Client case study · 5 months Illustrative

$41→$139

Revenue per thousand sends, over 5 months.

Elapsed: 5 months
How it was measured: Platform-attributed revenue per send, comparing the batch newsletter baseline with lifecycle flows.
Running alongside: List growth continued at the same rate; no paid acquisition change.
Published with permission: Anonymised at client request

The constraint

One newsletter, everyone, every Tuesday

A single weekly send to the whole list, regardless of what anyone had bought, browsed or ignored.

Unsubscribes were climbing and revenue per send was falling as the list grew — the classic sign of batch sending.

One segment: everybody
No triggered flows at all
Unsubscribe rate rising month on month

What we found

The audit, including the unflattering parts

We looked at what the list was actually doing.

$41 revenue per thousand sends
62% of the list had not opened in 90 days
No welcome, cart, browse, win-back or replenishment flow

The plan

The 90-day roadmap as it was actually written

Replace the batch with behaviour.

Welcome sequence, because new subscribers convert best and were getting nothing
Cart and browse recovery with purchase suppression
Replenishment timed to actual consumption cycles
Win-back before sunsetting, then sunset properly

Month by month

What shipped, and what it moved

The line extends as you scroll. Every step below is a real month, including the one where nothing happened.

01Month 1

Baseline

$41 per thousand sends, one segment, no flows, unsubscribes climbing.

Baseline: $41

02Month 2

Welcome and cart

The two highest-value flows first.

+41%

03Month 3

Suppression fixed

After the complaints below, flows now respect recent purchases.

+48%

04Month 4

Replenishment

Timed to real consumption cycles rather than a fixed interval.

+30%

05Month 5

Win-back and sunset

Dormant subscribers re-engaged, then retired cleanly.

+24%

What went wrong

The part most case studies leave out

The abandoned-browse flow initially fired on any product view, including from customers who had just bought that item. Complaints went up before we added purchase suppression.

The browse-abandonment flow fired on any product view, including for people who had just bought that exact item.

Getting chased about something you purchased an hour ago is worse than getting nothing, and complaints reflected that. We added purchase suppression across every flow and a global frequency cap.

Suppression rules are not an optimisation; they are part of the first build.

The numbers

Where it landed, and how we know

Revenue per thousand sends: $41 → $139 over 5 months. Platform-attributed revenue per send, comparing the batch newsletter baseline with lifecycle flows.

Platform-attributed revenue per send, batch baseline versus lifecycle flows. List growth rate unchanged.

Revenue per thousand sends: $41 to $139
Unsubscribe rate: down 44%
Flow revenue as a share of email revenue: 0% to 58%

Results reflect this client's market, licence status and starting position. We publish the method alongside the number so you can judge whether it transfers to yours.

In hindsight

What we'd do differently next time

Build suppression and frequency caps in the first pass
Welcome flow first — it is the cheapest and it converts best
Sunset dormant subscribers rather than carrying them; deliverability improved as much as revenue did

Before you ask us to do this for you

Does this actually apply to your situation?

This worked because of specific conditions. If yours don't match, say so on the first call and we'll tell you what would change.

Market: Any retailer or subscription business with a list and repeat purchase behaviour.
Starting point: An email platform that supports triggered flows and a store that emits events.
Timeline: Four to six months to build out the full lifecycle.

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