Marketing

Lifecycle Email Agent

Writes the sequence, and tells you which segment you may not email

Version 2Published Sep 2, 2026
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4 of 8 lifecycle emails need attention.

8 lifecycle emails checked. 4 flagged. The largest gap is 136 days.

Start with Win-back offer. Engagement has the most flagged.

Whether the message is good is for the marketer; the list shows which emails the numbers or the calendar are questioning.

4
4/8
Flagged
4
8
Flagged emails
4
Longest (days)
136
Share flagged
50%

Why rows were flagged

4
  • Unsubscribes over 0.5%38%
  • Open rate under 15%38%
  • On but not sent for 90 days25%

Value flagged by Stage

  • Engagement2
  • Retention1
  • Growth1

Items to act on, worst first

ItemStageValueDays since the last sendWhy
Win-back offerRetention1136Unsubscribes over 0.5%, Open rate under 15%, On but not sent for 90 days
Feature announcementEngagement10Unsubscribes over 0.5%, Open rate under 15%
Upgrade nudgeGrowth10Unsubscribes over 0.5%, Open rate under 15%
Survey requestEngagement1121On but not sent for 90 days

What to do this week

  • Resolve Win-back offer first: it is the most urgent on the list.
  • Fix the data or the status on every flagged row, then re-run.
  • Re-run this check every time the list changes, before it reaches a decision.

Do

  • Fix the highest-risk item first, then run the check again on fresh data.

Don't

  • Don't act on one row alone: open the source record first.

How to improve

  • Add more detail per row (owner, date, source) so the next report can trace each item.
  • Add a second period of data so the next report can show whether things are improving.

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Overview

"Personalise emails with AI" is one of the most-copied automations there is, and every version treats a list as a resource rather than as people who each did or did not give permission.

This drafts the sequence — onboarding, re-engagement, renewal, a campaign — from what you actually know about the segment, in your own voice, with each message doing one job rather than three.

And before the copy, it reports what the copy cannot fix: segments with no recorded lawful basis, addresses suppressed elsewhere that this sequence would reach again, people already inside another live sequence who are about to receive two things at once, and messages missing the identification and unsubscribe elements that marketing mail requires. Sending without a basis is enforced in the EU and UK, one complaint run can cost a domain its reputation, and no amount of good copy survives either.

Benefits

Nothing sent you should not have sent

The failure that costs a sending domain, not a campaign.

Sequences written in an afternoon

The work that is always planned and rarely done.

Fewer unsubscribes

Mostly by not mailing people twice in a day.

What it does

  • Checks the basis before the copy

    A segment with no recorded lawful basis is reported first. No sequence fixes that.

  • Catches cross-list suppression

    Someone who unsubscribed from one list and is about to be reached through another — the exact failure regulators write about.

  • Finds collision with live sequences

    Two automations reaching the same person in one day is how a list gets trained to ignore you.

  • One job per message

    A message with three calls to action has none, and it is the commonest fault in a drafted sequence.

  • Writes from what you know

    Personalisation from your data, never from an invented assumption about the recipient.

  • Sends nothing

    Drafts and findings. Queuing a sequence is a decision with a domain's reputation attached.

What this changes

What this changes about your week

It takes over
Writing lifecycle sequences and checking who may actually be emailed.
Done today by
A marketer, and in practice nobody checks the second part.
How often
Every campaign and every lifecycle stage.
Typical manual effort
A multi-step sequence written properly is days.

Why Marketing in particular. Sending without a lawful basis is enforced in the EU and UK, and one complaint run can cost a sending domain its reputation. No amount of good copy survives that.

  • Runs unattended

    Started by you or by an event, and it finishes on its own. Nothing waits for someone to be at a desk.

  • The same standard every time

    The two-hundredth item is held to the bar the first one was. Consistency is the part people cannot sustain.

  • It cannot act on its own

    Lifecycle Email Agent has no path to sending, spending or committing. That limit is why its output is safe to act on.

How it runs

This agent runs server-side through the PROMIVO runtime. Each run is logged step by step and every tool call is permission-checked before it executes.

  1. 1InputValidated against the agent input schema
  2. 2Modelclaude-sonnet-5 with automatic fallback
  3. 3Toolssearch_knowledge, extract_structured_data
  4. 4PermissionsRuns READ actions automatically; anything higher waits for approval
  5. 5OutputStructured result matching the output schema
  6. 6LoggingTokens, duration and every step recorded

Requirements

Integrations

No integrations required.

Before you start

  • The segment and what you know about it
  • Consent and suppression records
  • Sequences already live
  • Requires the Starter plan or higher

Use cases

Onboarding

A sequence built around what a new customer actually needs to do.

Re-engagement

Written for people who stopped opening — and checked before it runs.

Auditing what is live

Find the collisions and suppression gaps in sequences already running.

Pricing

Starter

Billed monthly through your PROMIVO subscription. Cancel at any time.

Runs consume your plan allowance for agent executions and tokens. See plan limits

FAQ

Is the consent check legal advice?

No. It reports what your own data records — a basis present, absent, or unclear — and flags segments to check. Marketing rules differ by country and it does not interpret them.

Will it send the emails?

No. It drafts and reports. Queuing a sequence puts your sending domain's reputation on the line, and that decision stays with a person.

Can it personalise deeply?

From what your data contains. It will not invent a company size, an industry or a use case to make a line land — a wrong personal detail is worse than none.

Reviews

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