscribes-per-order column that condemns one of them.
Timing Method
How the hazard is computed, the four caveats that belong on the sheet, and the four ways the table comes out wrong.
Sequence Brief
The current sequence, the two that replace it, and what the change is worth stated as sends and placement rather than projected revenue.
Drafted Emails
Nine drafts with subject, preheader, body direction and a must-not line, which is the field that blocks the discount reflex.
Testing Plan
Four tests in order, each with the events per arm per month worked out first, so an unresolvable test never gets queued. The email A/B testing plan template does that sizing for a whole programme.
How to use it
- 1
Open in River, or take it blank
Let River read your exports and do the arithmetic, or take the four documents and four sheets away and compute the curve by hand.
- 2
Send two exports
Subscribers with a signup date and an acquisition source, and orders with a customer id and an order date. Four columns is enough to compute the curve.
- 3
Read the curve before the schedule
You get the hazard table, then the same table split by source, and a straight answer on whether your curve has one peak or two.
- 4
Take the schedule off it
One sequence per cohort with a peak nobody else shares, each message carrying the hazard that justifies its day, and the stop rule derived per source.
Frequently asked questions
Is this template free?
Yes. Download the Word documents and CSV sheets with no account, no card and no email gate. Edit with AI is the optional half: River computes the curve from your exports, splits it by source and reads the schedule off it. Every pack sits in the template library.
How many emails should a welcome sequence have?
As many as your curve has high-hazard bands, which is the only honest answer. The worked example here needs nine authored messages across two sequences, and any one subscriber receives four or five. A brand with a single early peak needs three or four and nothing later.
What is a hazard, and why not just use conversion rate?
A hazard is first orders in a band divided by the subscribers who still have no first order at that band's start. Because the denominator shrinks, the number can fall and rise. Cumulative conversion only rises, so it can never show you a window where nothing is happening.
Can I not just extend my sequence to three weeks?
Sometimes, and check the split first. A blended curve with a second bump is usually two cohorts with one peak each, and extending one sequence sends the late messages to everybody, including the cohort whose hazard has been under 0.7% for a fortnight.
Should I stop mailing subscribers who never open?
Derive it rather than inherit it. Here, fourteen-day non-openers convert at 0.626% over ten weeks against 7.731% for openers, but that splits to 0.315% and 2.276% by source. Complaint volume also has a ceiling: Google asks senders to keep the Postmaster Tools spam rate below 0.10%.
Does a longer sequence change anything about compliance?
One thing that is easy to miss. The FTC's guidance requires an opt-out mechanism to work for at least 30 days after the message that carried it, and requests honoured within ten business days. Stretch a sequence to day 17 and a day-0 unsubscribe link is suddenly load-bearing.
What format are the downloaded files?
Four .docx documents and four .csv sheets, in a zip. They open in Word, Pages, Google Docs, Excel, Numbers and Sheets with no conversion. Add ?format=pdf to the download link if you want the documents as PDFs to circulate instead.
Find out when your subscribers actually buy
Take the Word documents and CSV sheets blank, or open this exact pack in River and send it a subscriber export and an order export.
Edit with AI